Testing the hospital value proposition: an empirical analysis of efficiency and quality.
OBJECTIVE
To assess the relationship between hospitals' X-inefficiency levels and overall care quality based on the National Quality Forum's 27 safe practices score and to improve the analytic strategy for assessing X-inefficiency.


METHODS
The 2005 versions of the American Hospital Association and Leapfrog Group's annual surveys were the basis of the study. Additional case mix indices and market variables were drawn from the Centers for Medicare and Medicaid Services data sources and the Area Resource File. Data envelopment analysis was used to determine hospitals' X-inefficiency scores relative to their market-level competitors. Regression was used to assess the relationship between X-inefficiency and quality, controlling for organizational and market characteristics. Expenses (total and labor expenditures), case-mix-adjusted admissions, length of stay, and licensed beds defined the X-inefficiency function. The overall National Quality Forum's safe practice score, health maintenance organization penetration, market share, and teaching status served as independent control variables in the regression.


RESULTS
The National Quality Forum's safe practice scores are significantly and positively correlated to hospital X-inefficiency levels (beta = .105, p < or = .05). The analysis of the value proposition had very good explanatory power (adjusted R(2) = .414; p < or = .001; df = 7, 265). Contrary to earlier findings, health maintenance organization penetration and being a teaching hospital were positively related to X-inefficiency. Similar with others' findings, greater market share and for-profit ownership were negatively associated with X-inefficiency.


CONCLUSIONS
Measurement of overall hospital quality is improving but can still be made better. Nevertheless, the National Quality Forum's measure is significantly related to efficiency and could be used to create differential pay-for-performance programs. A market-segmented analytic strategy for studying hospitals' efficiency yields results with a high degree of explanatory power.
Huerta
Timothy R
TR
Health Organization Management, Rawls College of Business Administration, Texas Tech University, Lubbock, TX, USA. tim.huerta@ttu.edu
Ford
Eric W
EW
Peterson
Lori T
LT
Brigham
Keith H
KH
D019985:Benchmarking; D002391:Catchment Area, Health; D003953:Diagnosis-Related Groups; D017598:Efficiency, Organizational / Q000706:statistics & numerical data*; D036262:Empirical Research; D019981:Health Care Sector; D006279:Health Maintenance Organizations / Q000706:statistics & numerical data; D006302:Health Services Research; D006739:Hospital Administration / Q000592:standards*; D006742:Hospital Bed Capacity; D006784:Hospitals, Teaching; D006801:Humans; D007902:Length of Stay; D010067:Ownership; D011382:Programming, Linear; D011787:Quality of Health Care / Q000706:statistics & numerical data*; D012044:Regression Analysis; D017751:Safety Management / Q000706:statistics & numerical data*; D014481:United States