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Workforce requirements in rheumatology: a systematic literature review informing the development of a workforce prediction risk of bias tool and the EULAR points to consider.
Unger, Julia; Putrik, Polina; Buttgereit, Frank; Aletaha, Daniel; Bianchi, Gerolamo; Bijlsma, Johannes W J; Boonen, Annelies; Cikes, Nada; Dias, João Madruga; Falzon, Louise; Finckh, Axel; Gossec, Laure; Kvien, Tore K; Matteson, Eric L; Sivera, Francisca; Stamm, Tanja A; Szekanecz, Zoltan; Wiek, Dieter; Zink, Angela; Dejaco, Christian; Ramiro, Sofia.
Afiliação
  • Unger J; Department of Health Studies, Institute of Occupational Therapy, FH JOANNEUM University of Applied Sciences, Bad Gleichenberg, Austria.
  • Putrik P; Department of Internal Medicine, Division of Rheumatology, Maastricht University Medical Center and CAPHRI Research Institute, Maastricht, The Netherlands.
  • Buttgereit F; Department of Rheumatology and Clinical Immunology, Charitè University Medicine, Berlin, Germany.
  • Aletaha D; Division of Rheumatology, Medical University Vienna, Vienna, Austria.
  • Bianchi G; Division of Rheumatology, ASL3-Azienda Sanitaria Genovese, Genova, Italy.
  • Bijlsma JWJ; Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Boonen A; Department of Internal Medicine, Division of Rheumatology, Maastricht University Medical Center and CAPHRI Research Institute, Maastricht, The Netherlands.
  • Cikes N; Division of Clinical Immunology & Rheumatology, University of Zagreb School of Medicine, Zagreb, Croatia.
  • Dias JM; Department of Rheumatology, Centro Hospitalar Médio Tejo, Torres Novas, Portugal.
  • Falzon L; Columbia University Medical Center, New York City, New York, USA.
  • Finckh A; Division of Rheumatology, University Hospital of Geneva, Geneva, Switzerland.
  • Gossec L; Rheumatology Department, Sorbonne Université, Paris, and Pitié Salpêtrière Hhospital APHP, Paris, France.
  • Kvien TK; Department of Rheumatology, Diakonhjemmet Hospital, Oslo, Norway.
  • Matteson EL; Division of Rheumatology and Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
  • Sivera F; Department of Rheumatology, Hospital General Universitario de Elda, Elda, Spain.
  • Stamm TA; Section for Outcomes Research, Medical Unversity Viennna, Center for Medical Statistics, Informatics, and Intelligent Systems, Vienna, Austria.
  • Szekanecz Z; Faculty of Medicine, Department of Internal Medicine, Division of Rheumatology, University of Debrecen, Debrecen, Hungary.
  • Wiek D; EULAR Standing Committee of PARE, Zurich, Switzerland.
  • Zink A; Department of Rheumatology and Clinical Immunology, Charitè University Medicine, Berlin, Germany.
  • Dejaco C; Deutsches Rheuma-Forschungszentrum, Berlin, Germany.
  • Ramiro S; Department of Rheumatology, Hospital of Bruneck, Bruneck, Italy.
RMD Open ; 4(2): e000756, 2018.
Article em En | MEDLINE | ID: mdl-30714580
OBJECTIVE: To summarise the available information on physician workforce modelling, to develop a rheumatology workforce prediction risk of bias tool and 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. Data on the type of workforce prediction models and the factors considered in the models were extracted. Key general as well as specific need/demand and supply factors for workforce calculation in rheumatology were identified. 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, need/demand and supply). The majority of studies revealed high or moderate risk of bias for most of the factors. CONCLUSIONS: 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 European League Against Rheumatism points to consider for the conduction of workforce requirement studies in rheumatology.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies / Systematic_reviews Idioma: En Revista: RMD Open Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Áustria País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies / Systematic_reviews Idioma: En Revista: RMD Open Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Áustria País de publicação: Reino Unido