MEDication reminder Apps to improve medication adherence in

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MEDication reminder Apps to improve medication adherence in Coronary Heart Disease (MedApp-CHD) Study: A randomised controlled trial protocol

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Manuscript ID Article Type:

Date Submitted by the Author:

Complete List of Authors:

BMJ Open bmjopen-2017-017540 Protocol 29-Apr-2017

Secondary Subject Heading:

Public health, Health informatics

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Keywords:

Cardiovascular medicine

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Primary Subject Heading:

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Santo, Karla ; The George Institute for Global Health, Cardiovascular Division; University of Sydney, Sydney Medical School Chow, Clara; The George Institute for Global Health, Cardiovascular Division; Westmead Hospital, Cardiology Department Thiagalingam, Aravinda; University of Sydney, Sydney Medical School; Westmead Hospital, Cardiology Department Rogers, Kris; The George Institute for Global Health Chalmers, John; The George Institute for Global Health, Professorial Unit; University of Sydney, Sydney Medical School Redfern, Julie; The George Institute for Global Health, Cardiovascular Division; University of Sydney, Sydney Medical School

Coronary heart disease < CARDIOLOGY, Telemedicine < BIOTECHNOLOGY & BIOINFORMATICS, PREVENTIVE MEDICINE, PUBLIC HEALTH

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on For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml

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TITLE MEDication reminder Apps to improve medication adherence in Coronary Heart Disease (MedApp-CHD) Study: A randomised controlled trial protocol

AUTHORS

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Karla Santo1,2, Clara K Chow1,2,3, Aravinda Thiagalingam2,3,4, Kris Rogers1, John Chalmers1,2, Julie Redfern1,2 AFFILIATIONS

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1. The George Institute for Global Health, Sydney, Australia

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2. Sydney Medical School, University of Sydney, Sydney, Australia 3. Cardiology Department, Westmead Hospital, Sydney, Australia

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4. Westmead Institute for Medical Research, Sydney, Australia CORRESPONDING AUTHOR Karla Santo

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Cardiovascular Division, The George Institute for Global Health, PO BOX M201, Missenden Rd, Camperdown, NSW 2050, Australia. Email: [email protected]

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Phone: +61 2 8052 4620 WORD COUNT (excluding title page, abstract, references, figures and tables): 4235 FIGURES AND TABLES: 1 Figure + 2 Tables

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For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml

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ABSTRACT INTRODUCTION: The growing number of smartphone health applications available in the app stores makes these apps a promising tool to help reduce the global problem of nonadherence to long-term medications. However, to date, there is limited evidence that available medication reminder apps are effective. This study aims to determine the impact of medication reminder apps on adherence to cardiovascular medication when compared to

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usual care for people with coronary heart disease (CHD) and to determine whether an advanced app compared to a basic app is associated with higher adherence. METHODS AND ANALYSIS: Randomised controlled trial with follow-up at 3 months to

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evaluate the effectiveness, feasibility, acceptability of medication reminder apps on medication adherence compared to usual care. An estimated sample size of 156 patients with

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CHD will be randomised to one of three groups (usual care group, basic medication reminder

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app group, advanced medication reminder app group). The usual care group will receive standard care for CHD with no access to a medication reminder app. The basic medication

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reminder app group will have access to a medication reminder app with a basic feature of

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providing simple daily reminders with no interactivity. The advanced medication reminder

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app group will have access to a medication reminder app with additional interactive and customisable features. The primary outcome is medication adherence measured by the 8-item

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Morisky Medication Adherence Scale at 3 months. Secondary outcomes include clinical measurements of blood pressure and cholesterol levels, and medication knowledge. A process evaluation to assess acceptability and utility of the intervention will also be performed. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the Western Sydney

Local

Health

Network

Human

Research

Ethics

Committee

(AU/RED/HREC/1/WMEAD/3). Study findings will be disseminated via scientific forums

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including peer-reviewed publications and presentations at international and national conferences. CLINICAL TRIAL REGISTRATION NUMBER: ACTRN12616000661471 ABSTRACT WORD COUNT: 300 (Max. 300)

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STRENGTHS AND LIMITATIONS OF THIS STUDY: •

Adherence to cardiovascular medication is a cornerstone of secondary prevention of coronary heart disease, however medication non-adherence is a global concern and

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interventions to improve it are needed. •

Smartphone apps have been proposed as potential tools to improve adherence,

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however there is limited evidence that available medication reminder apps are effective.

There is also a lack of information on which characteristics and features of medication

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•

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reminder apps are more likely to be useful, increase patient engagement and optimise effects.

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•

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In this study, we will examine the impact of available medication reminder apps on adherence to cardiovascular medications, as well as explore whether an advanced

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medication reminder app with additional interactive and customisable features compared to a basic medication reminder app with no interactivity is associated with higher adherence. •

This study is limited by its small sample size and short-term follow-up.

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KEYWORDS: Medication adherence; medication compliance; mobile phone; smartphone; apps; applications; mHealth; eHealth; coronary heart disease; randomised controlled trial

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INTRODUCTION

Cardiovascular disease and medication adherence Coronary heart disease (CHD) is the leading cause of death worldwide, accounting for more than eight million deaths in 2015.1 After an acute coronary event, about half of patients have recurrent events, which can be reduced by adhering to a healthy lifestyle and to evidence-

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based cardiovascular medication.2 However, non-adherence to long-term therapies is a global concern especially in chronic diseases,3,4 such as cardiovascular diseases (CVD),5,6 as highlighted by the World Health Organisation (WHO) report in 2003.7 In Australia, it is

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estimated that 14 to 43% of the patients do not adhere to their cardiovascular medication after 12 to 24 months.8

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Given this sub-optimal adherence to cardiovascular medication, a growing body of research

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has been investigating different interventions to improve medication adherence. Recently, a meta-analysis of randomised controlled trials (RCT) investigating interventions to improve

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adherence to multiple cardiovascular medication in a CHD population found that

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interventions significantly improved the odds of being adherent, however the interventions

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varied widely and the majority of the interventions were complex, comprising several components.9 When compared to simple one-component interventions, such as a text-

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message intervention, the complex interventions were found to have similar results.

mHealth interventions In 2014, there were around 7 billion mobile phone subscriptions globally.10 In addition, mobile subscriptions with internet access were expected to reach 2.3 billion in 2014.10 In Australia, 86% of the household access the internet via mobile or smart phones.11 This Page 5 of 26


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growing mobile phone ownership makes it a promising tool to deliver healthcare interventions, so called mHealth interventions. mHealth interventions can be used to deliver education to patients and health professionals, to collect data, to diagnose, screen and monitor patients, to offer treatment and behavioural change support, as well as, to facilitate communication between patients, health professionals and health services.12 Systematic reviews have shown that interventions delivered by mobile phone text-messages can improve

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appointment attendance,13 preventive care14 and smoking cessation.15 mHealth interventions can also be used to improve medication adherence by sending regular reminders to the patients aiming to reduce forgetfulness, a known non-intentional reason for

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non-adherence. A meta-analysis of text-messaging interventions to improve adherence to medication in chronic diseases showed that text-message reminders were associated with

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increased odds of being adherent.16 Although, cost-effectiveness analyses of mHealth

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interventions are limited, a text-messaging intervention in a population with CHD has been shown to be cost-saving.17

Smartphone apps for medication adherence

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More recently, the use of smartphone apps has been proposed as a potential tool to improve adherence. The increasing popularity of apps is evident as there has been exponential growth

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in numbers of apps available in online stores. This plethora of health apps has triggered a growing interest in mHealth research, however the majority of research has focused on designing and testing new mHealth interventions instead of testing what is already available to the general public. There has also been relatively little research that examines which characteristics and features make health apps more effective. To design this study, we first conducted a systematic search and a stepwise process to identify high-quality medication Page 6 of 26


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reminder apps.18 We identified around 300 medication adherence apps, of which about half were broadly classified into those with basic features of simple timed medication reminders and the other half into those with more advanced features including interactivity and customisation. Although these medication reminder apps are readily available to the public and have the potential to improve the effectiveness and reduce the costs of traditional interventions to

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improve medication adherence,19 there is no published evidence that such apps are effective in improving medication adherence. In addition, it is important to investigate whether daily reminders will be well accepted by patients. In a population with CHD, who are usually

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overwhelmed with a high pill burden and complex medication regimens, such apps might be a successful strategy to improve medication adherence and potentially improve clinical

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outcomes and reduce healthcare costs.

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Aims 1.

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To determine whether medication reminder apps compared to usual care alone will improve adherence to cardiovascular medications at 3 months;

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To determine whether an advanced medication reminder app with additional interactive and customisable features compared to a basic medication reminder app with no interactivity is associated with higher adherence;

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To determine the impact of the apps on blood pressure and cholesterol levels at 3 months;

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To determine whether the intervention is associated with higher medication knowledge;

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To determine whether the intervention is associated with lower health services utilisation; Page 7 of 26


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To determine feasibility of the intervention by evaluating the acceptability, utility and engagement with the apps.

METHODS AND ANALYSIS

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Study design

The MedApp-CHD Study is designed as parallel, prospective, single-blind, randomised, controlled trial (Figure 1). The study will be conducted at a large urban tertiary public

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hospital in Sydney, Australia, that serves a culturally and socio-economically diverse

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population. A total of 156 patients attending the hospital with a diagnosis of CHD will be randomised to one of three groups (usual care group, basic medication reminder app group,

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advanced medication reminder app group). The usual care group will receive standard care

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for CHD with no access to a medication reminder app. The basic medication reminder app group will have access to a medication reminder app with a basic feature of providing simple

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daily reminders with no interactivity. The advanced medication reminder app group will have

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access to a medication reminder app with additional interactive and customisable features.

Randomisation and blinding

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Randomisation will be performed using a central password-protected web-based computerised randomisation program with a 1:1:1 allocation ratio. There will be no stratification for the randomisation procedure and group allocation will be concealed from the study personnel. Due to the nature of the intervention, it is not possible to blind participants

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to group allocation. However, to minimise bias, at the 3-month follow-up visit, outcome assessors will be blinded to group allocation and objective clinical measures will be measured. In addition, analyses will be conducted by investigators who will be also blinded.

Study population

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Participants will be eligible to participate in the study if they have a confirmed diagnosis of CHD, including a prior diagnosis of myocardial infarction, unstable or stable angina, coronary revascularisation procedure or >50% stenosis in at least one major vessel on a coronary angiogram. In addition, participants must meet the following criteria: 1) be an adult

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(> 18 years), 2) own an active smartphone that operates with iOS or Android operating

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systems, 3) have sufficient English language skills, and 4) provide written informed consent. Patients will be excluded if they already use a medication reminder app or other electronic

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reminder systems to help them adhere to their medication regimen, e.g. calendar alerts in

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their phones. In addition, smartphones that are not capable of downloading the apps, for example older Apple™ iPhones, such as iPhones 4, that operate with older iOS versions, will

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be excluded, as the basic app is only compatible with iOS version 7.0 or later and the advanced app with iOS version 8.0 or later.

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Recruitment

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Potential participants will be any patient presenting to the hospital with CHD. Participants will be identified by screening daily admissions in the cardiology wards, coronary angiogram case lists, cardiology and cardiac rehabilitation outpatient clinics. Eligible participants will be approached either in person or by phone by the researcher responsible for recruitment while

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the participant is still in hospital, before or after their outpatient clinics or cardiac rehabilitation appointments. Interested individuals will be invited to an initial face-to-face interview at the hospital. At this initial visit, written informed consent will be obtained and a baseline assessment will be completed by the research assistant. A record of basic demographic information and reasons for non-participation will be kept for those who are ineligible or who decline to participate in the study.

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Interventions

There will be three treatment groups in the study, which are: usual care group, basic

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medication reminder app group and advanced medication reminder app group. The basic and

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advanced medication reminder apps being used in this study were selected through a systematic review and stepwise process to identify high-quality apps. This process has been

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described previously,18 but in brief, it consisted of: (1) a search strategy; (2) assessment of

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eligibility criteria; (3) app selection process; (4) data extraction to evaluate the presence of features considered important in medication reminder apps; (5) analysis including

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classification of the apps as basic and advanced medication reminder apps, scoring and

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ranking; and (6) a quality assessment by using the Mobile App Rating Scale. Among the 272 medication reminder apps identified in this review, the best basic and advanced apps were

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selected to be used in this study. The features present in each app are presented in Table 1.

Table 1: Characteristics and features of the basic and advanced medication reminder apps18 Basic app

Advanced app

Availability in the app stores: Available in both iTunes and Google Play app stores

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Available for free

App updated in 2016

Ability to add a medication list from an in-app medication database

Ability to schedule reminders to occur on a non-daily basis

Medicine-related features:

Ability to track taken or missed doses

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Ability to snooze the reminder

Ability to set refill reminders

Consumer medicine information

Availability of icons or a picture to provide visual clues to ensure

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the correct medication is taken

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No internet connection required for the reminders to function

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Adherence statistics and charts

Ability to change time zones to ensure medication is taken at the right time when travelling

Customisable reminder alert sounds

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Ability to export/share the medication information to a third party

Ability to generate medication reminders to more than one user

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Availability of an option to alert other people about when missed doses are registered. Other features:

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Languages other than English Password protection

Ability to track clinical measurements such as BP and weight

Ability to set appointment reminders

Ability to add personal health information

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Information about general health Information about heart disease

Information about healthy diet

BP, blood pressure

Usual care group

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Participants allocated to the usual care group will receive standard care for their cardiovascular health as determined by their doctors, including cardiovascular medication prescription and advice, as well as, lifestyle counselling. The participants in this group will

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have no access to a medication reminder app.

