Health Workforce Planning Under Conditions Of Uncertainty: Identifying Supportive Integrated Care Policies Using Scenario Analysis

JOURNAL OF INTEGRATED CARE(2021)

Cited 1|Views8
No score
Abstract
Purpose Integrated care presents health workforce planners with significant uncertainty. This results from: (1) these workforces are likely in the future to be different from the present, (2) integrated care's variable definitions and (3) workforce policy and planning is not familiar with addressing such challenges. One means to deal with uncertainty is scenario analysis. In this study we reveal some integration-supportive workforce governance and planning policies that were derived from the application of scenario analysis. Design/methodology/approach Through a mixed methods design that applies content analysis, scenario construction and the policy Delphi method, we analysed a set of New Zealand's older persons health sector workforce scenarios. Developed from data gathered from workforce documents and studies, the scenarios were evaluated by a suitably qualified panel, and derived policy statements were assessed for desirability and feasibility. Findings One scenario was found to be most favourable, based on its broad focus, inclusion of prevention and references to patient dignity, although funding changes were indicated as necessary for its realisation. The integration-supportive policies are based on promoting network-based care models, patient-centric funding that promotes collaboration and the enhancement of interprofessional education and educator involvement. Originality/value Scenario analysis for policy production is rare in health workforce planning. We show how it is possible to identify policies to address an integrated care workforce's development using this method. The article provides value for planners and decision-makers by identifying the pros and cons of future situations and offers guidance on how to reduce uncertainty through policy rehearsal and reflection.
More
Translated text
Key words
Integrated care, Uncertainty, Health workforce governance, Health workforce planning, Health policy, Scenarios, New Zealand
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined