Impact of Hourly Rounds Implementation on Obstetric

Impact of Hourly Rounds Implementation on Obstetric Patients’ Perception of Care

by Elena Lobatch

DNP Project submitted to American Sentinel University December 8, 2017

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AMERICAN SENTINEL UNIVERSITY

The DNP Project Committee for the DNP Project of Elena Lobatch Impact of Hourly Rounds Implementation on Obstetric Patients’ Perception of Care

DNP Project Chair: EM Vitug Garcia DHEd, DNS, MA, RN, FN-CSp, FACLNC Committee Member: Sandra Wise, PhD, RN

Date of Final Defense: December 8, 2017

iii Abstract Healthcare organizations in the United States embrace multiple challenges in order to provide affordable and high quality care to consumers. Major stakeholders, such as Medicare and Medicaid, task hospitals with accepting patients’ perception of care as one of important quality metrics. Hospital Consumer Assessment of Healthcare Providers and Services (HCAHPS) survey became an important publicly reported tool for federal, state and private payers as well as healthcare consumers in comparing patients’ perception of quality of care received in hospitals. Hourly rounds (HR) have been identified as a successful strategy in improving medical and surgical patients’ clinical outcomes (Studer Group, 2007), contributing to increase in patients’ perception in communication with nurses and satisfaction with hospital stay (Ford, 2010; Meade et al., 2006; Olrich et al., 2012). Literature search, however, revealed a lack of evidence demonstrating benefits of HR on postpartum/Mother Baby Units (MBU) for obstetrical patients. This DNP project examined a possible impact of implementation of nursing staff HR on patients admitted to a MBU of a metropolitan hospital in northeastern part of the US and patients’ perception of communication with nurses and likelihood to recommend the hospital, as evidenced from HCAHPS surveys results. Keywords: communication with nurses, HCAHPS survey, hourly rounds, likelihood to recommend the hospital, obstetric patient

iv Table of Contents SECTION 1: INTRODUCTION .................................................................................................... 1 Background of the Problem ........................................................................................................ 5 Review and Summary of Relevant Literature............................................................................. 9 Statement of the Problem .......................................................................................................... 19 Purpose of the Project ............................................................................................................... 20 Significance of the Project ........................................................................................................ 22 Nature, Scope and Limitations of the Project ........................................................................... 24 Theoretical Framework ............................................................................................................. 30 Definition of Terms .................................................................................................................. 33 Summary ................................................................................................................................... 34 SECTION II: METHODS............................................................................................................. 37 Introduction ............................................................................................................................... 37 Project Design ........................................................................................................................... 40 Setting and Sample ................................................................................................................... 41 Instrumentation ......................................................................................................................... 44 Data Collection ......................................................................................................................... 45 Data Analysis Methods ............................................................................................................. 46 Data Management Methods ...................................................................................................... 49 Ethical Considerations .............................................................................................................. 50 Internal and External Validity................................................................................................... 50 Summary ................................................................................................................................... 52 SECTION III: RESULTS AND DISCUSSION OF FINDINGS ................................................. 54 Introduction ............................................................................................................................... 54 Summary of Methods and Procedures ...................................................................................... 56 Summary of Setting and Sample Characteristics ...................................................................... 60 Major Findings .......................................................................................................................... 72 Conclusion ................................................................................................................................ 82 Implications for Nursing Practice ............................................................................................. 83 Discussion ................................................................................................................................. 85 Recommendations ..................................................................................................................... 87

v Conclusions and Contributions to the Profession of Nursing ................................................... 88 References ..................................................................................................................................... 90 Appendix A ................................................................................................................................... 99 Appendix B ................................................................................................................................. 100 Appendix C ................................................................................................................................. 101 Appendix D ................................................................................................................................. 106 Appendix E ................................................................................................................................. 112 Appendix F.................................................................................................................................. 117

1 SECTION 1: INTRODUCTION American healthcare industry is in the process of undergoing rapid changes. Historically, Medicare, Medicaid, and private insurance companies provided reimbursements to healthcare institutions based on “fee for service” method (Ginsburg, 2012). Regardless of outcomes, hospitals were reimbursed for services, diagnostic procedures, and treatments patients received. According to State Health Care Cost Containment Commission (2014), the cost of healthcare in the United States of America has skyrocketed in recent years, bringing the expenditures to nearly double of what other developed countries spent on healthcare. American citizens’ health parameters are not better than that of people living in other developed countries. State Health Care Cost Containment Commission (2014) reported that healthcare quality in America in categories such as infant mortality, life expectancy, diabetes, chronic heart and lung conditions is either lower than average or at average mark at best, when compared with other developed countries. According to the 2014 report by the Commonwealth Fund, for example, life expectancy of an average American in 2013 was about 78.8 years, when the median life expectancy of citizens in high-income countries, members of Organization for Economic Co-operation and Development (OECD), was 81.2 years (Squires and Anderson, 2015, p. 7). Infant mortality in the U.S. in 2011 was “6.1 deaths per 1000 live births” (Squires and Anderson, 2015), when compared to 3.5 deaths for OECD countries. Chronic conditions were more prevalent in the U.S. adults 65 years of age and older (68 percent) as opposed to citizens of United Kingdom (33 percent) and Canada (56 percent) (Squires and Anderson, 2015, p. 7). In an effort to ensure that American healthcare consumers receive high quality healthcare at a reasonable cost, Centers for Medicare and Medicaid Services (CMS) initiated a transition

2 from the ”fee for service” to a “pay for performance” (P4P) modality (CMS, 2011). CMS introduced value-based purchasing (VBP) model for in-patient healthcare institutions in 2012. According to Hospital Inpatient VBP Program (CMS, 2011), hospitals have to meet several rigorous performance standards in order to benefit from the incentive payment program from Medicare and Medicaid. Along with numerous quality measures, CMS introduced Hospital Consumer Assessment of Healthcare Providers and Services (HCAHPS) survey to hospitals around the country and healthcare consumers. Hospitals strive to improve HCAHPS scores that reflect patients’ perception of care, while in the hospital, in order to benefit from return of percentage of potential revenue for the services rendered. Hourly rounds (HR) have been identified as a successful strategy in improving patients’ clinical outcomes in multiple areas, such as falls prevention, maintaining skin integrity, adequate pain management, and a decrease in number of call bells (Halm, 2009). Multiple researchers studying the effects of HR on clinical outcomes concluded that implementation of HR on medical surgical units contributed to increase in patients’ perception in communication with nurses as well as enhanced patient satisfaction with hospital stay, and linked HR to hospitals’ success in improving patient safety and quality of care (Ford, 2010; Meade et al., 2006; Olrich et al., 2012; Rondinelli et al., 2012). The studies supported effectiveness of HR in decreasing patient falls in medical surgical patient population, decreasing the number of call bells, and improving patient satisfaction. Lowe and Hudgeson (2012) found a correlation between HR and, along with increase in patient safety, an improvement in pain management, and decrease in pressure ulcers. Kessler (2012) reported an increase in staff satisfaction as a result of HR.

3 A large metropolitan hospital in northeastern part of the United States, where the DNP project was conducted, meets and exceeds the majority of clinical quality metrics for government’s VBP program. The institution struggles, however, to bring hospital’s HCAHPS scores up to 50th percentile, in order to successfully collect the full amount of revenues for the services rendered to the patients. Mother Baby Unit (MBU) of the hospital is busy with accepting over 3800 admissions per year. Although overall patient satisfaction with the care on MBU averages at about 80 to 83%, the overall rating of the hospital, communication with nursing staff, and likelihood to recommend the hospital by adult obstetric patients fall below 50th percentile. Executive management of the hospital and nursing leadership team anticipate that HR implementation on MBU will increase obstetric patients’ HCAHPS ratings of the hospital, which in turn will improve overall HCAHPS scores for the hospital. Hospital executives tasked nursing and medical leadership teams with developing a strategy in achieving an increase in HCAHPS scores to above 50th percentile for the institution. After reviewing options, hospital leadership team decided to adopt staff HR as the principal improvement strategy. Implementation of HR was rolled out through the whole hospital beginning late December 2015 - January 2016, as the single most important intervention in striving to reach 50th percentile in HCAHPS rating. MBU, where HR were not rigorously conducted prior to the rollout, was included in hospital-wide initiative as well. In spite of a strong research evidence of positive correlation between HR and quality of patient care and patient experiences on medical surgical units of a hospital (Deitrick et al., 2012), the literature search failed to reveal any significant evidence of similar correlation between HR and obstetric patients’ experiences. Searches in CINAHL, ProQuest, Ovid, Google Scholar and Nursing Reference Center did not discover studies that examined and/or supported a correlation

4 between HR for obstetric patients on a MBU and improvement in patients’ perception of quality of care and increase in patients’ HCAHPS scores. There is a strong need for a study that will examine a possible impact of HR conducted by registered nurses (RNs) and patient care associates (PCAs), auxiliary personnel, on MBU and obstetric patients’ perception of communication with nurses and patients’ likelihood to recommend the hospital as evidenced from HCAHPS surveys, when comparing HCAHPS results prior to initiation of HR on MBU and after the HR rollout on the unit. The results of the study will add to the body of evidence by demonstrating a possible correlation, or a lack thereof, between HR on MBU and patients’ HCAHPS responses about communication with nurses and likelihood to recommend the hospital domains. The study focused on examining possible changes in obstetric patients’ perception of communication with nurses and likelihood to recommend the hospital, as evidenced from HCAHPS surveys submitted by obstetric patients discharged from MBU of a large metropolitan hospital located in northeastern part of the United States as a result of HR implementation on MBU. The study compared HCAHPS results from 3rd and 4th quarters of 2015, prior to HR implementation on MBU, and from 3rd and 4th quarters of 2016, after HR implementation. The HCAHPS results for “Communication with Nurses” and “Likelihood to Recommend” the hospital were obtained from Press Ganey, hospital’s official vendor in distributing and processing patients HCAHPS surveys, website. Section I of the paper focused on describing the background of the problem and the need for the DNP project. Literature review on the HR implementation and correlation with changes in patients’ perception of communication with nurses and likelihood to recommend the hospital as well as possible limitations of the reviewed research studies was discussed. Section I of the

5 paper contained problem statement and purpose of the DNP project, including significance and feasibility of the study as well as potential barriers for the project. Donabedian’s theory on quality of care (1988) was used as the theoretical framework for the study. Donabedian’s triad of structure – process – outcome model is widely used as a theoretical basis for quality improvement efforts in healthcare (Glickman et. al., 2007; Moore et al., 2015). In the study, a MBU of a large metropolitan hospital in northeastern region of the US was identified as a structure, implementation of the HR rounds by the nursing staff – as process, and changes in HCAHPS scores pertaining to communication with nurses and likelihood to recommend the hospital – as outcomes. Background of the Problem HCAHPS survey is a tool developed by CMS, allowing consumers to compare hospitals based on patients’ perception of quality of care provided. HCAHPS is a part of assessed hospital’s performance standards. HCAHPS results are available to general public on a “Hospital Compare” website offered by CMS. Former patients rate hospitals in several domains included in HCAHPS surveys. A survey consists of multiple choice questions about nurses’ and physicians’ care and communication, hospital environment, and pain management. Surveys also include questions about assistance with toileting, understanding how to manage health after discharge from the hospital, as well as overall rating of the hospital and likelihood to recommend the hospital to others (HCAHPS Survey, 2015). The multiple choices answer options to the questions are: “always”, “usually”, “sometimes” and “never”. “Always” is the only option that is taken into consideration, when hospitals’ HCAHPS scores are computed and compared. When rating a hospital, patients use the scale from 0 – “worst hospital possible” to 10 – “best hospital possible”. Only ratings of 9 and 10 are counted. Hospitals that achieve HCAHPS scores at or

6 above 50th percentile receive about 25% of 2% of hospital’s total revenues (CMS, 2016), originally withheld by Medicare and Medicaid, pending HCAHPS scores results evaluation. Achieving HCAHPS results above 50th percentile first became a primary focus for the large metropolitan hospital in northeastern part of the United States in 2012, when CMS introduced patients’ responses gathered from the HCAHPS surveys as a part of quality performance metrics that must be met by in-patient healthcare organizations around the country. In accordance with CMS VBP, a seemingly modest amount of two percent of total revenues is withheld from hospitals, pending hospitals’ ability to demonstrate improvements in patient care, safety and quality, including patients’ HCAHPS surveys’ scores analysis. In-patient healthcare organizations that achieve HCAHPS scores at or above 50th percentile are eligible for a return of withheld revenues, which translates into substantial amounts of money. At a time of drastic changes in healthcare and with VBP program reimbursement model, collecting every dollar in revenues becomes an issue of survival. According to Dutta and Abbas (2015), HCAHPS results attributed to about 30% of value-based purchasing funds that could potentially be obtained by high performing hospitals in 2015. As outlined by CMS (2016), in 2017 HCAHPS surveys “weigh” 25% of potential incentives to be collected by high performing hospitals. Executive leadership of the hospital, where the DNP project was conducted, is determined to ensure implementation of measures, essential to improving HCAHPS results, and raising the scores above 50th percentile. Nursing and medical leadership of the hospital are tasked with designing and implementing processes that will result in accomplishing the task of improving and sustaining HCAHPS scores at or above 50th percentile. Among several suggested strategies in improving patients’ perception of quality of care in the hospital, such as quality of food and cleanliness of the hospital, HR were DNP as main intervention that all units

