Resource withdrawal from medical services
Notice bibliographique
Résumé
Resource withdrawal from unnecessary medical services is an important issue as the cost of health care continues to rise. In many countries, resource withdrawal is primarily determined by government policies that remove, restrict, reduce, or limit the availability of publically insured medical services. Ideally, resource withdrawal is the result of a careful assessment of clinical and economic evidence regarding a service’s safety and effectiveness in order to ensure that it is the most efficient use of resources. Despite advocacy for a routinized and systematic approach to the withdrawal of resources from medical services, research has indicated that political and social factors often influence government, resulting in decisions that are neither consistent nor transparent. In this dissertation I seek to understand factors that may influence resource withdrawal decisions in an attempt to promote a more routinized and systematic approach. In order to understand the resource withdrawal landscape and provide greater conceptual clarity, the first study in this dissertation identifies and explores its characteristics (antecedents, attributes, and outcomes). Definitions of two prominent terms, disinvestment, and rationing are proposed. In the second study, a qualitative analysis of two examples of resource withdrawal reveals how the characteristics of problem frames affect the shape and timing of government resource withdrawal policies. Findings support the proposition that the complexity of the story told within the problem frame affects the shape of the policy; while visibility affects the timing. In the third study, I analyzed the perspectives of key informants about the Choosing Wisely Canada (CWC) campaign, which has the aim of reducing unnecessary services by encouraging a discussion between physician and patient. Findings reveal that CWC was designed to address pressures from government, patients, and the public. However, CWC was not designed in a way that is expected to address the underlying reasons unnecessary services are provided, including limited time in the clinical encounter, patient demands, uncertainty in the care pathway, and physician fear of litigation. Results from all three studies help establish a common language, identify influences on government led resource withdrawal and reasons why CWC is unlikely to reduce unnecessary services. Together this thesis provides insights into some of the factors affecting resource withdrawal from medical services, and findings may be used to help assess ways to improve the formulation of resource withdrawal policies.
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 | 0,009 | 0,063 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,006 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,001 | 0,007 |
| Intégrité de la recherche | 0,002 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,026 | 0,003 |
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 ».