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Acad Med ; 86(9): 1084-92, 2011 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-21785307

RESUMO

Optimizing resource allocation is essential for effective academic health center (AHC) management, yet guidelines and principles for doing so in the research and educational arenas remain limited. To address this issue, the authors analyzed responses to the 2007-2008 Association of Academic Health Centers census using ratio analysis. The concept was to normalize data from an individual institution to that same institution, by creating a ratio of two separate values from the institution (e.g., total faculty FTEs/total FTEs). The ratios were then compared across institutions. Generally, this strategy minimizes the effect of institution size on the responses, size being the predominant limitation of using absolute values for developing meaningful metrics. In so doing, ratio analysis provides a range of responses that can be displayed in graphical form to determine the range and distribution of values. The data can then be readily scrutinized to determine where any given institution falls within the distribution. Staffing ratios and operating ratios from up to 54 institutions are reported. For ratios including faculty numbers in the numerator or denominator, the range of values is wide and minimally discriminatory, reflecting heterogeneity across institutions in faculty definitions. Values for financial ratios, in particular total payroll expense/total operating expense, are more tightly clustered, reflecting in part the use of units with a uniform definition (i.e., dollars), and emphasizing the utility of such ratios in decision guidelines. The authors describe how to apply these insights to develop metrics for resource allocation in the research and educational arenas.


Assuntos
Centros Médicos Acadêmicos/economia , Docentes de Medicina/estatística & dados numéricos , Alocação de Recursos/economia , Centros Médicos Acadêmicos/organização & administração , Eficiência Organizacional , Inquéritos Epidemiológicos , Humanos , Alocação de Recursos/estatística & dados numéricos
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