Literature DB >> 8168908

Using administrative data to screen hospitals for high complication rates.

L I Iezzoni1, J Daley, T Heeren, S M Foley, J S Hughes, E S Fisher, C C Duncan, G A Coffman.   

Abstract

Medicare's Peer Review Organizations (PROs) now are required to work with hospitals to improve patient outcomes. Which hospitals should be targeted? We used 1988 California discharge data to identify hospitals with higher-than-expected rates of complications in six adult, medical-surgical patient populations. Relative hospital complication rates generally were correlated across clinical areas, although correlations were lower between medical and surgical case types. Higher relative rates of complications were associated with larger size, major teaching facilities, and provision of open heart surgery, as well as with coding more diagnoses per case. Complication rates generally were not related significantly to hospital mortality rates as calculated by the Health Care Financing Administration. Different hospitals may be chosen for quality review depending on the method used to identify poor outcomes.

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Year:  1994        PMID: 8168908

Source DB:  PubMed          Journal:  Inquiry        ISSN: 0046-9580            Impact factor:   1.730


  34 in total

1.  Discrepancies between explicit and implicit review: physician and nurse assessments of complications and quality.

Authors:  Saul N Weingart; Roger B Davis; R Heather Palmer; Michael Cahalane; Mary Beth Hamel; Kenneth Mukamal; Russell S Phillips; Donald T Davies; Lisa I Iezzoni
Journal:  Health Serv Res       Date:  2002-04       Impact factor: 3.402

2.  Hospital organisation and outcomes.

Authors:  L H Aiken; D M Sloane; J Sochalski
Journal:  Qual Health Care       Date:  1998-12

3.  Electronically screening discharge summaries for adverse medical events.

Authors:  Harvey J Murff; Alan J Forster; Josh F Peterson; Julie M Fiskio; Heather L Heiman; David W Bates
Journal:  J Am Med Inform Assoc       Date:  2003-03-28       Impact factor: 4.497

Review 4.  Administrative data based patient safety research: a critical review.

Authors:  C Zhan; M R Miller
Journal:  Qual Saf Health Care       Date:  2003-12

Review 5.  The evolving science of quality measurement for hospitals: implications for studies of competition and consolidation.

Authors:  Patrick S Romano; Ryan Mutter
Journal:  Int J Health Care Finance Econ       Date:  2004-06

6.  How safe is primary knee replacement surgery? Perioperative complication rates in Northern Illinois, 1993-1999.

Authors:  Joe Feinglass; Hagay Amir; Patricia Taylor; Ithai Lurie; Larry M Manheim; Rowland W Chang
Journal:  Arthritis Rheum       Date:  2004-02-15

7.  Using computerized data to identify adverse drug events in outpatients.

Authors:  B Honigman; J Lee; J Rothschild; P Light; R M Pulling; T Yu; D W Bates
Journal:  J Am Med Inform Assoc       Date:  2001 May-Jun       Impact factor: 4.497

8.  Association of hospital participation in a quality reporting program with surgical outcomes and expenditures for Medicare beneficiaries.

Authors:  Nicholas H Osborne; Lauren H Nicholas; Andrew M Ryan; Jyothi R Thumma; Justin B Dimick
Journal:  JAMA       Date:  2015-02-03       Impact factor: 56.272

9.  Anticipating the effects of accountable care organizations for inpatient surgery.

Authors:  David C Miller; Zaojun Ye; Cathryn Gust; John D Birkmeyer
Journal:  JAMA Surg       Date:  2013-06       Impact factor: 14.766

10.  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

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