Dataset Information

Variability in case-mix adjusted in-hospital cardiac arrest rates.

ABSTRACT: It is unknown how in-hospital cardiac arrest (IHCA) rates vary across hospitals and predictors of variability.Measure variability in IHCA across hospitals and determine if hospital-level factors predict differences in case-mix adjusted event rates.Get with the Guidelines Resuscitation (GWTG-R) (n=433 hospitals) was used to identify IHCA events between 2003 and 2007. The American Hospital Association survey, Medicare, and US Census were used to obtain detailed information about GWTG-R hospitals.Adult patients with IHCA.Case-mix-adjusted predicted IHCA rates were calculated for each hospital and variability across hospitals was compared. A regression model was used to predict case-mix adjusted event rates using hospital measures of volume, nurse-to-bed ratio, percent intensive care unit beds, palliative care services, urban designation, volume of black patients, income, trauma designation, academic designation, cardiac surgery capability, and a patient risk score.We evaluated 103,117 adult IHCAs at 433 US hospitals. The case-mix adjusted IHCA event rate was highly variable across hospitals, median 1/1000 bed days (interquartile range: 0.7 to 1.3 events/1000 bed days). In a multivariable regression model, case-mix adjusted IHCA event rates were highest in urban hospitals [rate ratio (RR), 1.1; 95% confidence interval (CI), 1.0-1.3; P=0.03] and hospitals with higher proportions of black patients (RR, 1.2; 95% CI, 1.0-1.3; P=0.01) and lower in larger hospitals (RR, 0.54; 95% CI, 0.45-0.66; P<0.0001).Case-mix adjusted IHCA event rates varied considerably across hospitals. Several hospital factors associated with higher IHCA event rates were consistent with factors often linked with lower hospital quality of care.

SUBMITTER: Merchant RM

PROVIDER: S-EPMC3260453 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

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Variability in case-mix adjusted in-hospital cardiac arrest rates.

Merchant Raina M RM Yang Lin L Becker Lance B LB Berg Robert A RA Nadkarni Vinay V Nichol Graham G Carr Brendan G BG Mitra Nandita N Bradley Steven M SM Abella Benjamin S BS Groeneveld Peter W PW

Medical care 20120201 2

<h4>Background</h4>It is unknown how in-hospital cardiac arrest (IHCA) rates vary across hospitals and predictors of variability.<h4>Objectives</h4>Measure variability in IHCA across hospitals and determine if hospital-level factors predict differences in case-mix adjusted event rates.<h4>Research design</h4>Get with the Guidelines Resuscitation (GWTG-R) (n=433 hospitals) was used to identify IHCA events between 2003 and 2007. The American Hospital Association survey, Medicare, and US Census wer ...[more]

PMID: 22249921

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Project description:OBJECTIVES:To identify modifiable factors leading to unplanned readmission and characterize differences in adjusted unplanned readmission rates across hospitals. DESIGN:Retrospective cohort study using prospectively collected clinical registry data SETTING:: Pediatric Cardiac Critical Care Consortium clinical registry. PATIENTS:Patients admitted to a pediatric cardiac ICU at Pediatric Cardiac Critical Care Consortium hospitals. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:We examined pediatric cardiac ICU encounters in the Pediatric Cardiac Critical Care Consortium registry from October 2013 to March 2016. The primary outcomes were early (< 48?hr from pediatric cardiac ICU transfer) and late (2-7 d) unplanned readmission. Generalized logit models identified independent predictors of unplanned readmission. We then calculated observed-to-expected ratios of unplanned readmission and identified higher-than or lower-than-expected unplanned readmission rates for those with an observed-to-expected ratios greater than or less than 1, respectively, and a 95% CI that did not cross 1. Of 11,301 pediatric cardiac ICU encounters (16 hospitals), 62% were surgical, and 18% were neonates. There were 175 (1.6%) early unplanned readmission, and 300 (2.7%) late unplanned readmission, most commonly for respiratory (31%), or cardiac (28%) indications. In multivariable analysis, unique modifiable factors were associated with unplanned readmission. Although shorter time between discontinuation of vasoactive infusions and pediatric cardiac ICU transfer was associated with early unplanned readmission, nighttime discharge was independently associated with a greater likelihood of late unplanned readmission. Two hospitals had lower-than-expected unplanned readmission in both the early and late categories, whereas two other hospitals were higher-than-expected in both. CONCLUSIONS:This analysis demonstrated time from discontinuation of critical care therapies to pediatric cardiac ICU transfer as a significant, modifiable predictor of unplanned readmission. We identified two hospitals with lower-than-expected adjusted rates of both early and late unplanned readmission, suggesting that their systems are well designed to prevent unplanned readmission. This offers the possibility of disseminating best practices to other hospitals through collaborative learning.

