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Application of the Workload Indicators of Staffing Need method to predict nursing human resources at a Family Health Service. | LitMetric

AI Article Synopsis

  • The study aimed to evaluate how effectively the Workload Indicators of Staffing Need method predicts nursing staff requirements in a Family Health service in São Paulo.
  • This descriptive and quantitative research involved defining health service types, calculating available work time, and determining nursing workload components and needs.
  • Results indicated a balanced workload for nursing technicians and a relevant application of the method to help identify nursing staffing needs, supporting universal health coverage.

Article Abstract

Objective: verify the application of the Workload Indicators of Staffing Need method in the prediction of nursing human resources at a Family Health service.

Method: descriptive and quantitative study, undertaken at a Family Health service in the city of São Paulo. The set of sequential operations recommended in the Workload Indicators of Staffing Need method was used: definition of the professional category, type of health service and calculation of Available Work Time; definition of workload components; identification of mean time for workload components; dimensioning of staff needs based on the method, application and interpretation of the data.

Result: the workload proposed in the Workload Indicators of Staffing Need method to nursing technicians/auxiliary nurses was balanced with the number of professionals available at the Family Health service. The Workload Indicators of Staffing Need index amounted to 0.6 for nurses and 1.0 for nursing technicians/auxiliary nurses.

Conclusion: the application of the Workload Indicators of Staffing Need method was relevant to identify the components of the nursing professionals' workload. Therefore, it is recommendable as a nursing staffing tool at Family Health services, contributing to the access and universal health coverage.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4862749PMC
http://dx.doi.org/10.1590/1518-8345.1010.2683DOI Listing

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