Publications by authors named "Dan Friesner"

Hospitals are complex organizations which provide a wide array of health care services. This complexity creates challenges for stakeholders who wish to use financial accounting statements to make inferences about the productive choices made by a hospital's management. These challenges are especially salient when using data reported at the department (or cost center) level, or where the provision of care is coordinated across hospital departments.

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The relationship between resource allocation decisions within medical laboratory cost centers and overall hospital financial performance is empirically investigated using a panel of critical access hospitals in Washington State (2014-2016). In order to increase accessibility to hospital managers and health policy makers, a managerial finance perspective (defining performance using simple financial accounting ratios) is adopted. Results indicate that resource allocation decisions within the medical laboratory cost center have a significant impact on the financial performance of the hospital as a whole.

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One relatively new method of providing care to patients with chronic disease is disease state management (DSM). Diabetes is particularly interesting to study because it is not only one of the most prevalent chronic diseases, but it is also a disease for which DSM is highly cost effective. Similarly, registered nurses represent the group of practitioners most likely to provide a comprehensive set of DSM activities.

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Objectives: To analyze the impact of recent pharmacy graduates on a local economy.

Methods: Input-output analysis was applied to data from Spokane County, Washington, in 2006 and the findings were reviewed and conclusions were drawn.

Results: The local college of pharmacy added nearly $1 million (in 2006) directly to the local economy.

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The authors present a methodology that measures improvement in customer satisfaction scores when those scores are already high and the production process is slow and thus does not generate a large amount of useful data in any given time period. The authors used these techniques with data from a midsized rehabilitation institute affiliated with a regional, nonprofit medical center. Thus, this article functions as a case study, the findings of which may be applicable to a large number of other healthcare providers that share both the mission and challenges faced by this facility.

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