7 of the hospital will implement. A large obstetric patient population (over 3800 births per year) contributes to a substantial number of discharges, hence, a large number of obstetric patients receive HCAHPS surveys, and responses from obstetric patients impact hospital HCAHPS scores significantly. According to US Department of Labor (2013), a woman is the major decision maker about healthcare in the family. Women are the biggest healthcare consumers as well. Positive experiences of obstetric patients in the hospital are likely to ensure a return for subsequent deliveries and potentially contribute to women’s family members coming to the same hospital, when a need for hospitalization arises, ultimately leading to an increase in volume and revenues of the hospital. Since positive obstetric patient experiences can prospectively increase financial gain of the hospital, implementation of HR on MBU became the major quality improvement project for 2016. HR conducted by nursing staff on every unit of the hospital follow the same algorithm: every RN and PCA rounding on a patient, must ask the patient questions about pain level, positioning, personal belongings, and the need to use the restroom (proactive toileting). Studer (2007) claimed that the 4 Ps: pain, positioning, possessions and “potty” (toileting) are the main causes for patients’ alteration in comfort and reasons to press a call bell. The original quasiexperimental study by Meade et al. (2006), performed on 27 units (medical, surgical, and combined medical-surgical units) of 14 hospitals around the country, established that regular rounds, conducted by nursing staff, performing 4 Ps assessment, had a strong correlation with decrease in call lights, pressed by the patients, increase in patient safety, decrease in falls, decrease in pressure ulcers and better patient experiences. Numerous studies that replicated Meade et al.’s (2006) original study delivered similar results. Ford (2010) and Olrich et al. (2012), for example, concluded that HR by RNs and auxiliary nursing personnel led to increase

8 in patient safety, accuracy of medication administration, decrease in falls and skin breakdown, and improved patients’ perception of care and satisfaction with hospital stay. In spite of a significant number of studies supporting correlation between HR and patient experiences on medical surgical units, there is a limited body of evidence supporting any correlation between HR and obstetric patients’ perception of care and experience on MBU/postpartum units, although due to significant number of discharges, obstetric patients’ surveys potentially have a great impact on a hospital’s overall HCAHPS results. Galuska (2011) mentioned some significance of HR on Mother Baby units in preventing newborn falls by identifying mothers that fell asleep, while holding newborns, and assisting with putting the newborns in bassinets. However, the author of the article emphasized that the staff did not interrupt safely sleeping mother-baby dyad with the rounding. In a poster presentation at 2010 Association of Women's Health, Obstetric and Neonatal Nurses (AWHONN) National Convention, Brewer et al. (2010) mentioned a correlation between modified HR on maternity patients at the hospital and patients’ perception of nursing care and overall hospital experiences. While acknowledging the lack of evidence about correlation between HR on maternity units and patients’ experiences, Brewer et al. (2010) presented only anecdotal information on the subject in a poster presentation. Authors did not specify the meaning of “modified” rounds on maternity patients, or provide further details about the project. According to Press Ganey (2013), among many domains, surveyed in HCAHPS questionnaire, communication with nurses and likelihood to recommend the hospital play the most important role in patients’ perceptions of quality of care in a healthcare institution, and have a strong correlation with patients’ overall ratings of the hospital, a measure directly related to VBP reimbursement. Wolosin et al. (2012) noted a positive correlation between patients’

9 perception of communication with nurses and overall ratings of the hospital. Kutney-Lee, et al. (2009) argued that “Communication with nurses” and “Likelihood to Recommend” the hospital domains have a major impact on patients’ overall rating of a hospital. The literature searches in CINAHL, ProQuest, Ovid, Google Scholar and Nursing Reference Center did not reveal any studies examining effects of regular rounding on MBU on obstetric patients’ perception of hospital care, or correlation between HR and obstetric patients’ experiences. There is no clarity on whether the HR are not conducted routinely on maternity units, or there was a lack interest in studying the correlation between HR and obstetric patients’ experiences. The absence of existing knowledge about the subject justifies the urgent need for a project that examines a possible impact of HR on obstetric patients’ perception of care on MBU. The DNP project was a retrospective study of HR impact on obstetric patients’ perceptions of care as evidenced by comparing HCAHPS responses to questions addressing communication with nurses and likelihood to recommend the hospital before HR implementation on MBU and after. Review and Summary of Relevant Literature The literature review for the project aimed to find and review existing body of evidence that explores the concept of nursing staff HR and effects of HR on patients’ experiences while in the hospital. The ultimate goal of the literature search was to discover studies that examined and/or described a possible impact of nursing staff HR on MBU/postpartum unit on obstetric patients’ perception of communication with nurses and likelihood to recommend the hospital. Since the DNP project used Donabedian’s theoretical framework, literature search on Donabedian’s framework and use in healthcare research was conducted. Literature search revealed several scholarly articles describing the use of Donabedian’s Quality Model as an

10 appropriate basis for research studies related to hourly rounding and patients’ satisfaction, as well as changes in nursing care (Doran et al., 2014; Rondinelli et al., 2012; Wolf et al. 2014; Yen and Lo, 2004). The literature search utilized CINAHL, ProQuest, Ovid, Nursing Reference Center and Google Scholar. Keywords’ list for the literature search included the following words and phrases: “hourly rounds”, “Hospital Consumer Assessment of Healthcare Providers and Services (HCAHPS) scores”, “obstetric patients”, “communication with nurses”, “likelihood to recommend the hospital”, “managing expectations of obstetric patients”, “patient satisfaction”, “4 Ps of patient rounding”, “value based purchasing”. The search for above key words was limited to the articles published in peer reviewed journals between the years of 2006 and 2016 (Appendix A). There were no limits set for the search on keywords “Donabedian model”, and “theoretical framework”. Theoretical Framework Donabedian’s theory on quality of care (1988) was used as a theoretical framework for the project, identifying the structure, process, and outcome (Appendix B). An MBU at a large hospital in northeastern region of the United States served as a structure/setting for the project, the implementation of nursing staff HR on obstetric patients was identified as a quality improvement method, and changes in HCAHPS scores, pertaining to communication with nurses and likelihood to recommend the hospital, were identified as the outcomes to be analyzed. Donabedian, in the original work in 1966, and later in 1988, acknowledged and stressed the importance of examining the quality of medical care received by patients, suggesting that researches must identify, describe and study specific structures, processes, and outcomes for quality improvement initiatives and/or interventions (Donabedian, 1966; Donabedian, 1988).

11 As Ibn El Haj, et al. (2013) stated, Donabedian’s model has been widely used in healthcare research and by clinicians to examine, implement, and evaluate interventions instituted to enhance quality standards in healthcare. Dubois et al., (2013) stressed the importance of implementing Donabedian’s model as a foundation for quality improvement measures in healthcare, while concentrating on establishing a connection between structure, process, and outcomes. Yen and Lo (2004) utilized Donabedian’s model to study the relationship between nursing care and patient outcomes in Southern Taiwan. The use of Donabedian’s model allowed the authors to identify three essential components for the research in pursuit of discovering a correlation between the elements. The study examined a correlation between structural elements as age, education, and income of the patients, coordination of care and perceived quality of nursing care as processes, in relation to patient comfort, general satisfaction with care, and length of stay in the hospital as results to be studied. Wolf et al. (2014) also used Donabedian’s quality model in a study to evaluate the implementation and effectiveness of nursing caring protocol. The study’s structure consisted of in-patient population and discharged patients, process was identified as caring behaviors, implemented by nurses and outcomes represented by patients’ perception of nursing care and overall satisfaction during hospitalization and post discharge. Doran et al. (2014) applied Donabedian’s model in the study of evidence based practice (EBP) application by the nursing staff caring for medical surgical patients and patients’ episodes of pain, dyspnea, pressure ulcers, falls, and pain level outcomes. Nurses with various degrees of clinical experiences and education and patients with several medical diagnoses were identified as structure, the number of documented visits to patients’ bedside nursing staff accomplished represented the process, and changes in dyspnea episodes, pain level, pressure ulcers, and falls as outcome. Rondinelli et al.

12 (2012) utilized Donabedian’s model in the study of implementation of HR in various hospitals, where structure was identified as the “use of rounding behaviors”, the utilization of various rounding tools, such as clocks logs and boards, was identified as processes, and changes in patients care outcomes and the sustainability of hourly rounds on a unit, as outcomes. All studies presented results that established a relationship between patient outcomes and patients’ perception of nursing care in hospital settings as a result of nursing interventions, such as EBP, coordination of care and implementation of nursing caring behaviors. Donabedian’s model provided an appropriate and effective foundation for each study reviewed. The similarity of the studies to the DNP project consisted of three clearly identified components: structure, process and outcome, so Donabedian’s model was deemed an appropriate model for the DNP project. The structure (inpatient healthcare facility), process, which included quality improvement interventions, and studied outcomes were also comparable. In accordance with Donabedian’s triad model, the MBU of a large metropolitan hospital in the northeastern part of the US served as the structure. HR implementation, an EBP geared toward improving patient safety and experiences while in hospital (Blakley, Kroth and Gregson, 2011; Deitrick et al. 2012), was identified as the process for an improvement. HCAHPS scores pertaining to communication with nurses and likelihood to recommend the hospital before and after HR implementation on MBU were studied as the outcome for the DNP project. Population Population for the project consisted of adult obstetric patients admitted to MBU of a large metropolitan hospital in northeastern region of the US. The literature search revealed a gap in availability of scholarly articles describing/examining an implementation of HR on obstetric patient population. Numerous articles, however, identified adult patients on medical and medical

13 surgical units as population in the studies that examined the relationships between nursing staff HR and various patient care outcomes (Blakley, Kroth, and Gregson (2011); Meade et al., 2006; Olrich et al., 2012). Meade et al. (2006) performed a study of 27 units of 14 hospitals nationwide with a quasi-experimental design examining a correlation between HR and several patient outcomes, including the number of call bells, falls, and patient perception of quality of care. Surveyed patients were those admitted to medical, surgical or combined medical-surgical units. While providing information on average daily census for both “rounding units” (Meade et al., 2006) and control units, the authors did not specify age, sex or other demographic data of the patients on the units. Olrich et al. (2012) replicated Meade’s (2006) study on a medical surgical unit, with a mix of medical patients and patients admitted to the unit after surgery. No patient demographic details were offered in the article. Ford (2010) addressed the specifics of patient population in the study of correlation between HR and patient satisfaction. The sample Ford (2010) studied, consisted of 49 adult alert and oriented patients, who were rounded on by one nurse. Patients’ ages ranged from 21 and 90 years old, with the mean age of 58, 57% were females and 43% were males. Rondinelli et al. (2012) did not elaborate on patient population mix. Blakley, Kroth, and Gregson (2011) indicated that 200 medical-surgical patients were interviewed each quarter between October 3rd, 2008 and June 2009. Authors did not offer demographic details of the sample. The articles by Halm (2009) and Mitchell et al. (2014) presented a comprehensive literature review discussing the impact of hourly rounds on patients’ hospital experiences. However, in both articles the term “population” was generalized as to patients admitted to the hospital, without disclosing specific details about patient population mix or the type of unit patients were admitted to.

14 Intervention The DNP project evaluated RNs and PCAs’ HR on patients admitted to MBU as the intervention. Literature review identified several research studies, describing HR. Studer Group introduced a formal way to conduct hourly rounds in 2005 (Ford, 2010). The nursing staff performing HR on the patients asked the 4P questions, which addressed patient’s pain, position, “potty”, and possessions (Studer, 2007). The sample questions were: “How is your pain?”, “Are you comfortable?”, “Do you need to use the bathroom?”, and “Do you need us to move the phone, trash can, water pitcher or over-bed table within reach?” The goal of HR was to anticipate patients’ basic needs, before the patients had to call for the staff by pressing a call bell (McLead and Tetzlaf, 2015; Rondinelli, 2012; Studer, 2007). Several researchers described HR process involving nursing staff making a personal connection with a patient (Mahoney, 2016; Studer, 2007). Olrich et al. (2012) discussed a list of eight elements that were included in the rounds with 4 Ps questions incorporated, and a question “Is there anything I can do for you?” asked by the staff member before exiting patient’s room. Rondinelli et al. (2012) also suggested asking a question “Is there anything else I can do for you before I leave?” While some research suggested to utilize the use of scripting, while making HR (Studer, 2007), others argued the importance of hourly rounds’ modification to suit the needs of specific patient population. For example, Rondinelli (2012) mentioned that on postpartum unit the question of positioning addressed breast feeding positioning of an infant “at breast”. Halm (2009) strongly suggested customization of HR, depending on a unit and the needs of the patients as well. Studer (2007), Meade et al. (2006), Ford (2010) and Rondinelli (2012) also described hourly rounds education process for the frontline staff and tools used to monitor rounding

