interRAI home care quality indicators
Bibliographic record
Abstract
BACKGROUND: This paper describe the development of interRAI's second-generation home care quality indicators (HC-QIs). They are derived from two of interRAI's widely used community assessments: the Community Health Assessment and the Home Care Assessment. In this work the form in which the quality problem is specified has been refined, the covariate structure updated, and two summary scales introduced. METHODS: Two data sets were used: at the client and home-care site levels. Client-level data were employed to identify HC-QI covariates. This sample consisted of 335,544 clients from Europe, Canada, and the United States. Program level analyses, where client level data were aggregated at the site level, were also based on the clients from the samples from Europe, Canada, and the United States. There were 1,654 program-based observations - 22% from Europe, 23% from the US, and 55% from Canada.The first task was to identify potential HC-QIs, including both change and prevalence measures. Next, they were reviewed by industry representatives and members of the interRAI network. A two-step process adjustment was followed to identify the most appropriate covariance structure for each HC-QI. Finally, a factor analytic strategy was used to identify HC-QIs that cluster together and thus are candidates for summary scales. RESULTS: The set of risk adjusted HC-QIs are multi-dimensional in scope, including measures of function, clinical complexity, social life, distress, and service use. Two factors were identified. The first includes a set of eleven measures that revolve around the absence of decline. This scale talks about functional independence and engagement. The second factor, anchored on nine functional improvement HC-QIs, referenced positively, this scale indicates a return to clinical balance. CONCLUSIONS: Twenty-three risk-adjusted, HC-QIs are described. Two new summary HC-QI scales, the "Independence Quality Scale" and the "Clinical Balance Quality Scale" are derived. In use at a site, these two scales can provide a macro view of local performance, offering a way for a home care agency to understand its performance. When scales perform less positively, the site then is able to review the HC-QI items that make up the scale, providing a roadmap for areas of greatest concern and in need of targeted interventions.
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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 | 0.025 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".