Basic medication reminder app group

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medication reminder app in addition to standard care. The basic medication reminder app has

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a basic feature, which is the ability to provide simple daily reminders with no interactivity to

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reinforce correct medication-taking behaviour. The basic app reminders will act similarly to an alarm or text-message to remind the patients when it is time to take their medications. The

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basic app provides a one-time only reminder at each scheduled time, with no ability to snooze or reschedule the reminder. There is also no ability to register whether the medication was taken or not, once the reminder alerts the patient to take the medication. As the basic app was developed by a non-for-profit Australian organisation,18 it has a database of medications available in the Australian market, which includes consumer medicine information for some of the medications, providing additional information on what the medication is used for, how

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it works and side effects. In addition, the basic app has non-medication related features (Table 1), including: 1) ability to track clinical measurements, in which the patients can, for example, record blood pressure (BP) levels in the app whenever they measure their BP either at home or during a medical consultation; 2) information content about heart attack symptoms and action plan; and 3) healthy diet information with recipes suggestions. At the initial visit, after the baseline assessment and concealed randomisation, the researcher will

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provide an initial training session on how to use the basic app as described in the ‘apps training session’ section below.

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Advanced medication reminder app group

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Participants allocated to the advanced medication adherence app group will have access to an advanced medication reminder app in addition to standard care. The advanced medication

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reminder app has additional features that makes it more interactive and customisable than the

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basic app. These additional features aim to support prospective memory, which is the ability to remember to do something in the future, by providing daily reminders for medication-

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taking; as well as retrospective memory, which is the ability to remember something that was

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done in the past, by tracking taken or missed medication doses. This important tracking feature allows the patients to record whether the medication was taken and at what time it

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was taken, providing a tool for the patients to better control their medication adherence. The advanced app also allows that patients to snooze the reminder, if they cannot take their medication immediately after the reminder alerts them. By default, if the patient does not click that he/she took the medication when the first reminder pops in the smartphone screen, the reminder will be repeated up to three times at 10 minutes’ interval or until the patient registers that the medication was taken, whichever occurs first. However, the snooze time

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length can customize according to the patient’s preference, for example every 5 minutes. Importantly, if the patient does not confirm that they have “taken” their medication after the three default reminders, the dose is counted as “missed”. Similar to the basic app, the advanced app has a medication database and provides consumer medicine information in a written form or in videos. Other medication-related features are (Table 1): 1) refill reminders, in which the patients can set up reminders to alert them when

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they are running out of pills and prompt them to refill their prescriptions at a pharmacy; 2) medication adherence statistics, where the patients can check their weekly adherence rates based on the number of “taken” and “missed” doses; 3) exporting and sharing data, where the

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patients can send their medication list and adherence reports to family members or healthcare providers via email; and 4) the ability to provide alerts to other people, for example a family

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member, when the patient misses a dose, which can provide peer-support to encourage medication adherence.

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The advanced app also has non-medication related features (Table 1), including: 1) the ability

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to track clinical measurements, like the basic app; 2) the ability to record doctors and

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appointment details and set up appointment reminders; 3) the ability to record personal

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medical information in the “diary” section of the app; and 4) information content on general health, provided as health tips that are regularly updated in the app. At the initial visit, after

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the baseline assessment and concealed randomisation, the researcher will provide an initial training session on how to use the advanced app as described in the ‘apps training session’ section below.

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Apps training session The training session will be provided in the same manner for both the basic and advanced medication reminder app groups. The researcher will help the participant to download the allocated app through the patient’s smartphone app store, for example the iTunes App Store for smartphones that operate with iOS (e.g. iPhones) and the Google Play store for smartphones that operate with Android system (e.g. Samsung, HTC, Huawei, Sony). Once

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the app is downloaded, the researcher will demonstrate to the patient how to insert their current list of medications into the app, by searching the medication’s name and dosage in the app’s medication database. Next, the researcher will demonstrate how to select the

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appropriate dose frequency (e.g. once daily) and quantity of pills per dose, as well as how to set the time that the medication is usually taken (e.g. 8:00 am). The researcher will help the

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participants to insert the indicated cardiovascular medications prescribed by their doctors,

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including anti-platelets, angiotensin conversing enzyme inhibitor (ACEi) or angiotensin receptor blocker (ARB), beta-blocker and statin. Non-cardiovascular medications will also be

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inserted if the participant wishes. The researcher will always attempt to insert all the

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prescribed cardiovascular medication, however if after the demonstration of how to insert one medication, the patient feels confident he/she can insert the rest of the medications by

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himself/herself after the training is finished, he/she will be welcomed to do so. The researcher will also demonstrate how to edit or delete a medication, if the medication dosage or timing is

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changed or suspended by the treating doctor. Finally, the researcher will demonstrate how to access the consumer medicine information available for some of the medications. After inserting the medications in the app, the researcher will point out that every day, at the scheduled time, a reminder will pop-up on their smartphone screen, alerting them that it is time to take their medication. It will be emphasized that the reminders are set up by time,

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meaning that at 8:00am, for example, the reminder will alert them to take all the medications scheduled for that time. For the advanced reminder app group, after setting up the reminders for the cardiovascular medication, the researcher will demonstrate to the participants how to track if they have taken their daily doses. Every time that a reminder pops-up on their smartphone screen, the participant will be instructed to click on one of the following options: 1) take, 2) snooze, or 3)

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skip the dose. The researcher will also show that a dose is confirmed as “taken” with a green check-mark on the top of each pill icon in the app. In addition, it will be shown that the patients can access this information by viewing the medication adherence statistic feature,

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which will show a percentage of pills taken per week. Other medication-related features, mentioned above in the ‘Advanced medication reminder app group’ section, will also be

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demonstrated to the participants; however, it will be explained that these are optional features

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that they can use according to their own needs.

As part of the training, the researcher will also explain that the participants can use the non-

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medication related features of the app if they wish, however they are not required to use these features regularly for the purposes of the study.

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Study outcomes

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The primary outcome is self-reported medication adherence measured by the 8-item Morisky Medication Adherence Scale20-22 (Box 1). Medication adherence will also be a secondary outcome by asking the participants how many pills they have missed in the previous seven days and by calculating the proportion of days covered (PDC)23 using prescription refill data obtained through data linkage with the Australian Pharmaceutical Benefits Scheme (PBS).

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Other secondary outcomes include clinical measurements of blood pressure and cholesterol levels, and medication knowledge. Participants will be followed up 3 months after enrolment at a face-to-face interview with a researcher who is blinded to the group allocation. The data collection will include selfreported medication adherence questionnaires, as well as clinical assessments of the blood pressure and heart rate. A medication knowledge questionnaire, asking whether the

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participants know the names of their prescribed medications and what they are for, will also be administered. Participants will also be asked about the occurrence of any recent cardiovascular clinical events and hospitalisations and a fasting blood sample will be

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collected to check the participants’ cholesterol levels. At the end of the interview, after the blinded follow-up assessment, the participants will be asked which group they were assigned

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to. To avoid cross-group contamination, the researcher will not mention the names of the

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apps being used in the study during the enrolment visit. This strategy may not ensure that participants allocated to the control group will not download another medication reminder

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app during the study; however, at the follow-up interview, control patients will be asked

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whether they downloaded and used any medication reminder app during the study period. Participants allocated to the basic and advanced medication reminder app groups will be

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asked to complete an additional self-reported questionnaire about the acceptability and utility of the smartphone app. Participants who are unable to attend a face-to-face interview will be

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asked to answer the questionnaires over the phone and the clinical information will be obtain through their medical practitioner. At the end of the study, data about prescription refill rates and health services utilisation will also be obtained through data linkage with the Australian Medicare and Pharmaceutical Benefits Scheme (MBS and PBS). All data will be collected in paper case report forms and the data will be entered in a secure password-protected serverbased database. Page 17 of 26


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Box 1: Primary and secondary outcomes Primary •

Medication adherence – Self-reported 8-item Morisky Medication Adherence Scale

Secondary

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•

Systolic blood pressure – Resting, sitting digital recording, mean of two readings

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Diastolic blood pressure – Resting, sitting digital recording, mean of two readings

•

LDL-cholesterol – Fasting blood sample

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Total cholesterol – Fasting blood sample

•

Number of pills missed in the last seven days – Self-reported questionnaire

•

Proportion of days covered – Prescription refill data through PBS data linkage

•

Health services utilisation – MBS data linkage

•

Medication knowledge – Self-reported questionnaire

•

Acceptability and utility of the intervention – Self-reported questionnaire

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LDL, low-density lipoprotein; MBS, Medicare benefits scheme; PBS, Pharmaceutical benefits scheme

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Statistical considerations

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The primary analysis will be unadjusted, following an intention-to-treat principle, in which the participants will be analysed in the group that they were randomised to. If there are clear differences in baseline characteristics between groups, then sensitivity analyses with additional adjustments for baseline characteristics will performed. Continuous variables will be analysed using independent t tests and categorical variables using χ2 tests as appropriate. Mann-Whitney U tests will be used if data are not normally distributed. We will also

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calculate relative risks, 95% confidence intervals and two-sided p-values for both primary and secondary outcomes. Participants with missing data for medication adherence will be considered non-adherent (non-responder imputation). Pre-specified sub-group analyses will be performed for age, sex, level of education, adherent/non-adherent participants at baseline, advanced medication reminder app/basic medication reminder app, advanced medication reminder app/usual care and basic medication reminder app/usual care. The criterion for

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statistical significance will be set at α 0.05. Sample size calculations are focused on the difference between the proportion of adherent patients when comparing the control group to the intervention groups (basic and advanced

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medication reminder groups). The calculations assume a ratio of 2:1 for intervention and control subjects and that 50% of patients are fully adherent to all cardiovascular medication.

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Analysis of pooled data of previous studies that investigated text-message reminders in a

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population with CHD demonstrated significant improvements in adherence with an estimated absolute improvement of 29%.24-26 Therefore, a total sample size of 156 patients is needed to

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provide 90% power to detect an increase in the proportion of adherent patients from 50% to

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79%, with a two-sided α of 0.05 and allowing for a 20% loss of follow-up. Calculations were performed using PASS statistical software version 15.0.2.

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Process evaluation

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To determine feasibility, acceptability and utility of the intervention, participants in the basic and advanced medication reminder app groups will be administered an additional study questionnaire after the blinded 3-month follow-up assessment. The questionnaire will include items that address the utility of having the medication list in the smartphone, the acceptability and perceived usefulness of the repeated medication reminders, frequency of the reminders; Page 19 of 26


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as well as, whether it was easy to use the app, whether there were any technical difficulties while using the app, and whether the patients would recommend the app to family and friends. The participants in the advanced app group will also answer additional questions in regards to the additional features of the app, including the ability to track taken and missed doses, snooze the reminders and share medication history with family members and medical practitioners. Engagement with the apps will also be evaluated by analysing the usage

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patterns data obtained from the app developers, including how often participants used the app and which features were used the most. This qualitative evaluation will give insights into the role of interactivity and customisation, as well as identify the features that may make medication reminder apps more effective.

ETHICS AND DISSEMINATION

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The findings of this study will be disseminated via scientific forums including peer-reviewed

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publications and presentations at international and national conferences. The study will be administered at Westmead Hospital, with design and conduct overseen by a steering

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committee (authors) from The George Institute for Global Health. This committee has expertise in large-scale clinical trials, qualitative research and clinical CVD management.

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This study will adhere to the National Health and Medical Research Council ethical guidelines for human research. Ethical approval has been obtained from the Western Sydney Local Health Network Human Research Ethics Committee (AU RED HREC/1/WMEAD/3). Written informed consent will be obtained from all enrolled participants. Additional individual informed consent for data linkage through the Australian Medicare and

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Pharmaceutical Benefits Scheme will also be obtained. Clinical trial registration number: ACTRN12616000661471.

CONCLUSION

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The growing market of smartphones has promoted the use of smartphone apps as potential tools to be used in healthcare. In the last decade, there has been an exponential growth of health apps aimed at helping consumers to manage their health. Poor medication adherence is

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a common and major barrier to achieve improvement in clinical outcomes in patients with CVD. This study will provide new evidence from a randomised clinical trial on the

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effectiveness of commonly available medication reminder apps on adherence to cardiovascular medications among patients with CHD. It will also provide additional

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information on how these apps may work to improve medication adherence. Whilst the use of

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new technology is an attractive option, evidence is needed to help guide health providers and

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health services as to whether they should recommend such technologies to patients. Overall, this study will inform future research on the development of mHealth interventions that are

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likely to be transferrable across chronic diseases and open up a new approach for reinforcement of medication adherence and healthy behaviours.

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CONTRIBUTORS KS, CKC, JC and JR conceived the original concept of the study and the interventions. KS and KR performed the sample size calculations and will lead analysis of the results. KS, CKC, AT are supporting patient recruitment. KS drafted the protocol. All authors contributed

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to the scientific design of the study and the protocol development, are involved in the implementation of the project and have read and approved the final manuscript.

ACKNOWLEDGMENTS

The authors acknowledge the hospital staff who are fully engaged in helping us achieve our

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target recruitment number and the patients at Westmead Hospital for their support to the study. Use of the MMAS is protected by US copyright laws. A license agreement to use the scale was obtained from: Donald E. Morisky, ScD, ScM, MSPH, Professor, Department of Community Health Sciences, UCLA School of Public Health, 650 Charles E. Young Drive

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South, Los Angeles, CA 90095-1772, [email protected].

COMPETING INTERESTS

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rr The authors declare no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

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FUNDING

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This study is supported by a Vanguard Grant (ID101464) funded by the National Heart Foundation of Australia. KS is funded by a University of Sydney International Postgraduate Research Scholarship. CKC is funded by a Career Development Fellowship co-funded by National Health and Medical Research Council (NHMRC) and National Heart Foundation (APP1105447). JC is a chief investigator on NHMRC programme grant (ID1052555). JR is funded by a Career Development and Future Leader Fellowship co-funded by the NHMRC and the National Heart Foundation (APP1061793). Page 22 of 26


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ETHICS APPROVAL The study was approved by Western Sydney Local Health Network Human Research Ethics Committee.