15 practices on the units. According to research, staff education on HR ranged from rounding inservices, to educational sessions with clinical nurse specialist, to PowerPoint presentations and modeling of rounding behaviors (Ford, 2010, Rondinelli, 2012, Olrich et al., 2012; Studer, 2007). The tools used to assess frequency of rounds included white boards in the patients’ rooms, various HR logs and charting in patient records (Ford, 2010; Meade et al., 2006; Rondinelli, 2012; Studer, 2007). Evidently, there was no universal way to provide staff education. The lack of a consensus on who should be doing HR became apparent during the literature review. In Ford’s (2010) study, rounds were conducted by an RN, although the word “provider” was used to describe a person, conducting HR. Meade et al. (2006) reported a mix of nursing staff, conducting rounds (both RNs and axillary personnel). Halm (2009) insisted on a strong presence of axillary personnel during HR to ensure that RNs have adequate time to perform other tasks for the patents. With an exception of Rondinelli (2012) briefly mentioning a customization of HR for postpartum unit, no other research provided evidence of HR conducted on postpartum or Mother Baby Units. The literature review revealed another inconsistency in conducting the HR. Although the rounds were labeled as “hourly”, many researchers described variations in the time frame. For example, Studer Group (2007) suggested to conduct rounds hourly between the hours of 6 am and 10 pm, and every 2 hours between 10 pm and 6 am hours. Meade et al.’s (2006) study evaluated some units, where rounds were conducted on hourly basis, and others, where rounded were implemented every two hours. Blakley, Kroth and Gregson (2011) discussed nursing staff rounding on patients every two hours. McLeod and Tetzlaff (2015) suggested even to change the name from “hourly rounds” to “purposeful rounds”, arguing that depending on a unit and

16 situation, there may be no need for HR due to specifics of the unit, patient population and acuity, or the time of the day. Researchers reported an increase in patient satisfaction with nursing care, when HR were conducted. For instance, Blakley, Kroth and Gregson (2011) reported patient satisfaction increase from 3.5 to 3.6 on a scale from 1 (“completely dissatisfied”) to 4 (”completely satisfied”) during the study period, when HR were conducted at least every two hours. The authors, however, did not present any statistical analysis of the data, nor the thorough description of the study sample. In review of clinical evidence on hourly rounds Halm (2009) concluded that although examined studies reported improvements in patients’ perception of nursing care and decrease in call bells and falls, more high quality studies are needed to further explore HR effects on patients’ outcomes in different settings. Comparison Regardless of the differences in the design of reviewed studies, all researchers compared variables of interest before the implementation of HR and after the roll-out of HR on nursing units. Meade et al. (2006) collected baseline data for two weeks prior to HR roll out on number and reasons for call bells, and then for four weeks after the implementation of HR, making data collection last 6 consecutive weeks. The same researchers also compared the number of falls in the 4 week period prior to HR implementation and 4 weeks after. Patient satisfaction data was examined before HR roll out on the unit and a year after, although the authors did not elaborate on the tools used to measure patient satisfaction, or a sample size. Meade et al. (2006) acknowledged also that raw data was not available to researchers for the analysis. Ford (2010) and Olrich et al. (2012) followed Meade et al.’s (2006) protocol collecting preliminary data on call bells and falls two week prior to HR implementation and three weeks after the roll out. Although the sample size was considerably smaller than in Meade et al.’s (2006), who also

17 offered a year later follow up data review, the original time frame for data collection was limited to two to four weeks (Ford, 2010; Meade et al., 2006; Olrich et al., 2012). Outcome Several studies indicated a positive correlation between nursing staff rounding on patients in a hospital and various patient outcomes, including decrease in call bells, reduction in falls and increase in patient satisfaction, improved perception of nursing care and likelihood to recommend the hospital. Meade et al. (2006) reported, for example, that as a result of staff rounds, the total number of call bells for all participating units decreased from 4527 (baseline data for the group, prior to implementation of HR) to 2986. No statistical data analysis, such as statistical significance, was offered. In the group that participated in rounds every two hours the results were 5628 and 4619 respectively. Meade et al. (2006) mentioned an increase in patient satisfaction after implementation of HR, with a more remarkable difference for the units, where rounds were conducted hourly as opposed to units with rounds conducted every 2 hours. No numeric values were provided in the article. Meade et al. (2006) also shared some follow up data a year after the project was concluded. The units that sustained hourly rounds noted an increase in patient satisfaction from 79.9% before implementation of rounding to 88.8%, with percentage of “excellent” ratings raising from 38.2% to 80.1%, and a 60% decrease in patient falls. Ford (2010) reported 52% decrease in call bells, and no falls reported during the time the study was conducted, which may be attributed to HR or a relatively small sample (49 patients), or a brevity of the study (3 weeks). Ford (2010) also mentioned an increase in patient satisfaction with nursing care in the hospital as reported during post discharge phone calls to the patients. There was no mentioning of a specific tool used to measure patient satisfaction.

18 Rondinelli et al. (2012) listed post HR implementation outcomes as well, admitting however, that although several participating sites reported decrease in patients’ falls, pressure ulcers, call bells and increase inpatient satisfaction scores, researchers were unable to complete a “meaningful” analysis of the data. Meade et al. (2012), Ford (2010) and Olrich et al. (2012) did not identify a specific theoretical framework used for the conducted research. Rondinelli et al. (2012) selected Donabedian’s model of structure, process and outcome (Donabedian, 1988) as a theoretical framework for the study. HR implementation, with “material resources, personnel, and constructed methods or items” (Rondinelli et al., 2012) was referred to as structure; interventions performed and leading to outcomes were identified as processes, and “intended result, effect or measure of success” (Rondinelli et al., 2012) were recognized as the outcomes of the study. Summary The DNP project aimed to answer the following question: in obstetric patient population, will implementation of HR impact Communication with Nurses and Likelihood to Recommend the hospital ratings, when comparing HCAHPS scores before HR implementation and after? Literature review utilized CINAHL, ProQuest, Ovid, Nursing Reference Center and Google Scholar. The search proved to be unsuccessful in identifying the scholarly articles examining relationships between HR on obstetric patients and changes in HCAHPS scores pertaining to communication with nurses and likelihood to recommend the hospital, identifying a gap in existing evidence. As many authors indicated, more research is needed to further study correlation between HR and various patient outcomes, such as use of call lights, responsiveness of hospital staff, falls, patient comfort and satisfaction (Halm, 2009; Mitchell et al., 2014).

19 Researchers used large samples for the studies, which eliminates small sample bias (Price et al., 2014). Meade et al. (2006) were successful in surveying a large sample of 46 participating units from 22 various hospitals around the country. Olrich et al. (2012) were able to replicate Meade et al.’s (2006) study with a considerable sample of 4418 discharges in a year, with study conducted in a teaching hospital with 506 beds. Literature search revealed a definite gap in availability of research articles/studies examining relationship between conducting HR on MBU/postpartum units, and specific obstetric patient-related outcomes. None of the reviewed studies were conducted on a postpartum/MBU and, while some researchers identified a positive impact of HR on patients’ perception on communication with nurses (Blakley, Kroth and Gregson, 2011; Ford, 2010), obstetric patients were not among surveyed categories of patients. The DNP project findings will contribute to the body of evidence on relationship between nursing staff HR on adult obstetric patients admitted to MBU and patients’ perception of communication with nurses and likelihood to recommend the hospital. The project may be one of the first studies to examine a possible correlation between HR on an obstetric unit and HCAHPS scores. Statement of the Problem HCAHPS survey is the tool that measures patients’ perceptions of care while admitted to a hospital. HCAHPS results are published and available to healthcare consumers. Furthermore, CMS considers HCAHPS results a vital part of quality metrics hospitals must provide as a part of VBP program, in order to retrieve two to three percent of the revenues, originally withheld by Medicare and Medicaid (CMS, 2011). Only hospitals with HCAHPS scores at or above 50th percentile are eligible to receive the money. Although meeting and exceeding several vital CMS-mandates quality metrics, the hospital, where the DNP project was

20 conducted, currently falls below 50th percentile in HCAHPS scores. With severe financial constraints, every opportunity to collect all available dollars in revenues becomes imperative for the survival of organization. In an effort to improve HCAHPS scores, thus ensuring acquiring a higher percentage in revenues, the executive and nursing leadership of the hospital are determined and fully committed to invest considerable time and resources in an institution-wide implementation of nursing staff’s HR on all patients admitted to the hospital. Research revealed that implementation of HR on medical surgical units demonstrated significant improvements in patient safety and outcomes, such as decrease in falls, and an increase in patient experience (Blakley, Kroth and Gregson, 2011; Meade et al., 2006; Mitchell et al., 2014; Rondinelli et al., 2012). However, the literature search in CINAHL, ProQuest, Ovid, Google Scholar and Nursing Reference Center failed to identify studies exploring a potential correlation between HR and obstetric patients’ experiences and perception of care in hospital. With HR implementation on MBU, there was a strong need to examine whether nursing staff’s (RNs and PCAs) HR on patients admitted to a MBU will contribute to a change in obstetric patients’ HCAHPS scores pertaining to communication with nurses and likelihood to recommend the hospital, as evidenced from comparing HCAHPS surveys’ scores received from patients discharged from MBU prior to HR implementation and six months after HR roll-out on MBU. The DNP project was a retrospective quantitative study examining whether HR roll-out on MBU contributed to changes in obstetric patients’ perception about communication with nurses and likelihood to recommend the hospital. Purpose of the Project The purpose of the DNP project was to determine whether the implementation of nursing HR on MBU impacts obstetric patients’ perception of care by comparing changes in HCAHPS

21 scores in communication with nurses and likelihood to recommend the hospital prior to implementation of HR and after. Since obstetric patients attribute to a significant number of hospital discharges, a potential increase in HCAHPS scores submitted by patients, discharged from MBU, strongly impacts hospital-wide HCAHPS results, helping to bring the scores to above 50th percentile, thus, potentially increasing hospital revenues from Medicaid, Medicare, and private insurances (CMS, 2011). Multiple research studies established a correlation between HR and improvements in patients’ safety, comfort and hospital experiences. Meade et al. (2006) conducted one of the first studies, which was conducted on 27 medical, surgical and combined medical surgical units of 14 hospitals nationwide. The researchers reported a positive correlation between HR and decrease in patients’ call bells, decrease in falls and pressure ulcers and increase in patient satisfaction. Ford’s (2010) and Olrich et al.’s (2012) studies supported Meade et al.’s (2006) findings as well, providing more evidence in favor of implementing HR. Since there is a gap in literary evidence exploring a correlation between HR on postpartum/MBU and obstetric patients’ hospital experiences, as evidenced from HCAHPS scores submitted by patients discharged from MBU, there is a strong need for a quantitative study examining a possible relationship between nursing staff’s HR on patients admitted to MBU (independent variable) and obstetric patient population experiences with “Communication with Nurses” and “Likelihood to Recommend” the hospital before and after HR roll out on MBU (dependent variable), as evidenced from HCAHPS scores collected from adult patients discharged from MBU. The DNP project examined a possible change in obstetric patients’ scores in “Communication with Nurses” and “Likelihood to Recommend” the hospital questions before and after of HR implementation, because research indicated close relationship between HCAHPS scores in these domains and overall rating of a hospital. Shaffer and Tuttas (2008)

22 indicated a positive correlation between patients’ ratings in communication with nurses and overall ratings of the institution. Gupta et al. (2009) also emphasized a positive correlation between “Communication with Nurses” domain in patients’ HCAHPS surveys, patients’ pain relief and overall rating of the hospital. The DNP project can be potentially replicated by other postpartum units/MBU of various hospitals around the country, and study results will add to the body of knowledge on HR implementation on postpartum/MBU. The DNP project focused on answering the question: In obstetric patient population, will implementation of HR impact Communication with Nurses and Likelihood to Recommend the hospital ratings, when comparing HCAHPS scores before HR implementation and after? The DNP project assumed a null hypothesis that there is no statistically significant relationship between implementation of HR on MBU of a large metropolitan hospital in northeastern region of the U.S. and change in patients’ perception of “Communication with Nurses” and “Likelihood to Recommend the Hospital” (p is equal or more than .05). Significance of the Project The goal of HR implementation on MBU is to support patient comfort, safety and perception of care, which, ultimately, would lead to improvements in HCAHPS scores. Due to a large number of discharges from MBU (about 3800 per year), establishing a positive relationship between HR implementation on MBU and HCAHPS scores should contribute to a rise in hospital-wide HCAHPS scores and, potentially, to an increase in hospital revenues, essential for hospital financial sustainability in current economy. Dutta and Abbas (2015) suggested that HCAHPS results attribute about 30% of value-based purchasing funds, potentially available to high performing hospitals in 2015. Besides, the evidence of HR’s positive impact on obstetric

23 patients’ hospital experiences will provide the rationale to nursing leadership for an expansion of HR best practices to maternity/postpartum/MBU of other hospitals within the healthcare system. Since implementation of HR contributes to increase in patient safety and satisfaction with care (Mitchell et al., 2014), establishing a connection between implementation of HR on MBU and obstetric patients’ perception of communication with nurses and likelihood to recommend the hospital may validate the need for establishing HR on postpartum/MBU, and, possibly, improve obstetric patients’ hospital experiences. Senti and LeMire (2011) concluded that obstetrical patients, who gave high ratings of communication with nurses, rated healthcare institution significantly higher as oppose to patients, who gave lower ratings for communication with nurses. The DNP project presented a contribution to a limited body of evidence about significance of HR implementation on a Mother Baby Unit of a hospital. Literature review was not able to identify studies examining effects and/or possible benefits of HR on obstetric patients admitted to a MBU of a hospital. Similarly to Meade et al. (2006) and Mitchell et al.’s (2014) studies, the DNP project evaluated effects of HR on patients’ perception of care, specifically, on communication with nurses and likelihood to recommend the hospital. As in Ford (2010), Olrich et al. (2012) and Meade et al.’s (2006) studies, baseline data collected prior to HR implementation on MBU was compared to data collected after HR roll out. Unlike existing studies that examined responses of medical surgical patients, the DNP project concentrated on analyzing changes in obstetric patients’ responses to HCAHPS questions about communication with nurses and likelihood to recommend the hospital, as a result of HR implementation on MBU. The results of the DNP project were aimed to validate the need for a HR structure on Postpartum/MBU. The study design and methodology presents an opportunity for a replication at a different hospital to

