TY - JOUR
T1 - Impact of a High-Risk, Ambulatory COVID-19 Remote Patient Monitoring Program on Utilization, Cost, and Mortality
AU - Haddad, Tufia C.
AU - Coffey, Jordan D.
AU - Deng, Yihong
AU - Glasgow, Amy E.
AU - Christopherson, Laura A.
AU - Sangaralingham, Lindsey R.
AU - Bell, Sarah J.
AU - Shah, Vishal P.
AU - Pritchett, Joshua C.
AU - Orenstein, Robert
AU - Speicher, Leigh L.
AU - Maniaci, Michael J.
AU - Ganesh, Ravindra
AU - Borah, Bijan J.
N1 - Funding Information:
Dr Haddad has received research grant funding from Takeda Oncology to Mayo Clinic to conduct a clinical trial unrelated to the research presented in this manuscript. Dr Borah has received consulting fees from Exact Sciences and Boehringer Ingelheim in the last 3 years on topics not related to the content of the manuscript. The remaining authors report no potential competing interests.
Funding Information:
Grant Support : This study was made possible in part by funding from the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery. The funders had no role in the study design, conduct, and preparation of the manuscript. The Mayo Clinic Remote Patient Monitoring program is an enterprise shared service supported by the Mayo Clinic practice. There were no funding sources external to Mayo Clinic associated with this research study.
Publisher Copyright:
© 2022 The Authors
PY - 2022/12
Y1 - 2022/12
N2 - Objective: To evaluate care utilization, cost, and mortality among high-risk patients enrolled in a coronavirus disease 2019 (COVID-19) remote patient monitoring (RPM) program. Methods: This retrospective analysis included patients diagnosed with COVID-19 at risk for severe disease who enrolled in the RPM program between March 2020 and October 2021. The program included in-home technology for symptom and physiologic data monitoring with centralized care management. Propensity score matching established matched cohorts of RPM-engaged (defined as ≥1 RPM technology interactions) and non-engaged patients using a logistic regression model of 59 baseline characteristics. Billing codes and the electronic death certificate system were used for data abstraction from the electronic health record and reporting of care utilization and mortality endpoints. Results: Among 5796 RPM-enrolled patients, 80.0% engaged with the technology. Following matching, 1128 pairs of RPM-engaged and non-engaged patients comprised the analysis cohorts. Mean patient age was 63.3 years, 50.9% of patients were female, and 81.9% were non-Hispanic White. Patients who were RPM-engaged experienced significantly lower rates of 30-day, all-cause hospitalization (13.7% vs 18.0%, P=.01), prolonged hospitalization (3.5% vs 6.7%, P=.001), intensive care unit admission (2.3% vs 4.2%, P=.01), and mortality (0.5% vs 1.7%; odds ratio, 0.31; 95% CI, 0.12 to 0.78; P=.01), as well as cost of care ($2306.33 USD vs $3565.97 USD, P=0.04), than those enrolled in RPM but non-engaged. Conclusion: High-risk COVID-19 patients enrolled and engaged in an RPM program experienced lower rates of hospitalization, intensive care unit admission, mortality, and cost than those enrolled and non-engaged. These findings translate to improved hospital bed access and patient outcomes.
AB - Objective: To evaluate care utilization, cost, and mortality among high-risk patients enrolled in a coronavirus disease 2019 (COVID-19) remote patient monitoring (RPM) program. Methods: This retrospective analysis included patients diagnosed with COVID-19 at risk for severe disease who enrolled in the RPM program between March 2020 and October 2021. The program included in-home technology for symptom and physiologic data monitoring with centralized care management. Propensity score matching established matched cohorts of RPM-engaged (defined as ≥1 RPM technology interactions) and non-engaged patients using a logistic regression model of 59 baseline characteristics. Billing codes and the electronic death certificate system were used for data abstraction from the electronic health record and reporting of care utilization and mortality endpoints. Results: Among 5796 RPM-enrolled patients, 80.0% engaged with the technology. Following matching, 1128 pairs of RPM-engaged and non-engaged patients comprised the analysis cohorts. Mean patient age was 63.3 years, 50.9% of patients were female, and 81.9% were non-Hispanic White. Patients who were RPM-engaged experienced significantly lower rates of 30-day, all-cause hospitalization (13.7% vs 18.0%, P=.01), prolonged hospitalization (3.5% vs 6.7%, P=.001), intensive care unit admission (2.3% vs 4.2%, P=.01), and mortality (0.5% vs 1.7%; odds ratio, 0.31; 95% CI, 0.12 to 0.78; P=.01), as well as cost of care ($2306.33 USD vs $3565.97 USD, P=0.04), than those enrolled in RPM but non-engaged. Conclusion: High-risk COVID-19 patients enrolled and engaged in an RPM program experienced lower rates of hospitalization, intensive care unit admission, mortality, and cost than those enrolled and non-engaged. These findings translate to improved hospital bed access and patient outcomes.
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U2 - 10.1016/j.mayocp.2022.08.015
DO - 10.1016/j.mayocp.2022.08.015
M3 - Article
C2 - 36464463
AN - SCOPUS:85142474849
SN - 0025-6196
VL - 97
SP - 2215
EP - 2225
JO - Mayo Clinic Proceedings
JF - Mayo Clinic Proceedings
IS - 12
ER -