Assessing the Impact and Cost of Short-Term Health Workforce in Remote Indigenous Communities in Australia: A Mixed Methods Study Protocol
Notice bibliographique
Résumé
BACKGROUND: Remote Australia is a complex environment characterized by workforce shortages, isolated practice, a large resident Indigenous population, high levels of health need, and limited access to services. In recent years, there has been an increasing trend of utilizing a short-term visiting (fly-in/fly-out) health workforce in many remote areas. However, there is a dearth of evidence relating to the impact of this transitory workforce on the existing resident workforce, consumer satisfaction, and the effectiveness of current services. OBJECTIVE: This study aims to provide rigorous empirical data by addressing the following objectives: (1) to identify the impact of short-term health staff on the workload, professional satisfaction, and retention of resident health teams in remote areas; (2) to identify the impact of short-term health staff on the quality, safety, and continuity of patient care; and (3) to identify the impact of short-term health staff on service cost and effectiveness. METHODS: Mixed methods will be used. Administrative data will be extracted that relates to all 54 remote clinics managed by the Northern Territory Department of Health, covering a population of 35,800. The study period will be 2010 to 2014. All 18 Aboriginal Community-Controlled Health Services in the Northern Territory will also be invited to participate. We will use these quantitative data to describe staffing stability and turnover in these communities, and then utilize multiple regression analyses to determine associations between the key independent variables of interest (resident staff turnover, stability or median survival, and socioeconomic status, community size, and per capita funding) and dependent variables related to patient care, service cost, quality, and effectiveness. The qualitative component of the study will involve in-depth interviews and focus groups with staff and patients, respectively, in six remote communities. Three communities will be high staff turnover communities and three characterized by low turnover. This will provide information on service quality, impact on resident and visiting staff, and patient satisfaction with the services. The research team will work with staff, patients, and a key stakeholder group of senior policymakers to develop workforce strategies to maintain or attain remote health workforce stability. RESULTS: The study commenced in 2015. As of October 2016, fieldwork has been almost completed and quantitative analysis has commenced. Results are expected to be published in 2017. CONCLUSIONS: The study has commenced, but it is too early to provide results or conclusions.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,033 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, pas un consensus.
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