24 enhance the body of knowledge on a relationship between HR implementation on a postpartum/MBU and obstetric patients’ perceptions of care. Nature, Scope and Limitations of the Project The DNP project was a retrospective quantitative study, examining a an impact of nursing staff HR implementation on MBU of a large metropolitan hospital in northeastern region of the US on obstetric patients’ perception of hospital experiences pertaining to communication with nurses and likelihood to recommend the hospital as evidenced by HCAHPS scores, submitted by patients discharged from MBU. The study compared obstetric patients’ HCAHPS scores of Communication with Nurses and Likelihood to Recommend from 3rd and 4th quarters of 2015 (prior to HR implementation on MBU) and 3rd and 4th quarters of 2016 (after implementation of HR). The probability sampling method was used while establishing a sample for the study. G-Power 3.1.9.2 software (Faul et al., 2007) was used to perform the priory test to determine the sample size for the DNP project. With the effect size of .5, and type 1 error probability of .05, the sample size had to have between 53 responses for each group (before and after implementation of HR), if the power of .8 was to be chosen, and 92 responses for each group (before and after HR implementation), if the power of .95 was to be chosen. Donabedian’s structure – process – outcome model served as a theoretical framework for the DNP project, with MBU of the hospital as the structure/setting, nursing staff HR implementation as the process, and changes in HCAHPS scores in communication with nurses and likelihood to recommend the hospital as the outcomes to be examined. Kobayashi et al. (2010) confirmed the reliability and validity of the use of Donabedian’s theoretical model, when studying interventions pertaining to patients’ experiences while in hospital. Data collection for the DNP project was conducted after American Sentinel University Institutional Review Board (IRB) approval of the

25 DNP project, May 22nd, 2017. An approval for the study and data use from Press Ganey website was granted by the Chief Nursing Officer of the hospital. Scope The scope of the project targeted patient population consisting of all adult patients discharged from MBU, including postpartum patients after vaginal deliveries, cesarean sections, and antepartum patients. Generally, an accessible sample population for the study is selected from the target population. The adequacy of a sample would be based on a researcher’s opportunity to have access to population database in order to engage participants, and participants’ availability and willingness to participate in research (Creswell, 2008). The DNP project incorporated the sample available from Press Ganey (hospital‘s official vendor for HCAHPS surveys distribution and collection), thus, the accessible sample population consisted of the patients, who received HCAHPS surveys upon discharge from MBU from Press Ganey, answered and mailed the responses back. The accessible sample population for the study represents target population, consisting of obstetric patients discharged from the MBU. Probability sampling consists of randomly selecting a study sample (Tappen, 2011). Population sample for the DNP project was randomly selected from a list of all eligible discharges, in accordance with CMS HCAHPS Quality Assurance Guidelines (CMS, 2012). The hospital submits the entire list of all eligible discharged patients to Press Ganey, where an appropriate number of patients that will receive an HCAHPS survey is selected randomly. The sampling is conducted by Press Ganey continuously through the month, using the same sampling technique. For example, every 3rd discharged patient receives a HCAHPS survey by mail. This strategy is implemented to ensure a large sample, randomness and minimization of introduction of bias (Tappen, 2011) and in accordance with CMS guidelines (CMS, 2012). Researcher’s bias

26 during sample selection for the DNP project was eliminated, since the researcher did not participate in sample selection. Exclusion criteria for HCAHPS survey participation are outlined by CMS (2015). Patients discharged to a rehab facility or nursing home, “No-Publicity” patients: those who submitted a written request not be contacted, prisoners, patients with foreign permanent home addresses, and patients with primary psychiatric diagnoses are not eligible to receive an HCAHPS survey. The DNP project was conducted in a hospital setting: an acute care facility located in the northeastern region of the U.S., with obstetric service accommodating about 3800 deliveries per year. HR by all RNs and PCAs is an intervention that was implemented on MBU. The entire nursing staff has been educated on HR implementation process: RNs and PCAs participated in interactive educational sessions conducted by the nurse manager of the unit, who explained the significance and expectations for HR: smiling, knocking on the patient’s door, asking for a permission to enter the room, 4Ps of hourly rounding (pain, “potty”, positioning and possessions (Studer, 2007)), and establishing a personal connection with the patient. The didactic portion was followed by a role play simulation sessions, where the nursing staff took turns practicing HR with a “patient” in a hospital room. In order to ensure the designed way HR are conducted, the nurse manager launched a coaching phase on the unit starting January 2016, where every RN and PCA rounds with the nurse manager. Nursing staff’s rounding competencies were validated by the nurse manager via direct observation of rounding once a month for three months (February, March, and April 2016) and then quarterly. The nurse manager observed MBU staff rounding on obstetric patients and coach rounding behaviors, ensuring that the nursing staff was competent and compliant with HR process. The nurse manager of MBU conducted daily interviews with obstetric patients admitted to the hospital to seek feedback about staff rounding.

27 Limitations Several limitations for the DNP project were readily identified. An implementation of another patient experience improvement initiative affecting patients’ perception of communication with nurses and likelihood to recommend the hospital could potentially skew the results of the study. A possible reluctance of the nursing staff to consistently follow HR protocol and/or staffing challenges on MBU could interfere with the successful implementation of the project, and affect HCAHPS scores. With the hospital’s choice to mail HCAHPS surveys to eligible participants, there was no guarantee that the survey was filled by a participant personally and not by a family member or a proxy (CMS, 2015). The survey instructions state that the survey must be filled only by the person identified in the cover letter sent with HCAHPS survey. However, an opportunity for somebody other than the patient discharged from MBU to fill out the survey presented another limitation for the DNP project. Sudden changes in the number of responses can cause an “n bias” (Price et al., 2014), presenting another important limitation to validity and reliability of the project, and contribute to altering of the results’ accuracy. Patients’ participation in HCAHPS surveys is voluntary thus the number of responses cannot be controlled. Gupta et al. (2009) identified a “nonresponse bias” as a potential threat to validity of HCAHPS results. The Agency for Healthcare Research and Quality (2003), acknowledged the effects of low response rates on reliability of HCAHPS scores. The developers of HCAHPS survey, however, provided statistical adjustments in attempt to regulate the data in relationship to a “nonresponse bias” (Gupta, 2009). The DNP project was a retrospective study. Kaji et al. (2014) cautioned about possible limitations of a retrospective study design, such as utilization of an available sample that may not

28 necessarily represent study’s target population. Although the DNP project used a sample, available from Press Ganey website, the target population was appropriately represented, since available sample was chosen from the HCAHPS survey responses submitted by obstetric patients discharged from MBU. Thus, this limitation was avoided. Kaji et al. (2014) also discussed opportunities for mistakes, when transferring data into a coding spreadsheet. The data for the DNP project was transferred into a codebook and rechecked several times to avoid transcription mistakes. Delimitations The DNP project analyzed obstetric patients’ HCAHPS scores pertaining to Communication with Nurses and Likelihood to Recommend the hospital domains only, since these domains were identified as the most impactful on overall ratings of a hospital (Agency for Healthcare Research and Quality, 2003; Press Ganey, 2013). The rest of HCAHPS survey responses was not examined. This delimitation was set to ensure palatability of the DNP project’s statistical analysis. Since HCAHPS survey currently consists of 32 questions, a full data analysis would be extremely labor-intensive and unrealistic to accomplish within a reasonable time frame for the DNP project. Contextual factors Contextual factors are important for a researcher in evaluating an opportunity to make a generalized conclusion about a target population. According to Agency for Healthcare Quality and Research (2013), researchers’ awareness of contextual factors and influence on study outcomes may contribute to a better understanding of research outcomes and improve accuracy of future replication studies. Obstetric patient population mix of the hospital, where the DNP project was conducted, is an important contextual factor. Obstetric patients of the hospital are

29 very racially and ethnically diverse, mostly residing within metropolitan area. About 80 percent of obstetric patients have Medicaid and Medicaid-supported healthcare plans, and about 20 percent of patient have commercial health insurance. About 70 percent of obstetrical patients receive prenatal care from faculty practices, which are the clinics affiliated with the hospital. Obstetrical provider covering “service” patients oversees labor, delivery and recovery period of faculty practice patients in the hospital. About 30 present of patients receive prenatal care in private offices, and the private obstetrician is in charge of care patients receive in the hospital. There are certain variations in patients’ educational and income level that may have a significant impact on HCAHPS scores (Price et al., 2014). Since mentioned factors may be potentially relevant to the research outcomes, the results of the study may not be applicable to the hospitals with more homogenous and less diverse obstetric patient population. The DNP project includes demographic data and analysis of the study sample: age, race/ethnicity and highest level of education, available through HCAHPS surveys. There was no anticipated additional cost associated with the DNP project. Although requiring significant resources and time allocation, HR education and implementation roll-out was performed as a part of hospital-wide initiative. Nurse-managers participated in training on HR implementation process and nursing staff education and support on the units. Nursemanager of MBU conducted education for nursing staff as a part for hospital-wide education effort. Didactic training and practice exercises for the staff members were conducted on the unit, mostly during staff’s regular working hours. Some over-time pay to the nursing staff was utilized as well. Didactic portion of the training took about 60 minutes, followed by interactive role-play practice exercises for each nursing staff participant.

30 Theoretical Framework Avedis Donabedian developed a theoretical framework for healthcare quality assessment and improvement in 1966. Although the aim of the original document was to look solely at medical practices and individual practitioners (Donabedian, 1966), Donabedian (1988) elaborated on the theory later on, and further developed the concepts to be applied to a wider varieties of healthcare organizations in need of quality improvement processes. The concept of structure, process, and outcome as essential elements of quality of care assessment and elements’ correlation represents the foundation of Donabedian’s Quality Model. Donabedian (1988) suggested that researches must identify, describe and study specific structures, processes and outcomes for quality improvement initiatives, as well as the correlations, “causal linkages”, between three essential parts of the model. Several researchers emphasized the importance of structure – process – outcome triad (Dubois et al., 2013; Glickman et al., 2007; Moore et al., 2015). Glickman et al. (2007) impressed importance of structure-process-outcome components’ interconnectedness in order to yield improvements in quality. Dubois et al. (2013) stressed the significance of implementing Donabedian’s model as a foundation for quality improvement measures in healthcare, while concentrating on establishing a connection between structure, process and outcomes. Moore et al. (2015) stated that changes in structure and/or processes should result in improvement of outcomes. Multiple researchers agreed that Donabedian’s theoretical framework is acceptable for studies, evaluating relationships between structure, processes, and outcomes for quality improvement efforts in healthcare (Glickman et. al., 2007; Moore et. al., 2015). As Ibn El Haj et al. (2013) indicated, Donabedian’s model has been widely used in healthcare research and by

31 clinicians to examine, implement, and evaluate interventions instituted to enhance quality standards in healthcare. Researchers tested and utilized Donabedian’s structure – process – outcome model in studies related to quality improvement processes in healthcare. Gardner, et al. (2013), for example, utilized Donabedian’s theoretical framework to study quality and safety of services provided by nurse practitioners (NP), where the service settings were identified as structure, NP services - as process, and the effect of NP services on patients – as an outcome. Gardner, et al. (2013) concluded that Donabedian’s model was an acceptable methodology for examining nursing innovations. Kobayashi et al. (2010) successfully implemented Donabedian’s methodology in the study of patient’s perception of nursing care quality, where patients’ surroundings were identified as structure, patient-nurse interactions as process and changes in patient satisfaction as the outcomes. The DNP project used Donabedian’s Quality Model as the theoretical framework (Appendix B). The aim of the study was to establish a relationship between the structure, process and outcomes, where an MBU at a large metropolitan teaching hospital in northeastern region of the US, and patients admitted to the MBU were identified as a structure for the project. The process consisted of nursing staff (RNs and PCAs) implementing HR on patients admitted to MBU. The changes in obstetric patients’ HCAHPS scores in communication with nurses and likelihood to recommend the hospital as evidenced from HCAHPS surveys submitted by the patients, discharged from MBU were considered to be the outcomes for the study. The aim of the study was to establish a possible change in patients’ perception of communication with nurses and likelihood to recommend the hospital (outcome) as a result of nursing staff HR implementation (process) performed on patients admitted to MBU (structure).

