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Table 1.  Patients With Positive SARS-CoV-2 Test Result by Home Monitoring Program Participation (Overall and Subgroups)
Patients With Positive SARS-CoV-2 Test Result by Home Monitoring Program Participation (Overall and Subgroups)
Table 2.  Patients With Positive SARS-CoV-2 Test Result by Home Monitoring Program Participation and the Overlap Between Propensity Score Weighted Characteristics and Outcomes Overall and by Subgroup
Patients With Positive SARS-CoV-2 Test Result by Home Monitoring Program Participation and the Overlap Between Propensity Score Weighted Characteristics and Outcomes Overall and by Subgroup
1.
Morgan  AU, Balachandran  M, Do  D,  et al. Remote monitoring of patients with Covid-19: design, implementation, and outcomes of the first 3,000 patients in COVID Watch. Published online July 21, 2020. Accessed January 22, 2021. https://catalyst.nejm.org/doi/full/10.1056/CAT.20.0342
2.
Ye  S, Hiura  G, Fleck  E,  et al.  Hospital readmissions after implementation of a discharge care program for patients with COVID-19 illness.   J Gen Intern Med. 2021;36(3):722-729. doi:10.1007/s11606-020-06340-w PubMedGoogle ScholarCrossref
3.
Gordon  WJ, Henderson  D, DeSharone  A,  et al.  Remote patient monitoring program for hospital discharged COVID-19 patients.   Appl Clin Inform. 2020;11(5):792-801. doi:10.1055/s-0040-1721039 PubMedGoogle ScholarCrossref
4.
Aalam  AA, Hood  C, Donelan  C, Rutenberg  A, Kane  EM, Sikka  N.  Remote patient monitoring for ED discharges in the COVID-19 pandemic.   Emerg Med J. 2021;38(3):229-231. doi:10.1136/emermed-2020-210022 PubMedGoogle ScholarCrossref
5.
Li  F, Thomas  LE, Li  F.  Addressing extreme propensity scores via the overlap weights.   Am J Epidemiol. 2019;188(1):250-257. doi:10.1093/aje/kwy201PubMedGoogle Scholar
6.
Wright  A, Salazar  A, Mirica  M, Volk  LA, Schiff  GD.  The invisible epidemic: neglected chronic disease management during COVID-19.   J Gen Intern Med. 2020;35(9):2816-2817. doi:10.1007/s11606-020-06025-4PubMedGoogle ScholarCrossref
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    Views 3,884
    Research Letter
    May 6, 2021

    COVID-19 Home Monitoring After Diagnosis and Health Care Utilization in an Integrated Health System

    Author Affiliations
    • 1Healthcare Delivery and Implementation Science Center, Cleveland Clinic, Cleveland, Ohio
    • 2Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio
    • 3Department of Neurology, Neurological Institute, Cleveland Clinic, Cleveland, Ohio
    • 4Center for Value-Based Care Research, Cleveland Clinic Community Care, Cleveland, Ohio
    JAMA Health Forum. 2021;2(5):e210333. doi:10.1001/jamahealthforum.2021.0333
    Introduction

    Remote monitoring programs have been implemented for patients with suspected or confirmed COVID-191 after hospital discharge2,3 or emergency department (ED) visits.4 The Cleveland Clinic Health System (CCHS) established a home monitoring program (HMP) for patients with positive test results for SARS-Co-V-2. We assessed health care utilization patterns for patients enrolled in the HMP compared with similar patients who were not enrolled.

