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Linear Programming in Healthcare Organisations Research Paper

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Updated: Jun 25th, 2020

In their study, Zon and Kommer (1999) want to develop a model that can optimise the use of resources available to medical institutions. In order to achieve this goal, they rely on multiple linear regression analysis which is an important part of dynamic programming. In particular, the scholars want show how various resource allocation decisions taken by healthcare organisations affect the future demand for medical services. The framework developed by researchers can be useful for improving the policies of healthcare administrators.

In this case, the use of multiple linear regression analysis is required because there are several independent variables affecting demand for medical services. In particular, one should speak about the interventions which are related to the allocation of resources such as technologies or employees. It should be noted that any form of medical activity entails the distribution of resources. For example, the decision to choose a certain treatment mode results in the necessity to allocate resources such as employees, costs, and time (Zon & Kommer, 1999, p. 88). In turn, the dependent variable will be the health state of patients and their subsequent demand for medical services as well as resources.

For instance, this demand can be determined by examining the daily needs of a patient. Among such needs, one can mention the number of minutes or hours that physicians and nurses will need to spend on this individual (Zon & Kommer, 1999, p. 88). Provided that medical workers identify the type of services required by a patient, they will be able to estimate the amount of costs which will be needed. In turn, multiple linear regression analysis will be useful for determining how different interventions influence patients’ demand for the resources. Moreover, they may single out and eliminate those interventions that significantly increase the costs of a hospital and increase the demand for services.

Yet, this step can be taken only if it does not compromise the quality of patient care. These data will be needed for meeting the constraints that hospital administrators should consider. Among such constraints, one can distinguish the budgetary requirements that medical institutions have to meet. Another constraint is the minimum amount of money and other resources that should be spent on a patient in order to ensure adequate treatment. Thus, the use of linear regression analysis is important for choosing the most suitable intervention. These are some of main details that can be distinguished.

One should note that this analysis is necessary for creating a dynamic linear programming model developed by researchers. This approach has to be adopted at the time when a person has to take a set of subsequent decisions. More importantly, the range of decisions available to a person or an organisation at a certain point is dependent on the steps that were already taken in the past. In turn, the researchers argue that dynamic linear programming is necessary because each resource allocation decision taken by the hospital will affect the future demand for resources (Zon and Kommer, 1999, p. 87). The results of multiple linear aggression analysis will be needed to select the most optimal interventions during every stage of dynamic programming.

On the whole, this discussion shows that linear aggression analysis can be useful for improving the work of healthcare institutions. In particular, this approach can help administrators optimise the use of available resources. The use of this method is particular important if it is necessary to develop dynamic linear programming models. These are the main aspects that can be distinguished.

Reference

Zon, A., & Kommer, G. (1999). Patients flows and optimal health-care allocation at the macro-level: a dynamic linear regression approach. Health Care Management Science, 2(7), 87-96. Web.

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