32 Literature review revealed a successful use of Donabedian’s model in studies examining relationships between nursing care processes and patients’ outcomes in various settings. Yen and Lo (2004) utilized Donabedian’s model to examine a correlation between structural elements of patients’ age, education and income, coordination of care and perceived quality of nursing care as processes, in relation to patient comfort, general satisfaction with care and length of stay in the hospital as results to be studied. Wolf et al. (2014) used Donabedian’s quality model in a study to evaluate the implementation and effectiveness of nursing caring protocol. The study’s structure consisted of in-patient population and discharged patients, process was identified as caring behaviors, implemented by nurses and outcomes represented by patients’ perception of nursing care and overall satisfaction during hospitalization and post discharge. Doran et al. (2014) applied Donabedian’s model in the study of evidence based practice application by the nursing staff caring for medical surgical patients and patients’ episodes of pain, dyspnea, pressure ulcers, falls and pain level outcomes, where structural elements consisted of nurses with various degrees of clinical experiences and education and patients with several medical diagnoses, the process was represented by the number of documented visits to patients’ bedside nursing staff accomplished, and the outcomes, measured by changes in dyspnea episodes, pain level, pressure ulcers, and falls. Rondinelli et al. (2012) utilized Donabedian’s model in the study of implementation of HR in various hospitals, where structure was identified as the “use of rounding behaviors”, the utilization of various rounding tools, such as clocks logs and boards, was identified as process, and changes in patients care outcomes and the sustainability of hourly rounds on a unit, as outcomes. The similarity of the DNP project to reviewed studies is evidenced by several elements. Three essential components, structure, process and outcome, are clearly identified, and

33 relationship between the components is documented by testing how new processes within established structure may affect outcomes. The settings for the DNP project and the reviewed studies were inpatient healthcare facilities; processes consisted of quality improvement nursing interventions, and studied/anticipated outcomes were also comparable. Since Donabedian’s quality model provided an appropriate and effective foundation for each study reviewed, the same theoretical framework was deemed to be appropriate for the DNP project. Definition of Terms Several terms were extensively mentioned in the DNP project. Although most are routinely used by inpatient clinicians and hospital officials, the terms may not be familiar to healthcare professionals working outside of hospital care settings and to general public. Communication with nurses: One of the HCAHPS survey domains, consisting of three questions: “During this hospital stay, how often did nurses treat you with courtesy and respect?”; “During this hospital stay, how often did nurses listen carefully to you?”; “During this hospital stay, how often did nurses explain things in a way you could understand?” There are 4 possible answers to choose from: “never”, “sometimes”, “usually”, and “always”. Only “always” choice is counted when calculation HCAHPS scores (HCAHPS Survey, 2015). HCAHPS survey: Hospital Consumer Assessment of Healthcare Providers and Services (HCAHPS) survey is a publicly available tool that allows healthcare consumers to compare patients’ perceptions of quality of care in the US hospitals (CMS, 2012). Hospital Inpatient Value Based Purchasing (VBP) Program: an incentive program that is designed to make value-based incentive payments to the hospital that met performance standards in regards to quality metrics, patients’ perception of care and outcomes (CMS, 2011).

34 Hourly rounds (HR): HR is a nursing intervention, where patients’ needs in a hospital are proactively assessed and addressed at regular intervals (Deitrick et al., 2012). Likelihood to recommend the hospital: One of the HCAHPS survey questions: “Would you recommend this hospital to your friends and family?” with four possible choices for an answer: “definitely no”, “probably no”, “probably yes”, “definitely yes” (HCAHPS Survey, 2014). Obstetric patient: Patient admitted to the hospital due to pregnancy or within six week after delivery (Orsini et al., 2012). Summary The American healthcare system is in the midst of major changes. Healthcare organizations of all calibers embrace a transition from “fee-for-service” model, where insurance companies reimburse providers and institutions for services rendered to patients regardless of outcomes, to a “pay-for-performance” model (Stanowski, Simpson and White., 2015), or VBP. CMS launched VBP program in 2012, where hospitals receiving payments from Medicare and Medicaid are obligated to collect and report data on multiple quality metrics, including HCAHPS surveys results. HCAHPS is a publicly available tool that measures patients’ perceptions of quality of care while in hospital. Hospitals, able to achieve 50th percentile or above in HCAHPS scores, receive about 25% of two to three percent of revenues, originally withheld by Medicare and Medicaid, plus some additional funds as an incentive for achieving high scores in patient perception of quality of care while in the hospital, whereas hospitals, unable to achieve 50th percentile in HCAHPS scores, lose revenues. As indicated by multiple research, HR by nursing staff play an important role in improving patient safety and outcomes in the hospital. Mead et al. (2006), Ford (2010), Olrich et

35 al. (2012) and Rondinelli et al. (2012) suggested that HR contribute to decrease in number of call bells, falls and hospital-acquired skin breakdowns, and increase in patient. Ulanimo and Ligotti (2011) noted that HR implementation contributed to increase in patient satisfaction scores and perception of quality of care provided to patients. Many US hospitals embraced a concept of HR in effort to improve patients’ safety, experiences and achieve CMS-outlined goals in quality of patient care. A large metropolitan hospital in northeastern region of the US where the DNP project will take place, struggles to raise HCAHPS scores to 50th percentile. Executive team tasked nursing and medical leadership of the hospital with devising and implementing a program that will ensure increase in patient safety, quality of care, and outcomes while improving HCAHPS results. Based on current evidence, HR implementation was identified as the major intervention to be implemented house-wide in an attempt to meet the goals outlined by executive team. HR implementation throughout the whole organization became the primary intervention and focus in improving patient experience and perception of care. The MBU of the hospital has over 3800 discharges per year, contributing to a large pool of patients, who can potentially receive an HCAHPS survey. Positive HCAHPS responses provided by obstetric patients contribute to an increase in HCAHPS scores for the entire hospital. Although overall obstetric patients’ satisfaction presently ranges at 80 – 83%, the HCAHPS scores fall below 50th percentile for MBU. HR were not implemented on the unit consistently in the past, and hospital-wide rollout in January – March 2016 was a major educational effort for MBU staff. Every RN and PCA participated in interactive educational sessions, led by the nurse manager. The sessions consisted of a didactic part and a role-play simulation portion, when

36 every staff member joined in in a HR simulation, taking turns at being a patient, a nursing staff (RN or PCA) and a coach. The DNP project examined changes in HCAHPS scores received from obstetric patients in Communication with Nurses and Likelihood to Recommend the hospital before implementation of HR and six month after (dependent variable) as a result of HR roll-out on MBU (independent variable). The project examined obstetric patients’ HCAHPS scores of 3rd and 4th quarters 2015 (before completion of HR implementation on MBU) and 3rd and 4th quarters 2016 (after HR implementation on MBU). Data was obtained from Press Ganey, hospital’s official HCAHPS vendor’s website. According to Press Ganey (2013), among many domains, surveyed in HCAHPS questionnaire, Communication with Nurses and Likelihood to Recommend the hospital play the most important role in patients’ perceptions of quality of care while in hospital, and have a strong correlation with patients’ overall ratings of the hospital, a measure directly related to VBP reimbursement. Extensive literature search did not reveal studies that examined a relationship between HR and obstetric patients’ perception of care in hospital, or a relationship between HR on postpartum/MBU and changes in HCAHPS scores. The DNP project may be one of the first studies to examine a possible relationship between HR and obstetric patients’ perception of communication with nurses and the likelihood to recommend the hospital.

37 SECTION II: METHODS Introduction The US healthcare industry is in the process of adapting to major changes in reimbursement for hospital services. Medicare, Medicaid and numerous private payers moved away from traditional “fee for service” payment model for hospital services (Ginsburg, 2012), adopting VBP instead (CMS, 2011). According to VBP model of reimbursement for 2017 (CMS, 2016), 2% of total revenues will be withheld from hospitals around the country pending evaluation of performance in various areas, such as clinical care, patient experience of care, efficiency, and safety. HCAHPS scores have a significant impact on hospital reimbursement from Medicare, Medicaid and private payers: patient experience of care is reflected by hospital’s HCAHPS scores and in 2017 will attribute to 25 percent of the VBP performance score (CMS, 2016), which translates into hundreds of thousands of dollars for the hospital, where the DNP project was conducted. With implementation of VBP by CMS, hospitals country-wide devise strategies to ensure maximum reimbursement from insurance companies for services rendered to patients. HR have been identified as the single most important intervention, essential for improvement in patients’ perception of care on hospital medical surgical units (Deitrich et al., 2012; Ford, 2010; Meade et al., 2006), including communication with nurses and patients’ likelihood to recommend the hospital to friends and family (Institute for Innovation, 2014). Research indicates that HCAHPS scores in both Communication with Nurses and Likelihood to Recommend the hospital are linked to patients’ overall ratings of the hospital (Gupta et al., 2009; Shaffer and Tuttas, 2008). HR implementation became the main focus of patient experience improvement efforts at a large

38 metropolitan hospital in the northeastern region of the US, where the DNP project was conducted. In spite of significant number of studies supporting the effects of HR on patient safety and experiences on medical surgical units, there is a very limited body of evidence examining a relationship between HR on Mother Baby/postpartum units and obstetric patients’ experiences and perception of care. With nearly 3800 deliveries per year at a hospital, where the DNP project took place, responses submitted by obstetric patients discharged from a MBU have a major impact on the hospital’s HCAHPS ratings. The DNP project attempted to address a strong need to study a possible impact of HR implementation on a MBU of one of large metropolitan hospitals in northeastern region of the US on obstetric patients’ perception of care, as evidenced by comparing HCAHPS scores of Communication with Nurses and Likelihood to Recommend the hospital domains before HR implementation and after. The research question for the DNP project was: in obstetric patient population, will implementation of HR impact Communication with Nurses and Likelihood to Recommend the hospital ratings, when comparing HCAHPS scores before HR implementation and after? All members of nursing care team on MBU, including RNs and PCAs, participated in small group (four to five participants) educational sessions conducted by the nurse manager of MBU. The sessions consisted of an interactive lecture and a practicum. The main focus of the education was to provide nursing staff with knowledge about importance and impact of HR on patients’ safety, comfort and perception of care. The practical portion provided nursing team with an opportunity to practice conducting rounds in a training environment and receive feedback from peers in the group and the nurse manager. With roll-out of HR on MBU, nurse manager rounded with each RN and PCA on both day and night shifts to evaluate staff rounding skills and

39 to provide feedback at least monthly in February, March, April and May of 2016. Nurse manager’s rounds with RNs and PCAs continued quarterly to validate rounding skills and behaviors to ensure competency and coach. The DNP project was a retrospective quantitative “Before-After” study, examining a possible change in obstetric patients’ perception of hospital experiences pertaining to communication with nurses and likelihood to recommend the hospital as evidenced by HCAHPS scores, submitted by patients discharged from MBU of a large metropolitan hospital, before and after implementation of HR. The DNP project compared obstetric patients’ HCAHPS scores of Communication with Nurses and Likelihood to Recommend the hospital from 3rd and 4th quarters of 2015 (prior to HR implementation on MBU) and 3rd and 4th quarters of 2016 (after implementation of HR). Donabedian’s Quality Model (Appendix A) was used as the theoretical framework for the DNP project. HR implementation on MBU to improve patients’ perception of care is an important quality improvement initiative with clearly identified structure-processoutcome triad: MBU with obstetric patients is defined as structure, nursing HR on obstetric patients are the process, and changes in HCAHPS scores in communication with nurses and likelihood to recommend the hospital are the outcome. Glickman et al. (2007), Ibn El Haj et al. (2013) and Moore et al. (2015) agreed that Donabedian’s model has been widely and effectively used in healthcare to design and study quality improvement measures. With existing evidence of successful use of Donabedian’s model in studying patient perception of nursing care (Kobayashi et al., 2010), this model was deemed fit to be used as the DNP project’s theoretical model. The DNP project examined patients’ responses to Communication with Nurses and Likelihood to Recommend the hospital domain questions of HCAHPS surveys within a set timeframe before and after HR implementation on MBU. All responses received by Press Ganey

40 from obstetric patients, discharged during 3rd and 4th quarters of 2015 and 3rd and 4th quarters of 2016 from MBU, were studied. Press Ganey is the hospital’s official vendor responsible for HCAHPS surveys’ distribution, collection and submission to CMS. Press Ganey follows a rigorous process for sampling techniques, outlined by CMS (2012), discussed in detail in Sample and Setting section of this paper. Project Design The DNP project was a retrospective quantitative descriptive study that examined changes in obstetric patients’ perception pertaining to communication with nurses and likelihood to recommend the hospital as a result of HR implementation on MBU of a large metropolitan hospital in northeastern region of the US. The DNP project had a non-experimental comparative “Before-After” design. HCAHPS scores in Communication with Nurses and Likelihood to Recommend the hospital domains submitted by obstetric patients were identified as the dependent variable for the DNP project. The baseline data, consisting of HCAHPS scores in Communication with Nurses and Likelihood to Recommend the hospital domains submitted by obstetric patients discharged in the 3rd and 4th quarters of 2015, was compared to HCAHPS scores submitted by obstetric patients discharged in the 3rd and 4th quarters of 2016, after the implementation of HR on MBU. HR conducted by nursing care team, composed of RNs and PCAs, were the project’s independent variable. Every patient admitted to MBU is rounded on hourly basis by an RN and/or PCA between 6 am and 10 pm and every two hours between 10 pm and 6 am. When rounding, nursing staff ask patients four targeted questions concerning four Ps: pain, positioning, “potty”, personal belongings (Studer, 2007). Every time during the rounds an RN or PCA will inquire about patient’s pain level and a need for relief measures/pain medicine, whether the

41 patient needs to use the bathroom and an assistance with this task, help getting into a comfortable position, and a need for supplies or personal items. HR conducted by members of nursing team (RNs and PCAs) is the only significant intervention implemented by the hospital in order to improve patients’ experiences in effort to increase HCAHPS scores. Non-experimental comparative “Before-After” design was appropriate for this retrospective quantitative descriptive study. Sample for the DNP project was retrieved from Press Ganey website and contained obstetric patients’ HCAHPS responses submitted before the beginning of the study, 3rd and 4th quarters of 2015 and 3rd and 4th quarters of 2016, retrospectively. The project examined and compared a baseline sample of HCAHPS scores, submitted by obstetric patients, discharged from the hospital prior to implementation of HR on MBU, and a sample consisting of HCAHPS scores of obstetric patients, discharged after roll-out of HR on MBU occurred. Polit and Beck (2010) mentioned that quantitative approach is appropriate in a comparative study to determine whether a relationship between variables exists. There was no manipulation of the study samples, the DNP project had a non-experimental design (Tappen, 2011). Setting and Sample Setting The setting for the DNP project was a MBU of a large metropolitan hospital in the northeastern region of the US with about 3800 deliveries per year. Obstetric patients admitted to the unit are either antepartum (pregnant and in the hospital for prolonged monitoring and observation or treatment), status post vaginal delivery or cesarean section, or re-admitted within six weeks postpartum due to postpartum complications. A small Nursery transition unit is a part of the MBU. Patients stay in double-bedded and private rooms (provided as an extra charge).

