Economic Evaluations of Remote Patient Monitoring for Chronic Disease: A Systematic Review



This study aimed to systematically review and summarize economic evaluations of noninvasive remote patient monitoring (RPM) for chronic diseases compared with usual care.


A systematic literature search identified economic evaluations of RPM for chronic diseases, compared with usual care. Searches of PubMed, Embase, CINAHL, and EconLit using keyword synonyms for RPM and economics identified articles published from up until September 2021. Title, abstract, and full-text reviews were conducted. Data extraction of study characteristics and health economic findings was performed. Article reporting quality was assessed using the Consolidated Health Economic Evaluation Reporting Standards checklist.


This review demonstrated that the cost-effectiveness of RPM was dependent on clinical context, capital investment, organizational processes, and willingness to pay in each specific setting. RPM was found to be highly cost-effective for hypertension and may be cost-effective for heart failure and chronic obstructive pulmonary disease. There were few studies that investigated RPM for diabetes or other chronic diseases. Studies were of high reporting quality, with an average Consolidated Health Economic Evaluation Reporting Standards score of 81%. Of the final 34 included studies, most were conducted from the healthcare system perspective. Eighteen studies used cost-utility analysis, 4 used cost-effectiveness analysis, 2 combined cost-utility analysis and a cost-effectiveness analysis, 1 used cost-consequence analysis, 1 used cost-benefit analysis, and 8 used cost-minimization analysis.


RPM was highly cost-effective for hypertension and may achieve greater long-term cost savings from the prevention of high-cost health events. For chronic obstructive pulmonary disease and heart failure, cost-effectiveness findings differed according to disease severity and there was limited economic evidence for diabetes interventions.


Keshia R. De Guzman Centaine L. Snoswell Monica L. Taylor Leonard C. Gray Liam J. Caffery

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