The Role of Telehealth Payment Parity on Recommended Care and Emergency Department Service Utilization Among Workers With Chronic Conditions
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: State-level telehealth payment parity, requiring equal payment rates for telehealth and in-person visits, played an important role in ensuring access to telehealth services. The objective of our study is to evaluate how improved access, driven by telehealth payment parity, affected the utilization of disease-specific recommended care management services and emergency department (ED) services among insured patients with chronic conditions. RESEARCH DESIGN: We adopted a 2-way fixed-effect difference-in-differences approach using the Merative Commercial Claims and Encounters database from 2019 to 2021. SUBJECTS: We focused on insured workers aged 19-64 with pre-existing mental health disorders or cardiometabolic risks (CMRs). MEASURES: Outcomes include psychotherapy for mental health disorders, preventive care counseling for CMRs, and ED visits. RESULTS: Telehealth payment parity was associated with a significant increase in the number of psychotherapy visits and tele-psychotherapy by 0.221 visits (95% CI: 0.050-0.391) and 0.411 visits (95% CI: 0.003-0.818) per patient per quarter, respectively. The regulation significantly reduced E.D. visits among individuals with mental health disorders by 0.003 visits (95% CI: -0.007 to 0.000) per quarter, a 25% relative decrease compared with the control at preperiod. However, payment parity was not statistically associated with increasing preventive care visits and lowering ED visits among individuals with CMRs. CONCLUSION: Telehealth payment parity has effectively promoted the adoption of psychotherapy and reduced ED visits among insured workers with mental health disorders. However, it has not significantly improved the uptake of preventive care counseling for individuals with CMRs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".