42 Patients are followed by private obstetricians, midwifes, perinatologists, laborists (attending obstetricians-hospitalists that are in charge of care for clinic and “walk-in” patients). Nursing care team consists of RNs, PCAs, lactation consultants, a social worker, nurse manager and unit clerks. Although all members of patient care team round on patients, HR are performed by RNs and PCAs only. Every patient is rounded on hourly between 6 am and 10 pm, and every two hours between 10 pm and 6 am. Every RN and PCA on MBU received HR education that contested of a didactic and interactive parts. After participating in a 45 minute long small group (4-5 staff members) lecture, during simulation activity every staff member was able to practice rounding on a “patient” and receive feedback from the team members and the nurse manager. The nurse manager observed every RN and PCA during HR on the unit at least monthly during February, March and April of 2016 to ensure staff competency in conducting HR and to provide feedback and to coach. Staff observations continue quarterly. To assess staff compliance, the nurse manager inquired about HR when rounding on patients on MBU. Sample Population sample for the DNP project was retrieved from Press Ganey website. Baseline sample consisted of HCAHPS responses received from patients discharged from MBU between 3rd and 4th quarters of 2015. Post-intervention sample consisted of responses received from patients discharged from MBU between 3rd and 4th quarters of 2016. Press Ganey, hospital’s official vendor for HCAHPS, creates a population sample derived from surveys sent to all eligible adult patients discharged from MBU: postpartum patients after vaginal deliveries, cesarean sections, patients admitted to the hospital within six weeks postpartum due to postpartum complications and antepartum patients. Patients’ eligibility to receive an HCAHPS

43 survey is outlined in CMS HCAHPS Quality Assurance Guidelines (CMS, 2012). Patients fulfilling general HCAHPS survey eligibility criteria are identified by CMS as adults (over the age of 18) discharged to a home address, who had at least an overnight stay at a hospital, and received medical, surgical or maternity care. Some examples of general HCAHPS participation exclusion criteria (CMS, 2012) are the following: patients discharged to a rehab facility or nursing home, “No-Publicity” patients: those who submitted a written request not be contacted, prisoners, patients with foreign permanent home addresses, and patients with primary psychiatric diagnoses. Although most of the patients, discharged from MBU may not fall under exclusion criteria categories, these general guidelines apply nevertheless. As mandated by CMS (2012), the sampling is conducted by Press Ganey continuously throughout the month, using the same sampling technique and is submitted to My QualityNet website. Described strategy is implemented to ensure a large sample, randomness and minimization of introduction of bias (Tappen, 2011) and in accordance with CMS guidelines (CMS, 2012). In order to determine the adequate size of the sample for the DNP project, a priori test was performed using G-Power 3 software (Faul et al., 2007). The effect size of .5 and type 1 error probability of .05 were chosen for the DNP project. According to Farrokhyar et al. (2012) and McCrum (2010), a power of .8 is typical for many behavioral studies. When the power of .8 is chosen, the sample size was estimated to have at least 53 responses for each group (the group before HR implementation and the group after HR implementation). When the power of .95 is chosen, the study sample needed to consist of 92 responses for each group (the group before HR implementation and the group after HR implementation). The final determination of what power would be chosen for the DNP project depended on the total number of responses from MBU

44 available on Press Ganey website for the study periods. Historically, the number of MBU patients’ responses averages at 60 returned surveys per quarter on Press Ganey website. An approximate anticipated n value for each sample was to be about 100 responses. Instrumentation The DNP project analyzed the data collected with HCAHPS survey (Appendix C). Bobrowitz et al. (2013) stressed that developing the right tool in evaluating patients’ perception of quality of care is “a key challenge” in research design. HCAHPS survey assesses patients’ perceptions of quality of care while in hospital, and consists of 32 questions. All HCAHPS survey participants in the country receive the same questionnaire. HCAHPS survey was developed by Agency for Healthcare Research and Quality (AHRQ) on behalf of CMC in order to establish a high validity/high reliability tool that could be used in HCAHPS surveys. At the conclusion of the design phase of HCAHPS survey, a pilot study was conducted in three various states (Maryland, Arizona and New York) to test and analyze the tool (Agency for Healthcare Research and Quality, 2003; CMS, 2012). The pilot study was conducted in 132 hospitals, obtaining close to 19,000 surveys. Several revisions of HCAHPS survey resulted in present version, which was approved and deemed valid and reliable by both CMS and National Quality Forum. Presently, HCAHPS survey is utilized as a reference tool to validate the new tools developed by researchers. Bobrowitz et al. (2013), for example, used HCAHPS survey to test a proposed tool that would be used to measure trauma patients’ perception of quality of care. With extensive testing, multiple revisions and use, HCAHPS survey is deemed a reliable and valid tool in measuring patient perception of quality of care, while in hospital (CMS, 2012).

45 Data Collection The hospital, where the DNP project was conducted, chose to mail HCAHPS surveys to eligible discharged patients. According to CMS (2012), 61 percent of hospitals nation-wide choose the same mode of survey distribution, while about 39 percent of the hospitals elect to use a telephone survey. Both methods are acceptable for conducting an HCAHPS survey, provided that multiple attempts to contact a patient are met. Surveys must be answered by patients only, responses from a proxy are not allowed (CMS, 2012). Statistical adjustments for the mode of HCAHPS survey delivery are factored in by CMS during survey analysis (Elliot et al., 2009). Press Ganey sends out HCAHPS surveys on continuous basis to a random sample of eligible participants within 48 hours of discharge. For example, an HCAHPS survey is sent to every 3rd patient discharged from the hospital within the 48 hours. In two weeks, a duplicate survey is sent to every participant, as a reminder to answer and send the survey back. All HCAHPS surveys received by Press Ganey are forwarded to My QualityNet, HCAHPS data warehouse established by CMS, for analysis. Press Ganey also submits the data on the total number of discharged patients eligible to receive an HCAHPS survey, total number of sent surveys, and total number of surveys received. The data for the DNP project consisting of HCAHPS scores specific to MBU was retrieved from Press Ganey website. Monthly aggregated data on scores in Communication with Nurses and Likelihood to Recommend the hospital in percent was transcribed into the codebook for the subsequent statistical analysis. Several approvals for data collection and analysis were obtained from the hospital officials (Appendix D, Appendix E). The hospital Institutional Review Board (IRB) Director was contacted to request an IRB approval for the project (Appendix D). Due to the fact that data used for the project will be aggregate and de-identified, and that there will be no personal

46 interaction between the principal investigator and HCAHPS survey participants, the IRB Director stated that there was no need for hospital IRB approval for the DNP project. Chief Nursing Officer (CNO) of the hospital was contacted with a request for a permission to conduct the DNP project at the hospital and the use of HCAHPS scores data available from Press Ganey website. The email with CNO’s approval to conduct the study and to use the data was received (Appendix E). A request for the DNP project was submitted to American Sentinel University’s (ASU) IRB, and the approval from ASU IRB received May 22nd, 2017. Collaborative Institutional Training Initiative (CITI) Program course (Appendix F) was successfully completed by the principal investigator of the DNP project and the certificate was sent to ASU IRB with the IRB application. Data Analysis Methods The DNP project compared obstetric patients’ scores for Communication with Nurses and Likelihood to Recommend the Hospital (dependent variable) as evidenced from the HCAHPS surveys collected by Press Ganey, before and after implementation of HR (independent variable) on a MBU of a large metropolitan hospital in northeastern region of the US. Press Ganey is hospital’s official vendor responsible for distribution and collection of HCAHPS surveys to a sample of patients discharged home from the hospital. Population sample is randomly selected by Press Ganey from a list of all eligible discharges, in accordance with CMS HCAHPS Quality Assurance Guidelines (CMS, 2012). Inpatient HCAHPS reports from Press Ganey website was generated using several filters. The “unit” filter, when applied, allowed only responses received from patients discharged from MBU to be displayed. The “date of discharge” filter allowed to group responses by the dates of discharge quarterly: for example, all patients discharged between July 1st and December 31st

47 2015. The responses were broken down by a month, for example 4th quarter of 2016 HCAHPS scores were arranged in three groups: 10/01/2016 – 10/31/2016, 11/01/2016 – 11/30/2016, 12/01/2016 – 12/31/2016. No patient-specific identifiers, such as name, date of birth, or medical record number were used for the DNP project. The codebook for the DNP project was developed. Since data extracted from Press Ganey website is aggregate, rather than containing individual responses, the “Individual ID” variable was not generated in the codebook. Monthly aggregate data about participants’ race, ethnicity and highest level of education was extracted from Press Ganey reports. This data was included in the codebook in order to perform samples’ comparison and possible need for statistical adjustment for one or more of the demographic characteristics (Pallant, 2016). A number of patients of a certain age are provided in a sample as well. For example age 24: n=3. Arranging the number of ns by the years of age, however, created an extensive number of “Age” categories. In order to improve visualization of data, Pallant (2016) suggested to reduce, or collapse, the number of categories. In the codebook the “Age” categories were collapsed into five new categories: “less than 20 years old”, “20 – 25 years old”, “26 – 30 years old”, “31 – 35 years old”, and “older than 35 years”. Two sample groups representing dependent variable were studied: the first included all responses submitted by patients, discharged from MBU in the period between July 1st, 2015 and December 31st, 2015, prior to HR implementation (baseline data). The second group consisted of all responses submitted by patients, discharged in the period between July 1st, 2016 and December 31st, 2016, after HR implementation on MBU. The codebook contains monthly breakdown of percentages of patients’ responses to dependent variables: “Communication with Nurses”, “Nurses Treated You with Courtesy and Respect”, “Nurses Listen Carefully to You”,

48 “Nurses Explain in a Way You Understand” and “Likelihood to Recommend the Hospital”. In accordance with HCAHPS survey options, response choices to categorical variables “Communication with Nurses”, “Nurses Treated You with Courtesy and Respect”, “Nurses Listen Carefully to You”, “Nurses Explain in a Way You Understand” are “Never”, “Sometimes”, “Usually”, “Always”. Response choices to “Likelihood to recommend the hospital” are “Definitely no”, “Probably no”, “Probably yes”, and “Definitely yes”. The DNP project assumed a null hypothesis that there is no relationship between implementation of HR on MBU of a large metropolitan hospital in northeastern region of the U.S. and change in obstetric patients’ perception of “Communication with Nurses” and “Likelihood to Recommend the Hospital” (p is equal or more than .05). To test the hypothesis, statistical analysis of data was executed. After entering data in the codebook and checking for errors, descriptive statistical analysis was performed. As Pallant (2016) mentioned, obtaining descriptive statistics allowed to visualize number of participants falling in certain age categories, level of education and ethnic groups. Monthly aggregate data for certain descriptive statistic parameters secured a demographics comparison of the sample groups. Descriptive statistics was performed also in order to reveal the need to control for one or multiple demographic factors, such as age, race/ethnicity or education. Bar graphs were created for a clear display of the DNP project’s demographic data. Data for the DNP project was measured using ordinal scale. For similar instances Pallant (2016) suggested utilizing non-parametric statistics for data analysis, cautioning, however, to check for randomness of a sample and independence of observations. Due to sampling design, the study sample for the DNP project was random, in accordance with CMS (2012) guidelines. Each patient, whose response were examined, only appeared in one of the two sample groups:

49 either in July 1st, 2015 to December 31st, 2015, before HR implementation on MBU, or in July 1st, 2016 to December 31st, 2016, after HR implementation. Mann-Whitney test was used during the DNP project’s categorical data statistical analysis. If less than .05, p-value would signify that there is a relationship between patients’ responses to “Communication with Nurses”, “Nurses Treated You with Courtesy and Respect”, “Nurses Listen Carefully to You”, “Nurses Explain in a Way You Understand” and “Likelihood to Recommend the Hospital” and HR implementation on MBU, and the null hypothesis would be rejected. However, if p-value is greater than .05, the null hypothesis will not be rejected. Data Management Methods The DNP project used aggregate data collected by Press Ganey, hospital official vendor for HCAHPS surveys distribution and processing. The data for the project was obtained from a report generated on Press Ganey Website with a password-protected access by the principal investigator. No patient-specific identifiers, such as name, date of birth or medical number, are available on Press Ganey website. General aggregate data containing demographic information about age, race/ethnicity, and highest level of education was retrieved and included in data samples. Quarterly HCAHPS results, filtered by unit and discharge date, and arranged by the month were collected and saved in a password-protected file on a password-protected laptop computer and copied to a Google Drive password-protected file. No paper copies of the reports were generated. In spite of absence of patient-specific information in data displayed on Press Ganey’s website, the data obtained for the DNP project is stored in a password-protected file on a password-protected laptop computer. The data will be shared with Capstone Committee Chair and Capstone Committee members, during the DNP project preparation, defense and possible

