dc.contributor.author	Valdmanis, Vivian G.
dc.contributor.author	Rosko, Michael D.
dc.contributor.author	Mutter, Ryan L.
dc.date.accessioned	2021-07-16T19:44:24Z
dc.date.available	2021-07-16T19:44:24Z
dc.date.issued	2008-09-20
dc.description.abstract	Objective. To use an advance in data envelopment analysis (DEA) called congestion analysis to assess the trade-offs between quality and efficiency in U.S. hospitals. Study Setting. Urban U.S. hospitals in 34 states operating in 2004. Study Design and Data Collection. Input and output data from 1,377 urban hospitals were taken from the American Hospital Association Annual Survey and the Medicare Cost Reports. Nurse-sensitive measures of quality came from the application of the Patient Safety Indicator (PSI) module of the Agency for Healthcare Research and Quality (AHRQ) Quality Indicator software to State Inpatient Databases (SID) provided by the Healthcare Cost and Utilization Project (HCUP). Data Analysis. In the first step of the study, hospitals' relative output-based efficiency was determined in order to obtain a measure of congestion (i.e., the productivity loss due to the occurrence of patient safety events). The outputs were adjusted to account for this productivity loss, and a second DEA was performed to obtain input slack values. Differences in slack values between unadjusted and adjusted outputs were used to measure either relative inefficiency or a need for quality improvement. Principal Findings. Overall, the hospitals in our sample could increase the total amount of outputs produced by an average of 26 percent by eliminating inefficiency. About 3 percent of this inefficiency can be attributed to congestion. Analysis of subsamples showed that teaching hospitals experienced no congestion loss. We found that quality of care could be improved by increasing the number of labor inputs in low-quality hospitals, whereas high-quality hospitals tended to have slack on personnel. Conclusions. Results suggest that reallocation of resources could increase the relative quality among hospitals in our sample. Further, higher quality in some dimensions of care need not be achieved as a result of higher costs or through reduced access to health care.	en_US
dc.description.uri	https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1475-6773.2008.00893.x	en_US
dc.format.extent	19 pages	en_US
dc.genre	journal articles	en_US
dc.identifier	doi:10.13016/m2salt-yrke
dc.identifier.citation	Valdmanis, Vivian G.; Rosko, Michael D.; Mutter, Ryan L.; Hospital Quality, Efficiency, and Input Slack Differentials; Health Services Research, 43, 5p2, p 1830-1848, 20 September, 2008; https://doi.org/10.1111/j.1475-6773.2008.00893.x	en_US
dc.identifier.uri	https://doi.org/10.1111/j.1475-6773.2008.00893.x
dc.identifier.uri	http://hdl.handle.net/11603/21947
dc.language.iso	en_US	en_US
dc.publisher	Wiley Online Library	en_US
dc.relation.isAvailableAt	The University of Maryland, Baltimore County (UMBC)
dc.relation.ispartof	UMBC School of Public Policy Collection
dc.rights	This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rights	Public Domain Mark 1.0	*
dc.rights	This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
dc.rights.uri	http://creativecommons.org/publicdomain/mark/1.0/	*
dc.title	Hospital Quality, Efficiency, and Input Slack Differentials	en_US
dc.type	Text	en_US

Hospital Quality, Efficiency, and Input Slack Differentials

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