Talk to the Veterans Crisis Line now
U.S. flag
An official website of the United States government

Health Services Research & Development

Go to the ORD website
Go to the QUERI website

HSR&D Citation Abstract

Search | Search by Center | Search by Source | Keywords in Title

An Alternative Method of Public Reporting of Comparative Hospital Quality and Performance Data for Transparency Initiatives.

O'Mahen P, Mehta P, Knox MK, Yang C, Kuebeler M, Rajan SS, Hysong SJ, Petersen LA. An Alternative Method of Public Reporting of Comparative Hospital Quality and Performance Data for Transparency Initiatives. Medical care. 2021 Sep 1; 59(9):816-823.

Dimensions for VA is a web-based tool available to VA staff that enables detailed searches of published research and research projects.

If you have VA-Intranet access, click here for more information

VA staff not currently on the VA network can access Dimensions by registering for an account using their VA email address.
   Search Dimensions for VA for this citation
* Don't have VA-internal network access or a VA email address? Try searching the free-to-the-public version of Dimensions


BACKGROUND: Hospital performance comparisons for transparency initiatives may be inadequate if peer comparison groups are poorly defined. OBJECTIVE: The objective of this study was to evaluate a new approach identifying hospital peers for comparison. DESIGN/SETTING: We used Mahalanobis distance as a new method of developing peer-specific groupings for hospitals to incorporate both external and internal complexity. We compared the overlap in groups with an existing method used by the Veterans'' Health Administration''s Office for Productivity, Efficiency, and Staffing (OPES). PARTICIPANTS: One hundred twenty-two acute-care Veterans'' Health Administration''s Medical Facilities as defined in the OPES fiscal year 2014 report. MEASURES: Using 15 variables in 9 categories developed from expert input, including both hospital internal measures and community-based external measures, we used principal components analysis and calculated Mahalanobis distance between each hospital pair. This method accounts for correlation between variables and allows for variables having different variances. We identified the 50 closest hospitals, then eliminated any potential peer whose score on the first component was > 1 SD from the reference hospital. We compared overlap with OPES measures. RESULTS: Of 15 variables, 12 have SDs exceeding 25% of their means. The first 2 components of our analysis explain 24.8% and 18.5% of variation among hospitals. Eight of 9 variables scaling positively on the first component measure internal complexity, aligning with OPES groups. Four of 5 variables scaling positively on the second component but not the first are factors from the policy environment; this component reflects a dimension not considered in OPES groups. CONCLUSION: Individualized peers that incorporate external complexity generate more nuanced comparators to evaluate quality.

Questions about the HSR&D website? Email the Web Team.

Any health information on this website is strictly for informational purposes and is not intended as medical advice. It should not be used to diagnose or treat any condition.