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Hospital Quality: A PRIDIT Approach

Authors

  • Robert D. Lieberthal

    1. Health Care Systems Department, The Wharton School, University of Pennsylvania, 3641 Locust Walk, Philadelphia, PA 19104
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    • Address correspondence to Robert D. Lieberthal, B.A., Health Care Systems Department, The Wharton School, University of Pennsylvania, 3641 Locust Walk, Philadelphia, PA 19104.

Errata

This article is corrected by:

  1. Errata: Correction to “Hospital Quality: A PRIDIT Approach” Volume 46, Issue 4, 1332, Article first published online: 5 July 2011

Abstract

Background. Access to high quality medical care is an important determinant of health outcomes, but the quality of care is difficult to determine.

Objective. To apply the PRIDIT methodology to determine an aggregate relative measure of hospital quality using individual process measures.

Design. Retrospective analysis of Medicare hospital data using the PRIDIT methodology.

Subjects. Four-thousand-two-hundred-seventeen acute care and critical access hospitals that report data to CMS' Hospital Compare database.

Measures. Twenty quality measures reported in four categories: heart attack care, heart failure care, pneumonia care, and surgical infection prevention and five structural measures of hospital type.

Results. Relative hospital quality is tightly distributed, with outliers of both very high and very low quality. The best indicators of hospital quality are patients given assessment of left ventricular function for heart failure and patients given β-blocker at arrival and patients given β-blocker at discharge for heart attack. Additionally, teaching status is an important indicator of higher quality of care.

Conclusions. PRIDIT allows us to rank hospitals with respect to quality of care using process measures and demographic attributes of the hospitals. This method is an alternative to the use of clinical outcome measures in measuring hospital quality. Hospital quality measures should take into account the differential value of different quality indicators, including hospital “demographic” variables.

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