50 publishing of the study. Upon the DNP project’s completion, the Google Drive file containing the project’s data will be permanently deleted from Google Drive. The data will be kept for five years in a password-protected file on a password-protected laptop computer, in accordance with Office of Human Research Protections regulations (U.S. Department of Health and Human Services, 2009). The data will be permanently erased from the laptop computer after five years. Ethical Considerations The DNP project was designed to introduce and inflict no risk or harm. In order to protect privacy of the institution where the DNP project was conducted, the principal investigator did not reveal the name of the institution in the body of the project. There was no personal interaction between the principal investigator and HCAHPS survey respondents. The permission for the DNP project and the use of data was received from the CNO of the hospital. Hospital IRB Director stated that there was no need to receive hospital’s IRB approval for the DNP project, since data used in the study is de-identified, and there would be no contact between the principal investigator and HCAHPS respondents. ASU IRB application was submitted by the principal investigator and approved on May 22nd, 2017. The DNP project evaluated HCAHPS scores data collected by Press Ganey, hospital’s official vendor for HCAHPS surveys distribution, collection and submission to CMS for analysis. As per CMS regulations (CMS, 2012), a cover letter accompanying HCAHPS questionnaire is sent to every prospective HCAHPS survey participant. The letter discloses the purpose of HCAHPS survey and why the prospective participant was chosen. The cover letter also explains how the information received from a participant will be used and shared. Internal and External Validity

51 Tappen (2011) accentuated importance of being mindful of internal and external validity of a research, when developing a study design. Trochim (2006) argued that the threat to internal validity would only be relevant in studies that aim to establish causal relationships between variables. Thus, due to a descriptive design of the DNP project, potential threats to internal validity are irrelevant. However, careful consideration of the DNP project’s external validity threats identified several possible opportunities. Since the DNP project analyzed the relationship between an independent variable (hourly rounds) and dependent variable (HCAHPS scores pertaining to Communication with Nurses and Likelihood to Recommend the hospital), an implementation of another major improvement initiative would pose a potential threat to validity of the project. Failure of the nursing staff on the MBU to follow HR protocol may present a threat to validity of the DNP project as well. Tappen (2011) identified that selection bias presents a threat to internal validity of a study. The principal investigator for the DNP project did not participate in sample selection, since the population sample for the DNP project was retrieved form Press Ganey website retrospectively. This detail of research design eliminated selection bias as a threat to internal validity in the DNP project. Sample selection criteria implemented by Press Ganey, where randomization method is used in accordance with CMS requirements (CMS, 2012), considerably lowers the risks to generalizability of the DNP project’s results, by lowering selection and testing effects that present a threat to external validity of a study (Tappen, 2011; Trochim, 2006). Price et al. (2014) cautioned about “n” bias threat to external validity of a study. The number of HCAHPS surveys, received from obstetric patients, averages at about 60 responses per quarter. Ensuring that an adequate sample size is obtained for the DNP project, in accordance with a priory test, performed using G-Power 3 software (Faul et al., 2007) (53 to 92

52 responses per group), would decrease this treat. Gupta et al. (2009) identified a “nonresponse bias” as yet another potential threat to validity of HCAHPS survey results. Elliot et al. (2015) reported that HCAHPS response rates average at about 32 percent. However, according to CMS (2012), AHRQ ensured implementation of certain statistical adjustments for a “nonresponse bias”. Although an attempt to predict and account for every threat to validity of the study is unrealistic, a careful consideration for possible threats to validity of the DNP project is a prudent way to address the most probable obstacles. Summary The DNP project is a retrospective quantitative descriptive study examining possible changes in perception of communication with nurses and likelihood to recommend the hospital of obstetric patients discharged from MBU of a large metropolitan hospital in northeastern part of the US before and after implementation of HR on MBU, as evidenced by HCAHPS survey results distributed and collected by Press Ganey, hospital official vendor for HCAHPS surveys. The DNP project attempted to answer the following research question: in obstetric patient population, will implementation of HR impact Communication with Nurses and Likelihood to Recommend the hospital ratings, when comparing HCAHPS scores before and after HR implementation? The data was retrieved from Press Ganey website. The dependent variable of the DNP project consisted of a baseline sample with aggregate data from HCAHPS survey responses submitted by obstetric patients discharged from MBU in 3rd and 4th quarters of 2015, prior to nursing staff (RNs and PCAs) HR implementation in MBU, and the outcome sample with aggregate data from patients discharged in 3rd and 4th quarter of 2016, after HR implementation on MBU. HR conducted by nursing care team, consisted of RNs and PCAs, was the project’s

53 independent variable. A priori test conducted with the help of G-Power software (Faul et al., 2007) revealed that depending on whether the power of .8 or .95 is selected, the sample size has to have 53 to 92 responses for each of the sample groups. The DNP project assumed a null hypothesis that there is no relationship between implementation of HR on MBU of a large metropolitan hospital in northeastern region of the U.S. and change in obstetric patients’ perception of “Communication with Nurses” and “Likelihood to Recommend” the hospital (p is equal or more than .05). Mann-Whitney test was used during the DNP project’s statistical analysis. If p-value is less than .05, the null hypothesis is rejected, signifying that there is a relationship between obstetric patients’ responses and HR implementation on MBU. However, if p-value is found to be greater than .05, the null hypothesis cannot be rejected. An approval from the hospital IRB and CNO to conduct the study was obtained. ASU IRB request was approved on May 22nd, 2017. Data management measures for the DNP project were designed to ensure data security and to prevent unnecessary data exposure. All data for the DNP project is de-identified and free of patient-specific information. Several threats to external validity were identified and monitored.

54 SECTION III: RESULTS AND DISCUSSION OF FINDINGS Introduction The U.S. healthcare is in the midst of undergoing major changes. In spite of having the most expensive healthcare system in the world, with the budget of over 16 % of gross domestic product (GDP) (OECD, 2015), Americans have the lowest life expectancy among highly developed countries (State Health Care Cost Containment Commission, 2014). Infant mortality rates in the U.S. were at “6.1 deaths per 100 live births” (Squires and Anderson, 2015) in 2011, which is almost double of Organization for Economic Co-operation and Development countries’ that reported 3.5 deaths per 1000 live births. According to Avendano and Kawachi (2014), prevalence of chronic conditions such as diabetes, heart and lung disease, obesity and stroke among Americans older than 50 is much more significant than in Europeans. CMS designed and implemented several important initiatives that aim to reduce healthcare costs, while improving quality. Value Based Purchasing (VBP) is the program that ties hospitals’ revenues from Medicare and Medicaid to quality outcomes. As a result of VBP program roll-out in 2012 by Centers for Medicare and Medicaid Services (CMS), American healthcare institutions must implement a wide range of quality initiatives to monitor and maintain numerous quality metrics. Along with clinical indicators, such as compliance with prophylactic antibiotic administration prior to surgery and number of early elective deliveries, HCAHPS surveys, assessing patients’ perception of care while in hospital, are among important quality indicators (CMS, 2014). Research suggests that hourly rounds (HR) may be one of the most effective approaches in optimizing patients’ perception of care and improving Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) scores (Mitchel et al., 2014).

55 Research offers a significant body of evidence supporting HR effectiveness in increasing patient satisfaction with hospital stay on a medical surgical unit. Blackley et al. (2011) noted a rise in patient satisfaction after implementation of regular (at least every two hours) nursing rounding with medical surgical patients. Dempsey et al. (2014) pointed out that consistent purposeful HR promotes effective nurse-patient relationship and positively affects HCAHPS scores. Ford (2010), Meade et al. (2006) and Rondinelli et al. (2012) argued that HR contributes to increase in medical surgical patients’ safety, improvements in nursing communication and satisfaction with hospital stay. In spite of great wealth of studies investigating relationships between HR and medical surgical patients’ perception of care while in hospital, there is a very limited research on examining effects of HR on mother-baby and/or postpartum units and obstetric patients’ perception of care. A large metropolitan hospital in northeastern part of the United States, where the Doctor of Nursing Practice (DNP) project was conducted, chose HR as the single most important tactic to improve HCAHPS scores. Extensive education on purposeful HR was provided for nursing staff (registered nurses (RNs) and patient care associates (PCAs)) of all inpatient units, including Mother Baby Unit (MBU). With over 3800 deliveries annually until 2016, HCAHPS scores received from obstetric patients discharged from MBU greatly contributed to hospital–wide HCAHPS results. With substantial time and resources allocated for HR education and implementation, and a very limited evidence demonstrating benefits of HR on a mother baby or postpartum unit, there was a need to study a possible relationship between HR on MBU and obstetric patients’ perception of care. This DNP project examined a possible impact of HR conducted by RNs and PCAs on MBU and obstetric patients’ perception of communication with nurses, and patients’ likelihood to recommend the hospital as evidenced from HCAHPS surveys,

56 when comparing HCAHPS results prior to initiation of HR on MBU and after the HR rollout on the unit. Summary of Methods and Procedures The DNP project was a retrospective quantitative descriptive study, examining possible changes in obstetric patients’ perception of communication with nurses and likelihood to recommend the hospital as a result of HR implementation on MBU of a large metropolitan hospital in northeastern region of the United States. The DNP project had a non-experimental comparative “Before-After” design and focused on answering the following question: In obstetric patient population, will implementation of HR impact Communication with Nurses and Likelihood to Recommend the hospital ratings, when comparing HCAHPS scores before HR implementation and after? The DNP project defined the null hypothesis, which assumed that there is no statistically significant relationship between implementation of HR on MBU of a large metropolitan hospital in northeastern region of the U.S. and changes in patients’ perception of “Communication with Nurses” and “Likelihood to Recommend the Hospital” (p is equal or more than .05). Approvals for data collection were obtained from the Chief Nursing Officer (CNO) of the hospital (Appendix E), where the DNP project was conducted. The Institutional Review Board (IRB) Director of the hospital determined that the DNP project would not be required to go through the IRB approval process (Appendix D). American Sentinel University (ASU) IRB approval request for the DNP project was submitted, and approval was received on May 22nd, 2017. The HCAHPS scores of Communication with Nurses and Likelihood to Recommend the hospital from 3rd and 4th quarters of 2015 (prior to HR implementation on MBU) and 3rd and 4th quarters of 2016 (after implementation of HR), submitted by obstetric patients, were analyzed.

57 The DNP project utilized Donabedian’s Quality Model as the theoretical framework (Appendix A). The structure-process-outcome triad was identifies: MBU with admitted obstetric patients as the structure, nursing HR on obstetric patients on the unit as the process and possible HCAHPS scores’ changes as outcome. Patients’ HCAHPS responses within the set time frame, before and after implementation of HR on MBU, were studied. The DNP project examined HCAHPS scores received from obstetric patients discharged from MBU during 3rd and 4th quarters of 2015 and 3rd and 4th quarters of 2016. The DNP project identified HCAHPS scores in Communication with Nurses and Likelihood to Recommend the hospital as the dependent variable. The baseline data, consisting of HCAHPS scores in Communication with Nurses and Likelihood to Recommend the hospital domains submitted by obstetric patients discharged in the 3rd and 4th quarters of 2015, was compared to HCAHPS scores submitted by obstetric patients discharged in the 3rd and 4th quarters of 2016, after the implementation of HR on MBU. The DNP identified HR conducted by the nursing team, RNs and PCAs, as the independent variable. Every obstetric patient admitted to MBU was rounded hourly between six am and ten pm, and every two hours between ten pm and six am. HR conducted by members of nursing team (RNs and PCAs) was the only significant intervention implemented by the hospital in order to improve patients’ experiences in effort to increase HCAHPS scores. HCAHPS survey, a tool developed on behalf of CMS, is a valid tool in assessing patients’ perception of care (Agency for Healthcare Research and Quality, 2003; CMS, 2012), tested on large samples of participants and deemed reliable. Response choices for questions in “Communication with Nurses” domain: “Nurses Treated You with Courtesy and Respect”, “Nurses Listen Carefully to You”, “Nurses Explain in a Way You Understand” had four possible choices: 1 - “Never”, 2 - “Sometimes”, 3 - “Usually”, and 4 -

58 “Always”. Response choices to the question “Would you recommend this hospital to your friends and family?” were: 1 - “Definitely no”, 2 - “Probably no”, 3 - “Probably yes”, 4 “Definitely yes”. Population sample used was randomly selected by Press Ganey, hospital official vendor for HCAHPS, from a list of all eligible discharges, in accordance with CMS HCAHPS Quality Assurance Guidelines (CMS, 2012). HCAHPS survey results, specific to patients discharged from MBU, were retrieved from Press Ganey’s website. Several filters were applied during data retrieval. The “unit” filter ensured that only responses from patients discharged from MBU unit were pooled. The “date of discharge” filter allowed to group patients’ responses according to the dates of discharge quarterly. Two sample groups representing dependent variable were studied: the first included all responses submitted by patients, discharged from MBU in the period between July 1st, 2015 and December 31st, 2015, prior to HR implementation (baseline/preintervention). The second group consisted of all responses submitted by patients, discharged in the period between July 1st, 2016 and December 31st, 2016, after HR implementation on MBU (post intervention). The codebook was developed to log in data. Only aggregate data was available for analysis. The baseline (pre-intervention sample) consisted of 94 responses, and post-intervention sample consisted of 61 responses. Due to the samples’ size, a power of .8 was chosen. According to McCrum (2010) and Farrokhyar et al. (2012), a power of .8 is typical for behavioral studies. Sample’s demographics (monthly aggregate data) consisted of participants’ age, race, ethnicity, and education. The “age” category was collapsed in codebook into five new groups: “less than 20 years old”, “20 – 25 years old”, “26 – 30 years old”, “31 – 35 years old”, and “older than 35 years”.

