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

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.


Introduction
Human resources are one of the central pillars for access and universal health coverage, but represent a permanent challenge for many countries in Latin America, in view of disequilibria in their availability, composition, distribution and productivity, mainly in primary health care (1) .
In view of the essential role health professionals play in the protection, promotion and restoring of populations' health, it is fundamental for quantitative and qualitative planning and investment in the development of these professionals be done cautiously, so as to respond to the different and changeable health needs of the communities efficient and effectively (2) .
The planning process of health professionals looks for a balance between what is available in terms of market and what is necessary to guarantee attendance to the users' health demands (3) .  (4) .
Although scientific evidence (5) indicates a possible association between nursing staff density and maternal mortality, childhood mortality and immunization rates, predicting the number of professionals needed to attend to the users' needs at a FHS has not been easy.
The Workload Indicators of Staffing Need (WISN), a method the World Health Organization has proposed for staffing at a health institution (6) , signals great potential applicability at FHS and in a region's entire health service network.
The WISN departs from the workload, using activity (time) standards that are applicable to each workload component and to each professional's available time.
This method provides results like the difference between the real and calculated number of nursing professionals, identifying the lack or surplus of a certain professional category (6) .
In view of the insufficient number of studies to support nursing staffing in PHC, the objective in this study is to verify the application of the WISN method in the prediction of nursing human resources at FHS.

Method
In this descriptive study with a quantitative approach, a set of operations was used, recommended in the WISN, to calculate nursing professionals at a FHS in the city of São Paulo, Brazil, selected through a convenience sample, based on the criterion of being considered best primary health care practices.  diseases. This service's status was due to the fact that one of its strengths was the union and participation of the attended population.
Following the steps described in the WISN method, the goal was to identify the core variables for nursing staffing.

st
Step: definition of professional category, type of health service and calculation of Available Working Time The WISN method can be applied to all categories of health professionals and all types of services (6) . In Bonfim D, Laus AM, Leal AE, Fugulin FMT, Gaidzinski RR.
this study, the nursing professionals from one FHS were analyzed.
The Available Working Time (AWT) refers to how long a health professional has available, in one year, to perform his job, discounting established (holidays and vacation) and unexpected (medical leave and training) days of absence. It can be expressed as days or hours per year (6) .  Individual Allowance Factor (IAF), respectively.
To adapt to the proposed WISN terminology, the work-related activities and personal activities that were considered in the data collection tool were considered as support activities for the category and, as they represent a significant number of hours, they were allocated proportionately among the three workload components: standard, support and additional interventions/activities.
In this step, the lengths of time can be expressed as actual work time or as a percentage of the work time.
The percentage distributions and mean lengths of the interventions found in this study were used according to the professional category (nurse and nursing technician/auxiliary nurse) as nursing staffing parameters.

th
Step: staffing based on the method The difference between the number of staff available at the service and the staff needed was verified by analyzing the index between these two. When bordering on one (~1), the available staff is balanced with the staff demands for the workload at the service.
An index superior to one (>1) evidences too much staff in relation to the workload and inferior to one (<1) that the current staff is insufficient to cope with the workload at the health service. Therefore, the lower the index, the greater the pressure at work (6) .

Results
The nursing interventions/activities were classified according to the workload component, as demonstrated in Figure 1.  The number of nursing professionals required, according to the professional category, is demonstrated in Figures   2 and 3, which summarize the workload components, the steps proposed in the WISN method and the analysis and interpretation of the data.

Discussion
This research identified the nursing staffing needs at a FHS in the city of São Paulo to attend to the care demands through the application of the WISN method.
The use of this method presupposes the availability of routinely stored data on the investigated professionals and services' workload. These statistics need to be updated, complete and consistent.
In that sense, a study appointed that the information system at the FHS contains insufficient spaces to report on the nursing team's work, showing the importance of qualifying the information systems developed to support the planning of nursing staffing needs (9) .
Therefore, the nursing care records provided to the users need to be systemized in reports or worksheets that permit monitoring the information for decision making, such as the service's annual production and data on professionals' expected and non-expected absences. In an Indonesian province, the midwives affirmed that the method was useful because it helped to focus their work time more clearly on key activities, besides permitting an analysis of their own work situation at the services (11) . The WISN showed that the midwives were spending up to 50% of their time on activities not related to the midwife (elderly care, care for tuberculosis and malaria patients).
Hence, the initial proposal that the number of midwives was insufficient for the category's specific workload, without the necessary clarification the WISN provides, could have resulted in an increased number of midwives instead of nurses (11) .
In provinces of Mozambique, the WISN was used to assessed its applicability, and thus expand the use of workload measures for the decision process.
As a result, based on the staffing calculation, it was concluded that all health services had a lack of general clinicians, nurses and midwives. Therefore, the activities were performed within much less time than the minimum standard required, resulting in low quality. In addition, the distribution of nurses was unbalanced in the city of Nampula, with great disequilibrium between the hospital and the health services (11) . is a lack of professionals and provides information support for planning, training and allocation at local, regional and national level (13) .
In terms of efficiency, the WISN can be considered a tool with potential to show ways to equate this distribution. Nevertheless, some limitations should be