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      Comparing hospital mortality – how to count does matter for patients hospitalized for acute myocardial infarction (AMI), stroke and hip fracture

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          Abstract

          Background

          Mortality is a widely used, but often criticised, quality indicator for hospitals. In many countries, mortality is calculated from in-hospital deaths, due to limited access to follow-up data on patients transferred between hospitals and on discharged patients. The objectives were to: i) summarize time, place and cause of death for first time acute myocardial infarction (AMI), stroke and hip fracture, ii) compare case-mix adjusted 30-day mortality measures based on in-hospital deaths and in-and-out-of hospital deaths, with and without patients transferred to other hospitals.

          Methods

          Norwegian hospital data within a 5-year period were merged with information from official registers. Mortality based on in-and-out-of-hospital deaths, weighted according to length of stay at each hospital for transferred patients (W30D), was compared to a) mortality based on in-and-out-of-hospital deaths excluding patients treated at two or more hospitals (S30D), and b) mortality based on in-hospital deaths (IH30D). Adjusted mortalities were estimated by logistic regression which, in addition to hospital, included age, sex and stage of disease. The hospitals were assigned outlier status according to the Z-values for hospitals in the models; low mortality: Z-values below the 5-percentile, high mortality: Z-values above the 95-percentile, medium mortality: remaining hospitals.

          Results

          The data included 48 048 AMI patients, 47 854 stroke patients and 40 142 hip fracture patients from 55, 59 and 58 hospitals, respectively. The overall relative frequencies of deaths within 30 days were 19.1% (AMI), 17.6% (stroke) and 7.8% (hip fracture). The cause of death diagnoses included the referral diagnosis for 73.8-89.6% of the deaths within 30 days. When comparing S30D versus W30D outlier status changed for 14.6% (AMI), 15.3% (stroke) and 36.2% (hip fracture) of the hospitals. For IH30D compared to W30D outlier status changed for 18.2% (AMI), 25.4% (stroke) and 27.6% (hip fracture) of the hospitals.

          Conclusions

          Mortality measures based on in-hospital deaths alone, or measures excluding admissions for transferred patients, can be misleading as indicators of hospital performance. We propose to attribute the outcome to all hospitals by fraction of time spent in each hospital for patients transferred between hospitals to reduce bias due to double counting or exclusion of hospital stays.

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          Most cited references23

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          League Tables and Their Limitations: Statistical Issues in Comparisons of Institutional Performance

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            Explaining differences in English hospital death rates using routinely collected data.

            To ascertain hospital inpatient mortality in England and to determine which factors best explain variation in standardised hospital death ratios. Weighted linear regression analysis of routinely collected data over four years, with hospital standardised mortality ratios as the dependent variable. England. Eight million discharges from NHS hospitals when the primary diagnosis was one of the diagnoses accounting for 80% of inpatient deaths. Hospital standardised mortality ratios and predictors of variations in these ratios. The four year crude death rates varied across hospitals from 3.4% to 13.6% (average for England 8.5%), and standardised hospital mortality ratios ranged from 53 to 137 (average for England 100). The percentage of cases that were emergency admissions (60% of total hospital admissions) was the best predictor of this variation in mortality, with the ratio of hospital doctors to beds and general practitioners to head of population the next best predictors. When analyses were restricted to emergency admissions (which covered 93% of all patient deaths analysed) number of doctors per bed was the best predictor. Analysis of hospital episode statistics reveals wide variation in standardised hospital mortality ratios in England. The percentage of total admissions classified as emergencies is the most powerful predictor of variation in mortality. The ratios of doctors to head of population served, both in hospital and in general practice, seem to be critical determinants of standardised hospital death rates; the higher these ratios, the lower the death rates in both cases.
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              Using quality indicators to improve hospital care: a review of the literature.

              To review the literature concerning strategies for implementing quality indicators in hospital care, and their effectiveness in improving the quality of care. A systematic literature study was carried out using MEDLINE and the Cochrane Library (January 1994 to January 2008). Hospital-based trials studying the effects of using quality indicators as a tool to improve quality of care. Two reviewers independently assessed studies for inclusion, and extracted information from the studies included regarding the health care setting, type of implementation strategy and their effectiveness as a tool to improve quality of hospital care. A total of 21 studies were included. The most frequently used implementation strategies were audit and feedback. The majority of these studies focused on care processes rather than patient outcomes. Six studies evaluated the effects of the implementation of quality indicators on patient outcomes. In four studies, quality indicator implementation was found to be ineffective, in one partially effective and in one it was found to be effective. Twenty studies focused on care processes, and most reported significant improvement with respect to part of the measured process indicators. The implementation of quality indicators in hospitals is most effective if feedback reports are given in combination with an educational implementation strategy and/or the development of a quality improvement plan. Effective strategies to implement quality indicators in daily practice in order to improve hospital care do exist, but there is considerable variation in the methods used and the level of change achieved. Feedback reports combined with another implementation strategy seem to be most effective.
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                Author and article information

                Journal
                BMC Health Serv Res
                BMC Health Serv Res
                BMC Health Services Research
                BioMed Central
                1472-6963
                2012
                22 October 2012
                : 12
                : 364
                Affiliations
                [1 ]Norwegian Knowledge Centre for the Health Services, Quality Measurement Unit, PO Box 7004, St.Olavs plass, N-0130, Oslo, Norway
                [2 ]Division of Mental Health, Norwegian Institute of Public Health, Oslo, Norway
                [3 ]Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
                Article
                1472-6963-12-364
                10.1186/1472-6963-12-364
                3526398
                23088745
                e4952af9-9e9e-4a2a-9e6b-318c1653013c
                Copyright ©2012 Kristoffersen et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 20 September 2011
                : 15 October 2012
                Categories
                Research Article

                Health & Social care
                cause of death,ami,stroke,hospital comparison,hip fracture,mortality,transferred patients,quality indicator,episode of care

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