W Aelvoet1, N Terryn2, A Blommaert3, G Molenberghs4, N Hens5, F De Smet6, M Callens7, P Beutels8. 1. Federal Public Service (FPS) Health, Food Chain Safety and Environment, Eurostation Bloc II-First Floor-01D327, Place Victor Horta 40 bte 10, B-1060 Brussels, Belgium Vrije Universiteit Brussel, Faculteit Geneeskunde en Farmacie, Brussels, Belgium. 2. Federal Public Service (FPS) Health, Food Chain Safety and Environment, Eurostation Bloc II-First Floor-01D327, Place Victor Horta 40 bte 10, B-1060 Brussels, Belgium. 3. Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute (WHO Collaborating Centre), University of Antwerp, Antwerp, Belgium. 4. Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Universiteit Hasselt and KU Leuven, Belgium. 5. Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute (WHO Collaborating Centre), University of Antwerp, Antwerp, Belgium Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BIOSTAT), Hasselt University. 6. National Alliance of Christian Mutualities, Brussels, Belgium Department of Public Health and Primary Care, Occupational, Environmental and Insurance Medicine, KU Leuven, Louvain, Belgium. 7. National Alliance of Christian Mutualities, Brussels, Belgium. 8. Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute (WHO Collaborating Centre), University of Antwerp, Antwerp, Belgium School of Public Health and Community Medicine, The University of New South Wales, Sydney, Australia.
Abstract
OBJECTIVE: To assess between-hospital variations in standardized in-hospital mortality ratios of community-acquired pneumonia (CAP), and identify possible leads for quality improvement. DESIGN: We used an administrative database to estimate standardized in-hospital mortality ratios for 111 Belgian hospitals, by carrying out a set of hierarchical logistic regression models, intended to disentangle therapeutic attitudes and biases. To facilitate the detection of false-negative/positive results, we added an inconclusive zone to the funnel plots, derived from the results of the study. Data quality was validated by comparison with (i) alternative data from the largest Belgian Sickness Fund, (ii) published German hospital data and (iii) the results of an on-site audit. SETTING: All Belgian hospital discharge records from 2004 to 2007. STUDY PARTICIPANTS: A total of 111 776 adult patients were admitted for CAP. MAIN OUTCOME MEASURE: Risk-adjusted standardized in-hospital mortality ratios. RESULTS: Out of the 111 hospitals, we identified five and six outlying hospitals, with standardized mortality ratios of CAP consistently on the extremes of the distribution, as providing possibly better or worse care, respectively, and 18 other hospitals as having possible quality weaknesses/strengths. At the individuals' level of the analysis, adjusted odds ratios showed the paramount importance of old age, comorbidity and mechanical ventilation. The data compared well with the different validation sources. CONCLUSIONS: Despite the limitations inherent to administrative data, it seemed possible to establish inter-hospital differences in standardized in-hospital mortality ratios of CAP and to identify leads for quality improvement. Monitoring is needed to assess progress in quality.
OBJECTIVE: To assess between-hospital variations in standardized in-hospital mortality ratios of community-acquired pneumonia (CAP), and identify possible leads for quality improvement. DESIGN: We used an administrative database to estimate standardized in-hospital mortality ratios for 111 Belgian hospitals, by carrying out a set of hierarchical logistic regression models, intended to disentangle therapeutic attitudes and biases. To facilitate the detection of false-negative/positive results, we added an inconclusive zone to the funnel plots, derived from the results of the study. Data quality was validated by comparison with (i) alternative data from the largest Belgian Sickness Fund, (ii) published German hospital data and (iii) the results of an on-site audit. SETTING: All Belgian hospital discharge records from 2004 to 2007. STUDY PARTICIPANTS: A total of 111 776 adult patients were admitted for CAP. MAIN OUTCOME MEASURE: Risk-adjusted standardized in-hospital mortality ratios. RESULTS: Out of the 111 hospitals, we identified five and six outlying hospitals, with standardized mortality ratios of CAP consistently on the extremes of the distribution, as providing possibly better or worse care, respectively, and 18 other hospitals as having possible quality weaknesses/strengths. At the individuals' level of the analysis, adjusted odds ratios showed the paramount importance of old age, comorbidity and mechanical ventilation. The data compared well with the different validation sources. CONCLUSIONS: Despite the limitations inherent to administrative data, it seemed possible to establish inter-hospital differences in standardized in-hospital mortality ratios of CAP and to identify leads for quality improvement. Monitoring is needed to assess progress in quality.
Authors: Ilona Wm Verburg; Rebecca Holman; Niels Peek; Ameen Abu-Hanna; Nicolette F de Keizer Journal: Stat Methods Med Res Date: 2017-03-23 Impact factor: 3.021