Potential Return on Investment (RoI) on web-based Diabetes Education in UK Omid SHABESTARI and Abdul ROUDSARI 1 Centre for Health Informatics, City University, London, UK Abstract. The incidence of diabetes mellitus is growing in the UK. As most diabetes care is performed by the patients themselves, structured education is one way to encourage their responsible participation in delivering effective care. Continuous e-learning by Internet has proven to be a useful method of diabetes education. “Return on Investment” (RoI) can be used as an indicator of the costbenefit of web-based education. RoI is the ratio of money gained or lost on an investment relative to the amount of money invested. This report uses system dynamics modeling to predict the flow of patients in the educational system and the cost of their care. The analysis compared traditional and web-based education. Separate models were developed for each educational method and simulated until 2020 in one year intervals. The population of diabetic patients was adjusted at each cycle according to anticipated incidence and mortality rates. The population of educated diabetic patients was based on the educational capacity and literacy limits of each method. A report by the National Health Service (NHS) was used to calculate the cost of care by considering the cost difference between uneducated and educated patients. By 2020 with an annual rate of inflation of 3%, the annual cost of care is projected to increase to £3.67 billion for the traditional model as compared to £3.39 billion for the web-based model. RoI is estimated to be a ratio of 32.33. Investment in web-based diabetes education is not only a health benefit but also a reduction in care cost. Keywords. return on investment, diabetes, web-based education, e-learning
Introduction Diabetes mellitus is a growing chronic disease characterized by high level of blood glucose which is caused by the inadequate secretion of insulin hormone or a problem in receptors of this hormone on the target cells. Diabetes prevalence in UK is 3.66% and its incidence rate is 0.33%. Diabetes complications involve different parts of the body like eyes, kidneys, and the nervous and cardio-vascular systems. These complications significantly increase the cost of diabetes care. Due to the high prevalence of complications and costly treatments for them, diabetes care is one of the most budget-consuming parts of the health care in many countries like UK. Any method that can reduce these complications and cost of diabetes care can be very beneficial. There is good evidence that better control of the blood glucose level near normal range can decrease the risk of these complications. A major part of the care in diabetes is controlling the caloric intake and oral or injection treatment which is performed by 1 Corresponding author: Abdul Roudsari, Centre for Health Informatics, City University, Northampton Square, EC1V 0HB, London, UK; e-mail:
[email protected]
the patients themselves. As a result, one of the best ways to achieve control on blood glucose level is increasing the patient’s responsibility for better control of their disease. Because of this self responsibility target, patient education is considered as one of the important components of diabetes care. Structured education of patients has proven to be effective in diabetes management, decreasing the HbA1c level of the patients which is an indicator of middle-term (120 days) control of blood glucose level. Return on Investment is the ratio of money gained or lost on an investment relative to the amount of money invested. This variable can be utilized as a good indicator of the cost-benefit of methods in education for diabetes. 1. Review of the literature According to a report from the Department of Health the cost of diabetes care in UK is £5 million per day. Control of diabetes can significantly reduce this cost because the management of complication in diabetes has the highest cost in diabetes care. Wagner et al [1] showed that this cost reduction is 7.5% per each percent reduction in HbA1C. Structured education has shown to be able to reduce 1.6% of HbA1C [2,3]. In a randomized clinical trial in 2007 Ko et al [4]evaluated diabetes education in long-term follow up of the educated patients and concluded that the efficacy of education is not long-lasting and the difference between HbA1c level of the educated patients and the control group will not remain significant after one year. Other research agrees with this finding [5,6]. There were suggestions that continuous reinforcement may prevent this relapse [7]. Bloomgarden et al supported this hypothesis in their study [8]. Educational capacity for diabetes in UK is limited and, considering the reports from Diabetes UK and Healthcare Watchdog, the increase in coverage of structured education between 2005 and 2007 was 1.5% per year. A single course for diabetic patients is insufficient because, as the 2007 report of the Healthcare Watchdog indicates, only 11% of the patients are already