Nursing Requirements for Ontario Over the Next Twenty Years: Development and Application of Estimation Methods
In this study we develop, appraise and compare alternative approaches to addressing the problem of determining the quantity and mix of nursing resources required for the health- care system in Ontario in the future. We argue that there is no ‘right’ number of nurses per se. On the contrary, the appropriate number of nurses is conditional upon society’s decisions about the right amount of health-care services to produce - decisions which are essentially political. A critical appraisal of the literature notes that existing research on nursing human resource planning has generally overlooked the political context of the issue (Section 2). Most studies focus attention exclusively on issues of the future supply of nurses and nursing hours. Some studies relate estimates of future supplies to assessments of the future need for nurses. However in these studies assessments of need have been based on adjusting or projecting current levels of provision in accordance with expected demographic changes in the populations being served (the utilization-based approach), or quantifying the resource requirements to meet the estimated burden of illness in the population (the needs-based approach). In some instances authors recognize that planning for future resources is largely determined by what governments decide to allocate to these resources. But this is usually dealt with in the studies by costing the utilization or needs-based requirements and noting that these requirements are likely to be in excess of even the most optimistic estimates of what governments might allocate to nursing resources (i.e., effective demand). In developing the alternative approaches for thinking about the future requirements for nurses a distinction is made between the conceptual basis of the model (i.e., the nature of the question being addressed) and the methodological approach used to apply the model (i.e., the nature of the data requirements) (Section 3). The utilization-based approach is essentially concerned with calculating the numbers of nurses required to serve the estimated future population in the same ways that the current population is served. The needs-based approach bases calculations of requirements on meeting the service needs of the estimated future population in cost-effective ways. The effective-demand-based approach calculates the number of nurses required by the health-care system within the context of current and future resource constraints. Although each approach requires different types of data, these requirements can be addressed by using existing values of the respective variables (i.e., projections), estimating future values of those variables based on exogenous changes (i.e., forecasts) or estimating future values of the variables based on exogenous and endogenous changes (i.e., plans). The applications of the alternative approaches are limited by the availability of appropriate data (Sections 4-6). However illustrative calculations are performed for the utilization and effective-demand based approaches and the sensitivity of the estimates to different assumptions is illustrated. In the case of the needs-based approach, the absence of any appropriate data prevented the illustration of the approach. In other studies, the absence of such information has lead to other types of data, in particular data on nurse vacancies, being used as an indicator of unmet need. Although corresponding data for Ontario are presented here (Section 5), these are not used to calculate future requirements because the determinants of these vacancy data have little, if anything, to do with needs. In summary, the resources required for an ongoing exercise in nurse human resources planning, in terms of the research skills and analytical techniques, already exist. But major issues remain about the willingness and/or ability of those agencies involved directly with issues of nurse human resources to invest in both the collection and management of appropriate data and the further development of analytical techniques.
|Date of creation:||1994|
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