만성질환 관리를 위한 정보통신기술 기반 모니터링방법의 경제성평가 연구에 대한 체계적 문헌 고찰: 고혈압·당뇨질환을 중심으로
Systematic Review of Economic Evaluation Model of Information and Communication Technologies Based Monitoring in Chronic Disease Management: Hypertension and Diabetes Mellitus
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Objectives: Chronic diseases are associated with increased cardiovascular disease (CVD) and mortality, causing premature death and undermining individual quality of life, which has a huge economic impact on society. As new interventions become available, estimates of economic and clinical outcome based on decision-analytic models are required. We aimed to systematically review economic models of information and communication technologies (ICT) based Monitoring in Chronic Disease Management. Methods: The search for potentially relevant studies was conducted on using PubMed, Cochrane Library, and two Korean databases up to October 2020. Data related to model structure and assumptions, effect estimation and cost estimation were extracted from each model. Data synthesis of the included studies was performed using a qualitative method. Results: Selected models were classified into hypertension models (n=2) and diabetes models (n=5). Typically, the published models utilized frameworks based on systolic blood pressure or HbA1c. Under the assumption that short-term effects of intervention will last for a long time, core structures are Markov models that estimates long-term effects based on the patient’s baseline risk factors observed in clinical trials, using CVD risk assessment tools such as the Framingham prediction model. From the perspective of the healthcare system, the cost items expend during a time horizon of lifetime included Physician visit, Drug, intervention (consisting of equipment, running, training and coordinator costs) and treatment costs of complications. Conclusion: This study confirmed the conceptualization and structuring process of the economic model of ICT-based monitoring services for patients with chronic disease. Clarifying this process, and evaluating structural uncertainty will improve the quality of the model and increase the reliability of predicting outcomes. We suggest to design models through the published literature review to increase model validity, which is expected to help provide reliable information to decision makers by enhancing transparency, comprehensiveness and consistency of model structuring.
Abstract
Objectives: Chronic diseases are associated with increased cardiovascular disease (CVD) and mortality, causing premature death and undermining individual quality of life, which has a huge economic impact on society. As new interventions become available, estimates of economic and clinical outcome based on decision-analytic models are required. We aimed to systematically review economic models of information and communication technologies (ICT) based Monitoring in Chronic Disease Management. Methods: The search for potentially relevant studies was conducted on using PubMed, Cochrane Library, and two Korean databases up to October 2020. Data related to model structure and assumptions, effect estimation and cost estimation were extracted from each model. Data synthesis of the included studies was performed using a qualitative method. Results: Selected models were classified into hypertension models (n=2) and diabetes models (n=5). Typically, the published models utilized frameworks based on systolic blood pressure or HbA1c. Under the assumption that short-term effects of intervention will last for a long time, core structures are Markov models that estimates long-term effects based on the patient’s baseline risk factors observed in clinical trials, using CVD risk assessment tools such as the Framingham prediction model. From the perspective of the healthcare system, the cost items expend during a time horizon of lifetime included Physician visit, Drug, intervention (consisting of equipment, running, training and coordinator costs) and treatment costs of complications. Conclusion: This study confirmed the conceptualization and structuring process of the economic model of ICT-based monitoring services for patients with chronic disease. Clarifying this process, and evaluating structural uncertainty will improve the quality of the model and increase the reliability of predicting outcomes. We suggest to design models through the published literature review to increase model validity, which is expected to help provide reliable information to decision makers by enhancing transparency, comprehensiveness and consistency of model structuring.
