How a government strategy of active performance management has influenced District Health Boards' delivery of publicly funded elective services
Notice bibliographique
Résumé
New Zealand, like most countries, is limited in the amount of publicly funded non-emergency (elective) medical and surgical services that it can provide to its population. In 2000, the ‘Reduced Waiting Times for Public Hospital Elective Services: Government Strategy’ outlined the systematic approach New Zealand would take with elective service waiting time management. The approach included the Government’s use of active performance management, namely, the setting of accountability and clear performance expectations; the ongoing monitoring, measurement, and reporting of performance; and the management of system change using facilitative networks. Since 2001, District Health Boards (DHBs) have been accountable for implementing government electives policy. The thesis examines how the Government’s strategic use of active performance management has influenced DHBs in their delivery of publicly funded elective services. In order to better understand and evaluate elective service delivery outcomes, (in particular that equity of service access has been achieved), and to evaluate the improvement of health service decision-making, there is a need to understand how decision-makers at the macro, meso, and micro levels of the health system are influenced by performance management practices. The research has examined influence from a multi-stakeholder and performance management system perspective. Methods include interviews with DHB and government stakeholders, review of Nationwide Service Framework and government policy documents, and the analysis of ten years of publicly available DHB performance reports to understand compliance patterns. The research narrative synthesised from study data is interpreted using a blend of neo-institutional meta-theories and institutional logics. The research found the government uses two performance models: an administrative control performance model which relies on information collection, control logic and performance feedback, and a professional services performance model which relies on the management of change using networks. Each DHB has established organisational practices in response to active performance management which are largely concerned with the promotion of DHB legitimacy. The influence of the two performance models and the interests of multiple DHB stakeholders is explained by considering the interplay between fifteen organisational practices, the government institutional logics of Active Performance Management and Service Improvement and the organisational field-level institutional logics of Population Health Management, Service Management, Medical Professional, and Integrated Care. Overall, the research concludes that ‘Active Performance Management’ has made a significant contribution reducing public hospital waiting times. It focuses the attention of DHB service managers who are concerned with mitigating risks of financial penalties and loss of leadership legitimacy. However, there are different ‘supply’ decision-making agendas and criteria operating at different levels of the health system. In particular, it is difficult to lock in appropriate accountability arrangements with primary care, and the strategic use of active performance management has led to tensions between DHB management and hospital specialists. If New Zealand wishes to expand its evaluation of health service delivery to take into account outcomes measures, there needs to be a better understanding of the aggregated impact of performance management practices on the health system.
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 | 0,019 | 0,054 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,008 | 0,007 |
| Communication savante | 0,012 | 0,004 |
| Science ouverte | 0,001 | 0,006 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».