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REFERENCES

1. World Health Organisation: The top 10 cause of death. Fact Sheet N° 310. 2017 [updated January 2017]. Available from: http://www.who.int/mediacentre/factsheets/fs310/en/

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accessed 21 April 2017.

2. Mozaffarian D, Benjamin EJ, Go AS, et al. Heart disease and stroke statistics--2015

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3. Osterberg L, Blaschke T. Adherence to medication. N Engl J Med 2005;353(5):487-97.

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4. Bosworth HB, Granger BB, Mendys P, et al. Medication adherence: a call for action. Am Heart J 2011;162(3):412-24. doi: http://dx.doi.org/10.1016/j.ahj.2011.06.007

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5. Choudhry NK, Fischer MA, Avorn J, et al. The implications of therapeutic complexity on adherence to cardiovascular medications. Arch Intern Med 2011;171(9):814-22. doi: 10.1001/archinternmed.2010.495

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6. Chowdhury R, Khan H, Heydon E, et al. Adherence to cardiovascular therapy: a metaanalysis of prevalence and clinical consequences. Eur Heart J 2013;34(38):2940-8. doi: http://dx.doi.org/10.1093/eurheartj/eht295

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7. Adherence to long-term therapies: evidence for action. Geneva, Switzerland: World Health Organization; 2003. Available from: http://www.who.int/chp/knowledge/publications/adherence_full_report.pdf. 8. McKenzie SJ, McLaughlin D, Clark J, et al. The burden of non-adherence to cardiovascular medications among the aging population in Australia: a meta-analysis. Drugs Aging 2015;32(3):217-25. doi: 10.1007/s40266-015-0245-1 [published Online

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First: 2015/03/10]

9. Santo K, Kirkendall S, Laba T-L, et al. Interventions to improve medication adherence in coronary disease patients: A systematic review and meta-analysis of randomised controlled trials. European Journal of Preventive Cardiology 2016;23(10):1065-76.

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doi: 10.1177/2047487316638501

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10. Measuring the Information Society Report International Telecommunication Union; 2014. Available from: http://www.itu.int/en/ITU-

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D/Statistics/Documents/publications/mis2014/MIS2014_without_Annex_4.pdf

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11. Australia Bureau of Statistics. Household Use of Information Technology, Australia, 2014-15 2016 [updated 18 February 2016]. Available from:

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http://www.abs.gov.au/ausstats/[email protected]/mf/8146.0 accessed 12 April 2017.

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12. Santo K, Chalmers J, Chow CK, et al. m-Health in Coronary Disease Preventive Care. Journal of Cardiology and Therapy 2015;2(5):237-78. doi: 10.17554/j.issn.23096861.2015.02.98

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13. Free C, Phillips G, Watson L, et al. The effectiveness of mobile-health technologies to improve health care service delivery processes: a systematic review and metaanalysis. PLoS Med 2013;10(1):e1001363. doi: 10.1371/journal.pmed.1001363 [published Online First: 2013/03/06]

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14. Vodopivec-Jamsek V, de Jongh T, Gurol-Urganci I, et al. Mobile phone messaging for preventive health care. Cochrane Database Syst Rev 2012;12:CD007457. doi: http://dx.doi.org/10.1002/14651858.CD007457.pub2 15. Whittaker R, Borland R, Bullen C, et al. Mobile phone-based interventions for smoking cessation. Cochrane Database Syst Rev 2009(4):Cd006611. doi: 10.1002/14651858.CD006611.pub2 [published Online First: 2009/10/13]

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16. Thakkar J, Kurup R, Laba TL, et al. Mobile telephone text messaging for medication adherence in chronic disease: A meta-analysis. JAMA Intern Med 2016;176(3):34049. doi: 10.1001/jamainternmed.2015.7667 [published Online First: 01/02/16] 17. Burn E, Nghiem S, Jan S, et al. Cost-effectiveness of a text message programme for the

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prevention of recurrent cardiovascular events. Heart 2017 doi: 10.1136/heartjnl-2016-

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310195 [published Online First: 2017/02/27] 18. Santo K, Richtering SS, Chalmers J, et al. Mobile Phone Apps to Improve Medication

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Adherence: A Systematic Stepwise Process to Identify High-Quality Apps. JMIR

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mHealth and uHealth 2016;4(4):e132. doi: 10.2196/mhealth.6742 19. Dayer L, Heldenbrand S, Anderson P, et al. Smartphone medication adherence apps:

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potential benefits to patients and providers. J Am Pharm Assoc (2003)

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2013;53(2):172-81. doi: http://dx.doi.org/10.1331/JAPhA.2013.12202 20. Morisky DE, Ang A, Krousel-Wood M, et al. Predictive Validity of A Medication

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Adherence Measure in an Outpatient Setting. Journal of clinical hypertension (Greenwich, Conn) 2008;10(5):348-54. 21. Krousel-Wood M, Islam T, Webber LS, et al. New medication adherence scale versus pharmacy fill rates in hypertensive seniors. The American journal of managed care 2009;15(1):59-66.

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22. Morisky DE, DiMatteo MR. Improving the measurement of self-reported medication nonadherence: response to authors. J Clin Epidemiol 2011;64(3):255-7; discussion 58-63. doi: 10.1016/j.jclinepi.2010.09.002 [published Online First: 2010/12/15] 23. Pharmacy Quality Alliance. Update on Medication Quality Measures in Medicare Part D Plan Star Ratings-2016. Available from: http://pqaalliance.org/measures/cms.asp accessed 12 April 2017.

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24. Quilici J, Fugon L, Beguin S, et al. Effect of motivational mobile phone short message service on aspirin adherence after coronary stenting for acute coronary syndrome. International journal of cardiology 2013;168(1):568-9. doi: 10.1016/j.ijcard.2013.01.252

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25. Khonsari S, Subramanian P, Chinna K, et al. Effect of a reminder system using an

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automated short message service on medication adherence following acute coronary syndrome. European journal of cardiovascular nursing : journal of the Working

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Group on Cardiovascular Nursing of the European Society of Cardiology

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2015;14(2):170-9. doi: 10.1177/1474515114521910 [published Online First: 2014/02/05]

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26. Park LG, Howie-Esquivel J, Chung ML, et al. A text messaging intervention to promote

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medication adherence for patients with coronary heart disease: a randomized controlled trial. Patient education and counseling 2014;94(2):261-8. doi: 10.1016/j.pec.2013.10.027

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LEGENDS: Figure 1: MedApp-CHD flow-diagram

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279x215mm (300 x 300 DPI)

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SPIRIT 2013 Checklist: Recommended items to address in a clinical trial protocol and related documents* Section/item

Item No

Administrative information

Description

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Addressed on page number

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Title

1

Descriptive title identifying the study design, population, interventions, and, if applicable, trial acronym

______1 ______

Trial registration

2a

Trial identifier and registry name. If not yet registered, name of intended registry

___3 and 21_____

2b

All items from the World Health Organization Trial Registration Data Set

______NA______

Protocol version

3

Date and version identifier

Funding

4

Sources and types of financial, material, and other support

______22_______

Roles and responsibilities

5a

Names, affiliations, and roles of protocol contributors

____1 and 21-22_

5b

Name and contact information for the trial sponsor

5c

Role of study sponsor and funders, if any, in study design; collection, management, analysis, and interpretation of data; writing of the report; and the decision to submit the report for publication, including whether they will have ultimate authority over any of these activities

5d

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______NA______

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____1 and 20____

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Composition, roles, and responsibilities of the coordinating centre, steering committee, endpoint adjudication committee, data management team, and other individuals or groups overseeing the trial, if applicable (see Item 21a for data monitoring committee)

___20-21_______

_____NA_______

1


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Introduction Background and rationale

6a

Description of research question and justification for undertaking the trial, including summary of relevant studies (published and unpublished) examining benefits and harms for each intervention

____5-7______

6b

Explanation for choice of comparators

_____6-7_______

Objectives

7

Specific objectives or hypotheses

_____7-8_______

Trial design

8

Description of trial design including type of trial (eg, parallel group, crossover, factorial, single group), allocation ratio, and framework (eg, superiority, equivalence, noninferiority, exploratory)

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Methods: Participants, interventions, and outcomes

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______8______

Study setting

9

Description of study settings (eg, community clinic, academic hospital) and list of countries where data will be collected. Reference to where list of study sites can be obtained

_____8_______

Eligibility criteria

10

Inclusion and exclusion criteria for participants. If applicable, eligibility criteria for study centres and individuals who will perform the interventions (eg, surgeons, psychotherapists)

_____9_______

Interventions

11a

Interventions for each group with sufficient detail to allow replication, including how and when they will be administered

____10-16_____

11b

Criteria for discontinuing or modifying allocated interventions for a given trial participant (eg, drug dose change in response to harms, participant request, or improving/worsening disease)

11c

Strategies to improve adherence to intervention protocols, and any procedures for monitoring adherence (eg, drug tablet return, laboratory tests)

_____NA______

11d

Relevant concomitant care and interventions that are permitted or prohibited during the trial

___12-13_____

Outcomes

12

Primary, secondary, and other outcomes, including the specific measurement variable (eg, systolic blood pressure), analysis metric (eg, change from baseline, final value, time to event), method of aggregation (eg, ____16-18____ median, proportion), and time point for each outcome. Explanation of the clinical relevance of chosen efficacy and harm outcomes is strongly recommended

Participant timeline

13

Time schedule of enrolment, interventions (including any run-ins and washouts), assessments, and visits for _9-10 and 16-17__ participants. A schematic diagram is highly recommended (see Figure)

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_____NA______

2


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Sample size

14

Estimated number of participants needed to achieve study objectives and how it was determined, including clinical and statistical assumptions supporting any sample size calculations

_____19____

Recruitment

15

Strategies for achieving adequate participant enrolment to reach target sample size

____9-10______

Methods: Assignment of interventions (for controlled trials) Allocation:

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Sequence generation

16a

Method of generating the allocation sequence (eg, computer-generated random numbers), and list of any ____8-9______ factors for stratification. To reduce predictability of a random sequence, details of any planned restriction (eg, blocking) should be provided in a separate document that is unavailable to those who enrol participants or assign interventions

Allocation concealment mechanism

16b

Mechanism of implementing the allocation sequence (eg, central telephone; sequentially numbered, opaque, sealed envelopes), describing any steps to conceal the sequence until interventions are assigned

____8-9______

Implementation

16c

Who will generate the allocation sequence, who will enrol participants, and who will assign participants to interventions

____8-10______

Blinding (masking)

17a

Who will be blinded after assignment to interventions (eg, trial participants, care providers, outcome assessors, data analysts), and how

__8-9 and 16-17__

17b

If blinded, circumstances under which unblinding is permissible, and procedure for revealing a participant’s allocated intervention during the trial

_____NA______

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Methods: Data collection, management, and analysis Data collection methods

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18a

Plans for assessment and collection of outcome, baseline, and other trial data, including any related __9-10 and 16-17_ processes to promote data quality (eg, duplicate measurements, training of assessors) and a description of study instruments (eg, questionnaires, laboratory tests) along with their reliability and validity, if known. Reference to where data collection forms can be found, if not in the protocol

18b

Plans to promote participant retention and complete follow-up, including list of any outcome data to be collected for participants who discontinue or deviate from intervention protocols

____16-17______

3


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Data management

19

Plans for data entry, coding, security, and storage, including any related processes to promote data quality (eg, double data entry; range checks for data values). Reference to where details of data management procedures can be found, if not in the protocol

____16-17_____

Statistical methods

20a

Statistical methods for analysing primary and secondary outcomes. Reference to where other details of the statistical analysis plan can be found, if not in the protocol

___18-19_____

20b

Methods for any additional analyses (eg, subgroup and adjusted analyses)

____18-19______

20c

Definition of analysis population relating to protocol non-adherence (eg, as randomised analysis), and any statistical methods to handle missing data (eg, multiple imputation)

Methods: Monitoring Data monitoring

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_____18-19____

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21a

Composition of data monitoring committee (DMC); summary of its role and reporting structure; statement of _____NA_____ whether it is independent from the sponsor and competing interests; and reference to where further details about its charter can be found, if not in the protocol. Alternatively, an explanation of why a DMC is not needed

21b

Description of any interim analyses and stopping guidelines, including who will have access to these interim _____NA_____ results and make the final decision to terminate the trial

Harms

22

Plans for collecting, assessing, reporting, and managing solicited and spontaneously reported adverse events and other unintended effects of trial interventions or trial conduct

_____NA______

Auditing

23

Frequency and procedures for auditing trial conduct, if any, and whether the process will be independent from investigators and the sponsor

_____NA_____

Ethics and dissemination

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Research ethics approval

24

Plans for seeking research ethics committee/institutional review board (REC/IRB) approval

____20______

Protocol amendments

25

Plans for communicating important protocol modifications (eg, changes to eligibility criteria, outcomes, analyses) to relevant parties (eg, investigators, REC/IRBs, trial participants, trial registries, journals, regulators)

_____20______

4


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Consent or assent

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26a

Who will obtain informed consent or assent from potential trial participants or authorised surrogates, and how (see Item 32)

26b

Additional consent provisions for collection and use of participant data and biological specimens in ancillary _____20______ studies, if applicable

Confidentiality

27

How personal information about potential and enrolled participants will be collected, shared, and maintained _____16-17_____ in order to protect confidentiality before, during, and after the trial

Declaration of interests

28

Financial and other competing interests for principal investigators for the overall trial and each study site

Access to data

29

Statement of who will have access to the final trial dataset, and disclosure of contractual agreements that limit such access for investigators

Ancillary and posttrial care

30

Provisions, if any, for ancillary and post-trial care, and for compensation to those who suffer harm from trial participation

_____NA______

Plans for investigators and sponsor to communicate trial results to participants, healthcare professionals, the public, and other relevant groups (eg, via publication, reporting in results databases, or other data sharing arrangements), including any publication restrictions

_____20______

31b

Authorship eligibility guidelines and any intended use of professional writers

_____21-22_____

31c

Plans, if any, for granting public access to the full protocol, participant-level dataset, and statistical code

Informed consent materials

32

Model consent form and other related documentation given to participants and authorised surrogates

____Appendix___

Biological specimens

33

Plans for collection, laboratory evaluation, and storage of biological specimens for genetic or molecular analysis in the current trial and for future use in ancillary studies, if applicable

____NA_______

Dissemination policy 31a

Appendices

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____9-10______

_____22______

_____20-22____

____NA_______

*It is strongly recommended that this checklist be read in conjunction with the SPIRIT 2013 Explanation & Elaboration for important clarification on the items. Amendments to the protocol should be tracked and dated. The SPIRIT checklist is copyrighted by the SPIRIT Group under the Creative Commons “Attribution-NonCommercial-NoDerivs 3.0 Unported” license. 5


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TITLE

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MEDication reminder Apps to improve medication adherence in Coronary Heart Disease

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(MedApp-CHD) Study: A randomised controlled trial protocol

4

5

AUTHORS

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Karla Santo1,2, Clara K Chow1,2,3, Aravinda Thiagalingam2,3,4, Kris Rogers1, John

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Chalmers1,2, Julie Redfern1,2

8

AFFILIATIONS

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2. Sydney Medical School, University of Sydney, Sydney, Australia

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3. Cardiology Department, Westmead Hospital, Sydney, Australia

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4. Westmead Institute for Medical Research, Sydney, Australia

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CORRESPONDING AUTHOR

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Karla Santo

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Cardiovascular Division, The George Institute for Global Health, PO BOX M201, Missenden

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Rd, Camperdown, NSW 2050, Australia.

