Dataset Information

Variation in Adjusted Mortality for Medical Admissions to Pediatric Cardiac ICUs.

ABSTRACT: OBJECTIVES:Pediatric cardiac ICUs should be adept at treating both critical medical and surgical conditions for patients with cardiac disease. There are no case-mix adjusted quality metrics specific to medical cardiac ICU admissions. We aimed to measure case-mix adjusted cardiac ICU medical mortality rates and assess variation across cardiac ICUs in the Pediatric Cardiac Critical Care Consortium. DESIGN:Observational analysis. SETTING:Pediatric Cardiac Critical Care Consortium clinical registry. PATIENTS:All cardiac ICU admissions that did not include cardiac surgery. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:The primary endpoint was cardiac ICU mortality. Based on multivariable logistic regression accounting for clustering, we created a case-mix adjusted model using variables present at cardiac ICU admission. Bootstrap resampling (1,000 samples) was used for model validation. We calculated a standardized mortality ratio for each cardiac ICU based on observed-to-expected mortality from the fitted model. A cardiac ICU was considered a statistically significant outlier if the 95% CI around the standardized mortality ratio did not cross 1. Of 11,042 consecutive medical admissions from 25 cardiac ICUs (August 2014 to May 2017), the observed mortality rate was 4.3% (n = 479). Final model covariates included age, underweight, prior surgery, time of and reason for cardiac ICU admission, high-risk medical diagnosis or comorbidity, mechanical ventilation or extracorporeal membrane oxygenation at admission, and pupillary reflex. The C-statistic for the validated model was 0.87, and it was well calibrated. Expected mortality ranged from 2.6% to 8.3%, reflecting important case-mix variation. Standardized mortality ratios ranged from 0.5 to 1.7 across cardiac ICUs. Three cardiac ICUs were outliers; two had lower-than-expected (standardized mortality ratio <1) and one had higher-than-expected (standardized mortality ratio >1) mortality. CONCLUSIONS:We measured case-mix adjusted mortality for cardiac ICU patients with critical medical conditions, and provide the first report of variation in this quality metric within this patient population across Pediatric Cardiac Critical Care Consortium cardiac ICUs. This metric will be used by Pediatric Cardiac Critical Care Consortium cardiac ICUs to assess and improve outcomes by identifying high-performing (low-mortality) centers and engaging in collaborative learning.

SUBMITTER: Gaies M

PROVIDER: S-EPMC6373463 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Variation in Adjusted Mortality for Medical Admissions to Pediatric Cardiac ICUs.

Gaies Michael M Ghanayem Nancy S NS Alten Jeffrey A JA Costello John M JM Lasa Javier J JJ Chanani Nikhil K NK Shin Andrew Y AY Retzloff Lauren L Zhang Wenying W Pasquali Sara K SK Banerjee Mousumi M Tabbutt Sarah S

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies 20190201 2

<h4>Objectives</h4>Pediatric cardiac ICUs should be adept at treating both critical medical and surgical conditions for patients with cardiac disease. There are no case-mix adjusted quality metrics specific to medical cardiac ICU admissions. We aimed to measure case-mix adjusted cardiac ICU medical mortality rates and assess variation across cardiac ICUs in the Pediatric Cardiac Critical Care Consortium.<h4>Design</h4>Observational analysis.<h4>Setting</h4>Pediatric Cardiac Critical Care Consort ...[more]

