ArticleBMJ open2015
Survival curves to support quality improvement in hospitals with excess 30-day mortality after acute myocardial infarction, cerebral stroke and hip fracture: a before-after study.
Article in BMJ open, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- In-hospital versus postdischarge 30-day mortality in patients admitted after acute myocardial infarction (AMI), cerebral stroke or hip fracture: a cohort study based on registry data.BMJ open quality · 2025Article
- Reducing unwarranted variation: can a 'clinical dashboard' be helpful for hospital executive boards and top-level leaders?BMJ leader · 2024Article
- Managing unwarranted variation in hospital care - findings from a regional audit in Norway.Research in health services & regions · 2023Article
- Application of machine learning model to predict lacunar cerebral infarction in elderly patients with femoral neck fracture before surgery.BMC geriatrics · 2022Article
- Exploring the usefulness of Lexis diagrams for quality improvement.BMC medical informatics and decision making · 2020Article
- Associations between work satisfaction, engagement and 7-day patient mortality: a cross-sectional survey.BMJ open · 2019Article
- 'Who does this patient belong to?' boundary work and the re/making of (NSTEMI) heart attack patients.Sociology of health & illness · 2018Article
- Observed to expected or logistic regression to identify hospitals with high or low 30-day mortality?PloS one · 2018Article
- Patient healthcare trajectory. An essential monitoring tool: a systematic review.Health information science and systems · 2017Review
- Article
- 30-Day Survival Probabilities as a Quality Indicator for Norwegian Hospitals: Data Management and Analysis.PloS one · 2015Article
- Calculating the 30-day Survival Rate in Acute Myocardial Infarction: Should we Use the Treatment Chain or the Hospital Catchment Model?Heart internationalArticle
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Authors and funding
8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
objectivesTo evaluate survival curves (Kaplan-Meier) as a means of identifying areas in the clinical pathway amenable to quality improvement.
designObservational before-after study.
settingIn Norway, annual public reporting of nationwide 30-day in-and-out-of-hospital mortality (30D) for three medical conditions started in 2011: first time acute myocardial infarction (AMI), stroke and hip fracture; reported for 2009. 12 of 61 hospitals had statistically significant lower/higher mortality compared with the hospital mean.
participantsThree hospitals with significantly higher mortality requested detailed analyses for quality improvement purposes: Telemark Hospital Trust Skien (AMI and stroke), Østfold Hospital Trust Fredrikstad (stroke), Innlandet Hospital Trust Gjøvik (hip fracture). OUTCOME MEASURES: Survival curves, crude and risk-adjusted 30D before (2008-2009) and after (2012-2013).
interventionsUnadjusted survival curves for the outlier hospitals were compared to curves based on pooled data from the other hospitals for the 30-day period 2008-2009. For patients admitted with AMI (Skien), stroke (Fredrikstad) and hip fracture (Gjøvik), the curves suggested increased mortality from the initial part of the clinical pathway. For stroke (Skien), increased mortality appeared after about 8 days. The curve profiles were thought to reflect suboptimal care in various phases in the clinical pathway. This informed improvement efforts.
resultsFor 2008-2009, hospital-specific curves differed from other hospitals: borderline significant for AMI (p=0.064), highly significant (p≤0.005) for the remainder. After intervention, no difference was found (p>0.188). Before-after comparison of the curves within each hospital revealed a significant change for Fredrikstad (p=0.006). For the three hospitals, crude 30D declined and they were non-outliers for risk-adjusted 30D for 2013.
conclusionsSurvival curves as a supplement to 30D may be useful for identifying suboptimal care in the clinical pathway, and thus informing design of quality improvement projects.
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