    Methods

    We identified patients with positive test results for SARS-CO-V-2 in the CCHS (US Centers for Disease Control and Prevention assay, Roche magnapure extraction, ABI 7500 DX polymerase chain reaction) from March 1 to July 31, 2020, from the CCHS COVID-19 registry, which included demographic and clinical variables. Utilization in the year before the SARS-Co-V-2 test (eg, hospitalizations, ED, outpatient visits) was obtained from the electronic medical record (EMR). While all patients with COVID-19 were offered HMP enrollment to receive telephone outreach (a description of the HMP can be found in eAppendix 1 in the Supplement), to more confidently capture EMR utilization data, we limited our analysis to patients with an assigned CCHS primary care physician (the study population is described in eAppendix 2 in the Supplement). Race/ethnicity was captured from the EMR and included, given its potential contribution to COVID-19 outcomes. Descriptive statistics were reported as counts (percentages) or median values (interquartile ranges). For demographic characteristic and comorbidity comparisons, Wilcoxon signed-rank tests were used for numeric variables and χ2 or Fisher exact tests for categorical variables. Overlap propensity score weighting5 using all collected variables was then used to address baseline group differences in those enrolled vs not enrolled in the HMP. The 30-day and 90-day utilization outcomes, including hospitalizations (primary outcome) and ED and outpatient visits, were measured while excluding ED visits or hospitalizations that occurred within 24 hours of the positive SARS-Co-V-2 test result. Subgroup analyses were performed for patients with positive test results that were associated with hospitalization/ED or outpatient visits. This study was approved by the CCHS institutional review board as minimal risk; thus, consent was not required. The reporting follows the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. All statistical analyses were performed using the tidyverse and survey package with R software (R Foundation). Statistical significance was set at P < .05.

    Results

    Baseline characteristics of the study population by HMP participation and subgroup are shown in Table 1. There were 3975 patients who participated and 3221 who did not. Those participating overall were younger; more likely to be women, Black individuals, and/or individuals with non-Hispanic ethnicity; and have more asthma diagnoses, a lower proportion of several other comorbidities, and more prior year outpatient visits. Overlap propensity score weighting and odds ratios (ORs) for the outcomes are shown in Table 2. There were lower odds of 30-day or 90-day hospitalization (OR, 0.73; 95% CI, 0.60-0.88; and OR, 0.79; 95% CI, 0.67-0.93, respectively) but no significant association of the HMP with 30-day or 90-day ED utilization (OR, 0.91; 95% CI, 0.75-1.12; and OR, 0.96; 95% CI, 0.81-1.15, respectively), and there were higher odds of outpatient visits at 30 and 90 days (OR, 1.97; 95% CI, 1.68-2.30; and OR, 2.09; 95% CI, 1.76-2.48, respectively). A subgroup analysis showed lower odds of future hospitalization that was limited to patients posthospitalization or ED visits (OR, 0.62; 95% CI, 0.48-0.81; and OR, 0.70; 95% CI, 0.55-0.89 for 30-day and 90-day hospitalization, respectively).

    Discussion

    The COVID-19 HMP was associated with lower odds of hospitalization, particularly for the posthospital or ED subgroup, with no significant association with ED utilization up to 90 days after diagnosis and with higher odds of subsequent outpatient utilization. Limitations include that these findings are from a single health system, and our analytic methods may not have adjusted for all confounders, specifically the choice for HMP enrollment. The COVID-19 pandemic has prompted resource distribution discussions and concern for missed opportunities for chronic disease management.6 This study’s outcomes support the need for randomized clinical trials to evaluate HMPs and consideration of targeted resource allocation for home monitoring after COVID-19 diagnosis or to other opportunities to maintain the health of patients during the pandemic.

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    Article Information

    Accepted for Publication: March 3, 2021.

    Published: May 6, 2021. doi:10.1001/jamahealthforum.2021.0333

    Corresponding Author: Anita D. Misra-Hebert, MD, MPH, 9500 Euclid Ave, G10, Cleveland, OH 44915 (misraa@ccf.org).

    Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Misra-Hebert AD et al. JAMA Health Forum.

    Author Contributions: Dr Misra-Hebert and Ms Ji had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Misra-Hebert, Jehi, Pfoh, Young.

    Acquisition, analysis, or interpretation of data: Misra-Hebert, Ji, Milinovich, Kattan.

    Drafting of the manuscript: Misra-Hebert, Milinovich.

    Critical revision of the manuscript for important intellectual content: Misra-Hebert, Ji, Jehi, Pfoh, Kattan, Young.

