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Cost-effectiveness of a Digital Health Intervention for Acute Myocardial Infarction Recovery.
Bhardwaj, Vinayak; Spaulding, Erin M; Marvel, Francoise A; LaFave, Sarah; Yu, Jeffrey; Mota, Daniel; Lorigiano, Ting-Jia; Huynh, Pauline P; Shan, Rongzi; Yesantharao, Pooja S; Lee, Matthias A; Yang, William E; Demo, Ryan; Ding, Jie; Wang, Jane; Xun, Helen; Shah, Lochan; Weng, Daniel; Wongvibulsin, Shannon; Carter, Jocelyn; Sheidy, Julie; McLin, Renee; Flowers, Jennifer; Majmudar, Maulik; Elgin, Eric; Vilarino, Valerie; Lumelsky, David; Leung, Curtis; Allen, Jerilyn K; Martin, Seth S; Padula, William V.
Afiliação
  • Bhardwaj V; Johns Hopkins Bloomberg School of Public Health.
  • Spaulding EM; Johns Hopkins Bloomberg School of Public Health.
  • Marvel FA; Johns Hopkins University School of Nursing.
  • LaFave S; Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine.
  • Yu J; Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine.
  • Mota D; Johns Hopkins University School of Medicine, Baltimore, MD.
  • Lorigiano TJ; Johns Hopkins University School of Nursing.
  • Huynh PP; Johns Hopkins Bloomberg School of Public Health.
  • Shan R; Department of Pharmaceutical & Health Economics, School of Pharmacy, University of Southern California.
  • Yesantharao PS; Leonard D. Schaeffer Center for Health Economics & Policy, University of Southern California, Los Angeles, CA.
  • Lee MA; Johns Hopkins Bloomberg School of Public Health.
  • Yang WE; Dimock Center.
  • Demo R; Johns Hopkins University School of Medicine, Baltimore, MD.
  • Ding J; Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine.
  • Wang J; Johns Hopkins University School of Medicine, Baltimore, MD.
  • Xun H; Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine.
  • Shah L; Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine.
  • Weng D; Johns Hopkins University School of Medicine, Baltimore, MD.
  • Wongvibulsin S; Johns Hopkins University Whiting School of Engineering, Baltimore, MD.
  • Carter J; Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine.
  • Sheidy J; Johns Hopkins University School of Medicine, Baltimore, MD.
  • McLin R; Johns Hopkins University Whiting School of Engineering, Baltimore, MD.
  • Flowers J; Johns Hopkins Bloomberg School of Public Health.
  • Majmudar M; Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine.
  • Elgin E; Johns Hopkins University School of Medicine, Baltimore, MD.
  • Vilarino V; Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine.
  • Lumelsky D; Johns Hopkins University School of Medicine, Baltimore, MD.
  • Leung C; Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine.
  • Allen JK; Johns Hopkins University School of Medicine, Baltimore, MD.
  • Martin SS; Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine.
  • Padula WV; Johns Hopkins University School of Medicine, Baltimore, MD.
Med Care ; 59(11): 1023-1030, 2021 11 01.
Article em En | MEDLINE | ID: mdl-34534188
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Telemedicina / Anos de Vida Ajustados por Qualidade de Vida / Infarto do Miocárdio Tipo de estudo: Guideline / Health_economic_evaluation Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Telemedicina / Anos de Vida Ajustados por Qualidade de Vida / Infarto do Miocárdio Tipo de estudo: Guideline / Health_economic_evaluation Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article