Is There Evidence of Cream Skimming Among Nursing Homes Following the Publication of the Nursing Home Compare Report Card?
Bibliographic record
Abstract
PURPOSE: A national quality report card for nursing homes, Nursing Home Compare, has been published since 2002. It has been shown to have some, albeit limited, positive impact on quality of care. The objective of this study was to test empirically the hypothesis that nursing homes have responded to the publication of the report by adopting cream skimming admission policies. DESIGN AND METHODS: The study included all non-Medicare newly admitted patients to all Medicare- and Medicaid-certified nursing homes nationally during the 2001-2005 period. Using the Minimum Data Set data, we calculated for each quarter several admission cohort characteristics: average number of activity of daily living limitations and percent of residents admitted with pain, with pressure ulcers, with urinary incontinence, with diabetes, and with memory limitations. We tested whether residents admitted in the postpublication period were less frail and sick compared with residents admitted in the prepublication period by estimating fixed facility effects longitudinal regression models. Analyses were stratified by nursing home ownership, occupancy, reported quality ranking, chain affiliation, and region. RESULTS: Evidence for cream skimming was found with respect to pain and, to a lesser degree, with respect to memory limitation but not with respect to the 4 other admission cohort characteristics. IMPLICATIONS: Despite the theoretical expectation, empirical evidence suggests only a limited degree of cream skimming. Further studies are required to investigate this phenomenon with respect to other admission cohort characteristics and with respect to post-acute patients.
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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 | 0.017 | 0.138 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".