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Email: [email protected]

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Phone: +61 2 8052 4620

19

WORD COUNT (excluding title page, abstract, references, figures and tables): 4723

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FIGURES AND TABLES: 1 Figure + 2 Tables

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ABSTRACT

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INTRODUCTION: The growing number of smartphone health applications available in the

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app stores makes these apps a promising tool to help reduce the global problem of non-

25

adherence to long-term medications. However, to date, there is limited evidence that

26

available medication reminder apps are effective. This study aims to determine the impact of

27

medication reminder apps on adherence to cardiovascular medication when compared to

28

usual care for people with coronary heart disease (CHD) and to determine whether an

29

advanced app compared to a basic app is associated with higher adherence.

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METHODS AND ANALYSIS: Randomised controlled trial with follow-up at 3 months to

31

evaluate the feasibility and effectiveness of medication reminder apps on medication

32

adherence compared to usual care. An estimated sample size of 156 patients with CHD will

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be randomised to one of three groups (usual care group, basic medication reminder app

34

group, advanced medication reminder app group). The usual care group will receive standard

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care for CHD with no access to a medication reminder app. The basic medication reminder

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app group will have access to a medication reminder app with a basic feature of providing

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simple daily reminders with no interactivity. The advanced medication reminder app group

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will have access to a medication reminder app with additional interactive and customisable

39

features. The primary outcome is medication adherence measured by the 8-item Morisky

40

Medication Adherence Scale at 3 months. Secondary outcomes include clinical

41

measurements of blood pressure and cholesterol levels, and medication knowledge. A process

42

evaluation will also be performed to assess the feasibility of the intervention by evaluating

43

the acceptability, utility and engagement with the apps.

44

ETHICS AND DISSEMINATION: Ethical approval has been obtained from the Western

45

Sydney

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Local

Health

Network

Human

Research

Ethics

Committee

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Page 3 of 39

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(AU/RED/HREC/1/WMEAD/3). Study findings will be disseminated via usual scientific

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forums.

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CLINICAL TRIAL REGISTRATION NUMBER: ACTRN12616000661471

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ABSTRACT WORD COUNT: 300 (Max. 300)

50

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Recently smartphone apps have been proposed as potential tools to improve

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adherence, therefore, in this study an innovative strategy using medication reminder

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apps to improve the global problem of medication non-adherence will be investigated

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in a population with coronary heart disease. •

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To design this study, a systematic search and a stepwise process to identify high-

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quality medication reminder apps was conducted, in which the apps were classified

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into basic medication reminder apps with no interactivity and advanced medication

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reminder apps with additional interactive and customisable features. •

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A basic and an advanced medication reminder apps will be used in the study and a

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process evaluation will provide insights on which characteristics and features of

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medication reminder apps are more likely to be useful, increase patient engagement

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and optimise effects. •

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however more objective outcomes, such as prescription refills data and clinical

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measurements of blood pressure and cholesterol levels, will also be measured.

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This study is limited by its small sample size and short-term follow-up; however, the

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results of this study will provide preliminary data essential to design a bigger trial

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with a longer-term follow-up.

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KEYWORDS:

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Medication adherence; medication compliance; mobile phone; smartphone; apps;

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applications; mHealth; eHealth; coronary heart disease; randomised controlled trial

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INTRODUCTION

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Cardiovascular disease and medication adherence

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Coronary heart disease (CHD) is the leading cause of death worldwide, accounting for more

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than eight million deaths in 2015.1 After an acute coronary event, about half of patients have

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recurrent events, which can be reduced by adhering to a healthy lifestyle and to evidence-

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based cardiovascular medication.2 However, non-adherence to long-term therapies is a global

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concern especially in chronic diseases,3,4 such as cardiovascular diseases (CVD),5,6 as

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highlighted by the World Health Organisation (WHO) report in 2003.7 In Australia, it is

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estimated that 14 to 43% of the patients do not adhere to their cardiovascular medication after

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12 to 24 months.8

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has been investigating different interventions to improve medication adherence. Recently, a

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meta-analysis of randomised controlled trials (RCT) investigating interventions to improve

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varied widely and the majority of the interventions were complex, comprising several

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components.9 When compared to simple one-component interventions, such as a text-

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mHealth interventions

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In 2014, there were around 7 billion mobile phone subscriptions globally.10 In addition,

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mobile subscriptions with internet access were expected to reach 2.3 billion in 2014.10 In

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Australia, 86% of the household access the internet via mobile or smartphones.11 This Page 5 of 29


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growing mobile phone ownership makes it a promising tool to deliver healthcare

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interventions, so called mHealth interventions. mHealth interventions can be used to deliver

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education to patients and health professionals, to collect data, to diagnose, screen and monitor

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patients, to offer treatment and behavioural change support, as well as, to facilitate

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communication between patients, health professionals and health services.12 Systematic

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reviews have shown that interventions delivered by mobile phone text-messages can improve

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appointment attendance,13 preventive care14 and smoking cessation.15

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mHealth interventions can also be used to improve medication adherence by sending regular

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reminders to the patients aiming to reduce forgetfulness, a known non-intentional reason for

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non-adherence. A meta-analysis of text-messaging interventions to improve adherence to

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medication in chronic diseases showed that text-message reminders were associated with

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interventions are limited, a text-messaging intervention in a population with CHD has been

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shown to be cost-saving.17

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More recently, the use of smartphone apps has been proposed as a potential tool to improve

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adherence. The increasing popularity of apps is evident as there has been exponential growth

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in numbers of apps available in online stores. This plethora of health apps has triggered a

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growing interest in mHealth research, however the majority of research has focused on

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designing and testing new mHealth interventions instead of testing what is already available

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to the general public. There has also been relatively little research that examines which

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characteristics and features make health apps more effective. To design this study, we first

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conducted a systematic search and a stepwise process to identify high-quality medication

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reminder apps.18 We identified around 300 medication adherence apps, of which about half

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were broadly classified into those with basic features of simple timed medication reminders

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and the other half into those with more advanced features including interactivity and

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customisation.

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Although these medication reminder apps are readily available to the public and have the

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potential to improve the effectiveness and reduce the costs of traditional interventions to

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improve medication adherence,19 there is no published evidence that such apps are effective

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in improving medication adherence. In addition, it is important to investigate whether having

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medication information in the app is associated with improvements in medication knowledge,

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and whether daily reminders will be well accepted by patients. In a population with CHD,

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who are usually overwhelmed with a high pill burden and complex medication regimens,

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such apps might be a successful strategy to improve medication adherence and potentially

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improve clinical outcomes and reduce healthcare costs.

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Aims

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1.

To determine whether medication reminder apps compared to usual care alone will

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improve adherence to cardiovascular medications at 3 months;

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2.

To determine whether an advanced medication reminder app with additional interactive

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and customisable features compared to a basic medication reminder app with no

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interactivity is associated with higher adherence;

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3.

months;

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To determine the impact of the apps on blood pressure and cholesterol levels at 3

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5.

utilisation;

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To determine whether the intervention is associated with lower health services

6.


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Study design

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The MedApp-CHD Study is designed as parallel, prospective, single-blind, randomised,

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controlled trial (Figure 1). The study will be conducted at a large urban tertiary public

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population. A total of 156 patients attending the hospital with a diagnosis of CHD will be

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randomised to one of three groups (usual care group, basic medication reminder app group,

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for CHD with no access to a medication reminder app. The basic medication reminder app

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group will have access to a medication reminder app with a basic feature of providing simple

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Randomisation will be performed using a central password-protected web-based

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computerised randomisation program with a 1:1:1 allocation ratio. There will be no

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stratification for the randomisation procedure and group allocation will be concealed from the

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study personnel. Due to the nature of the intervention, it is not possible to blind participants

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to group allocation. However, to minimise bias, at the 3-month follow-up visit, outcome

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assessors will be blinded to group allocation and objective clinical measures will be

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measured. In addition, analyses will be conducted by investigators who will be also blinded.

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Study population

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Participants will be eligible to participate in the study if they have a confirmed diagnosis of

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CHD, including a prior diagnosis of myocardial infarction, unstable or stable angina,

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coronary revascularisation procedure or > 50% stenosis in at least one major vessel on a

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coronary angiogram. In addition, participants must meet the following criteria: 1) be an adult

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systems, 3) have sufficient English language skills, and 4) provide written informed consent.

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Patients will be excluded if they already use a medication reminder app or other electronic

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their phones. In addition, smartphones that are not capable of downloading the apps, for

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example older Apple™ iPhones, such as iPhones 4, that operate with older iOS versions, will

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be excluded, as the basic app is only compatible with iOS version 7.0 or later and the

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advanced app with iOS version 8.0 or later.

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Recruitment

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Potential participants will be any patient presenting to the hospital with CHD. Participants

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will be identified by screening daily admissions in the cardiology wards, coronary angiogram

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case lists, cardiology and cardiac rehabilitation outpatient clinics. Eligible participants will be

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approached either in person or by phone by the researcher responsible for recruitment while

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the participant is still in hospital, before or after their outpatient clinics or cardiac

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rehabilitation appointments. Interested individuals will be invited to an initial face-to-face

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interview at the hospital. At this initial visit, written informed consent will be obtained and a

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baseline assessment will be completed by the research assistant. A record of basic

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demographic information and reasons for non-participation will be kept for those who are

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ineligible or who decline to participate in the study.

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Interventions

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advanced medication reminder apps being used in this study were selected through a

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systematic review and stepwise process to identify high-quality apps. This process has been

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eligibility criteria; (3) app selection process; (4) data extraction to evaluate the presence of

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features considered important in medication reminder apps; (5) analysis including

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ranking; and (6) a quality assessment by using the Mobile App Rating Scale.20 Among the

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272 medication reminder apps identified in this review, the best basic and advanced apps

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were selected to be used in this study. The features present in each app are presented in Table

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1.

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Table 1: Characteristics and features of the basic and advanced medication reminder apps18

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Basic app

Advanced app


Available for free

App updated in 2016




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Availability of icons or a picture to provide visual clues to ensure the correct medication is taken

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Ability to export/share the medication information to a third party Ability to generate medication reminders to more than one user

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Information about general health

Information about heart disease


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BP, blood pressure

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Usual care group

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Participants allocated to the usual care group will receive standard care for their

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cardiovascular health as determined by their doctors, including cardiovascular medication

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prescription and advice, as well as, lifestyle counselling. The participants in this group will

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Participants allocated to the basic medication reminder app group will have access to a basic

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reinforce correct medication-taking behaviour. The basic app reminders will act similarly to

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an alarm or text-message to remind the patients when it is time to take their medications. The

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basic app provides a one-time only reminder at each scheduled time, with no ability to snooze

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or reschedule the reminder. There is also no ability to register whether the medication was

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taken or not, once the reminder alerts the patient to take the medication. As the basic app was

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developed by a non-for-profit Australian organisation,18 it has a database of medications

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available in the Australian market, which includes consumer medicine information for some

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of the medications, providing additional information on what the medication is used for, how

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it works and side effects. In addition, the basic app has non-medication related features

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(Table 1), including: 1) ability to track clinical measurements, in which the patients can, for

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example, record blood pressure (BP) levels in the app whenever they measure their BP either

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at home or during a medical consultation; 2) information content about heart attack

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symptoms and action plan; and 3) healthy diet information with recipes suggestions. At the

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initial visit, after the baseline assessment and concealed randomisation, the researcher will

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provide an initial training session on how to use the basic app as described in the ‘apps

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training session’ section below.

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Participants allocated to the advanced medication adherence app group will have access to an

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advanced medication reminder app in addition to standard care. The advanced medication

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basic app. These additional features aim to support prospective memory, which is the ability

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to remember to do something in the future, by providing daily reminders for medication-

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done in the past, by tracking taken or missed medication doses. This important tracking

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feature allows the patients to record whether the medication was taken and at what time it

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was taken, providing a tool for the patients to better control their medication adherence. The

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advanced app also allows that patients to snooze the reminder, if they cannot take their

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medication immediately after the reminder alerts them. By default, if the patient does not

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click that he/she took the medication when the first reminder pops in the smartphone screen,

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the reminder will be repeated up to three times at 10 minutes’ intervals or until the patient

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registers that the medication was taken, whichever occurs first. However, the snooze time

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length can customize according to the patient’s preference, for example every 5 minutes.

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Importantly, if the patient does not confirm that they have “taken” their medication after the

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three default reminders, the dose is counted as “missed”.