참고문헌 (29)
- International Telecommunication Union, "ICT facts and figures: the world in 2015", ITU, ~ (2015)
- Fiordelli M, "Mapping mHealth research: a decade of evolution", J Med Internet Res, 15, pp.e95~ (2013)
- Iribarren SJ, "What is the economic evidence for mHealth? A systematic review of economic evaluations of mHealth solutions", PLoS One, 12, pp.e0170581~ (2017)
- Labrique AB, "mHealth innovations as health system strengthening tools: 12 common applications and a visual framework", Glob Health Sci Pract, 1, pp.160~171 (2013)
- Davis RM, "Managing chronic disease", BMJ, 318, pp.1090~1091 (1999)
- GBD 2019 Diseases and Injuries Collaborators, "Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019:a systematic analysis for the Global Burden of Disease Study 2019", Lancet, 396, pp.1204~1222 (2020)
- Global report on diabetes, "World Health Organization", World Health Organization, ~ (2016)
- 보건복지부, "일차의료 만성질환관리 시범사업 안내", 보건복지부, ~ (2021)
- Peretz D, "Determining the cost of implementing and operating a remote patient monitoring programme for the elderly with chronic conditions: a systematic review of economic evaluations", J Telemed Telecare, 24, pp.13~21 (2018)
- Istepanian RSH, "m-Health interventions for diabetes remote monitoring and self management: clinical and compliance issues", Mhealth, 4, pp.4~ (2018)
- Teljeur C, "Economic evaluation of chronic disease self-management for people with diabetes: a systematic review", Diabet Med, 34, pp.1040~1049 (2017)
- Haji Ali Afzali H, "A critical review of model-based economic studies of depression: modelling techniques, model structure and data sources", Pharmacoeconomics, 30, pp.461~482 (2012)
- Varney JE, "The cost-effectiveness of hospital-based telephone coaching for people with type 2 diabetes: a 10 year modelling analysis", BMC Health Serv Res, 16, pp.521~ (2016)
- Monahan M, "Cost-effectiveness of telemonitoring and self-monitoring of blood pressure for antihypertensive titration in primary care (TASMINH4)", Hypertension, 73, pp.1231~1239 (2019)
- Halpern MT, "Health and economic outcomes modeling practices: a suggested framework", Value Health, 1, pp.131~147 (1998)
- Sculpher M, "Assessing quality in decision analytic cost-effectiveness models. A suggested framework and example of application", Pharmacoeconomics, 17, pp.461~477 (2000)
- Mistry H, "Systematic review of studies of the cost-effectiveness of telemedicine and telecare. Changes in the economic evidence over twenty years", J Telemed Telecare, 18, pp.1~6 (2012)
- Husereau D, "Consolidated health economic evaluation reporting standards (CHEERS) statement", Value Health, 16, pp.e1~e5 (2013)
- Kaambwa B, "elemonitoring and self-management in the control of hypertension (TASMINH2): a cost-effectiveness analysis", Eur J Prev Cardiol, 21, pp.1517~1530 (2014)
- Gilmer T, "Costeffectiveness of a technology-enhanced diabetes care management program in Mexico", Value Health Reg Issues, 20, pp.41~46 (2019)
- Gordon LG, "A cost-effectiveness analysis of a telephone-linked care intervention for individuals with type 2 diabetes", Diabetes Res Clin Pract, 104, pp.103~111 (2014)
- Odnoletkova I, "Delivering diabetes education through nurse-led telecoaching. Cost-effectiveness analysis", PLoS One, 11, pp.e0163997~ (2016)
- Chaugule S, "Cost-effectiveness of G5 Mobile continuous glucose monitoring device compared to self-monitoring of blood glucose alone for people with type 1 diabetes from the Canadian societal perspective", J Med Econ, 20, pp.1128~1135 (2017)
- Hamine S, "Impact of mHealth chronic disease management on treatment adherence and patient outcomes: a systematic review", J Med Internet Res, 17, pp.e52~ (2015)
- D’Agostino RB Sr, "General cardiovascular risk profile for use in primary care: the Framingham Heart Study", Circulation, 117, pp.743~753 (2008)
- Stevens RJ, "The UKPDS risk engine: a model for the risk of coronary heart disease in type II diabetes (UKPDS 56)", Clin Sci (Lond), 101, pp.671~679 (2001)
- Roberts M, "Conceptualizing a model: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--2", Value Health, 15, pp.804~811 (2012)
- Canadian Agency for Drugs and Technologies in Health, "Guidelines for the economic evaluation of health technologies: Canada" (2017), CADTH
- Haji Ali Afzali H, "Model structuring for economic evaluations of new health technologies", Pharmacoeconomics, 36, pp.1309~1319 (2018)