FRI0631 Workforce requirements in rheumatology: a systematic literature review informing the development of a workforce prediction quality appraisal tool. (12th June 2018)

• Record Type: Journal Article
• Authors: Putrik, P.; Unger, J.; Buttgereit, F.; Aletaha, D.; Bianchi, G.; Bijlsma, J. W.; Boonen, A.; Cikes, N.; Madruga Dias, J.; Falzon, L.; Finckh, A.; Gossec, L.; Kvien, T. K.; Matteson, E.; Sivera, F.; Stamm, T.; Szekanecz, Z.; Wiek, D.; Zink, A.; Dejaco, C.; Ramiro, S.
• Is Part Of: Annals of the rheumatic diseases. Volume 77(2018)Supplement 2
• Page Start: 838
• Page End: 838
• Publication Date: 2018-06-12
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2018-eular.2228
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: Workforce requirement studies should be conducted in order to ensure the right number of people with the right skills, in the right place at the right time to deliver organizational objectives. Objectives: As part of the EULAR project to develop points to consider for the conduction of workforce studies in rheumatology, we reviewed the literature on workforce prediction with the aim to develop a workforce prediction quality appraisal tool and apply it to existing studies in rheumatology. Methods: Two literature searches were performed in Ovid MEDLINE, EMBASE, CINAHL, Cochrane Library and the grey literature comprising: (1) an update of a previous systematic literature review (SLR) of workforce prediction studies in rheumatology[1] and (2) a hierarchical SLR of workforce prediction studies in other medical fields. We extracted data on type of model used, details on need, demand and supply factors considered in the model, and other relevant aspects such as regional heterogeneity or uncertainty analyses. Based on the results, key general as well as specific need/demand, and supply factors for workforce calculation in rheumatology were identified and each factor was assigned a quality level (low, moderate, high). The quality appraisal tool was applied to the existing workforce modeling studies in rheumatology. Results: Data was extracted from 14 original workforce prediction studies in rheumatology and 10 SLRs in other fields. Studies used a variety of prediction models based on a heterogeneous set of need and/or demand and/or supply factors. While only a few studies attempted to empirically validate the prediction quality of the model (n=3), the consensus was that an integrated model including all these factors is expected to have the highest validity. Based on the different factors considered in existing studies, our quality appraisal tool included the three groups of factors: general factors (e.g. type of the model, stakeholder involvement), need/demand factors (e.g. scope of diseases covered by rheumatologists, morbidity, demography) and supply factors (e.g. time dedicated to clinical work, entry to profession, demographic composition of workforce) (table 1). The majority of studies scored low or moderate on most of the factors. Conclusions: The existing evidence on workforce prediction in rheumatology and other fields is scarce, heterogeneous and of low or moderate quality. The workforce prediction quality appraisal tool will enable future evaluation of workforce prediction studies. This review informs the EULAR points to consider for the conduction of workforce requirement studies in rheumatology. Reference: 1. Dejaco C, et al. Arthritis Care Res (Hoboken)2016. Disclosure of Interest: None declared