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An evidence-based health workforce model for primary and community care

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Author(s): Segal Leonie | Leach Matthew

Journal: Implementation Science
ISSN 1748-5908

Volume: 6;
Issue: 1;
Start page: 93;
Date: 2011;
Original page

ABSTRACT
Abstract Background The delivery of best practice care can markedly improve clinical outcomes in patients with chronic disease. While the provision of a skilled, multidisciplinary team is pivotal to the delivery of best practice care, the occupational or skill mix required to deliver this care is unclear; it is also uncertain whether such a team would have the capacity to adequately address the complex needs of the clinic population. This is the role of needs-based health workforce planning. The objective of this article is to describe the development of an evidence-informed, needs-based health workforce model to support the delivery of best-practice interdisciplinary chronic disease management in the primary and community care setting using diabetes as a case exemplar. Discussion Development of the workforce model was informed by a strategic review of the literature, critical appraisal of clinical practice guidelines, and a consensus elicitation technique using expert multidisciplinary clinical panels. Twenty-four distinct patient attributes that require unique clinical competencies for the management of diabetes in the primary care setting were identified. Patient attributes were grouped into four major themes and developed into a conceptual model: the Workforce Evidence-Based (WEB) planning model. The four levels of the WEB model are (1) promotion, prevention, and screening of the general or high-risk population; (2) type or stage of disease; (3) complications; and (4) threats to self-care capacity. Given the number of potential combinations of attributes, the model can account for literally millions of individual patient types, each with a distinct clinical team need, which can be used to estimate the total health workforce requirement. Summary The WEB model was developed in a way that is not only reflective of the diversity in the community and clinic populations but also parsimonious and clear to present and operationalize. A key feature of the model is the classification of subpopulations, which gives attention to the particular care needs of disadvantaged groups by incorporating threats to self-care capacity. The model can be used for clinical, health services, and health workforce planning.
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