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Comparison of Quality Performance Measures for Patients Receiving In-Person vs Telemedicine Primary Care in a Large Integrated Health System

Educational Objective
To identify the key insights or developments described in this article
1 Credit CME
Key Points

Question  Is there a difference in standardized quality performance measures for primary care patients exposed to telemedicine compared with patients with office-only (in-person) care?

Findings  In this cohort study of 526 874 patients, telemedicine exposure was associated with significantly better performance or no difference in 13 of 16 comparisons, mostly in testing-based and counseling-based quality measures. Patients with office-only visits had modestly better performance in 3 of 5 medication-based quality measures.

Meaning  Findings suggest that telemedicine exposure in primary care poses a low risk for negatively affecting quality performance, highlighting its potential to suitably augment care capacity.

Abstract

Importance  Despite its rapid adoption during the COVID-19 pandemic, it is unknown how telemedicine augmentation of in-person office visits has affected quality of patient care.

Objective  To examine whether quality of care among patients exposed to telemedicine differs from patients with only in-person office-based care.

Design, Setting, and Participants  In this retrospective cohort study, standardized quality measures were compared between patients with office-only (in-person) visits vs telemedicine visits from March 1, 2020, to November 30, 2021, across more than 200 outpatient care sites in Pennsylvania and Maryland.

Exposures  Patients completing telemedicine (video) visits.

Main Outcomes and Measures  χ2 tests determined statistically significant differences in Health Care Effectiveness Data and Information Set (HEDIS) quality performance measures between office-only and telemedicine-exposed groups. Multivariable logistic regression controlled for sociodemographic factors and comorbidities.

Results  The study included 526 874 patients (409 732 office-only; 117 142 telemedicine exposed) with a comparable distribution of sex (196 285 [49.7%] and 74 878 [63.9%] women), predominance of non-Hispanic (348 127 [85.0%] and 105 408 [90.0%]) and White individuals (334 215 [81.6%] and 100 586 [85.9%]), aged 18 to 65 years (239 938 [58.6%] and 91 100 [77.8%]), with low overall health risk scores (373 176 [91.1%] and 100 076 [85.4%]) and commercial (227 259 [55.5%] and 81 552 [69.6%]) or Medicare or Medicaid (176 671 [43.1%] and 52 513 [44.8%]) insurance. For medication-based measures, patients with office-only visits had better performance, but only 3 of 5 measures had significant differences: patients with cardiovascular disease (CVD) receiving antiplatelets (absolute percentage difference [APD], 6.71%; 95% CI, 5.45%-7.98%; P < .001), patients with CVD receiving statins (APD, 1.79%; 95% CI, 0.88%-2.71%; P = .001), and avoiding antibiotics for patients with upper respiratory infections (APD, 2.05%; 95% CI, 1.17%-2.96%; P < .001); there were insignificant differences for patients with heart failure receiving β-blockers and those with diabetes receiving statins. For all 4 testing-based measures, patients with telemedicine exposure had significantly better performance differences: patients with CVD with lipid panels (APD, 7.04%; 95% CI, 5.95%-8.10%; P < .001), patients with diabetes with hemoglobin A1c testing (APD, 5.14%; 95% CI, 4.25%-6.01%; P < .001), patients with diabetes with nephropathy testing (APD, 9.28%; 95% CI, 8.22%-10.32%; P < .001), and blood pressure control (APD, 3.55%; 95% CI, 3.25%-3.85%; P < .001); this was also true for all 7 counseling-based measures: cervical cancer screening (APD, 12.33%; 95% CI, 11.80%-12.85%; P < .001), breast cancer screening (APD, 16.90%; 95% CI, 16.07%-17.71%; P < .001), colon cancer screening (APD, 8.20%; 95% CI, 7.65%-8.75%; P < .001), tobacco counseling and intervention (APD, 12.67%; 95% CI, 11.84%-13.50%; P < .001), influenza vaccination (APD, 9.76%; 95% CI, 9.47%-10.05%; P < .001), pneumococcal vaccination (APD, 5.41%; 95% CI, 4.85%-6.00%; P < .001), and depression screening (APD, 4.85%; 95% CI, 4.66%-5.04%; P < .001).

Conclusions and Relevance  In this cohort study of patients with telemedicine exposure, there was a largely favorable association with quality of primary care. This supports telemedicine’s value potential for augmenting care capacity, especially in chronic disease management and preventive care. This study also identifies a need for understanding relationships between the optimal blend of telemedicine and in-office care.

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CME Disclosure Statement: Unless noted, all individuals in control of content reported no relevant financial relationships. If applicable, all relevant financial relationships have been mitigated.

Article Information

Accepted for Publication: July 31, 2022.

Published: September 26, 2022. doi:10.1001/jamanetworkopen.2022.33267

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Baughman DJ et al. JAMA Network Open.

Corresponding Author: Derek J. Baughman, MD, Family Medicine Residency Program, WellSpan Good Samaritan Hospital, 308 Park Ave, Lebanon, PA 17042 (baughman.derek@gmail.com).

Author Contributions: Drs D. Baughman and Waheed 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: D. Baughman, Jabbarpour, Westfall, Zain, K. Baughman, Waheed.

Acquisition, analysis, or interpretation of data: D. Baughman, Westfall, Jetty, Pollak, Waheed.

Drafting of the manuscript: D. Baughman, Jetty, Zain, K. Baughman, Waheed.

Critical revision of the manuscript for important intellectual content: D. Baughman, Jabbarpour, Westfall, Zain, K. Baughman, Pollak, Waheed.

Statistical analysis: D. Baughman, Jetty, Waheed.

Administrative, technical, or material support: Westfall, K. Baughman, Pollak, Waheed.

Supervision: Jabbarpour, Westfall, Waheed.

Conflict of Interest Disclosures: None reported.

Additional Contributions: Steve Strom, MS, was an expert consulted for SlicerDicer data mining. Theodore Bell, BS, advised on the statistical analysis approach. There were not compensated for their time. The Robert Graham Center staff provided substantial guidance in research methods and editorial feedback.

AMA CME Accreditation Information

Credit Designation Statement: The American Medical Association designates this Journal-based CME activity activity for a maximum of 1.00  AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to:

  • 1.00 Medical Knowledge MOC points in the American Board of Internal Medicine's (ABIM) Maintenance of Certification (MOC) program;;
  • 1.00 Self-Assessment points in the American Board of Otolaryngology – Head and Neck Surgery’s (ABOHNS) Continuing Certification program;
  • 1.00 MOC points in the American Board of Pediatrics’ (ABP) Maintenance of Certification (MOC) program;
  • 1.00 Lifelong Learning points in the American Board of Pathology’s (ABPath) Continuing Certification program; and
  • 1.00 credit toward the CME [and Self-Assessment requirements] of the American Board of Surgery’s Continuous Certification program

It is the CME activity provider's responsibility to submit participant completion information to ACCME for the purpose of granting MOC credit.

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