{"title":"Comparison of risk-adjusted cumulative quality control charts compared with standardized mortality ratios in critical care.","authors":"Claudio M Martin, Fran Priestap, Raymond Kao","doi":"10.1007/s12630-024-02863-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>The optimal method for monitoring intensive care unit (ICU) performance is unknown. We sought to compare process control charts using standardized mortality ratio (SMR), p-charts, and cumulative sum (CUSUM) charts for detecting increases in risk-adjusted mortality within ICUs.</p><p><strong>Methods: </strong>Using data from 17 medical-surgical ICUs that included 29,592 patients in Ontario, Canada, we created risk-adjusted p-charts and SMRs on monthly intervals and CUSUM charts. We defined positive signals as any data point that was above the 3-sigma limit (approximating a 99% confidence interval [CI]) on a p-chart, any data point whose 95% CI did not include 1 for the SMR charts, and when a data point exceeded control limits for an odds ratio of 1.5 for CUSUM charts. We simulated increases in mortality of 10%, 30%, and 50% for each ICU to determine the sensitivity of each method. We calculated sensitivity as the number of positive signals divided by the number of ICUs (equal to number of simulated events).</p><p><strong>Results: </strong>Cumulative sum charts generated 31 signals in 12 different ICUs, while p-charts and SMR agreed in 10 and 6 of these signals, respectively, followed by 21 signals from p-charts across 14 ICUs (agreement in 10 of these signals for both CUSUM and SMR) and 15 signals from SMR charts across eight ICUs (agreement from p-charts and CUSUM in 10 and six signals, respectively). The p-chart had a sensitivity of 88% (95% CI, 73 to 104) for a 50% simulated increase in ICU mortality followed by CUSUM at 71% (95% CI, 49 to 102) and SMR at 59% (95% CI, 35 to 82). Performance with lower simulated increases was poor for all three methods.</p><p><strong>Conclusions: </strong>P-charts created with risk-adjusted mortality at monthly intervals are potentially useful tools for monitoring ICU performance. Future studies should consider usability testing with ICU leaders and application of these methods to additional clinical domains.</p>","PeriodicalId":56145,"journal":{"name":"Canadian Journal of Anesthesia-Journal Canadien D Anesthesie","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Canadian Journal of Anesthesia-Journal Canadien D Anesthesie","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s12630-024-02863-6","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ANESTHESIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: The optimal method for monitoring intensive care unit (ICU) performance is unknown. We sought to compare process control charts using standardized mortality ratio (SMR), p-charts, and cumulative sum (CUSUM) charts for detecting increases in risk-adjusted mortality within ICUs.
Methods: Using data from 17 medical-surgical ICUs that included 29,592 patients in Ontario, Canada, we created risk-adjusted p-charts and SMRs on monthly intervals and CUSUM charts. We defined positive signals as any data point that was above the 3-sigma limit (approximating a 99% confidence interval [CI]) on a p-chart, any data point whose 95% CI did not include 1 for the SMR charts, and when a data point exceeded control limits for an odds ratio of 1.5 for CUSUM charts. We simulated increases in mortality of 10%, 30%, and 50% for each ICU to determine the sensitivity of each method. We calculated sensitivity as the number of positive signals divided by the number of ICUs (equal to number of simulated events).
Results: Cumulative sum charts generated 31 signals in 12 different ICUs, while p-charts and SMR agreed in 10 and 6 of these signals, respectively, followed by 21 signals from p-charts across 14 ICUs (agreement in 10 of these signals for both CUSUM and SMR) and 15 signals from SMR charts across eight ICUs (agreement from p-charts and CUSUM in 10 and six signals, respectively). The p-chart had a sensitivity of 88% (95% CI, 73 to 104) for a 50% simulated increase in ICU mortality followed by CUSUM at 71% (95% CI, 49 to 102) and SMR at 59% (95% CI, 35 to 82). Performance with lower simulated increases was poor for all three methods.
Conclusions: P-charts created with risk-adjusted mortality at monthly intervals are potentially useful tools for monitoring ICU performance. Future studies should consider usability testing with ICU leaders and application of these methods to additional clinical domains.
期刊介绍:
The Canadian Journal of Anesthesia (the Journal) is owned by the Canadian Anesthesiologists’
Society and is published by Springer Science + Business Media, LLM (New York). From the
first year of publication in 1954, the international exposure of the Journal has broadened
considerably, with articles now received from over 50 countries. The Journal is published
monthly, and has an impact Factor (mean journal citation frequency) of 2.127 (in 2012). Article
types consist of invited editorials, reports of original investigations (clinical and basic sciences
articles), case reports/case series, review articles, systematic reviews, accredited continuing
professional development (CPD) modules, and Letters to the Editor. The editorial content,
according to the mission statement, spans the fields of anesthesia, acute and chronic pain,
perioperative medicine and critical care. In addition, the Journal publishes practice guidelines
and standards articles relevant to clinicians. Articles are published either in English or in French,
according to the language of submission.