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Ranking hospitals for outcomes in total hip replacement - administrative data with or without patient surveys? - Part 2: Patient survey and administrative data

Author(s): Bitzer, Eva Maria | Neusser, Silke | Lorenz, Christoph | Dörning, Hans | Schäfer, Thomas

Journal: GMS Medizinische Informatik, Biometrie und Epidemiologie
ISSN 1860-9171

Volume: 3;
Issue: 1;
Start page: Doc07;
Date: 2007;
Original page

Keywords: arthroplasty | replacement | hip/adverse effects and mortality | hospitals | community/statistics & numerical data | outcome assessment (health care) | treatment outcome | quality indicators | health care

Background: Many hospital rankings rely on the frequency of adverse outcomes and are based on administrative data. In the study presented here, we tried to find out, to what extent available administrative data of German Sickness Funds allow for an adequate hospital ranking and compared this with rankings based on additional information derived from a patient survey. Total hip replacement was chosen as an example procedure. In part II of the publication, we present the results of the approach based on administrative and patient-derived data. Methods: We used administrative data from a large health insurance (AOK-Lower Saxony) of the year 2002 and from a patient survey. The study population comprised mainly beneficiaries, who received primary total hip replacement in the year 2002, were mailed a survey 6 month post-operatively and participated in the survey. Performance indicators used where “Revision”, “Complications” and “Change of functional impairment”. Hospitals were ranked if they performed at least 20 procedures on AOK-beneficiaries. Multivariate modelling (logistic regression and generalized linear models) was used to estimate the performance indicators by case-mix variables (a.o. age, sex, co-morbidity, medical history) and hospital characteristics (hospital size, surgical volume). The actual ranking was based on these multivariate models, excluding hospital variables and adding dummy-variables for each hospital. Hospitals were ranked by their case-mix adjusted odds ratio or Standardized Difference (SDR) with respect to a pre-selected reference hospital. The resulting rankings were compared with each other and with regard to the impact of case-mix variables. Results: 4089 beneficiaries received primary total hip replacement in 2002. 3293 patients participated in the survey (80.5%). The ranking included 60 hospitals. The agreement of rankings based on different performance indicators in the same year was low to high (a correlation coefficient of Spearman between 0.07 to 0.88). Including case-mix variables improved the model fit remarkably. Odds ratios for hospitals varied from 0.0 to 6.5 (Revision), from 0.6 to 2.4 (Complications), and SDRs varied from -2.24 to 2.44 (Change of functional impairment). Conclusions: Accounting for case-mix with patient-reported variables is more reliable than with variables that can be drawn from administrative data. Furthermore, including a patient survey allows to expand performance measurement on patient-reported, desired outcomes. Focusing on patients after primary total hip replacement weakened “revision” as performance indicator (because revisions after primary hip replacement are less frequent than after revision hip replacement). Future hospital rankings should rely on a combination of administrative data for primary and secondary hip replacements and patient-reported health outcomes after primary hip-replacement. To include as many hospitals as possible, co-operation with other health insurances is warranted.
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