Change of Ownership and Quality of Home Health Agency Care
Bibliographic record
Abstract
Importance: The home health agency (HHA) market has seen increasingly more change in ownership transactions. Little is known about the organizational characteristics and quality of care of HHAs after ownership has changed. Objective: To examine whether an HHA change in ownership was associated with different quality-of-care outcomes, patient volume, and staffing levels. Design, Setting, and Participants: Using current HHA change of ownership files linked to publicly available Medicare HHA data, this staggered difference-in-differences analysis evaluated ownership change transactions of Medicare-certified HHAs from quarter 1 of 2016 to quarter 4 of 2019. Pretransaction and posttransaction HHA characteristics and quality-of-care outcomes were compared between HHAs that changed ownership and up to 8 matched controls. The transactions in the main analysis included (1) when an HHA remained as for-profit with a change in ownership and (2) when an HHA changed from nonprofit/public to for-profit ownership. The data were analyzed between November 2023 and September 2024. Main Outcomes and Measures: The primary outcomes were HHA-quarter measures of star ratings, the individual quality measures that compose the star ratings based on the Outcome and Assessment Information Set, and claims-based quality metrics, such as hospitalizations and emergency department visits. The secondary outcomes included HHA year measures of Medicare patient volume, per capita payments, and staffing levels (full-time equivalents and minutes per visit). Results: The main dataset included 294 Medicare-certified HHAs that changed ownership, matched with 2330 controls. In 3 years after an ownership change, quarterly star ratings increased by 0.18 (95% CI, 0.05-0.31) relative to matched controls, with greater increases among HHAs that converted from nonprofit/public to for-profit. No significant improvement was observed in the 60-day rates of hospital admissions or outpatient emergency department visits. Further, no significant changes were observed in the number of Medicare beneficiaries, but per capita payments increased within 2 years post-ownership change. Significant reductions were observed in full-time equivalents of registered nurses (-17% [95% CI, -31% to -3%]) and home health aides (-26% [95% CI, -39% to -13%]), as well as per-visit minutes for skilled nursing care (-5% [95% CI, -9% to -1%]), physical therapy (-3% [95% CI, -5% to 0%]), and home health aide care (-11% [95% CI, -15% to -6%]). Conclusions and Relevance: In this difference-in-differences analysis of Medicare-certified HHAs, ownership change was associated with higher star ratings and Medicare per capita payments, but not with claims-based quality measures. Reduction in staffing levels after ownership change raises concerns about implications for quality of care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".