Measuring effectiveness in long-term care facilities in British Columbia
Bibliographic record
Abstract
The involvement of government in the funding of health care, and especially the substantial expenditure of health care dollars for facility-based long-term care for the elderly, has led to rising pressure for accountability for the funds expended. The public expectation is that government will ensure an adequate quality of care is provided while at the same time ensuring the optimum and efficient use of the funds. While government wishes to maintain an arms-length relationship with providers, recently, an interest in linking the payment for care to its assessment has been expressed. It has been proposed that these expectations can be met through providing government funders with information about the effectiveness of care, using outcome measures. Such an approach would provide the information needed for assessing the adequacy of care, for use in cost-effectiveness and efficiency studies and potentially for use in assigning all or part of the payment for care. Also, from the funders1 perspective, if the outcomes of care are satisfactory, how these outcomes are achieved need not necessarily be of concern. The purpose of this study is to investigate and, if possible, to develop an outcome-based approach which links the assessment of the care provided in long-term care facilities in British Columbia (B.C.) to the current payment system. The long-term care system in B.C. was reviewed to identify the current mechanisms for assuring adequacy of care, the system of reimbursement and any problems encountered with these. The methodological, definitional and system factors which would act as constraining variables to the application of an outcome-based reimbursement system in B.C. were identified. The study reviewed and critiqued organizational and individual level outcome measurement approaches used in private industry, the public sector, health care and long-term care for their feasibility of application in the B.C. situation. Outcome approaches reviewed included generic approaches such as CBA/CEA, MBO, ZBB and health care approaches such as mortality and morbidity rates, and health status indexes. Existing applications in long-term care of the latter approach were reviewed. As the study progressed it became clear that effectiveness measures must be developed and the Impact of effectiveness on efficiency determined before a link to reimbursement can be made. A predictor model, using a multiattribute health status index as the outcome measure of effectiveness, and which uses "expected" versus "actual" outcomes to determine if the results were Better, Worse or the Same as predicted was recommended for use in B.C. Such an approach takes into account the fact that improvement of health status is not the only outcome expected in long-term care. It allows for multidimensional measures which accommodate the heterogeneity of long-term care residents. It is proposed that this effectiveness measurement approach be implemented as a joint research and service application to allow for empirical testing and resolution of the methodological and feasibility issues noted, including the limited experience with the use of effectiveness measures in facility-based long-term 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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".