A decision-analytic method to evaluate the cost-effectiveness of remote monitoring technology for chronic depression
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| Udgivet i: | International Journal of Technology Assessment in Health Care vol. 40, no. 1 (Jan 2025) |
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Cambridge University Press
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| Online adgang: | Citation/Abstract Full Text Full Text - PDF |
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| 001 | 3155894801 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 0266-4623 | ||
| 022 | |a 1471-6348 | ||
| 024 | 7 | |a 10.1017/S0266462324004677 |2 doi | |
| 035 | |a 3155894801 | ||
| 045 | 2 | |b d20250101 |b d20250228 | |
| 084 | |a 79035 |2 nlm | ||
| 100 | 1 | |a Sun, Xiaonan |u Department of Industrial and Systems Engineering, University of Washington, Seattle, WA, USA | |
| 245 | 1 | |a A decision-analytic method to evaluate the cost-effectiveness of remote monitoring technology for chronic depression | |
| 260 | |b Cambridge University Press |c Jan 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a ObjectivesAdvances in mobile apps, remote sensing, and big data have enabled remote monitoring of mental health conditions, but the cost-effectiveness is unknown. This study proposed a systematic framework integrating computational tools and decision-analytic modeling to assess cost-effectiveness and guide emerging monitoring technologies development.MethodsUsing a novel decision-analytic Markov-cohort model, we simulated chronic depression patients’ disease progression over 2 years, allowing treatment modifications at follow-up visits. The cost-effectiveness, from a payer’s viewpoint, of five monitoring strategies was evaluated for patients in low-, medium-, and high-risk groups: (i) remote monitoring technology scheduling follow-up visits upon detecting treatment change necessity; (ii) rule-based follow-up strategy assigning the next follow-up based on the patient’s current health state; and (iii–v) fixed frequency follow-up at two-month, four-month, and six-month intervals. Health outcomes (effects) were measured in quality-adjusted life-years (QALYs).ResultsBase case results showed that remote monitoring technology is cost-effective in the three risk groups under a willingness-to-pay (WTP) threshold of U.S. GDP per capita in year 2023. Full scenario analyses showed that, compared to rule-based follow-up, remote technology is 74 percent, 67 percent, and 74 percent cost-effective in the high-risk, medium-risk, and low-risk groups, respectively, and it is cost-effective especially if the treatment is effective and if remote monitoring is highly sensitive and specific.ConclusionsRemote monitoring for chronic depression proves cost-effective and potentially cost-saving in the majority of simulated scenarios. This framework can assess emerging remote monitoring technologies and identify requirements for the technologies to be cost-effective in psychiatric and chronic care delivery. | |
| 653 | |a Patients | ||
| 653 | |a Remote sensing | ||
| 653 | |a Simulation | ||
| 653 | |a Electronic health records | ||
| 653 | |a Datasets | ||
| 653 | |a Applications programs | ||
| 653 | |a Telemedicine | ||
| 653 | |a Mental disorders | ||
| 653 | |a Questionnaires | ||
| 653 | |a Mobile computing | ||
| 653 | |a Remote monitoring | ||
| 653 | |a Design specifications | ||
| 653 | |a Cost analysis | ||
| 653 | |a Mental depression | ||
| 653 | |a Mental health | ||
| 653 | |a Risk groups | ||
| 653 | |a Risk | ||
| 653 | |a Software | ||
| 653 | |a Evaluation | ||
| 653 | |a Cost effectiveness | ||
| 653 | |a Outpatient care facilities | ||
| 653 | |a Medical technology | ||
| 653 | |a Monitoring systems | ||
| 700 | 1 | |a Wissow, Lawrence |u Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA | |
| 700 | 1 | |a Liu, Shan |u Department of Industrial and Systems Engineering, University of Washington, Seattle, WA, USA | |
| 773 | 0 | |t International Journal of Technology Assessment in Health Care |g vol. 40, no. 1 (Jan 2025) | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3155894801/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3155894801/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3155894801/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |