In their article, Benton (2013) aimed to investigate the performance of the highest-quality hospitals in the US regarding their profitability based on a nine-year longitudinal investigation. The importance of the research stems from the idea that hospital financial resources can be used in different ways, ranging from attracting commercially insured patients to stock on the latest medical technologies. Therefore, the outcome of the resources’ use can also be different, and it is detrimental for hospitals to ensure that there is a return on their investment due to the fierce competition between them. The decision-making process for hospitals depends on a variety of industry factors and trends.
The researcher found that hospitals’ daily bed capacity was the critical decision-making variable in facilitating good financial performance. This was because it was the only independent variable with a relatively low level of complexity and dependency to act as the central aspect of the decision strategy. When it comes to the profitability of hospitals, it was found that the management should adjust the daily capacity of beds and other independent and semi-independent variables for the dependent ones to reach favorable operational regions and the curves of daily bed capacity. This could be possible with the help of comprehensive industry analysis and the understanding of trends to generate the most accurate power curves. Considering the influence of the environmental forces on financial performance is also essential. Such factors as increases in costs, supply, and demand, as well as price sensitivity, are necessary to take into account when making projections and decisions on financial performance, with hospitals’ management having to adjust the power curves according to industry trends and potential patient expectations.We'll create an entirely exclusive & plagiarism-free paper for $13.00 $11.05/page 569 certified experts on site View More
Benton, W. C. (2013). A profitability evaluation of America’s best hospitals, 2000-2008. Decision Sciences, 44(6), 1139-1153.