Literature DB >> 16116352

Evaluating the patient safety indicators: how well do they perform on Veterans Health Administration data?

Amy K Rosen1, Peter Rivard, Shibei Zhao, Susan Loveland, Dennis Tsilimingras, Cindy L Christiansen, Anne Elixhauser, Patrick S Romano.   

Abstract

BACKGROUND: The Patient Safety Indicators (PSIs), an administrative data-based tool developed by the Agency for Healthcare Research and Quality, are increasingly being used to screen for potential in-hospital patient safety problems. Although the Veterans Health Administration (VA) is a national leader in patient safety, accurate information on the epidemiology of patient safety events in the VA is still unavailable.
OBJECTIVES: Our objectives were to: (1) apply the AHRQ PSI software to VA administrative data to identify potential instances of compromised patient safety; (2) determine occurrence rates of PSI events in the VA; and (3) examine the construct validity of the PSIs.
METHODS: We examined differences between observed and risk-adjusted PSI rates in the VA, compared VA and non-VA PSI rates, and investigated the construct validity of the PSIs by examining correlations of the PSIs with other outcomes of VA hospitalizations.
RESULTS: We identified 11,411 PSI events in the VA nationwide in FY'01. Observed PSI rates per 1000 discharges ranged from 0.007 for "transfusion reaction" to 155.5 for "failure to rescue." There were significant, although small, differences between VA and non-VA risk-adjusted PSI rates. Hospitalizations with PSI events had longer lengths of stay, higher mortality, and higher costs than those without PSI events.
CONCLUSIONS: Our results suggest that the PSIs may be useful as a patient safety screening tool in the VA. Our PSI rates were consistent with the national incidence of low rates; however, differences between VA and non-VA rates suggest that inadequate case-mix adjustment may be contributing to these findings.

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Year:  2005        PMID: 16116352     DOI: 10.1097/01.mlr.0000173561.79742.fb

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  23 in total

1.  Incidence and Determinants of Traumatic Intracranial Bleeding Among Older Veterans Receiving Warfarin for Atrial Fibrillation.

Authors:  John A Dodson; Andrew Petrone; David R Gagnon; Mary E Tinetti; Harlan M Krumholz; J Michael Gaziano
Journal:  JAMA Cardiol       Date:  2016-04-01       Impact factor: 14.676

2.  Detecting adverse events in surgery: comparing events detected by the Veterans Health Administration Surgical Quality Improvement Program and the Patient Safety Indicators.

Authors:  Hillary J Mull; Ann M Borzecki; Susan Loveland; Kathleen Hickson; Qi Chen; Sally MacDonald; Marlena H Shin; Marisa Cevasco; Kamal M F Itani; Amy K Rosen
Journal:  Am J Surg       Date:  2013-11-07       Impact factor: 2.565

3.  The impact of electronic medical records data sources on an adverse drug event quality measure.

Authors:  Michael G Kahn; Daksha Ranade
Journal:  J Am Med Inform Assoc       Date:  2010 Mar-Apr       Impact factor: 4.497

4.  Comparing VA to Non-VA Care.

Authors:  William B Weeks
Journal:  J Gen Intern Med       Date:  2017-02       Impact factor: 5.128

5.  Improved hospital safety performance and reduced medicolegal risk: an ecological study using 2 Canadian databases.

Authors:  Qian Yang; Cathy Zhang; Kristen Hines; Lisa A Calder
Journal:  CMAJ Open       Date:  2018-11-19

6.  Enhancing patient safety through organizational learning: Are patient safety indicators a step in the right direction?

Authors:  Peter E Rivard; Amy K Rosen; John S Carroll
Journal:  Health Serv Res       Date:  2006-08       Impact factor: 3.402

7.  Establishing standard hospital performance measures for cervical spinal trauma: a Nationwide In-patient Sample study.

Authors:  D J Hoh; M Rahman; K M Fargen; D Neal; B L Hoh
Journal:  Spinal Cord       Date:  2015-10-20       Impact factor: 2.772

8.  Using estimated true safety event rates versus flagged safety event rates: does it change hospital profiling and payment?

Authors:  Amy K Rosen; Qi Chen; Ann M Borzecki; Marlena Shin; Kamal M F Itani; Michael Shwartz
Journal:  Health Serv Res       Date:  2014-04-30       Impact factor: 3.402

9.  Validity of selected AHRQ patient safety indicators based on VA National Surgical Quality Improvement Program data.

Authors:  Patrick S Romano; Hillary J Mull; Peter E Rivard; Shibei Zhao; William G Henderson; Susan Loveland; Dennis Tsilimingras; Cindy L Christiansen; Amy K Rosen
Journal:  Health Serv Res       Date:  2008-09-17       Impact factor: 3.402

10.  Comparison of the performance of the CMS Hierarchical Condition Category (CMS-HCC) risk adjuster with the Charlson and Elixhauser comorbidity measures in predicting mortality.

Authors:  Pengxiang Li; Michelle M Kim; Jalpa A Doshi
Journal:  BMC Health Serv Res       Date:  2010-08-20       Impact factor: 2.655

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