Implications and Limitations of Economic Feasibility - Statistics Project Example

Implications and Limitations of Economic FeasibilityLimitations Economic feasibility is one of the main interests of managements, whether for profit making or not profit making organizations. Comparing total costs with total revenues is important to ensuring this feasibility but an understanding of factors to total operations costs helps in determining the costs for optimal profit margins. Results from the study identify a significant relationship between hospitals’ total operations costs and the independent variables: variables Staffed beds_05, Medicare Days_05, Medicaid Days_05, Total Surgeries_05, RN FTE_05, Occupancy, Ownership, System Membership, Rural/Urban, Teaching Affiliation, Age 65+, Crime Rate, and Uninsured.

Out of the variables, however, only Staffed beds, Medicare Days, Total Surgeries, and RN FTE were significant to the hospitals total operations cost. One of the implications of the study is a target-specific approach to management of operations costs for greater profit margins. Identifying significance of only Staffed beds, Medicare Days, Total Surgeries, and RN FTE means that the other variables do not influence total operations costs and should therefore not utilize the managements’ time while planning for optimal cost for operations.

I would focus only on the four significant variables in managing costs and in using costs to determine optimal level of service delivery that a hospital should ensure. I would use operations management strategies to determine the optimal level of mix for Staffed beds, Medicare Days, Total Surgeries, and RN FTE that can optimize marginal returns through the coefficients suggest greater focus on RN FTE_05 then Staffed beds_05 in determination of costs and its derivative decisions. Reducing the costs through efficiency strategies would be a priority for ensuring sustainable profit margins (White and Wu, 2014).

The study is also important to healthcare professionals, especially in managerial position, through its information of market segments that organizations can explore at profits. Insignificance of type of locality, whether rural or urban, to total operations cost implies that I could establish a care facility in any area and expect same level of operations cost. This also implies that profitability of hospitals do not depend on type of locality and with consideration of competition due to concentration of facilities in urban areas, I would locate a hospital, especially for a new organization, in a rural area because while competition is lower in the locality, costs are the same, ceteris paribus.

This is contrary to previous observations that urban hospitals have higher level efficiencies that could identify lower operations costs (Charalambous, Maniadakis, Polyzos, Fragoulakis and Theodorou, 2013). Consequently, locating a facility in a rural area is likely to offer same marginal returns, with constant costs, and higher cumulative returns because of low-level competition. Based on insignificance of crime rates, uninsured, and ownership, I would not consider these factors inferring costs and associated decisions.

Limitations One limitation to the study is the non-representative nature of the data. Some of the cities have more representation in the sample than other. Abingdon only has one hospital in the sample while Richmond has seven hospitals in the sample. This threatens reliability of the data and its results and stratified sampling would mitigate the challenge. The study is also cross sectional and may therefore portray limited information on significance of the dependent variables. Seasonal factors, which could have changed in the year, would mean that the developed model is not suitable for differencing into a year that falls in a different season.

A longitudinal study that would average values for the variables or management of seasonal factors would resolve this. References Charalambous, C. et al. (2013). The efficiency of the public dental services (PDS) in Cyprus and selected determinants. BS Health Services Research, 13(1);1-19. White, C. and Wu, V. (2014). How do hospitals cope with sustained slow growth in Medicare prices? Health Sciences Research, 49(1);11-31.