Forecasting imbalances of human resources for health in the Thailand health service system: application of a health demand method View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Nonglak Pagaiya, Pudtan Phanthunane, Adun Bamrung, Thinakorn Noree, Karnwarin Kongweerakul

ABSTRACT

BACKGROUND: For an effective health system, human resources for health (HRH) planning should be aligned with health system needs. To provide evidence-based information to support HRH plan and policy, we should develop strategies to quantify health workforce requirements and supply. The aim of this study is to project HRH requirements for the Thai health service system in 2026. HRH included in this study were doctors, dentists, nurses, pharmacists, medical technicians (MTs), physiotherapists (PTs), and Thai traditional medicine (TTM) practitioners. METHODS AND RESULTS: The study mainly relied on the secondary data in relation to service utilization and population projection together with expert opinions. Health demand method was employed to forecast the HRH requirements based on the forecasted service utilizations. The results were then converted into HRH requirements using the staffing norm and productivity. The HRH supply projection was based on the stock and flow approach in which current stock and the flow in and out were taken into account in the projection. The results showed that in 2026, nurses are likely to be in critical shortages. The supply of doctors, pharmacists, and PTs is likely to be surplus. The HRH requirements are likely to match with the supply in cases of dentists, MTs, and TTM practitioners. CONCLUSION: In 2026, the supply of key professionals is likely to be sufficient except nurses who will be in critical shortages. The health demand method, although facing some limitations, is useful to project HRH requirements in such a situation that people are accessible to health services and future service utilizations are closely linked to current utilization rates. More... »

PAGES

4

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12960-018-0336-2

DOI

http://dx.doi.org/10.1186/s12960-018-0336-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111266716

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30621716


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