59 A null hypothesis stated that there is no relationship between implementation of HR on MBU of a large metropolitan hospital in northeastern region of the U.S. and change in obstetric patients’ perception of “Communication with Nurses” and “Likelihood to Recommend” the hospital (p is equal or more than .05). To test the hypothesis, statistical analysis of data was executed. The data was measured using ordinal scale utilizing non-parametric statistics. Randomness of the sample and independence of observations were ensured by the sampling design, in accordance with CMS guidelines (CMS, 2012). HCAHPS survey participant only appeared in one of the two sample groups, either in baseline/pre-intervention (3rd and 4th quarters of 2015) or post-intervention (3rd and 4th quarters of 2016). Mann-Whitney U test was used for the categorical data statistical analysis. If less than .05, p-value would signify that the changes in patients’ responses were statistically significant, which would indicate that there was a relationship between patients’ responses to “Communication with Nurses”, “Nurses Treated You with Courtesy and Respect”, “Nurses Listen Carefully to You”, “Nurses Explain in a Way You Understand” and “Likelihood to Recommend the Hospital” and HR implementation on MBU, and the null hypothesis would be rejected. However, if p-value was greater than .05, the changes in patients’ responses would not be considered statistically significant, and the null hypothesis would not be rejected. MannWhitney U test was an appropriate non-parametric statistical test for comparing ordinal or continuous response variables across two groups, since data did not follow a normal distribution. Since HCHAPS responses of 4 – “Always” and 4 – “Definitely yes” are the only ones acknowledged and “counted” by CMS (CMS, 2012), the principal investigator was interested in analyzing whether there was a change in the number of 4 – “Always” and 4 – “Definitely yes” responses when pre- intervention (baseline) and post- intervention groups were compared. A

60 chi-square analysis was done to determine, whether the change if any, was statistically significant. Chi-square test was appropriate, since the participants either checked the choice “4” or did not. Summary of Setting and Sample Characteristics Setting MBU of a large metropolitan hospital in the north eastern region of the United States with about 3800 deliveries per year was the setting for the DNP project. Obstetric patient population consisted of patients admitted to the unit, status post vaginal delivery and post c/section as well as antepartum patients admitted to the hospital for prolonged observation and monitoring or treatment, and patients, readmitted to the hospital within six week postpartum period as a result of postpartum complications. Patients were admitted to either a double-bedded room, or a private room, offered at extra charge. Obstetrical medical team was comprised of private obstetricians, midwifes, perinatologists and laborists, and obstetrical resident physicians. Nursing care team consisted of RNs, PCAs, lactation consultants, a social worker, nurse manager and unit clerks. Patient rounds were performed by RNs and PCAs hourly, between six am and ten pm, and every two hours between ten pm and six am. Nurse manager rounded on every patient daily during the week to seek feedback on nursing care and to assess staff compliance. During the time the DNP project was conducted on MBU, the hospital announced a major organizational restructuring due to a merger with a large healthcare system. As a result of the merger, the hospital where the project was conducted would be downsized, eliminating obstetric services by mid-2017. A decline in the number of deliveries and some resignations of the medical and nursing staff were observed. Staffing needs were addressed by contracting agency and travel nurses to fill existing vacancies on the MBU. Due to changes in nursing

61 leadership, the MBU nurse manager left the organization in July of 2016, and MBU has been covered by a nurse manager from another unit within Women and Children’s Services Department. Sample The population sample was retrieved from Press Ganey’s website. Press Ganey is the hospital’s official vendor for HCAHPS, creates a population sample, derived from surveys, sent to all eligible patients discharged from MBU. The MBU sample included postpartum patients after vaginal deliveries, cesarean sections, patients admitted to the hospital within six weeks postpartum due to postpartum complications and antepartum patients. Patients’ eligibility to receive an HCAHPS survey is outlined in CMS HCAHPS Quality Assurance Guidelines (CMS, 2012). Patients fulfilling general HCAHPS survey eligibility criteria are identified by CMS as adults (over the age of 18) discharged to a home address, who had at least an overnight stay at a hospital, and received medical, surgical or maternity care. Baseline (pre-intervention) sample consisted of 94 HCAHPS responses received from patients, discharged from MBU between the 3rd and 4th quarters of 2015. Post-intervention sample consisted of 61 HCAHPS responses received from obstetric patients discharged from MBU in the 3rd and 4th quarters of 2016. The adequate sample size for the DNP project was determined using G-Power 3 software (Faul et al., 2007). The effect size of .5 and type 1 error probability of .05 were chosen. Due to the number of responses, 94 for the baseline sample and 61 for post-intervention sample, available from Press Ganey website, a power of .8, typical for behavioral studies (Farrokhyar et al., 2012; McCrum, 2010) was chosen. Table 1 demonstrates distribution of responses per month within baseline (pre-intervention) and post-intervention sample. Figure 1 graphically demonstrates responses’ distribution in a bar diagram. The post-

62 intervention sample, reflecting HCAHPS responses of patients discharged from the MBU in the 3rd and 4th quarters of 2016 was smaller than baseline sample (61 versus 94 responses respectively). There were also fewer patients in each individual month, with the exception of November in post-intervention sample. Table 1. Distribution of Patients by Month within Pre/Post Intervention Period

Time PreIntervention PostIntervention

Month 9 10

7

8

15

11

13

10

4

9

11

12

Total

24

10

21

94

12

17

9

61

Figure 1. Distribution of Patients by Month within Pre/Post Intervention Period Demographic data collected in HCAHPS survey from the patients in accordance with CMS guidelines (CMS, 2011) contained information on patients’ ethnicity, race, age, and education. Table 2 through Table 5 display the frequency distributions of this demographic

63 information overall between the pre- (baseline) and post-intervention time periods. Bar graphs accompany each table to provide a pictorial representation of the distribution. Bar graphs display percentages within each time period, rather than simple counts. This allows the two time periods to be compared more easily, despite the different numbers of participants. Ethnicity When asked about ethnicity, “Are you of Spanish, Hispanic or Latino origin or descent?” patients had 5 answer options: 1- No, not Spanish/Hispanic/Latino; 2- yes, Puerto Rican; 3 – Yes, Mexican, Mexican American, Chicano; 4 – Yes, Cuban; 5 – Yes, other Spanish/Hispanic/Latino. A total of 90 participants provided responses from the pre- (baseline) intervention group, and a total of 59 participants from the post-intervention group responded to ethnicity question. Four and two participants from each group respectively did not answer the question about ethnicity. A chi-square test to determine whether there was a significant difference in ethnic composition of the pre- and post- intervention sample was performed. The result of the chisquare test is χ2(2) = 1.622, p = .444. The chi-square statistic with two degrees of freedom is 1.622, with a p-value of .444. The p-value of .444 indicates that if the ethnic distribution of the entire population of patients did not change between the two time periods, the probability that a random sample of patients like the one displayed in Table 2 would have distributions that differ at least as much as patients do in this table is 44.4%. This is not particularly low, since usually p < .05 is considered to be statistically significant, and the ethnic distribution across the two time periods is not considered unlikely if the patient population has not changed. This leads to a conclusion that the two time periods have similar ethnic distributions. Table 2 provides

64 distribution of ethnicity across pre- (baseline) and post-intervention sample. Figure 1 displays data in percentages and in graph format. Table 2. Distribution of Patient Ethnicities by Time Period Ethnicity Time

Not Span/Hispan/La

Pre-Intervention Count % within PrePost-Intervention Count % within Post-

Puerto Rican

Other

Total

8

10

90

8.9%

11.1%

100.0%

3

10

59

5.1%

16.9%

100.0%

72 80.0% 46 78.0%

Figure 2. Bar Graph of Patient Ethnicities by Time Period Race

65 When asked about race, “What is your race? Please choose one or more”, patients had the following response options: 1 – White; 2 – Black or African American; 3 – Asian; 4 – Native Hawaiian or Other Pacific Islander; 5 – American Indian or Alaska Native. When filling out HCAHPS survey, patients were not asked to only choose one race, rather one or more choices could have been made. Thus, rather than being a single categorical variable, race was essentially presented as series of yes/no questions about patient’s association with each race. Since the patients could have belonged to more than one race, different racial categories were summarized separately through four different tables (Tables 3.1 – 3.4). None of the patients identified with being a Native American. Also, the sample size varied due to not every patient providing the answer to race question. As with ethnicity, chi-square test was used to determine if there was a difference in the percentage of patients identifying as White. The results were χ2(1) = 1.120, p = .290. The pvalue of .290 is greater than .05, which indicates that there is no evidence of a difference in the proportion of the patient population reporting a white background between the pre- (baseline) and post-intervention time periods.

Table 3.1. Distribution of Patient Race: White by Time Period White Time PreIntervention Count % within PrePostIntervention Count % within Post-

No

Yes

Total

36 40.4%

53 59.6%

89 100.0%

30 49.2%

31 50.8%

61 100.0%

66

Figure 3.1. Bar Graph of Patient Race: White by Time Period A chi-square test was performed to determine whether there was a difference in the percentage of patients reporting a Black/African American racial background between the preand post- intervention sample. The results were χ2(1) = 6.755, p = .009. The p-value of .009 is less than 0.05, thus there is a statistically significant difference in the percentage of patients with Black/African American racial background between the two time periods. The pre-intervention (baseline) group had 17.0% of participants, who identified with Black/African American race as opposed to 3.3% in the post-intervention group. Table 3.2. Distribution of Patient Race: Black/African American by Time Period Black Time Pre-Intervention Count % within Pre

No

Yes

73 83.0%

15 17.0%

Total 88 100.0%

Post-Intervention Count % within Post

59 96.7%

2 3.3%

61 100.0%

67

Figure 3.2. Bar Graph of Patient Race: Black/African American by Time Period A chi-square test was used to determine if there was a difference in the percentage of patients identifying as Asian between the pre- and post- intervention groups. The results were χ2(1) = 1.837, p = .175. The p-value of .175 is greater than .05, thus a conclusion can be made that there is not a statistically significant difference in the percentage of patients identifying as Asian between the pre- and post- intervention group. Table 3.3. Distribution of Patient Race: Asian by Time Period Asian Time PreIntervention PostIntervention

No

Yes

Total

Count % within Pre

70 78.7%

19 21.3%

89 100.0%

Count % within Post

42 68.9%

19 31.1%

61 100.0%

68

Figure 3.3. Bar Graph of Patient Race: Asian by Time Period There was only one patient in each pre- and post- intervention group who identified as Hawaiian/Pacific Islander. Due to the sample size, chi-square test would not be considered valid. In this instance Fisher’s Exact Test was used, since the test does not have a separate statistic, only a p-value. The p-value in this case is 1.00, meaning that there is a 100% chance of seeing differences this large in the sample if the distribution of Hawaiian/Pacific Islanders is equal in the patient population pre- and post- intervention. In other words, there is no evidence that there is a difference in the Hawaiian/Pacific Islander patient population in pre- and postintervention group. Table 3.4. Distribution of Patient Race: Hawaiian/Pacific Islander by Time Period

Time PreIntervention PostIntervention

Hawaiian/Pacific Islander No Yes

Total

Count % within Pre

85 98.8%

1 1.2%

86 100.0%

Count % within Post

60 98.4%

1 1.6%

61 100.0%

69

Figure 3.4. Bar Graph of Patient Race: Hawaiian/Pacific Islander by Time Period Age Patient age was available as a continuous variable. In order to optimize visualization of the data, five “Age” categories were created: “less than 20 years old”, “20 – 25 years old”, “26 – 30 years old”, “31 – 35 years old”, and “older than 35 years”. This allowed the data to be categorized into an ordinal categorical variable. Since the age group could be considered an ordinal variable, and pre- and post-intervention can also be considered as having an order, a gamma statistic was used to determine whether the typical age of the patients changed when preand post- intervention groups are compared. The gamma statistic is γ = .024, with p = .847. The gamma statistic value closer to -1 would indicate a shift to younger ages, and a value closer to +1 would indicate a shift to older ages. The existing value of .024 is very close to 0. With a large p-value of .847, the results of the test suggest that there is no significant directional shift in the age of the patients in either direction, and the typical patient age remains the same from pre- to post- intervention group. Table 4 shows the distribution of patient age categories, and Figure 4 provides a bar chart of those categories within the pre- and post- intervention group. Table 4. Distribution of Patient Age Groups by Time Period

70

Time PreIntervention

PostIntervention

19-25 years Count % within Pre Count % within Post

26-30 years

Age Group 31-35 36-40 years years

13

22

37

19

13.8%

23.4%

39.4%

20.2%

7

15

25

11

11.5%

24.6%

41.0%

18.0%

> 40 years 3

Total 94

3.2% 100.0% 3

61

4.9% 100.0%

Figure 4. Bar Chart of Patient Age Group by Time Period Education All 91 patients from pre- intervention group responded to the question about education, “What is the highest grade or level of school you have completed?”. Three patients from the post- intervention group did not respond to the question about highest level of education, with 58 total number of responses. As with age group, gamma statistic was used for analysis, with γ = .011, and with p = .928. With value of .011, which is close to 0 and p = .928, a conclusion can be made that there is no significant directional shift in the education level of the patients in either

71 direction, and the typical patient education level remains the same from pre- to postinterventional group. Table 5 shows the distribution of patient education categories, and Figure 5 provides a bar graph of those categories within the pre- and post- intervention group. Table 5. Distribution of Patient Education by Time Period Education Level

Time PreIntervention

PostIntervention

Some high schoo l