PMID: 30371635

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Project description:OBJECTIVE:To develop a postoperative mortality case-mix adjustment model to facilitate assessment of cardiac ICU quality of care, and to describe variation in adjusted cardiac ICU mortality across hospitals within the Pediatric Cardiac Critical Care Consortium. DESIGN:Observational analysis. SETTING:Multicenter Pediatric Cardiac Critical Care Consortium clinical registry. PARTICIPANTS:All surgical cardiac ICU admissions between August 2014 and May 2016. The analysis included 8,543 admissions from 23 dedicated cardiac ICUs. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:We developed a novel case-mix adjustment model to measure postoperative cardiac ICU mortality after congenital heart surgery. Multivariable logistic regression was performed to assess preoperative, intraoperative, and immediate postoperative severity of illness variables as candidate predictors. We used generalized estimating equations to account for clustering of patients within hospital and obtain robust SEs. Bootstrap resampling (1,000 samples) was used to derive bias-corrected 95% CIs around each predictor and validate the model. The final model was used to calculate expected mortality at each hospital. We calculated a standardized mortality ratio (observed-to-expected mortality) for each hospital and derived 95% CIs around the standardized mortality ratio estimate. Hospital standardized mortality ratio was considered a statistically significant outlier if the 95% CI did not include 1. Significant preoperative predictors of mortality in the final model included age, chromosomal abnormality/syndrome, previous cardiac surgeries, preoperative mechanical ventilation, and surgical complexity. Significant early postoperative risk factors included open sternum, mechanical ventilation, maximum vasoactive inotropic score, and extracorporeal membrane oxygenation. The model demonstrated excellent discrimination (C statistic, 0.92) and adequate calibration. Comparison across Pediatric Cardiac Critical Care Consortium hospitals revealed five-fold difference in standardized mortality ratio (0.4-1.9). Two hospitals had significantly better-than-expected and two had significantly worse-than-expected mortality. CONCLUSIONS:For the first time, we have demonstrated that variation in mortality as a quality metric exists across dedicated cardiac ICUs. These findings can guide efforts to reduce mortality after cardiac surgery.

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:It is important that actual outcomes of care and not surrogate markers, such as process measures, be used to evaluate the quality of inpatient care. Because of the heterogenous composition of patients, risk-adjustment is essential for the objective evaluation of outcomes following inpatient care. Comparative evaluation of risk-adjusted outcomes can be used to identify suboptimal performance and can provide direction for care improvement initiatives.We studied the risk-adjusted outcomes of 6 medical conditions during the inpatient and 90-day post-discharge period to identify the opportunities for care improvement. The Medicare Limited Dataset for 2012 to 2014 was used to identify acute myocardial infarction (AMI), chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), pneumonia (PNEU), cerebrovascular accidents (CVA), and gastrointestinal hemorrhage (GIH). Stepwise logistic predictive models were developed for the adverse outcomes (AOs) of inpatient deaths, 3-sigma prolonged length-of-stay outliers, 90-day post-discharge deaths, and 90-day readmissions after unrelated events were excluded. Observed and predicted AOs were determined for each hospital with ?75 cases for each of the 6 medical conditions. Z-scores and risk-adjusted AO rates for each hospital permitted comparative analysis of outcomes after adjusting for covariance among the medical conditions.There were a total of 1,811,749 patients from 973 acute care hospitals with the 6 medical conditions. A total of 41% of all patients had ?1 AO events. One or more readmissions were identified in 29.8% of patients. A total of 64 hospitals (6.4%) were 2 standard deviations better than the mean for risk-adjusted outcomes, and 72 (7.4%) were 2 standard deviations poorer. The best performing decile of hospitals had mean AO rates of 35.1% (odds ratio?=?0.766; 95% confidence interval (CI) CI: 0.762-0.771) and the poorest performing decile a mean AO rate of 48.5% (odds ratio?=?1.357; 95% CI: 1.346-1.369). Volume of qualifying cases ranged from 670 to 9314; no association was identified for increased volume of patients (P?<?.40).Risk-adjusted AO rates demonstrated nearly a 14% opportunity for care improvement between top and suboptimal performing hospitals. Hospitals must be able to benchmark objective measurement of outcomes to inform quality initiatives.