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Similar to the basic app, the advanced app has a medication database and provides consumer

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medicine information in a written form or in videos. Other medication-related features are

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(Table 1): 1) refill reminders, in which the patients can set up reminders to alert them when

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they are running out of pills and prompt them to refill their prescriptions at a pharmacy; 2)

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medication adherence statistics, where the patients can check their weekly adherence rates

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based on the number of “taken” and “missed” doses; 3) exporting and sharing data, where the

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patients can send their medication list and adherence reports to family members or healthcare

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providers via email; and 4) the ability to provide alerts to other people, for example a family

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member, when the patient misses a dose, which can provide peer-support to encourage

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medication adherence.

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medical information in the “diary” section of the app; and 4) information content on general

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health, provided as health tips that are regularly updated in the app. At the initial visit, after

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the baseline assessment and concealed randomisation, the researcher will provide an initial

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training session on how to use the advanced app as described in the ‘apps training session’

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section below.

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Apps training session

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The training session will be provided in the same manner for both the basic and advanced

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medication reminder app groups. The researcher will help the participant to download the

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allocated app through the patient’s smartphone app store, for example the iTunes App Store

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for smartphones that operate with iOS (e.g. iPhones) and the Google Play store for

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smartphones that operate with Android system (e.g. Samsung, HTC, Huawei, Sony). Once

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the app is downloaded, the researcher will demonstrate to the patient how to input their

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current list of medications into the app, by searching the medication’s name and dosage in the

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app’s medication database. Next, the researcher will demonstrate how to select the

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appropriate dose frequency (e.g. once daily) and quantity of pills per dose, as well as how to

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set the time that the medication is usually taken (e.g. 8:00 am). The researcher will help the

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participants to enter the indicated cardiovascular medications prescribed by their doctors,

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including anti-platelets, angiotensin conversing enzyme inhibitor (ACEi) or angiotensin

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receptor blocker (ARB), beta-blocker and statin. Non-cardiovascular medications will also be

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inserted if the participant wishes. The researcher will always attempt to enter all the

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prescribed cardiovascular medication, however if after the demonstration of how to input one

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medication, the patient feels confident he/she can insert the rest of the medications by

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himself/herself after the training is finished, he/she will be welcomed to do so. The researcher

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will also demonstrate how to edit or delete a medication, if the medication dosage or timing is

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changed or suspended by the treating doctor. Finally, the researcher will demonstrate how to

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access the consumer medicine information available for some of the medications. After

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entering the medications in the app, the researcher will point out that every day, at the

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scheduled time, a reminder will pop-up on their smartphone screen, alerting them that it is

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time to take their medication. It will be emphasized that the reminders are set up by time,

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meaning that at 8:00am, for example, the reminder will alert them to take all the medications

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scheduled for that time.

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For the advanced reminder app group, after setting up the reminders for the cardiovascular

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medication, the researcher will demonstrate to the participants how to track if they have taken

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their daily doses. Every time that a reminder pops-up on their smartphone screen, the

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participant will be instructed to click on one of the following options: 1) take, 2) snooze, or 3)

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skip the dose. The researcher will also show that a dose is confirmed as “taken” with a green

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check-mark on the top of each pill icon in the app. In addition, it will be shown that the

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patients can access this information by viewing the medication adherence statistic feature,

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which will show a percentage of pills taken per week. Other medication-related features,

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mentioned above in the ‘Advanced medication reminder app group’ section, will also be

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medication related features of the app if they wish, however they are not required to use these

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features regularly for the purposes of the study.

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Study outcomes

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The primary outcome is self-reported medication adherence measured by the 8-item Morisky

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Medication Adherence Scale21-23 (Box 1). Medication adherence will also be a secondary

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outcome by asking the participants how many pills they have missed in the previous seven

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days at 3 months and by calculating the proportion of days covered (PDC)24 using

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prescription refill data obtained through data linkage with the Australian Pharmaceutical

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Benefits Scheme (PBS) at 3, 6 and 12 months. Other secondary outcomes include clinical

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measurements of blood pressure and cholesterol levels, and medication knowledge.

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Participants will be followed up 3 months after enrolment at a face-to-face interview with a

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researcher who is blinded to the group allocation. The data collection will include self-

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reported medication adherence questionnaires, as well as clinical assessments of the blood

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pressure and heart rate. A medication knowledge questionnaire, adapted from a validated

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questionnaire,25 asking whether the participants know the names of their prescribed

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medications and what they are for, will also be administered. Participants will also be asked

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about the occurrence of any recent cardiovascular clinical events and hospitalisations and a

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fasting blood sample will be collected to check the participants’ cholesterol levels. At the end

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of the interview, after the blinded follow-up assessment, the participants will be asked which

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group they were assigned to. To avoid cross-group contamination, the researcher will not

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mention the names of the apps being used in the study during the enrolment visit. This

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strategy may not ensure that participants allocated to the control group will not download

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another medication reminder app during the study; however, at the follow-up interview,

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control patients will be asked whether they downloaded and used any medication reminder

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app during the study period. Participants allocated to the basic and advanced medication

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reminder app groups will be asked to complete an additional self-reported questionnaire

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about the acceptability and utility of the smartphone app. Participants who are unable to

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attend a face-to-face interview will be asked to answer the questionnaires over the phone and

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the clinical information will be obtain through their medical practitioner. At the end of the

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study, data about prescription refill rates and health services utilisation will also be obtained

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through data linkage with the Australian Medicare and Pharmaceutical Benefits Scheme

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(MBS and PBS). All data will be collected in paper case report forms and the data will be

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entered in a secure password-protected server-based database.

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Secondary

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Acceptability, utility and engagement with the intervention – Self-reported

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questionnaire and focus groups

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The primary analysis will be unadjusted, following an intention-to-treat principle, in which

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the participants will be analysed in the group that they were randomised to. If there are clear

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differences in baseline characteristics between groups, then sensitivity analyses with

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additional adjustments for baseline characteristics will performed. Continuous variables will

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be analysed using independent t tests and categorical variables using χ2 tests as appropriate.

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Mann-Whitney U tests will be used if data are not normally distributed. We will also

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calculate relative risks, 95% confidence intervals and two-sided p-values for both primary

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and secondary outcomes. We will also perform a sensitivity analysis, in which participants

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with missing data for medication adherence at the follow-up, e.g. patients who withdrew from

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the study or were loss of follow-up, will be considered non-adherent (non-responder

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imputation). Pre-specified sub-group analyses will be performed for age, sex, level of

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education, adherent/non-adherent participants at baseline, advanced medication reminder

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app/basic medication reminder app, advanced medication reminder app/usual care and basic

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medication reminder app/usual care. The criterion for statistical significance will be set at α

373

0.05.

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Sample size calculations are focused on the difference between the proportion of adherent

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patients when comparing the control group to the intervention groups (basic and advanced

376

medication reminder groups). The calculations assume a ratio of 2:1 for intervention and

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control subjects and that 50% of patients are fully adherent to all cardiovascular medication.

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population with CHD demonstrated significant improvements in adherence with an estimated

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absolute improvement of 29%.26-28 Therefore, a total sample size of 156 patients is needed to

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79%, with a two-sided α of 0.05 and allowing for a 20% loss of follow-up. Calculations were

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performed using PASS statistical software version 15.0.2.

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Process evaluation

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A process evaluation will also be performed to assess the feasibility of the intervention by

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follow-up assessment, all participants in the basic and advanced medication reminder app

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groups will be administered an additional study questionnaire, adapted from a previous study

390

(Appendix 1).29,30 In addition, a sample of the intervention patients will be invited to

391

participate in focus groups, which will explore in more depth several aspects of the

392

intervention. In this process evaluation, we will examine acceptability and utility of the

393

intervention by asking the participants whether the participants liked or disliked the app,

394

whether the repeated medication reminders were acceptable to them or found to be intrusive,

395

whether they believe the reminders improved their medication-taking behaviour, their

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opinion on the timing and frequency of the reminders, how was their experience of using the

397

app, and which features they used the most; as well as, whether it was easy to use the app,

398

whether there were any technical difficulties while using the app, and whether the patients

399

would recommend the app to family and friends. The participants in the advanced app group

400

will also answer additional questions in regards to the additional features of the app,

401

including the ability to track taken and missed doses, snooze the reminders and share

402

medication history with family members and medical practitioners. Engagement with the

403

apps will also be evaluated by analysing the usage patterns data obtained from the app

404

developers, including how often participants used the app and which features were used the

405

most. This qualitative evaluation will give insights into the role of interactivity and

406

customisation, as well as identify the features that may make medication reminder apps more

407

effective.

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publications and presentations at international and national conferences. The study will be

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administered at Westmead Hospital, with design and conduct overseen by a steering

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committee (authors) from The George Institute for Global Health. This committee has

415

expertise in large-scale clinical trials, qualitative research and clinical CVD management.

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This study will adhere to the National Health and Medical Research Council ethical

417

guidelines for human research. Ethical approval has been obtained from the Western Sydney

418

Local Health Network Human Research Ethics Committee (AU RED HREC/1/WMEAD/3).

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Written informed consent will be obtained from all enrolled participants. Additional

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individual informed consent for data linkage through the Australian Medicare and

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Pharmaceutical Benefits Scheme will also be obtained. Clinical trial registration number:

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ACTRN12616000661471.

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DISCUSSION AND CONCLUSION

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Poor medication adherence is a common and major barrier to achieve improvement in clinical

427

outcomes in patients with CVD. In the last decade, there has been an increasing interest in

428

mHealth research investigating how mHealth interventions, such as text-messaging

429

interventions, can help consumers to manage their health and, more specifically, their

430

medications. More recently, the growing market of smartphones has promoted the use of

431

smartphone apps as potential tools to improve medication adherence. Currently, there is a

432

plethora of health apps available to the public aimed at improving medication adherence;

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however, there is a lack of evidence on whether they are effective and on which apps’

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characteristics and features would increase engagement and, potentially, improve

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effectiveness.

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This study will provide new evidence from a randomised clinical trial on the feasibility and

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effectiveness of using these commonly available medication reminder apps to improve

438

adherence to cardiovascular medications among patients with CHD. A basic and advanced

439

medication reminder apps, selected through a systematic and stepwise approach to identify

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high quality apps, will be tested. Medication adherence will be measured using a validated

441

self-report questionnaire,21-23 however more objective outcomes, such as prescription refills

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data and clinical measurements of blood pressure and cholesterol levels, will also be

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measured. The process evaluation of the study will explore the acceptability, utility and

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engagement with the apps and will potentially give insights into the role of customisation and

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interactivity, as well as the important features that are essential for medication adherence

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apps to be effective, and how they may be improved.

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This study has some limitations. The study primary outcome is self-reported medication

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adherence and, although self-reported adherence is associated with overestimation of

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adherence, it is the simplest, most inexpensive and most useful method of assessing

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adherence in a clinical setting.3,31 We acknowledge that a 3-months period is a short-term

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follow-up and that the study has a small sample size; however, our findings will provide

452

preliminary data essential to design a bigger trial with a longer-term follow-up, including

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providing a better estimate of effect size, enabling accurate powering of a large-scale trial.

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We also acknowledge that the intervention is not likely to change cardiovascular clinical

455

events and hospitalisations, given the short-term follow-up. If this intervention is shown to be

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feasible and acceptable, a future larger trial with hard outcomes and a cost-effectiveness

457

evaluation can expand the knowledge in this area.

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In conclusion, whilst the use of new technology, such as smartphone apps, is an attractive

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option, evidence is needed to help guide health providers and health services as to whether

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they should recommend such technologies to patients. Overall, this study will inform future

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research on the development of mHealth interventions that are likely to be transferrable

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across chronic diseases and open up a new approach for reinforcement of medication

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adherence and healthy behaviours.

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CONTRIBUTORS

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KS, CKC, JC and JR conceived the original concept of the study and the interventions. KS

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and KR performed the sample size calculations and will lead analysis of the results. KS,

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CKC, AT are supporting patient recruitment. KS drafted the protocol. All authors contributed

469

to the scientific design of the study and the protocol development, are involved in the

470

implementation of the project and have read and approved the final manuscript.

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ACKNOWLEDGMENTS

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The basic medication reminder app being used in this study is called My Heart My life and

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was developed by the National Heart Foundation of Australia. The advanced medication

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reminder app being used in this study is called Medisafe and was developed by the Medisafe

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Inc. The authors acknowledge the hospital staff who are fully engaged in helping us achieve

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our target recruitment number and the patients at Westmead Hospital for their support to the

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study. Use of the MMAS is protected by US copyright laws. A license agreement to use the

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scale was obtained from: Donald E. Morisky, ScD, ScM, MSPH, Professor, Department of

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Community Health Sciences, UCLA School of Public Health, 650 Charles E. Young Drive

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COMPETING INTERESTS

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The authors declare no potential conflicts of interest with respect to the research, authorship

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and/or publication of this article.

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FUNDING

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This study is supported by a Vanguard Grant (ID101464) funded by the National Heart

489

Foundation of Australia. KS is funded by a University of Sydney International Postgraduate

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Research Scholarship. CKC is funded by a Career Development Fellowship co-funded by

491

National Health and Medical Research Council (NHMRC) and National Heart Foundation

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(APP1105447). JC is a chief investigator on NHMRC programme grant (ID1052555). JR is

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funded by a Career Development and Future Leader Fellowship co-funded by the NHMRC

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and the National Heart Foundation (APP1061793).

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ETHICS APPROVAL

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The study was approved by Western Sydney Local Health Network Human Research Ethics

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Committee.

