Measuring effectiveness in long-term care facilities in British Columbia
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,004 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».