期刊
MEDICAL CARE
卷 59, 期 11, 页码 1023-1030出版社
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/MLR.0000000000001636
关键词
cost-effectiveness; cost-utility analysis; medical economics; myocardial infarction; readmission; mobile health; digital health
类别
资金
- Maryland Innovation Initiative
- Wallace H. Coulter Translational Research Partnership
- Louis B. Thalheimer Fund
- Ciccarone Center
- Pollin Digital Innovation Fund
- Johns Hopkins Individualized Health Initiative
- NIH/NHLBI Post-Doctoral Fellowship in Cardiovascular Epidemiology Institutional Training [T32 HL007024]
- NIH/NINR Ruth L. Kirschstein National Research Service Award [F31 NR017328]
- NIH/NINR Pre-Doctoral Fellowship in Interdisciplinary Cardiovascular Health Research [T32 NR012704]
- Aetna Foundation
- Johns Hopkins School of Medicine Medical Scientist Training Program (National Institutes of Health: Institutional Predoctoral Training T32 Grant) [5T32GM007309]
- National Institutes of Health [5 F30 HL142131]
- American Heart Association [20SFRN35380046, COVID19-811000]
- PCORI [ME-2019C1-15328]
- NIH [P01 HL108800, KL2 TR001854]
- David and June Trone Family Foundation
- PJ Schafer Cardiovascular Research Fund
- Sandra and Larry Small
- CASCADE FH
- Apple
- Amgen
The digital health intervention (DHI) is cost-saving by reducing the risk of all-cause readmissions among AMI patients, promoting adherence to guideline-based healthcare, and reducing hospital readmissions and associated costs.
Background: Acute myocardial infarction (AMI) is a common cause of hospital admissions, readmissions, and mortality worldwide. Digital health interventions (DHIs) that promote self-management, adherence to guideline-directed therapy, and cardiovascular risk reduction may improve health outcomes in this population. The Corrie DHI consists of a smartphone application, smartwatch, and wireless blood pressure monitor to support medication tracking, education, vital signs monitoring, and care coordination. We aimed to assess the cost-effectiveness of this DHI plus standard of care in reducing 30-day readmissions among AMI patients in comparison to standard of care alone. Methods: A Markov model was used to explore cost-effectiveness from the hospital perspective. The time horizon of the analysis was 1 year, with 30-day cycles, using inflation-adjusted cost data with no discount rate. Currencies were quantified in US dollars, and effectiveness was measured in quality-adjusted life-years (QALYs). The results were interpreted as an incremental cost-effectiveness ratio at a threshold of $100,000 per QALY. Univariate sensitivity and multivariate probabilistic sensitivity analyses tested model uncertainty. Results: The DHI reduced costs and increased QALYs on average, dominating standard of care in 99.7% of simulations in the probabilistic analysis. Based on the assumption that the DHI costs $2750 per patient, use of the DHI leads to a cost-savings of $7274 per patient compared with standard of care alone. Conclusions: Our results demonstrate that this DHI is cost-saving through the reduction of risk for all-cause readmission following AMI. DHIs that promote improved adherence with guideline-based health care can reduce hospital readmissions and associated costs.
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