Literature DB >> 20070388

Using a hierarchical model to estimate risk-adjusted mortality for hospitals not included in the reference sample.

David E Clark1, Edward L Hannan, Stephen W Raudenbush.   

Abstract

OBJECTIVE: To provide a method for any hospital to evaluate patient mortality using a hierarchical risk-adjustment equation derived from a reference sample. DATA SOURCE: American College of Surgeons National Trauma Data Bank (NTDB). STUDY
DESIGN: Hierarchical logistic regression models predicting mortality were estimated from NTDB data. Risk-adjusted hospital effects obtained directly from models using standard software were compared with approximations derived from a summary equation and data from each individual hospital. PRINCIPAL
FINDINGS: Theoretical approximations were similar to results using standard software.
CONCLUSIONS: To allow independent verification, agencies using reference databases for hospital mortality "report cards" should publish their risk-adjustment equations. Similar hospitals not in the reference database may also use the published equations along with the approximations described to evaluate their own outcomes using their own data.

Entities:  

Mesh:

Year:  2010        PMID: 20070388      PMCID: PMC2838162          DOI: 10.1111/j.1475-6773.2009.01074.x

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


  7 in total

1.  The Major Trauma Outcome Study: establishing national norms for trauma care.

Authors:  H R Champion; W S Copes; W J Sacco; M M Lawnick; S L Keast; L W Bain; M E Flanagan; C F Frey
Journal:  J Trauma       Date:  1990-11

Review 2.  A comparison between traditional methods and multilevel regression for the analysis of multicenter intervention studies.

Authors:  Mirjam Moerbeek; Gerard J P van Breukelen; Martijn P F Berger
Journal:  J Clin Epidemiol       Date:  2003-04       Impact factor: 6.437

3.  Predicting in-hospital mortality. A comparison of severity measurement approaches.

Authors:  L I Iezzoni; A S Ash; G A Coffman; M A Moskowitz
Journal:  Med Care       Date:  1992-04       Impact factor: 2.983

4.  Comparison of "risk-adjusted" hospital outcomes.

Authors:  David M Shahian; Sharon-Lise T Normand
Journal:  Circulation       Date:  2008-04-07       Impact factor: 29.690

Review 5.  Comparing risk-adjustment methods for provider profiling.

Authors:  E R DeLong; E D Peterson; D M DeLong; L H Muhlbaier; S Hackett; D B Mark
Journal:  Stat Med       Date:  1997-12-15       Impact factor: 2.373

6.  Predicting risk-adjusted mortality for CABG surgery: logistic versus hierarchical logistic models.

Authors:  Edward L Hannan; Chuntao Wu; Elizabeth R DeLong; Stephen W Raudenbush
Journal:  Med Care       Date:  2005-07       Impact factor: 2.983

7.  Variations in the utilization of coronary angiography for elderly patients with an acute myocardial infarction. An analysis using hierarchical logistic regression.

Authors:  C A Gatsonis; A M Epstein; J P Newhouse; S L Normand; B J McNeil
Journal:  Med Care       Date:  1995-06       Impact factor: 2.983

  7 in total
  1 in total

1.  Predicting risk-adjusted mortality for trauma patients: logistic versus multilevel logistic models.

Authors:  David E Clark; Edward L Hannan; Chuntao Wu
Journal:  J Am Coll Surg       Date:  2010-07-01       Impact factor: 6.113

  1 in total

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