educated. Assuming that the number of patients waiting for education remains at a constant level (first-come, first-served) in the traditional model, it would take nearly 60 years for a recently diagnosed diabetic patient to attend an education course. This shows that an alternate method for patient education is needed. [E]-learning via Internet has been used for many years in different courses as a wide spread and efficient way of education. This system has proven to be useful for diabetes education by many researchers. Facilitating this method of education can be a big step forward in diabetes care. A report from “UK Office of National Statistics” shows that 61% of UK households have access to Internet, so a considerable percentage of diabetes patients can be covered by web-based education. Literacy could be considered as a barrier for self education via web. In this research coached education by parents are not included because there is no quantitative evidence about this support. Based on this assumption 12.5% of the UK population who are below 10 years old are considered not suitable for this method of education. Also, there are some people who do not like to use high-tech systems for any reason. This group is considered as technology-refusing and, according to a report from a similar web-based education in USA, the percentage of flow toward this level is considered to be 18.72% [9]. Another limiting factor for diabetic patients is the
mortality rate. Based on a diabetes UK report, this rate in diabetes is five times more than normal mortality rate which gives the assumption of 4.1% in UK. Most of the similar previous projects were retrospective and did not give the financial prospect of future. This article is trying to demonstrate this prospect by modeling of diabetes education. 2. Method There are many interrelated factors affecting diabetes education and the cost reduction resulting from it which makes it a complicated model. In this study, system dynamics modeling is used to predict the flow of the patients in education system and the cost of care comparing traditional and web-based educational systems. PowerSim version 2005 was used for developing and simulating the models. Separate models were developed for each educational method and variables affecting these educational systems were included in those models. For a long prospect the models were simulated until 2020. Because most variables affecting this system have an annual basis, the system is calculated with one year interval. In both models, there is a level object for UK non-diabetic population, which is increased by population increase rate. This population increase is the overall effect of birth rate, mortality rate, immigration and emigration. Patients will be transferred from this level to “Un-educated Diabetic Population” level according to “Diabetes Incidence Rate”. “Diabetes Mortality Rate” is a restricting factor which decreases this level. This level is affected by different behaviors in developed models. In the traditional education model, patients shift from this level to “Educated Diabetic Population” based on the mentioned education rate, but fall back to the uneducated level after one year according to evidence in a review of literature. In a web-based education model (Figure 1), initially a group of patients leave this level to “Education Refusing Population” for separating them from the group that intend to receive education, from whom the ones above 10 years old will climb to “Educated Diabetic Population” based on “Internet Availability Rate”. This group will remain at “Educated Diabetic Population” because they can reinforce their knowledge whenever they want to by taking the online course again. The cost of diabetes care was calculated based on the report from NHS per number of patients considering the difference of cost between uneducated and educated patients. In both models the total cost of diabetes care was considered as a level which showed the cumulative value of diabetes care in all diabetes patient levels. This level in the traditional model is equal to the cost of care for uneducated patients plus the cost of care for educated patients. In the web based model, in addition to cost of care for uneducated, educated and technology refusing population, £50 million was estimated as the setup cost for the first year and £1 million for the cost of system maintenance and upgrading for each year. Because of the long duration of the model simulation (12 years) the inflation rate of 3% was added as a constant value affecting the cost of diabetes care and the cost of web-based diabetes education.
Figure 1. System dynamics Model for web-based diabetes education.
Figure 2. Forecast of diabetes cost in web-based and traditional education model.
3. Results Considering the current population of UK which is equal to 61.1 million in 2008 and the population increase rate of 0.9% in our model the UK population would be 66 million in 2020 which gives the similar results used in the model of National Statistics.
