Rheumatology in the community of Madrid: current availability of rheumatologists and future needs using a predictive model

• Published in: Reumatologia clinica Vol. 9; no. 6; p. 353
• Main Authors: Lázaro y De Mercado, Pablo, Blasco Bravo, Antonio Javier, Lázaro y De Mercado, Ignacio, Castañeda, Santos, López Robledillo, Juan Carlos
• Format: Journal Article
• Language: English; Spanish
• Published: Spain 01-11-2013
• Subjects: Adult; Aged; Female; Forecasting; Health Services Needs and Demand - statistics & numerical data; Health Services Needs and Demand - trends; Humans; Male; Middle Aged; Models, Statistical; Rheumatology - manpower; Spain; Urban Health; Spain; Needs forecast; Predicción de necesidades; Comunidad de Madrid; Predictive models; Community of Madrid; Modelos predictivos; Recursos humanos; Human resources
• ISSN: 1885-1398
• DOI: 10.1016/j.reuma.2013.01.005

To: 1) describe the distribution of the public sector rheumatologists; 2) identify variables on which the workload in Rheumatology depends; and 3) build a predictive model on the need of rheumatologists for the next 10 years, in the Community of Madrid (CM).
The information was obtained through structured questionnaires sent to all services/units of Rheumatology of public hospitals in the CM. The population figures, current and forecasted, were obtained from the National Statistics Institute. A predictive model was built based on information about the current and foreseeable supply, current and foreseeable demand, and the assumptions and criteria used to match supply with demand. The underlying uncertainty in the model was assessed by sensitivity analysis.
In the CM in 2011 there were 150 staff rheumatologists and 49 residents in 27 centers, which is equivalent to one rheumatologist for every 33,280 inhabitants in the general population, and one for every 4,996 inhabitants over 65 years. To keep the level of assistance of 2011 in 2021 in the general population, it would be necessary to train more residents or hire more rheumatologists in scenarios of demand higher than 15%. However, to keep the level of assistance in the population over 65 years of age it would be necessary to train more residents or hire more specialists even without increased demand.
The model developed may be very useful for planning, with the CM policy makers, the needs of human resources in Rheumatology in the coming years.