ACR Meeting Abstracts

ACR Meeting Abstracts

Abstract Number: 2177

Workforce Requirements in Rheumatology: A Systematic Literature Reviewinforming the Development of a Workforce Prediction Risk of Bias Tool and the EULAR Points to Consider

Polina Putrik1, Julia Unger2, Frank Buttgereit3, Daniel Aletaha4, Gerolamo Bianchi5, Johannes W. J. Bijlsma6, Annelies Boonen7, Nada Cikes8, Joao Madruga Dias9, Louise Falzon10, Axel Finckh11, Laure Gossec12,13, Tore Kvien14, Eric L. Matteson15, Francisca Sivera16, Tanja Stamm17, Zoltan Szekanecz18, Dieter Wiek19, Angela Zink20, Christian Dejaco21 and Sofia Ramiro22,23, 1Rheumatology, Maastricht University Medical Center, Maastricht, Netherlands, 2FH JOANNEUM, University of Applied Sciences, Institute of Occupational Therapy, Bad Gleichenberg, Austria, 3Department of Rheumatology and Clinical Immunology, Charité University Hospital Berlin, Berlin, Germany, 4Department of Internal Medicine III, Division of Rheumatology, Medical University of Vienna, Vienna, Austria, Vienna, Austria, 5Rheumatology, ASL3-Azienda Sanitaria Genovese, Genua, Italy, 6Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht, Netherlands, 7Caphri Research Institute, Maastricht, Netherlands, 8University of Zagreb School of Medicine, Zagreb, Croatia, 9Centro Hospitalar Médio Tejo, Torres Novas, Portugal, 10Center for Behavioral Cardiovascular Health, Columbia University Medical Center, New York, NY, 11University Hospital of Geneva, Geneva, Switzerland, 12Rheumatology, Sorbonne Université, Paris, France, 13Rheumatology, Pitié Salpêtrière Hospital, Paris, France, 14Dept. of Rheumatology, Diakonhjemmet Hospital, Oslo, Norway, 15Division of Rheumatology, Mayo Clinic College of Medicine and Science, Rochester, MN, 16Rheumatology, Hospital General Universitario de Elda. Comunidad Valenciana. Spain, Elda, Spain, 17Section for Outcomes Research, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Vienna, Austria, 18Department of Rheumatology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary, Debrecen, Hungary, 19EULAR Standing Committee of PARE, Zurich, Switzerland, 20Epidemiology Unit / Rheumatology and Clinical Immunology, German Rheumatism Research Centre (DRFZ) / Charité University Hospital, Berlin, Germany, 21Rheumatology and Immunology, Medical University Graz, Graz, Austria, 22Department of Rheumatology, Leiden University Medical Centre, Leiden, Netherlands, 23Department of Rheumatology, Zuyderland Medical Center, Heerlen, Netherlands

Meeting: 2018 ACR/ARHP Annual Meeting

Keywords:

Session Information

Date: Tuesday, October 23, 2018

Title: Health Services Research Poster III – ACR/ARHP

Session Type: ACR/ARHP Combined Abstract Session

Session Time: 9:00AM-11:00AM

Background/Purpose:

The projections from existing workforce studies in rheumatology vary by a factor of five, largely due to methodological heterogeneity. The purpose of this study was threefold: 1) to summarise the available information on physician workforce modelling, 2) to develop a rheumatology workforce prediction risk-of-bias tool and 3) to apply it to existing studies in rheumatology.

Methods:

A systematic literature review (SLR) was performed in key electronic databases (1946-2017) comprising an update of an SLR in rheumatology and a hierarchical SLR 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 risk of bias level (low, moderate, high). The workforce prediction risk of bias tool was developed and applied to existing workforce studies in rheumatology.

Results:

In total, 14 studies in rheumatology and 10 studies in other medical fields were included. Studies used a variety of prediction models based on a heterogeneous set of need/demand and/or supply factors. Only two studies attempted empirical validation of the prediction quality of the model. Based on evidence and consensus, the newly developed risk of bias tool includes 21 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). The majority of studies revealed high or moderate risk of bias for most of the factors (Table).

Conclusion:

The existing evidence on workforce prediction in rheumatology is scarce, heterogeneous and at moderate or high risk of bias. The new risk of bias tool should enable future evaluation of workforce prediction studies. This review informs the EULAR points to consider for the conduction of workforce requirement studies in rheumatology.

Table. Example of application of the workforce prediction risk of bias tool to rheumatology workforce studies (in total, 21 factors were evaluated)

Disclosure: P. Putrik, None; J. Unger, None; F. Buttgereit, None; D. Aletaha, None; G. Bianchi, None; J. W. J. Bijlsma, None; A. Boonen, None; N. Cikes, None; J. Madruga Dias, None; L. Falzon, None; A. Finckh, None; L. Gossec, None; T. Kvien, None; E. L. Matteson, None; F. Sivera, None; T. Stamm, None; Z. Szekanecz, None; D. Wiek, None; A. Zink, None; C. Dejaco, None; S. Ramiro, None.

To cite this abstract in AMA style:

Putrik P, Unger J, Buttgereit F, Aletaha D, Bianchi G, Bijlsma JWJ, Boonen A, Cikes N, Madruga Dias J, Falzon L, Finckh A, Gossec L, Kvien T, Matteson EL, Sivera F, Stamm T, Szekanecz Z, Wiek D, Zink A, Dejaco C, Ramiro S. Workforce Requirements in Rheumatology: A Systematic Literature Reviewinforming the Development of a Workforce Prediction Risk of Bias Tool and the EULAR Points to Consider [abstract]. Arthritis Rheumatol. 2018; 70 (suppl 9). https://acrabstracts.org/abstract/workforce-requirements-in-rheumatology-a-systematic-literature-reviewinforming-the-development-of-a-workforce-prediction-risk-of-bias-tool-and-the-eular-points-to-consider/. Accessed .

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