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automated short message service on medication adherence following acute coronary

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medication adherence for patients with coronary heart disease: a randomized

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29. Chow CK, Redfern J, Hillis GS, et al. Effect of lifestyle-focused text messaging on risk

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30. Redfern J, Santo K, Coorey G, et al. Factors Influencing Engagement, Perceived Usefulness and Behavioral Mechanisms Associated with a Text Message Support

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Program. PloS one 2016;11(10):e0163929. doi: 10.1371/journal.pone.0163929

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31. Ho PM, Bryson CL, Rumsfeld JS. Medication adherence: its importance in cardiovascular

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outcomes. Circulation 2009;119(23):3028-35. doi:

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http://dx.doi.org/10.1161/CIRCULATIONAHA.108.768986

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LEGENDS:

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Figure 1: MedApp-CHD flow-diagram

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MedApp-CHD Study User Survey Centre number

Patient number

Study ID |__|__|__|-|__|__|__|__|

Thank you for your participation in the MedApp-CHD Study. We seek your feedback about the smartphone apps so we can improve it in the future. All responses are strictly confidential. Today’s Date:

Day _________/ Month _________/ Year _________

PART A – Medication knowledge Please read each statement below and tick one option for each. 1) I can list the names of all my medications I am currently taking.     Strongly agree Agree Neutral Disagree

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 Strongly disagree

2) I can describe when to take all my prescribed medications.  Strongly agree

 Agree

 Neutral

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 Disagree


 Disagree


3) I can describe how to take all my prescribed medications.  Strongly agree

 Agree

 Neutral

rr

4) I confident I know what all my prescribed medications are for.  Strongly agree

 Agree

 Disagree


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PART B – Smartphone apps

 Neutral

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In the last 3 months, did you have access to Medisafe™ app or My heart my life™ app?  Yes  Go to Part C  No

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If no, did you use any other apps to help you take your medication?  Yes PART C – Feedback about the smartphone apps

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Please read each statement below and tick one option for each. a) I found it useful to have my medication list on my smartphone     Strongly agree Agree Neutral Disagree

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 No


b) I found it useful to set reminders to take my medication on the smartphone      Strongly agree Agree Neutral Disagree Strongly disagree

MedApp-CHD User Survey Version 4_dated 20 October 2016

Page 1 of 4


Page 31 of 39


Patient number

Study ID |__|__|__|-|__|__|__|__|

c) I found it useful to be able to track my measurements (e.g. blood pressure and sugar levels) in the smartphone app      Strongly agree Agree Neutral Disagree Strongly disagree d) The reminders helped me remember to take my medicines every day in the correct time      Strongly agree Agree Neutral Disagree Strongly disagree

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e) I found it easy to download the smartphone app    Strongly agree Agree Neutral

 Disagree


 Disagree


g) I found it easy to set up the reminders in the smartphone app     Strongly agree Agree Neutral Disagree


h) I found it easy to track my measurements in the smartphone app     Strongly agree Agree Neutral Disagree


i) I found it convenient to have this app on my smartphone     Strongly agree Agree Neutral Disagree


f)

I found it easy to use the smartphone app    Strongly agree Agree Neutral

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j) How often did you set up the reminders?     3 or more times Twice a day Once a day Weekly/Not per day regularly k) How often did you track your measurements in the smartphone app?     Daily 2 or more times Once a week Lessa than a week weekly l) How often did you have any technical issues with the smartphone app?     Daily Weekly Monthly Less than monthly m) I will continue using the smartphone app     Strongly agree Agree Neutral Disagree

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 Never

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 Never

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 Never  Strongly disagree

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Patient number

Study ID |__|__|__|-|__|__|__|__|

n) I would recommend the smartphone app to family and friends     Strongly agree Agree Neutral Disagree


Additional comments Please provide any further comments or suggestions about the smartphone app. ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________

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Patient number

Study ID |__|__|__|-|__|__|__|__|

PART D – Additional features of the Medisafe™ app Did you have access to the Medisafe™ app?  Yes  Go to Part E  No  Finished. PART E – Feedback about the additional features Please read each statement below and tick one option for each. o) I found it useful to be able to snooze the reminder    Strongly agree Agree Neutral

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 Disagree


 Disagree


p) I found it useful to track my taken and missed doses  Strongly agree

 Agree

 Neutral

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q) I found it useful to be able to share my medication history with my family and health professionals      Strongly agree Agree Neutral Disagree Strongly disagree

rr

r) I found it useful have additional information about my medication in the smartphone app  Strongly agree

 Neutral

 Disagree


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Additional comments

 Agree

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Please provide any further comments or suggestions about the smartphone app.

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________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________

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Item No


Description

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Title

1


______1 ______

Trial registration

2a


___3 and 21_____

2b


______NA______

Protocol version

3


Funding

4


______22_______


5a


____1 and 21-22_

5b


5c


5d

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______NA______

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____1 and 20____

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___20-21_______

_____NA_______

1


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6a


____5-7______

6b


_____6-7_______

Objectives

7


_____7-8_______

Trial design

8


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______8______

Study setting

9


_____8_______


10


_____9_______

Interventions

11a


____10-16_____

11b


11c


_____NA______

11d


___12-13_____

Outcomes

12



13


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_____NA______

2


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Sample size

14


_____19____

Recruitment

15


____9-10______


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Sequence generation

16a



16b


____8-9______

Implementation

16c


____8-10______

Blinding (masking)

17a


__8-9 and 16-17__

17b


_____NA______

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18b


____16-17______

3


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Data management

19


____16-17_____

Statistical methods

20a


___18-19_____

20b


____18-19______

20c



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21b


Harms

22


_____NA______

Auditing

23


_____NA_____


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24


____20______

Protocol amendments

25


_____20______

4


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Consent or assent

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26a


26b


Confidentiality

27



28


Access to data

29



30


_____NA______


_____20______

31b


_____21-22_____

31c



32


____Appendix___


33


____NA_______


Appendices

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____9-10______

_____22______

_____20-22____

____NA_______



BMJ Open


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BMJ Open bmjopen-2017-017540.R2 Protocol 14-Aug-2017



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Page 1 of 39

1

TITLE

2

MEDication reminder Apps to improve medication adherence in Coronary Heart Disease

3

(MedApp-CHD) Study: A randomised controlled trial protocol

4

5

AUTHORS

6

Karla Santo1,2, Clara K Chow1,2,3, Aravinda Thiagalingam2,3,4, Kris Rogers1, John

7

Chalmers1,2, Julie Redfern1,2

8

AFFILIATIONS

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2. Sydney Medical School, University of Sydney, Sydney, Australia

11

3. Cardiology Department, Westmead Hospital, Sydney, Australia

12

4. Westmead Institute for Medical Research, Sydney, Australia

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CORRESPONDING AUTHOR

14

Karla Santo

15

Cardiovascular Division, The George Institute for Global Health, PO BOX M201, Missenden

16

Rd, Camperdown, NSW 2050, Australia.

17

Email: [email protected]

18

Phone: +61 2 8052 4620

19

WORD COUNT (excluding title page, abstract, references, figures and tables): 4766

20

FIGURES AND TABLES: 1 Figure + 2 Tables

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ABSTRACT

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INTRODUCTION: The growing number of smartphone health applications available in the

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app stores makes these apps a promising tool to help reduce the global problem of non-

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adherence to long-term medications. However, to date, there is limited evidence that

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available medication reminder apps are effective. This study aims to determine the impact of

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medication reminder apps on adherence to cardiovascular medication when compared to

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usual care for people with coronary heart disease (CHD) and to determine whether an

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advanced app compared to a basic app is associated with higher adherence.

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METHODS AND ANALYSIS: Randomised controlled trial with follow-up at 3 months to

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evaluate the feasibility and effectiveness of medication reminder apps on medication

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adherence compared to usual care. An estimated sample size of 156 patients with CHD will

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be randomised to one of three groups (usual care group, basic medication reminder app

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group, advanced medication reminder app group). The usual care group will receive standard

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care for CHD with no access to a medication reminder app. The basic medication reminder

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app group will have access to a medication reminder app with a basic feature of providing

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simple daily reminders with no interactivity. The advanced medication reminder app group

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will have access to a medication reminder app with additional interactive and customisable

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features. The primary outcome is medication adherence measured by the 8-item Morisky

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Medication Adherence Scale at 3 months. Secondary outcomes include clinical

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measurements of blood pressure and cholesterol levels, and medication knowledge. A process

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evaluation will also be performed to assess the feasibility of the intervention by evaluating

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the acceptability, utility and engagement with the apps.

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ETHICS AND DISSEMINATION: Ethical approval has been obtained from the Western

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Sydney

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Local

Health

Network

Human

Research

Ethics

Committee

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(AU/RED/HREC/1/WMEAD/3). Study findings will be disseminated via usual scientific

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forums.

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CLINICAL TRIAL REGISTRATION NUMBER: ACTRN12616000661471

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ABSTRACT WORD COUNT: 300 (Max. 300)

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Recently smartphone apps have been proposed as potential tools to improve

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adherence, therefore, in this study an innovative strategy using medication reminder

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apps to improve the global problem of medication non-adherence will be investigated

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in a population with coronary heart disease. •

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To design this study, a systematic search and a stepwise process to identify high-

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quality medication reminder apps was conducted, in which the apps were classified

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into basic medication reminder apps with no interactivity and advanced medication

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reminder apps with additional interactive and customisable features. •

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A basic and an advanced medication reminder apps will be used in the study and a

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process evaluation will provide insights on which characteristics and features of

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medication reminder apps are more likely to be useful, increase patient engagement

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and optimise effects. •

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Medication adherence will be measured using a validated self-report questionnaire,

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however more objective outcomes, such as prescription refills data and clinical

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measurements of blood pressure and cholesterol levels, will also be measured.

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•

This study is limited by its small sample size and short-term follow-up; however, the

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results of this study will provide preliminary data essential to design a bigger trial

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with a longer-term follow-up.

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KEYWORDS:

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Medication adherence; medication compliance; mobile phone; smartphone; apps;

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applications; mHealth; eHealth; coronary heart disease; randomised controlled trial

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INTRODUCTION

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Cardiovascular disease and medication adherence

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Coronary heart disease (CHD) is the leading cause of death worldwide, accounting for more

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than eight million deaths in 2015.1 After an acute coronary event, about half of patients have

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recurrent events, which can be reduced by adhering to a healthy lifestyle and to evidence-

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based cardiovascular medication.2 However, non-adherence to long-term therapies is a global

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concern especially in chronic diseases,3,4 such as cardiovascular diseases (CVD),5,6 as

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highlighted by the World Health Organisation (WHO) report in 2003.7 In Australia, it is

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estimated that 14 to 43% of the patients do not adhere to their cardiovascular medication after

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12 to 24 months.8

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has been investigating different interventions to improve medication adherence. Recently, a

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meta-analysis of randomised controlled trials (RCT) investigating interventions to improve

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varied widely and the majority of the interventions were complex, comprising several

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components.9 When compared to simple one-component interventions, such as a text-

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mHealth interventions

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In 2014, there were around 7 billion mobile phone subscriptions globally.10 In addition,

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mobile subscriptions with internet access were expected to reach 2.3 billion in 2014.10 In

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Australia, 86% of the household access the internet via mobile or smartphones.11 This Page 5 of 29


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growing mobile phone ownership makes it a promising tool to deliver healthcare

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interventions, so called mHealth interventions. mHealth interventions can be used to deliver

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education to patients and health professionals, to collect data, to diagnose, screen and monitor

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patients, to offer treatment and behavioural change support, as well as, to facilitate

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communication between patients, health professionals and health services.12 Systematic

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reviews have shown that interventions delivered by mobile phone text-messages can improve

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appointment attendance,13 preventive care14 and smoking cessation.15

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mHealth interventions can also be used to improve medication adherence by sending regular

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reminders to the patients aiming to reduce forgetfulness, a known non-intentional reason for

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non-adherence. A meta-analysis of text-messaging interventions to improve adherence to

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medication in chronic diseases showed that text-message reminders were associated with

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interventions are limited, a text-messaging intervention in a population with CHD has been

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shown to be cost-saving.17

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More recently, the use of smartphone apps has been proposed as a potential tool to improve

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adherence. The increasing popularity of apps is evident as there has been exponential growth

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in numbers of apps available in online stores. This plethora of health apps has triggered a

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growing interest in mHealth research, however the majority of research has focused on

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designing and testing new mHealth interventions instead of testing what is already available

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to the general public. There has also been relatively little research that examines which

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characteristics and features make health apps more effective. To design this study, we first

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conducted a systematic search and a stepwise process to identify high-quality medication

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reminder apps.18 We identified around 300 medication adherence apps, of which about half

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were broadly classified into those with basic features of simple timed medication reminders

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and the other half into those with more advanced features including interactivity and

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customisation.

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Although these medication reminder apps are readily available to the public and have the

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potential to improve the effectiveness and reduce the costs of traditional interventions to

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improve medication adherence,19 there is no published evidence that such apps are effective

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in improving medication adherence. In addition, it is important to investigate whether having

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medication information in the app is associated with improvements in medication knowledge,

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and whether daily reminders will be well accepted by patients. In a population with CHD,

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who are usually overwhelmed with a high pill burden and complex medication regimens,

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such apps might be a successful strategy to improve medication adherence and potentially

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improve clinical outcomes and reduce healthcare costs.

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Aims

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1.

To determine whether medication reminder apps compared to usual care alone will

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improve adherence to cardiovascular medications at 3 months;

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2.

To determine whether an advanced medication reminder app with additional interactive

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and customisable features compared to a basic medication reminder app with no

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interactivity is associated with higher adherence;

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3.

months;

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To determine the impact of the apps on blood pressure and cholesterol levels at 3

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5.

utilisation;

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To determine whether the intervention is associated with lower health services

6.


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Study design

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The MedApp-CHD Study is designed as parallel, prospective, single-blind, randomised,

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controlled trial (Figure 1). The study will be conducted at a large urban tertiary public

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population. A total of 156 patients attending the hospital with a diagnosis of CHD will be

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randomised to one of three groups (usual care group, basic medication reminder app group,

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for CHD with no access to a medication reminder app. The basic medication reminder app

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group will have access to a medication reminder app with a basic feature of providing simple

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Randomisation will be performed using a central password-protected web-based

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computerised randomisation program with a 1:1:1 allocation ratio. There will be no

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stratification for the randomisation procedure and group allocation will be concealed from the

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study personnel. Due to the nature of the intervention, it is not possible to blind participants

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to group allocation. However, to minimise bias, at the 3-month follow-up visit, outcome

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assessors will be blinded to group allocation and objective clinical measures will be

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measured. In addition, analyses will be conducted by investigators who will be also blinded.