Based on the data from the prevalence and incidence of diabetes and its mortality rate, the population of UK diabetic patients will increase dramatically in the duration of this modeling, leading to 3.3 million patients in 2020 which is compatible with the results of diabetes population prevalence model developed by Yorkshire & Humber Public Health Observatory (YHPHO). Based on the simulation of the developed models, the web-based model is 63.47% higher in educated diabetic population at the end of simulation. The annual cost of diabetes care in traditional model will increase to £3.67 million in 2020 whereas the web-based model will keep this cost to £3.39 million (Figure 2). Because of initial price of setup and the low percentage of the educated diabetics in the beginning, the cost of web-based system is higher in the initial two years but, in comparison to traditional model, it will start to reduce significantly from the third year, giving a final difference in cumulative cost to more than £2 billion by 2020. 4. Discussion Education in diabetes is a very simple method which is very effective. Because of the limitation in requirements for establishing the education system, like lack of enough educators and conflict of the program schedule with patients other programs, it could not be implemented on a required scale. The web-based system would be under development in the first year and will not increase the education rate. Although there is a big investment for the initial setup of this system, it will cover all the investments by the third year. Return on Investment (RoI) in web-based diabetes education is calculated by cost and benefit of any system (Eq. 1), which will be equal to 3233% in this model. The average annual cost of diabetes care in the period of study is £2.7 million and considering the results from this model it can be assumed that implementation of webbased education will be equal to one year free diabetes care for UK.
2,187,000,000 65,000,000 Benefit Cost 100 = 3265% 100 = Cost 65,000,000
(1)
There might be some factors affecting this model which can not be predicted until the system is fully implemented. Technology adoption rate might be different in UK but we had no evidence on a similar in-house system. Also emerging concepts like web 2.0 is quite revolutionizing this medium which had a significant effect on adopting this channel of communication in other sectors. Many of the points of strength in this model, like increase in collaboration and communication and enriched medium by Rich Internet Application (R.I.A) technology, comply with theories of Technology Mediated Learning (T.M.L.) and can be applicable in diabetes education. Internet coverage rate is growing very fast both in width and depth regarding the availability and bandwidth which can accelerate feasibility of web-based education model. An important part of this system is support by health care members. The shift toward telemedicine and healthcare-patient communication via electronic media is dependent on the adoption of it by healthcare members. There are good initiatives to encourage this shift.
5. Conclusion Investment on web-based diabetes education is not a matter of benefit but a requirement to reduce the pressure of diabetes on NHS. A web-based system is more compatible with the life style of the younger generation. These are the people who are considered as computer native. They are more familiar with computer technology in comparison with previous generations and can adopt this technology more easily. Also, this system is expandable by the collaboration of expert patients, which is a major point of interest in recent policies of departments of health. References [1] [2] [3] [4] [5] [6] [7] [8] [9]
Wagner EH, Sandhu N, Newton KM, McCulloch DK, Ramsey SD, Grothaus LC. Effect of improved glycemic control on health care costs and utilization. J Am Med Assoc. 2001; 285(2): 182-189. Muhlhauser I, Jorgens V, Berger M, et al. Bicentric evaluation of a teaching and treatment programme for type 1 (insulin-dependent) diabetic patients: improvement of metabolic control and other measures of diabetes care for up to 22 months. Diabetologia. 1983 Dec; 25(6): 470-476. Sigurdardottir AK, Jonsdottir H, Benediktsson R. Outcomes of educational interventions in type 2 diabetes: WEKA data-mining analysis. Patient Educ Couns. 2007; 67(1-2): 21-31. Ko SH, Song KH, Kim SR, et al. Long-term effects of a structured intensive diabetes education programme (SIDEP) in patients with Type 2 diabetes mellitus--a 4-year follow-up study. Diabet Med. 2007; 24(1): 55-62. Kemp SF, Canfield ME, Kearns FS, Elders MJ. The effect of short-term intervention on long-term diabetes management. J Ark Med Soc. 1986; 83(6): 241-244. Bloomfield S, Calder JE, Chisholm V, et al. A project in diabetes education for children. Diabet Med. 1990; 7(2): 137-142. Rosenstock IM. Understanding and enhancing patient compliance with diabetic regimens. Diabetes Care. 1985; 8(6): 610-616. Bloomgarden ZT, Karmally W, Metzger MJ, et al. Randomized, controlled trial of diabetic patient education: improved knowledge without improved metabolic status. Diabetes Care. 1987; 10(3): 26372. Shea S. Health delivery system changes required when integrating telemedicine into existing treatment flows of information and patients. J Telemed Telecare. 2006;12(Suppl 2): S85-S90.
