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

CME Credits: 1.00

Released: 2022-09-26

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 -2 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 ?-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.


Educational Objective
To identify the key insights or developments described in this article


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