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Study population

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Participants will be eligible to participate in the study if they have a confirmed diagnosis of

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CHD, including a prior diagnosis of myocardial infarction, unstable or stable angina,

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coronary revascularisation procedure or > 50% stenosis in at least one major vessel on a

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coronary angiogram. In addition, participants must meet the following criteria: 1) be an adult

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systems, 3) have sufficient English language skills, and 4) provide written informed consent.

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Patients will be excluded if they already use a medication reminder app or other electronic

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their phones. In addition, smartphones that are not capable of downloading the apps, for

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example older Apple™ iPhones, such as iPhones 4, that operate with older iOS versions, will

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be excluded, as the basic app is only compatible with iOS version 7.0 or later and the

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advanced app with iOS version 8.0 or later.

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Recruitment

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Potential participants will be any patient presenting to the hospital with CHD. Participants

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will be identified by screening daily admissions in the cardiology wards, coronary angiogram

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case lists, cardiology and cardiac rehabilitation outpatient clinics. Eligible participants will be

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approached either in person or by phone by the researcher responsible for recruitment while

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the participant is still in hospital, before or after their outpatient clinics or cardiac

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rehabilitation appointments. Interested individuals will be invited to an initial face-to-face

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interview at the hospital. At this initial visit, written informed consent will be obtained and a

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baseline assessment will be completed by the research assistant. A record of basic

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demographic information and reasons for non-participation will be kept for those who are

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ineligible or who decline to participate in the study.

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Interventions

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advanced medication reminder apps being used in this study were selected through a

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systematic review and stepwise process to identify high-quality apps. This process has been

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eligibility criteria; (3) app selection process; (4) data extraction to evaluate the presence of

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features considered important in medication reminder apps; (5) analysis including

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ranking; and (6) a quality assessment by using the Mobile App Rating Scale.20 Among the

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272 medication reminder apps identified in this review, the best basic and advanced apps

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were selected to be used in this study. The features present in each app are presented in Table

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1.

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Table 1: Characteristics and features of the basic and advanced medication reminder apps18

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Basic app

Advanced app


Available for free

App updated in 2016




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Availability of icons or a picture to provide visual clues to ensure the correct medication is taken

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Ability to export/share the medication information to a third party Ability to generate medication reminders to more than one user

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Information about general health

Information about heart disease


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BP, blood pressure

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Usual care group

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Participants allocated to the usual care group will receive standard care for their

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cardiovascular health as determined by their doctors, including cardiovascular medication

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prescription and advice, as well as, lifestyle counselling. The participants in this group will

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Participants allocated to the basic medication reminder app group will have access to a basic

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reinforce correct medication-taking behaviour. The basic app reminders will act similarly to

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an alarm or text-message to remind the patients when it is time to take their medications. The

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basic app provides a one-time only reminder at each scheduled time, with no ability to snooze

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or reschedule the reminder. There is also no ability to register whether the medication was

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taken or not, once the reminder alerts the patient to take the medication. As the basic app was

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developed by a non-for-profit Australian organisation,18 it has a database of medications

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available in the Australian market, which includes consumer medicine information for some

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of the medications, providing additional information on what the medication is used for, how

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it works and side effects. In addition, the basic app has non-medication related features

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(Table 1), including: 1) ability to track clinical measurements, in which the patients can, for

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example, record blood pressure (BP) levels in the app whenever they measure their BP either

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at home or during a medical consultation; 2) information content about heart attack

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symptoms and action plan; and 3) healthy diet information with recipes suggestions. At the

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initial visit, after the baseline assessment and concealed randomisation, the researcher will

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provide an initial training session on how to use the basic app as described in the ‘apps

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training session’ section below.

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Participants allocated to the advanced medication adherence app group will have access to an

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advanced medication reminder app in addition to standard care. The advanced medication

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basic app. These additional features aim to support prospective memory, which is the ability

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to remember to do something in the future, by providing daily reminders for medication-

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done in the past, by tracking taken or missed medication doses. This important tracking

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feature allows the patients to record whether the medication was taken and at what time it

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was taken, providing a tool for the patients to better control their medication adherence. The

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advanced app also allows that patients to snooze the reminder, if they cannot take their

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medication immediately after the reminder alerts them. By default, if the patient does not

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click that he/she took the medication when the first reminder pops in the smartphone screen,

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the reminder will be repeated up to three times at 10 minutes’ intervals or until the patient

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registers that the medication was taken, whichever occurs first. However, the snooze time

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length can customize according to the patient’s preference, for example every 5 minutes.

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Importantly, if the patient does not confirm that they have “taken” their medication after the

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three default reminders, the dose is counted as “missed”.

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Similar to the basic app, the advanced app has a medication database and provides consumer

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medicine information in a written form or in videos. Other medication-related features are

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(Table 1): 1) refill reminders, in which the patients can set up reminders to alert them when

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they are running out of pills and prompt them to refill their prescriptions at a pharmacy; 2)

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medication adherence statistics, where the patients can check their weekly adherence rates

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based on the number of “taken” and “missed” doses; 3) exporting and sharing data, where the

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patients can send their medication list and adherence reports to family members or healthcare

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providers via email; and 4) the ability to provide alerts to other people, for example a family

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member, when the patient misses a dose, which can provide peer-support to encourage

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medication adherence.

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medical information in the “diary” section of the app; and 4) information content on general

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health, provided as health tips that are regularly updated in the app. At the initial visit, after

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the baseline assessment and concealed randomisation, the researcher will provide an initial

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training session on how to use the advanced app as described in the ‘apps training session’

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section below.

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Apps training session

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The training session will be provided in the same manner for both the basic and advanced

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medication reminder app groups. The researcher will help the participant to download the

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allocated app through the patient’s smartphone app store, for example the iTunes App Store

286

for smartphones that operate with iOS (e.g. iPhones) and the Google Play store for

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smartphones that operate with Android system (e.g. Samsung, HTC, Huawei, Sony). Once

288

the app is downloaded, the researcher will demonstrate to the patient how to input their

289

current list of medications into the app, by searching the medication’s name and dosage in the

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app’s medication database. Next, the researcher will demonstrate how to select the

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appropriate dose frequency (e.g. once daily) and quantity of pills per dose, as well as how to

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set the time that the medication is usually taken (e.g. 8:00 am). The researcher will help the

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participants to enter the indicated cardiovascular medications prescribed by their doctors,

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including anti-platelets, angiotensin conversing enzyme inhibitor (ACEi) or angiotensin

295

receptor blocker (ARB), beta-blocker and statin. Non-cardiovascular medications will also be

296

inserted if the participant wishes. The researcher will always attempt to enter all the

297

prescribed cardiovascular medication, however if after the demonstration of how to input one

298

medication, the patient feels confident he/she can insert the rest of the medications by

299

himself/herself after the training is finished, he/she will be welcomed to do so. The researcher

300

will also demonstrate how to edit or delete a medication, if the medication dosage or timing is

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changed or suspended by the treating doctor. Finally, the researcher will demonstrate how to

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access the consumer medicine information available for some of the medications. After

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entering the medications in the app, the researcher will point out that every day, at the

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scheduled time, a reminder will pop-up on their smartphone screen, alerting them that it is

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time to take their medication. It will be emphasized that the reminders are set up by time,

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meaning that at 8:00am, for example, the reminder will alert them to take all the medications

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scheduled for that time.

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For the advanced reminder app group, after setting up the reminders for the cardiovascular

309

medication, the researcher will demonstrate to the participants how to track if they have taken

310

their daily doses. Every time that a reminder pops-up on their smartphone screen, the

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participant will be instructed to click on one of the following options: 1) take, 2) snooze, or 3)

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skip the dose. The researcher will also show that a dose is confirmed as “taken” with a green

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check-mark on the top of each pill icon in the app. In addition, it will be shown that the

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patients can access this information by viewing the medication adherence statistic feature,

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which will show a percentage of pills taken per week. Other medication-related features,

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mentioned above in the ‘Advanced medication reminder app group’ section, will also be

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medication related features of the app if they wish, however they are not required to use these

321

features regularly for the purposes of the study.

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Study outcomes

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The primary outcome is self-reported medication adherence measured by the 8-item Morisky

325

Medication Adherence Scale21-23 (Box 1). Medication adherence will also be a secondary

326

outcome by asking the participants how many pills they have missed in the previous seven

327

days at 3 months and by calculating the proportion of days covered (PDC)24 using

328

prescription refill data obtained through data linkage with the Australian Pharmaceutical

329

Benefits Scheme (PBS) at 3, 6 and 12 months. In Australia, prescription refills for

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cardiovascular medications are dispensed every month at the pharmacy as a 28 or 30-day

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supply, and a record of each dispensing is included in the PBS data, enabling the calculation

332

of PDC at 3, 6 and 12 months. Other secondary outcomes include clinical measurements of

333

blood pressure and cholesterol levels, and medication knowledge.

334

Participants will be followed up 3 months after enrolment at a face-to-face interview with a

335

researcher who is blinded to the group allocation. The data collection will include self-

336

reported medication adherence questionnaires, as well as clinical assessments of the blood

337

pressure and heart rate. A medication knowledge questionnaire, adapted from a validated

338

questionnaire,25 asking whether the participants know the names of their prescribed

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medications and what they are for, will also be administered. Participants will also be asked

340

about the occurrence of any recent cardiovascular clinical events and hospitalisations and a

341

fasting blood sample will be collected to check the participants’ cholesterol levels. At the end

342

of the interview, after the blinded follow-up assessment, the participants will be asked which

343

group they were assigned to. To avoid cross-group contamination, the researcher will not

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mention the names of the apps being used in the study during the enrolment visit. This

345

strategy may not ensure that participants allocated to the control group will not download

346

another medication reminder app during the study; however, at the follow-up interview,

347

control patients will be asked whether they downloaded and used any medication reminder

348

app during the study period. Participants allocated to the basic and advanced medication

349

reminder app groups will be asked to complete an additional self-reported questionnaire

350

about the acceptability and utility of the smartphone app. Participants who are unable to

351

attend a face-to-face interview will be asked to answer the questionnaires over the phone and

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the clinical information will be obtain through their medical practitioner. At the end of the

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study, data about prescription refill rates and health services utilisation will also be obtained

354

through data linkage with the Australian Medicare and Pharmaceutical Benefits Scheme

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(MBS and PBS). All data will be collected in paper case report forms and the data will be

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entered in a secure password-protected server-based database.

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Acceptability, utility and engagement with the intervention – Self-reported

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The primary analysis will be unadjusted, following an intention-to-treat principle, in which

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the participants will be analysed in the group that they were randomised to. If there are clear

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differences in baseline characteristics between groups, then sensitivity analyses with

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additional adjustments for baseline characteristics will performed. Continuous variables will

366

be analysed using independent t tests and categorical variables using χ2 tests as appropriate.

367

Mann-Whitney U tests will be used if data are not normally distributed. We will also

368

calculate relative risks, 95% confidence intervals and two-sided p-values for both primary

369

and secondary outcomes. We will also perform a sensitivity analysis, in which participants

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with missing data for medication adherence at the follow-up, e.g. patients who withdrew from

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the study or were loss of follow-up, will be considered non-adherent (non-responder

372

imputation). Pre-specified sub-group analyses will be performed for age, sex, level of

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education, adherent/non-adherent participants at baseline, advanced medication reminder

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app/basic medication reminder app, advanced medication reminder app/usual care and basic

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medication reminder app/usual care. The criterion for statistical significance will be set at α

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0.05.

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Sample size calculations are focused on the difference between the proportion of adherent

378

patients when comparing the control group to the intervention groups (basic and advanced

379

medication reminder groups). The calculations assume a ratio of 2:1 for intervention and

380

control subjects and that 50% of patients are fully adherent to all cardiovascular medication.

381


382

population with CHD demonstrated significant improvements in adherence with an estimated

383

absolute improvement of 29%.26-28 Therefore, a total sample size of 156 patients is needed to

384


385

79%, with a two-sided α of 0.05 and allowing for a 20% loss of follow-up. Calculations were

386

performed using PASS statistical software version 15.0.2.

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Process evaluation

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A process evaluation will also be performed to assess the feasibility of the intervention by

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evaluating the acceptability, utility and engagement with the apps. After the blinded 3-month

391

follow-up assessment, all participants in the basic and advanced medication reminder app

392

groups will be administered an additional study questionnaire, adapted from a previous study

393

(Appendix 1).29,30 In addition, a sample of the intervention patients will be invited to

394

participate in focus groups, which will explore in more depth several aspects of the

395

intervention. In this process evaluation, we will examine acceptability and utility of the

396

intervention by asking the participants whether the participants liked or disliked the app,

397

whether the repeated medication reminders were acceptable to them or found to be intrusive,

398

whether they believe the reminders improved their medication-taking behaviour, their

399

opinion on the timing and frequency of the reminders, how was their experience of using the

400

app, and which features they used the most; as well as, whether it was easy to use the app,

401

whether there were any technical difficulties while using the app, and whether the patients

402

would recommend the app to family and friends. The participants in the advanced app group

403

will also answer additional questions in regards to the additional features of the app,

404

including the ability to track taken and missed doses, snooze the reminders and share

405

medication history with family members and medical practitioners. Engagement with the

406

apps will also be evaluated by analysing the usage patterns data obtained from the app

407

developers, including how often participants used the app and which features were used the

408

most. This qualitative evaluation will give insights into the role of interactivity and

409

customisation, as well as identify the features that may make medication reminder apps more

410

effective.

