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      Hospital quality reporting and improvement in quality of care for patients with acute myocardial infarction

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          Abstract

          Background

          Although public reporting of hospital performance is becoming common, it remains uncertain whether public reporting leads to improvement in clinical outcomes. This study was conducted to evaluate whether enrollment in a quality reporting project is associated with improvement in quality of care for patients with acute myocardial infarction.

          Methods

          We conducted a quasi-experimental study using hospital census survey and national inpatient database in Japan. Hospitals enrolled in a ministry-led quality reporting project were matched with non-reporting control hospitals by one-to-one propensity score matching using hospital characteristics. Using the inpatient data of acute myocardial infarction patients hospitalized in the matched hospitals during 2011–2013, difference-in-differences analyses were conducted to evaluate the changes in unadjusted and risk-adjusted in-hospital mortality rates over time that are attributable to intervention.

          Results

          Matching between hospitals created a cohort of 30,220 patients with characteristics similar between the 135 reporting and 135 non-reporting hospitals. Overall in-hospital mortality rates were 13.2% in both the reporting and non-reporting hospitals. There was no significant association between hospital enrollment in the quality reporting project and change over time in unadjusted mortality (OR, 0.98; 95% CI, 0.80–1.22). In 28,168 patients eligible for evaluation of risk-adjusted mortality, enrollment was also not associated with change in risk-adjusted mortality (OR, 0.98; 95% CI, 0.81–1.17).

          Conclusions

          Enrollment in the quality reporting project was not associated with short-term improvement in quality of care for patients with acute myocardial infarction. Additional efforts may be necessary to improve quality of care.

          Electronic supplementary material

          The online version of this article (10.1186/s12913-018-3330-4) contains supplementary material, which is available to authorized users.

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          Most cited references19

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          A critical appraisal of propensity-score matching in the medical literature between 1996 and 2003.

          Propensity-score methods are increasingly being used to reduce the impact of treatment-selection bias in the estimation of treatment effects using observational data. Commonly used propensity-score methods include covariate adjustment using the propensity score, stratification on the propensity score, and propensity-score matching. Empirical and theoretical research has demonstrated that matching on the propensity score eliminates a greater proportion of baseline differences between treated and untreated subjects than does stratification on the propensity score. However, the analysis of propensity-score-matched samples requires statistical methods appropriate for matched-pairs data. We critically evaluated 47 articles that were published between 1996 and 2003 in the medical literature and that employed propensity-score matching. We found that only two of the articles reported the balance of baseline characteristics between treated and untreated subjects in the matched sample and used correct statistical methods to assess the degree of imbalance. Thirteen (28 per cent) of the articles explicitly used statistical methods appropriate for the analysis of matched data when estimating the treatment effect and its statistical significance. Common errors included using the log-rank test to compare Kaplan-Meier survival curves in the matched sample, using Cox regression, logistic regression, chi-squared tests, t-tests, and Wilcoxon rank sum tests in the matched sample, thereby failing to account for the matched nature of the data. We provide guidelines for the analysis and reporting of studies that employ propensity-score matching. Copyright (c) 2007 John Wiley & Sons, Ltd.
            • Record: found
            • Abstract: not found
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            Treatment of myocardial infarction in a coronary care unit. A two year experience with 250 patients.

              • Record: found
              • Abstract: found
              • Article: not found

              Why We Should Not Be Indifferent to Specification Choices for Difference-in-Differences

              To evaluate the effects of specification choices on the accuracy of estimates in difference-in-differences (DID) models.

                Author and article information

                Contributors
                +81-3-5841-1887 , yamana-tky@umin.ac.jp
                kodan-mariko@hosp.go.jp
                sachikoono-tky@umin.ac.jp
                kojiromorita-tky@umin.ac.jp
                ptmatsui-tky@umin.ac.jp
                kfushimi.hci@tmd.ac.jp
                imamurat@naramed-u.ac.jp
                yasunagah-tky@umin.ac.jp
                Journal
                BMC Health Serv Res
                BMC Health Serv Res
                BMC Health Services Research
                BioMed Central (London )
                1472-6963
                4 July 2018
                4 July 2018
                2018
                : 18
                : 523
                Affiliations
                [1 ]ISNI 0000 0001 2151 536X, GRID grid.26999.3d, Department of Health Services Research, Graduate School of Medicine, , The University of Tokyo, ; 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033 Japan
                [2 ]GRID grid.416698.4, Department of Clinical Data Management and Research, Clinical Research Center, , National Hospital Organization Headquarters, ; 2-5-21 Higashigaoka, Meguro-ku, Tokyo, 152-8621 Japan
                [3 ]ISNI 0000 0001 1014 9130, GRID grid.265073.5, Department of Health Policy and Informatics, , Tokyo Medical and Dental University Graduate School of Medicine, ; 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8510 Japan
                [4 ]ISNI 0000 0001 2151 536X, GRID grid.26999.3d, Department of Biostatistics & Bioinformatics, , The University of Tokyo, ; 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033 Japan
                [5 ]ISNI 0000 0001 2151 536X, GRID grid.26999.3d, Department of Clinical Epidemiology and Health Economics, School of Public Health, , The University of Tokyo, ; 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033 Japan
                [6 ]ISNI 0000 0004 0372 782X, GRID grid.410814.8, Department of Public Health, Health Management and Policy, , Nara Medical University, ; 840 Shijo-cho, Kashihara, Nara, 634-0813 Japan
                Author information
                http://orcid.org/0000-0003-2214-6695
                Article
                3330
                10.1186/s12913-018-3330-4
                6033287
                29973281
                036ef002-1a72-4cde-bb1a-2c35ef6cf31a
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 30 November 2017
                : 26 June 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100003478, Ministry of Health, Labour and Welfare;
                Funded by: FundRef http://dx.doi.org/10.13039/501100001700, Ministry of Education, Culture, Sports, Science and Technology;
                Funded by: FundRef http://dx.doi.org/10.13039/100009619, Japan Agency for Medical Research and Development;
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                Health & Social care
                quality improvement,mortality,cardiovascular diseases
                Health & Social care
                quality improvement, mortality, cardiovascular diseases

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