    Statistical analysis: Ji, Kattan.

    Obtained funding: Misra-Hebert, Young.

    Administrative, technical, or material support: Jehi, Milinovich, Young.

    Supervision: Misra-Hebert, Pfoh, Young.

    Conflict of Interest Disclosures: Dr Misra-Hebert reported grants from the Agency for Healthcare Research and Quality, National Heart Lung and Blood Institute, National Human Genome Research Institute, Novo Nordisk, Merck, and Boehringer Ingelheim Pharmaceuticals outside the submitted work. Dr Jehi receives funding from the National Institute of Neurological Disorders and Stroke and from the National Center for Advancing Translational Science outside the submitted work. Mr Milinovich receives grants from Novo Nordisk, Merck, Boehringer Ingelheim Pharmaceuticals, National Institute on Aging, and NFL Players Association outside the submitted work. Dr Kattan receives grant funding from Novo Nordisk, Merck, and Boehringer Ingelheim Pharmaceuticals and is a consultant for GlaxoSmithKline and RenalytixAI outside of the submitted work. No other disclosures were reported.

    Funding/Support: This work was internally funded by the Healthcare Delivery and Implementation Science Center at Cleveland Clinic.

    Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    Data Sharing Statement: Data used for this study includes human research participant data that are sensitive and cannot be publicly shared due to legal and ethical restrictions by the Cleveland Clinic regulatory bodies, including the institutional review board and legal counsel. In particular, variables such as date of testing or dates of hospitalization are HIPAA protected health information and legally cannot be publicly shared. We will make our data sets available on request, under appropriate data use agreements with the specific parties interested in academic collaboration. Requests for data access can be made to Dr Misra-Hebert.

    Additional Contributions: We thank Nirav Vakharia, MD, Christopher Babiuch, MD, Robert Jones, MD, and Eric Boose, MD (Cleveland Clinic Community Care), for contributing their operational knowledge about the home monitoring program to the study team and to Janine Bauman, BSN, Cleveland Clinic, for her assistance with the regulatory components of the execution of the study. All named individuals have provided written permission for their acknowledgment and have received no financial compensation outside of their job-related duties.

    References
    1.
    Morgan  AU, Balachandran  M, Do  D,  et al. Remote monitoring of patients with Covid-19: design, implementation, and outcomes of the first 3,000 patients in COVID Watch. Published online July 21, 2020. Accessed January 22, 2021. https://catalyst.nejm.org/doi/full/10.1056/CAT.20.0342
    2.
    Ye  S, Hiura  G, Fleck  E,  et al.  Hospital readmissions after implementation of a discharge care program for patients with COVID-19 illness.   J Gen Intern Med. 2021;36(3):722-729. doi:10.1007/s11606-020-06340-w PubMedGoogle ScholarCrossref
    3.
    Gordon  WJ, Henderson  D, DeSharone  A,  et al.  Remote patient monitoring program for hospital discharged COVID-19 patients.   Appl Clin Inform. 2020;11(5):792-801. doi:10.1055/s-0040-1721039 PubMedGoogle ScholarCrossref
    4.
    Aalam  AA, Hood  C, Donelan  C, Rutenberg  A, Kane  EM, Sikka  N.  Remote patient monitoring for ED discharges in the COVID-19 pandemic.   Emerg Med J. 2021;38(3):229-231. doi:10.1136/emermed-2020-210022 PubMedGoogle ScholarCrossref
    5.
    Li  F, Thomas  LE, Li  F.  Addressing extreme propensity scores via the overlap weights.   Am J Epidemiol. 2019;188(1):250-257. doi:10.1093/aje/kwy201PubMedGoogle Scholar
    6.
    Wright  A, Salazar  A, Mirica  M, Volk  LA, Schiff  GD.  The invisible epidemic: neglected chronic disease management during COVID-19.   J Gen Intern Med. 2020;35(9):2816-2817. doi:10.1007/s11606-020-06025-4PubMedGoogle ScholarCrossref
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