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publications and presentations at international and national conferences. The study will be

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administered at Westmead Hospital, with design and conduct overseen by a steering

417

committee (authors) from The George Institute for Global Health. This committee has

418

expertise in large-scale clinical trials, qualitative research and clinical CVD management.

419

This study will adhere to the National Health and Medical Research Council ethical

420

guidelines for human research. Ethical approval has been obtained from the Western Sydney

421

Local Health Network Human Research Ethics Committee (AU RED HREC/1/WMEAD/3).

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Written informed consent will be obtained from all enrolled participants. Additional

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individual informed consent for data linkage through the Australian Medicare and

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Pharmaceutical Benefits Scheme will also be obtained. Clinical trial registration number:

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ACTRN12616000661471.

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DISCUSSION AND CONCLUSION

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Poor medication adherence is a common and major barrier to achieve improvement in clinical

430

outcomes in patients with CVD. In the last decade, there has been an increasing interest in

431

mHealth research investigating how mHealth interventions, such as text-messaging

432

interventions, can help consumers to manage their health and, more specifically, their

433

medications. More recently, the growing market of smartphones has promoted the use of

434

smartphone apps as potential tools to improve medication adherence. Currently, there is a

435

plethora of health apps available to the public aimed at improving medication adherence;

436

however, there is a lack of evidence on whether they are effective and on which apps’

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characteristics and features would increase engagement and, potentially, improve

438

effectiveness.

439

This study will provide new evidence from a randomised clinical trial on the feasibility and

440

effectiveness of using these commonly available medication reminder apps to improve

441

adherence to cardiovascular medications among patients with CHD. A basic and advanced

442

medication reminder apps, selected through a systematic and stepwise approach to identify

443

high quality apps, will be tested. Medication adherence will be measured using a validated

444

self-report questionnaire,21-23 however more objective outcomes, such as prescription refills

445

data and clinical measurements of blood pressure and cholesterol levels, will also be

446

measured. The process evaluation of the study will explore the acceptability, utility and

447

engagement with the apps and will potentially give insights into the role of customisation and

448

interactivity, as well as the important features that are essential for medication adherence

449

apps to be effective, and how they may be improved.

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This study has some limitations. The study primary outcome is self-reported medication

451

adherence and, although self-reported adherence is associated with overestimation of

452

adherence, it is the simplest, most inexpensive and most useful method of assessing

453

adherence in a clinical setting.3,31 We acknowledge that a 3-months period is a short-term

454

follow-up and that the study has a small sample size; however, our findings will provide

455

preliminary data essential to design a bigger trial with a longer-term follow-up, including

456

providing a better estimate of effect size, enabling accurate powering of a large-scale trial.

457

We also acknowledge that the intervention is not likely to change cardiovascular clinical

458

events and hospitalisations, given the short-term follow-up. If this intervention is shown to be

459

feasible and acceptable, a future larger trial with hard outcomes and a cost-effectiveness

460

evaluation can expand the knowledge in this area.

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461

In conclusion, whilst the use of new technology, such as smartphone apps, is an attractive

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option, evidence is needed to help guide health providers and health services as to whether

463

they should recommend such technologies to patients. Overall, this study will inform future

464

research on the development of mHealth interventions that are likely to be transferrable

465

across chronic diseases and open up a new approach for reinforcement of medication

466

adherence and healthy behaviours.

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CONTRIBUTORS

469

KS, CKC, JC and JR conceived the original concept of the study and the interventions. KS

470

and KR performed the sample size calculations and will lead analysis of the results. KS,

471

CKC, AT are supporting patient recruitment. KS drafted the protocol. All authors contributed

472

to the scientific design of the study and the protocol development, are involved in the

473

implementation of the project and have read and approved the final manuscript.

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ACKNOWLEDGMENTS

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The basic medication reminder app being used in this study is called My Heart My life and

477

was developed by the National Heart Foundation of Australia. The advanced medication

478

reminder app being used in this study is called Medisafe and was developed by the Medisafe

479

Inc. The authors acknowledge the hospital staff who are fully engaged in helping us achieve

480

our target recruitment number and the patients at Westmead Hospital for their support to the

481

study. Use of the MMAS is protected by US copyright laws. A license agreement to use the

482

scale was obtained from: Donald E. Morisky, ScD, ScM, MSPH, Professor, Department of

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Community Health Sciences, UCLA School of Public Health, 650 Charles E. Young Drive

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485 486

COMPETING INTERESTS

487

The authors declare no potential conflicts of interest with respect to the research, authorship

488

and/or publication of this article.

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FUNDING

491

This study is supported by a Vanguard Grant (ID101464) funded by the National Heart

492

Foundation of Australia. KS is funded by a University of Sydney International Postgraduate

493

Research Scholarship. CKC is funded by a Career Development Fellowship co-funded by

494

National Health and Medical Research Council (NHMRC) and National Heart Foundation

495

(APP1105447). JC is a chief investigator on NHMRC programme grant (ID1052555). JR is

496

funded by a Career Development and Future Leader Fellowship co-funded by the NHMRC

497

and the National Heart Foundation (APP1061793).

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ETHICS APPROVAL

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The study was approved by Western Sydney Local Health Network Human Research Ethics

501

Committee.

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3. Osterberg L, Blaschke T. Adherence to medication. N Engl J Med 2005;353(5):487-97. doi: 10.1056/NEJMra050100 [published Online First: 2005/08/05]

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5. Choudhry NK, Fischer MA, Avorn J, et al. The implications of therapeutic complexity on

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8. McKenzie SJ, McLaughlin D, Clark J, et al. The burden of non-adherence to

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9. Santo K, Kirkendall S, Laba T-L, et al. Interventions to improve medication adherence in

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10. International Telecommunication Union: Measuring the Information Society Report

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11. Australia Bureau of Statistics. Household Use of Information Technology, Australia,

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12. Santo K, Chalmers J, Chow CK, et al. m-Health in Coronary Disease Preventive Care.

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13. Free C, Phillips G, Watson L, et al. The effectiveness of mobile-health technologies to

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15. Whittaker R, Borland R, Bullen C, et al. Mobile phone-based interventions for smoking

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cessation. Cochrane Database Syst Rev 2009(4):Cd006611. doi:

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16. Thakkar J, Kurup R, Laba TL, et al. Mobile telephone text messaging for medication

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adherence in chronic disease: A meta-analysis. JAMA Intern Med 2016;176(3):340-

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17. Burn E, Nghiem S, Jan S, et al. Cost-effectiveness of a text message programme for the

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18. Santo K, Richtering SS, Chalmers J, et al. Mobile Phone Apps to Improve Medication

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19. Dayer L, Heldenbrand S, Anderson P, et al. Smartphone medication adherence apps:

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(Greenwich, Conn) 2008;10(5):348-54.

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pharmacy fill rates in hypertensive seniors. The American journal of managed care

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2009;15(1):59-66.

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23. Morisky DE, DiMatteo MR. Improving the measurement of self-reported medication

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nonadherence: response to authors. J Clin Epidemiol 2011;64(3):255-7; discussion

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58-63. doi: 10.1016/j.jclinepi.2010.09.002 [published Online First: 2010/12/15]

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24. Pharmacy Quality Alliance. Update on Medication Quality Measures in Medicare Part D

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25. Okere AN, Renier CM, Morse J. Development and validation of a survey to assess

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patient-perceived medication knowledge and confidence in medication use. J Nurs

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Meas 2014;22(1):120-34. [published Online First: 2014/05/24]

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26. Quilici J, Fugon L, Beguin S, et al. Effect of motivational mobile phone short message

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service on aspirin adherence after coronary stenting for acute coronary syndrome.

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10.1016/j.ijcard.2013.01.252

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automated short message service on medication adherence following acute coronary

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syndrome. European journal of cardiovascular nursing : journal of the Working

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2015;14(2):170-9. doi: 10.1177/1474515114521910 [published Online First:

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2014/02/05]

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medication adherence for patients with coronary heart disease: a randomized

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controlled trial. Patient education and counseling 2014;94(2):261-8. doi:

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10.1016/j.pec.2013.10.027

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29. Chow CK, Redfern J, Hillis GS, et al. Effect of lifestyle-focused text messaging on risk

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factor modification in patients with coronary heart disease: A randomized clinical

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30. Redfern J, Santo K, Coorey G, et al. Factors Influencing Engagement, Perceived Usefulness and Behavioral Mechanisms Associated with a Text Message Support

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Program. PloS one 2016;11(10):e0163929. doi: 10.1371/journal.pone.0163929

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31. Ho PM, Bryson CL, Rumsfeld JS. Medication adherence: its importance in cardiovascular

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outcomes. Circulation 2009;119(23):3028-35. doi:

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http://dx.doi.org/10.1161/CIRCULATIONAHA.108.768986

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LEGENDS:

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Figure 1: MedApp-CHD flow-diagram

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Patient number

Study ID |__|__|__|-|__|__|__|__|

Thank you for your participation in the MedApp-CHD Study. We seek your feedback about the smartphone apps so we can improve it in the future. All responses are strictly confidential. Today’s Date:

Day _________/ Month _________/ Year _________

PART A – Medication knowledge Please read each statement below and tick one option for each. 1) I can list the names of all my medications I am currently taking.     Strongly agree Agree Neutral Disagree

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2) I can describe when to take all my prescribed medications.  Strongly agree

 Agree

 Neutral

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 Disagree


 Disagree


3) I can describe how to take all my prescribed medications.  Strongly agree

 Agree

 Neutral

rr

4) I confident I know what all my prescribed medications are for.  Strongly agree

 Agree

 Disagree


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PART B – Smartphone apps

 Neutral

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In the last 3 months, did you have access to Medisafe™ app or My heart my life™ app?  Yes  Go to Part C  No

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If no, did you use any other apps to help you take your medication?  Yes PART C – Feedback about the smartphone apps

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Please read each statement below and tick one option for each. a) I found it useful to have my medication list on my smartphone     Strongly agree Agree Neutral Disagree

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 No


b) I found it useful to set reminders to take my medication on the smartphone      Strongly agree Agree Neutral Disagree Strongly disagree


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Patient number

Study ID |__|__|__|-|__|__|__|__|

c) I found it useful to be able to track my measurements (e.g. blood pressure and sugar levels) in the smartphone app      Strongly agree Agree Neutral Disagree Strongly disagree d) The reminders helped me remember to take my medicines every day in the correct time      Strongly agree Agree Neutral Disagree Strongly disagree

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e) I found it easy to download the smartphone app    Strongly agree Agree Neutral

 Disagree


 Disagree


g) I found it easy to set up the reminders in the smartphone app     Strongly agree Agree Neutral Disagree


h) I found it easy to track my measurements in the smartphone app     Strongly agree Agree Neutral Disagree


i) I found it convenient to have this app on my smartphone     Strongly agree Agree Neutral Disagree


f)

I found it easy to use the smartphone app    Strongly agree Agree Neutral

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j) How often did you set up the reminders?     3 or more times Twice a day Once a day Weekly/Not per day regularly k) How often did you track your measurements in the smartphone app?     Daily 2 or more times Once a week Lessa than a week weekly l) How often did you have any technical issues with the smartphone app?     Daily Weekly Monthly Less than monthly m) I will continue using the smartphone app     Strongly agree Agree Neutral Disagree

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 Never

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 Never

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 Never  Strongly disagree

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Patient number

Study ID |__|__|__|-|__|__|__|__|

n) I would recommend the smartphone app to family and friends     Strongly agree Agree Neutral Disagree


Additional comments Please provide any further comments or suggestions about the smartphone app. ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________

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Patient number

Study ID |__|__|__|-|__|__|__|__|

PART D – Additional features of the Medisafe™ app Did you have access to the Medisafe™ app?  Yes  Go to Part E  No  Finished. PART E – Feedback about the additional features Please read each statement below and tick one option for each. o) I found it useful to be able to snooze the reminder    Strongly agree Agree Neutral

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 Disagree


 Disagree


p) I found it useful to track my taken and missed doses  Strongly agree

 Agree

 Neutral

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q) I found it useful to be able to share my medication history with my family and health professionals      Strongly agree Agree Neutral Disagree Strongly disagree

rr

r) I found it useful have additional information about my medication in the smartphone app  Strongly agree

 Neutral

 Disagree


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Additional comments

 Agree

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Please provide any further comments or suggestions about the smartphone app.

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________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________

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Item No


Description

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Title

1


______1 ______

Trial registration

2a


___3 and 21_____

2b


______NA______

Protocol version

3


Funding

4


______22_______


5a


____1 and 21-22_

5b


5c


5d

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______NA______

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____1 and 20____

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___20-21_______

_____NA_______

1


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6a


____5-7______

6b


_____6-7_______

Objectives

7


_____7-8_______

Trial design

8


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______8______

Study setting

9


_____8_______


10


_____9_______

Interventions

11a


____10-16_____

11b


11c


_____NA______

11d


___12-13_____

Outcomes

12



13


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_____NA______

2


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Sample size

14


_____19____

Recruitment

15


____9-10______


Fo

rp

Sequence generation

16a



16b


____8-9______

Implementation

16c


____8-10______

Blinding (masking)

17a


__8-9 and 16-17__

17b


_____NA______

ee

rr

ev


iew

on

ly

18a


18b


____16-17______

3


BMJ Open

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48

Page 38 of 39

Data management

19


____16-17_____

Statistical methods

20a


___18-19_____

20b


____18-19______

20c



Fo

rp

_____18-19____

ee

rr

21a


21b


Harms

22


_____NA______

Auditing

23


_____NA_____


ev

iew

on

ly


24


____20______

Protocol amendments

25


_____20______

4


Page 39 of 39

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48

Consent or assent

BMJ Open

26a


26b


Confidentiality

27



28


Access to data

29



30


_____NA______


_____20______

31b


_____21-22_____

31c



32


____Appendix___


33


____NA_______


Appendices

Fo

rp

ee

rr

ev

iew

on

ly

____9-10______

_____22______

_____20-22____

____NA_______

