TY - JOUR
T1 - Digital Health Intervention in Acute Myocardial Infarction
AU - Marvel, Francoise
AU - Spaulding, Erin M.
AU - Lee, Matthias A.
AU - Yang, William
AU - Demo, Ryan
AU - Ding, Jie
AU - Wang, Jane
AU - Xun, Helen
AU - Shah, Lochan M.
AU - Weng, Daniel
AU - Carter, Jocelyn
AU - Majmudar, Maulik
AU - Elgin, Eric
AU - Sheidy, Julie
AU - McLin, Renee
AU - Flowers, Jennifer
AU - Vilarino, Valerie
AU - Lumelsky, David N.
AU - Bhardwaj, Vinayak
AU - Padula, William V.
AU - Shan, Rongzi
AU - Huynh, Pauline P.
AU - Wongvibulsin, Shannon
AU - Leung, Curtis
AU - Allen, Jerilyn K.
AU - Martin, Seth S.
N1 - Funding Information:
This study received material support from Apple and iHealth and funding from the Maryland Innovation Initiative, Reading Hospital Foundation, Wallace H. Coulter Translational Research Partnership, Louis B. Thalheimer Fund, the Johns Hopkins Individualized Health Initiative, Ciccarone Center, and the Pollin Digital Innovation Fund. Sponsors provided financial support and supplied materials, while the academic investigators had full rights in the design, collection, analysis, or interpretation of the data, and final approval of the article for submission. Dr Spaulding has received the following financial support for the research, authorship, and publication of this article: National Institutes of Health (NIH)/NHLBI T32 HL007024 PostDoctoral Fellowship in Cardiovascular Epidemiology Institutional Training, NIH/ NINR F31 NR017328, Ruth L. Kirschstein National Research Service Award and NIH/NINR T32 NR012704, PreDoctoral Fellowship in Interdisciplinary Cardiovascular Health Research. Drs Carter, Shan, and Huynh have received support from the Aetna Foundation. Dr Wongvibulsin has received support from the Johns Hopkins School of Medicine Medical Scientist Training Program (National Institutes of Health: Institutional Predoctoral Training Grant—T32) and the National Institutes of Health: Ruth L. Kirschstein Individual Predoctoral NRSA for MD/PhD: F30 Training Grant. In addition to the study specific funding above, Dr Martin has received research support from the American Heart Association (20SFRN35380046 and COVID19-811000), PCORI (ME-2019C1-15328), National Institutes of Health (P01 HL108800), the Aetna Foundation, the David and June Trone Family Foundation, the Pollin Digital Innovation Fund, the PJ Schafer Cardiovascular Research Fund, Sandra and Larry Small, CASCADE FH, Apple, Google, and Amgen.
Publisher Copyright:
© 2021 Lippincott Williams and Wilkins. All rights reserved.
PY - 2021/7/1
Y1 - 2021/7/1
N2 - Background: Thirty-day readmissions among patients with acute myocardial infarction (AMI) contribute to the US health care burden of preventable complications and costs. Digital health interventions (DHIs) may improve patient health care self-management and outcomes. We aimed to determine if patients with AMI using a DHI have lower 30-day unplanned all-cause readmissions than a historical control. Methods: This nonrandomized controlled trial with a historical control, conducted at 4 US hospitals from 2015 to 2019, included 1064 patients with AMI (DHI n=200, control n=864). The DHI integrated a smartphone application, smartwatch, and blood pressure monitor to support guideline-directed care during hospitalization and through 30-days post-discharge via (1) medication reminders, (2) vital sign and activity tracking, (3) education, and (4) outpatient care coordination. The Patient Activation Measure assessed patient knowledge, skills, and confidence for health care self-management. All-cause 30-day readmissions were measured through administrative databases. Propensity score-adjusted Cox proportional hazard models estimated hazard ratios of readmission for the DHI group relative to the control group. Results: Following propensity score adjustment, baseline characteristics were well-balanced between the DHI versus control patients (standardized differences <0.07), including a mean age of 59.3 versus 60.1 years, 30% versus 29% Women, 70% versus 70% White, 54% versus 54% with private insurance, 61% versus 60% patients with a non ST-elevation myocardial infarction, and 15% versus 15% with high comorbidity burden. DHI patients were predominantly in the highest levels of patient activation for health care self-management (mean score 71.7±16.6 at 30 days). The DHI group had fewer all-cause 30-day readmissions than the control group (6.5% versus 16.8%, respectively). Adjusting for hospital site and a propensity score inclusive of age, sex, race, AMI type, comorbidities, and 6 additional confounding factors, the DHI group had a 52% lower risk for all-cause 30-day readmissions (hazard ratio, 0.48 [95% CI, 0.26-0.88]). Similar results were obtained in a sensitivity analysis employing propensity matching. Conclusions: Our results suggest that in patients with AMI, the DHI may be associated with high patient activation for health care self-management and lower risk of all-cause unplanned 30-day readmissions. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03760796.
AB - Background: Thirty-day readmissions among patients with acute myocardial infarction (AMI) contribute to the US health care burden of preventable complications and costs. Digital health interventions (DHIs) may improve patient health care self-management and outcomes. We aimed to determine if patients with AMI using a DHI have lower 30-day unplanned all-cause readmissions than a historical control. Methods: This nonrandomized controlled trial with a historical control, conducted at 4 US hospitals from 2015 to 2019, included 1064 patients with AMI (DHI n=200, control n=864). The DHI integrated a smartphone application, smartwatch, and blood pressure monitor to support guideline-directed care during hospitalization and through 30-days post-discharge via (1) medication reminders, (2) vital sign and activity tracking, (3) education, and (4) outpatient care coordination. The Patient Activation Measure assessed patient knowledge, skills, and confidence for health care self-management. All-cause 30-day readmissions were measured through administrative databases. Propensity score-adjusted Cox proportional hazard models estimated hazard ratios of readmission for the DHI group relative to the control group. Results: Following propensity score adjustment, baseline characteristics were well-balanced between the DHI versus control patients (standardized differences <0.07), including a mean age of 59.3 versus 60.1 years, 30% versus 29% Women, 70% versus 70% White, 54% versus 54% with private insurance, 61% versus 60% patients with a non ST-elevation myocardial infarction, and 15% versus 15% with high comorbidity burden. DHI patients were predominantly in the highest levels of patient activation for health care self-management (mean score 71.7±16.6 at 30 days). The DHI group had fewer all-cause 30-day readmissions than the control group (6.5% versus 16.8%, respectively). Adjusting for hospital site and a propensity score inclusive of age, sex, race, AMI type, comorbidities, and 6 additional confounding factors, the DHI group had a 52% lower risk for all-cause 30-day readmissions (hazard ratio, 0.48 [95% CI, 0.26-0.88]). Similar results were obtained in a sensitivity analysis employing propensity matching. Conclusions: Our results suggest that in patients with AMI, the DHI may be associated with high patient activation for health care self-management and lower risk of all-cause unplanned 30-day readmissions. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03760796.
KW - cardiovascular disease
KW - hospitalization
KW - secondary prevention
KW - smartphone
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U2 - 10.1161/CIRCOUTCOMES.121.007741
DO - 10.1161/CIRCOUTCOMES.121.007741
M3 - Article
C2 - 34261332
AN - SCOPUS:85111112843
SN - 1941-7713
VL - 14
SP - E007741
JO - Circulation: Cardiovascular Quality and Outcomes
JF - Circulation: Cardiovascular Quality and Outcomes
IS - 7
ER -