Resumen

CAVALLERI, Fiorella; CASTROMAN, Pablo; RODRIGUEZ, Ana  y  RIVA, Juan. Utilidad de un método estadístico de simulación para evaluar la oferta y demanda de anestesiólogos en Uruguay (2011-2025) Propuesta para prospección y planificación de necesidad de recursos humanos en Anestesiología. Rev. Méd. Urug. [online]. 2013, vol.29, n.3, pp.165-173. ISSN 1688-0390.

Abstract Introduction: there is a human resource shortage in Anesthesiology that mainly affects the public sub-sector. Objectives: the study aimed at estimating the current deficit or surplus of anesthesiologists. It considered 2011 as a baseline and used statistical simulation to analyse the situation until 2025. Method: the supply/demand of anesthesiologist was categorized by creating different scenarios according to the data collected from the Ministry of Public Health in 2010 and the National Census of 2011. This information was integrated and a simulation model was created by the system dynamics method. This method allows for the analysis of sensitivity: to incorporate different scenarios and study their impact on the model's evolution every year. Results: deficit would disappear in a scenario with 11.28 anesthesiologists every 100,000 inhabitants. If the number of residents remains stable in 80, there would be a 50 surplus towards the end of the period (12.7 /100,000). These figures contemplate projections for the increase of surgeries. In the event of a demand that is larger and greater than the average in developed countries (15 every 100,000) it would be necessary to train as many as 113 residents. One of the main limitations for the application of the model was the absence of an appropriate organization of the practice of anesthesiology. Conclusion: the model enabled to project the need of human resources for every year. These estimates may be adapted to changing situations and thus, allows for the design of a plan to train human resources in anesthesiology to meet needs.

Palabras clave : ANESTHESIOLOGY [manpower]; ANESTHESIOLOGY [statistics & numerical data].

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