Project description:ObjectivesThe objective of this study was to associate ventilation rates during in-hospital cardiopulmonary resuscitation with 1) arterial blood pressure during cardiopulmonary resuscitation and 2) survival outcomes.DesignProspective, multicenter observational study.SettingPediatric and pediatric cardiac ICUs of the Collaborative Pediatric Critical Care Research Network.PatientsIntubated children (≥ 37 wk gestation and < 19 yr old) who received at least 1 minute of cardiopulmonary resuscitation.InterventionsNone.Measurements and main resultsArterial blood pressure and ventilation rate (breaths/min) were manually extracted from arterial line and capnogram waveforms. Guideline rate was defined as 10 ± 2 breaths/min; high ventilation rate as greater than or equal to 30 breaths/min in children less than 1 year old, and greater than or equal to 25 breaths/min in older children. The primary outcome was survival to hospital discharge. Regression models using Firth penalized likelihood assessed the association between ventilation rates and outcomes. Ventilation rates were available for 52 events (47 patients). More than half of patients (30/47; 64%) were less than 1 year old. Eighteen patients (38%) survived to discharge. Median event-level average ventilation rate was 29.8 breaths/min (interquartile range, 23.8-35.7). No event-level average ventilation rate was within guidelines; 30 events (58%) had high ventilation rates. The only significant association between ventilation rate and arterial blood pressure occurred in children 1 year old or older and was present for systolic blood pressure only (-17.8 mm Hg/10 breaths/min; 95% CI, -27.6 to -8.1; p < 0.01). High ventilation rates were associated with a higher odds of survival to discharge (odds ratio, 4.73; p = 0.029). This association was stable after individually controlling for location (adjusted odds ratio, 5.97; p = 0.022), initial rhythm (adjusted odds ratio, 3.87; p = 0.066), and time of day (adjusted odds ratio, 4.12; p = 0.049).ConclusionsIn this multicenter cohort, ventilation rates exceeding guidelines were common. Among the range of rates delivered, higher rates were associated with improved survival to hospital discharge.

Project description:BackgroundA hospital's risk-standardized survival rate (RSSR) for in-hospital cardiac arrest has emerged as an important metric to benchmark and incentivize hospital resuscitation quality. We examined whether hospital performance on the RSSR metric was stable or dynamic year-over-year and whether low-performing hospitals were able to improve survival outcomes over time.Methods and resultsWe used data from 84 089 adult patients with an in-hospital cardiac arrest from 166 hospitals with continuous participation in Get With The Guidelines-Resuscitation from 2012 to 2017. A 2-level hierarchical regression model was used to compute RSSRs during a baseline (2012-2013) and two follow-up periods (2014-2015 and 2016-2017). At baseline, hospitals were classified as top-, middle-, and bottom-performing if they ranked in the top 25%, middle 50%, and bottom 25%, respectively, on their RSSR metric during 2012 to 2013. We compared hospital performance on RSSR during follow-up between top, middle, and bottom-performing hospitals' at baseline. During 2012 to 2013, 42 hospitals were identified as top-performing (median RSSR, 31.7%), 82 as middle-performing (median RSSR, 24.6%), and 42 as bottom-performing (median RSSR, 18.7%). During both follow-up periods, >70% of top-performing hospitals ranked in the top 50%, a substantial proportion remained in the top 25% of RSSR during 2014 to 2015 (54.6%) and 2016 to 2017 (40.4%) follow-up periods. Likewise, nearly 75% of bottom-performing hospitals remained in the bottom 50% during both follow-up periods, with 50.0% in the bottom 25% of RSSR during 2014 to 2015 and 40.5% in the bottom 25% during 2016 to 2017. While percentile rankings were generally consistent over time at ≈45% of study hospitals, ≈1 in 5 (21.4%) bottom-performing hospitals showed large improvement in percentile rankings over time and a similar proportion (23.7%) of top-performing hospitals showed large decline in percentile rankings compared with baseline.ConclusionsHospital performance on RSSR during baseline period was generally consistent over 4 years of follow-up. However, 1 in 5 bottom-performing hospitals had large improvement in survival over time. Identifying care and quality improvement innovations at these sites may provide opportunities to improve in-hospital cardiac arrest care at other hospitals.

Project description:Background Hospitals participating in the national Get With The Guidelines-Resuscitation registry receive an award for high rates of adherence to quality metrics for in-hospital cardiac arrest. We sought to evaluate whether awards based on these quality metrics can be considered a proxy for performance on cardiac arrest survival. Methods and Results Among 195 hospitals with continuous participation in Get With The Guidelines-Resuscitation between 2012 and 2015, we identified 78 that received an award (Gold or Silver) for ≥85% compliance for all 4 metrics for in-hospital cardiac arrest-time to chest compressions, ≤1 minute; time to defibrillation, ≤2 minutes; device confirmation of endotracheal tube placement; and a monitored/witnessed arrest-for at least 12 consecutive months during 2014 to 2015. Award hospitals had higher cardiac arrest volumes than nonaward hospitals but otherwise had similar site characteristics. During 2014 to 2015, award hospitals had higher rates of return of spontaneous circulation for in-hospital cardiac arrest than nonaward hospitals (median [interquartile range], 71% [64%-77%] versus 66% [59%-74%]; Spearman ρ, 0.19; P=0.009). However, rates of risk-standardized survival to discharge at award hospitals (median, 25% [interquartile range, 22%-30%]) were similar to nonaward hospitals (median, 24% [interquartile range, 12%-27%]; Spearman ρ, 0.13; P=0.06). Among hospitals in the best tertile for survival to discharge in 2014 to 2015, 55.4% (36/65) did not receive an award, with poor discrimination of high-performing hospitals by award status (C statistic, 0.53). Similarly, there was only a weak association between hospitals' award status in 2014 to 2015 and their rates of survival to discharge in the preceding 2-year period (Spearman ρ, 0.16; P=0.03). Conclusions The current recognition mechanism within a national registry for in-hospital cardiac arrest captures hospital performance on return of spontaneous circulation but is not well correlated with survival to discharge. This suggests that current awards for resuscitation quality may not adequately capture hospital performance on overall survival-the outcome of greatest interest to patients.

Dataset Information

Variability in case-mix adjusted in-hospital cardiac arrest rates.

Publications

Variability in case-mix adjusted in-hospital cardiac arrest rates.

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