Project description:OBJECTIVES:In-hospital cardiac arrest occurs in 2.6-6% of children with cardiac disease and is associated with significant morbidity and mortality. Much remains unknown about cardiac arrest in pediatric cardiac ICUs; therefore, we aimed to describe cardiac arrest epidemiology in a contemporary multicenter cardiac ICU cohort. DESIGN:Retrospective analysis within the Pediatric Cardiac Critical Care Consortium clinical registry. SETTING:Cardiac ICUs within 23 North American hospitals. PATIENTS:All cardiac medical and surgical patients admitted from August 2014 to July 2016. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:There were 15,908 cardiac ICU encounters (6,498 medical, 9,410 surgical). 3.1% had cardiac arrest; rate was 4.8 cardiac arrest per 1,000 cardiac ICU days. Medical encounters had 50% higher rate of cardiac arrest compared with surgical encounters. Observed (unadjusted) cardiac ICU cardiac arrest prevalence varied from 1% to 5.5% among the 23 centers; cardiac arrest per 1,000 cardiac ICU days varied from 1.1 to 10.4. Over half cardiac arrest occur within 48 hours of admission. On multivariable analysis, prematurity, neonatal age, any Society of Thoracic Surgeons preoperative risk factor, and Society of Thoracic Surgeons-European Association for Cardio-Thoracic Surgery mortality category 4, 5 had strongest association with surgical encounter cardiac arrest. In medical encounters, independent cardiac arrest risk factors were acute heart failure, prematurity, lactic acidosis greater than 3 mmol/dL, and invasive ventilation 1 hour after admission. Median cardiopulmonary resuscitation duration was 10 minutes, return of spontaneous circulation occurred in 64.5%, extracorporeal cardiopulmonary resuscitation in 27.2%. Unadjusted survival was 53.2% in encounters with cardiac arrest versus 98.2% without. Medical encounters had lower survival after cardiac arrest (37.7%) versus surgical encounters (62.5%); Norwood patients had less than half the survival after cardiac arrest (35.6%) compared with all others. Unadjusted survival after cardiac arrest varied greatly among 23 centers. CONCLUSIONS:We provide contemporary epidemiologic and outcome data for cardiac arrest occurring in the cardiac ICU from a multicenter clinical registry. As detailed above, we highlight high-risk patient cohorts and periods of time that may serve as targets for research and quality improvement initiatives aimed at cardiac arrest prevention.

Project description:OBJECTIVE:To describe the epidemiology of noninvasive ventilation therapy for patients admitted to pediatric cardiac ICUs and to assess practice variation across hospitals. DESIGN:Retrospective cohort study using prospectively collected clinical registry data. SETTING:Pediatric Cardiac Critical Care Consortium clinical registry. PATIENTS:Patients admitted to cardiac ICUs at PC4 hospitals. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:We analyzed all cardiac ICU encounters that included any respiratory support from October 2013 to December 2015. Noninvasive ventilation therapy included high flow nasal cannula and positive airway pressure support. We compared patient and, when relevant, perioperative characteristics of those receiving noninvasive ventilation to all others. Subgroup analysis was performed on neonates and infants undergoing major cardiovascular surgery. To examine duration of respiratory support, we created a casemix-adjustment model and calculated adjusted mean durations of total respiratory support (mechanical ventilation + noninvasive ventilation), mechanical ventilation, and noninvasive ventilation. We compared adjusted duration of support across hospitals. The cohort included 8,940 encounters from 15 hospitals: 3,950 (44%) received noninvasive ventilation and 72% were neonates and infants. Medical encounters were more likely to include noninvasive ventilation than surgical. In surgical neonates and infants, 2,032 (55%) received postoperative noninvasive ventilation. Neonates, extracardiac anomalies, single ventricle, procedure complexity, preoperative respiratory support, mechanical ventilation duration, and postoperative disease severity were associated with noninvasive ventilation therapy (p < 0.001 for all). Across hospitals, noninvasive ventilation use ranged from 32% to 65%, and adjusted mean noninvasive ventilation duration ranged from 1 to 4 days (3-d observed mean). Duration of total adjusted respiratory support was more strongly correlated with duration of mechanical ventilation compared with noninvasive ventilation (Pearson r = 0.93 vs 0.71, respectively). CONCLUSIONS:Noninvasive ventilation use is common in cardiac ICUs, especially in patients admitted for medical conditions, infants, and those undergoing high complexity surgery. We observed wide variation in noninvasive ventilation use across hospitals, though the primary driver of total respiratory support time seems to be duration of mechanical ventilation.

Project description:ObjectivesCardiopulmonary failure in children with cardiac disease differs from the general pediatric critical care population, yet the epidemiology of extracorporeal membrane oxygenation support in cardiac ICUs has not been described. We aimed to characterize extracorporeal membrane oxygenation utilization and outcomes across surgical and medical patients in pediatric cardiac ICUs.DesignRetrospective analysis of the Pediatric Cardiac Critical Care Consortium registry to describe extracorporeal membrane oxygenation frequency and outcomes. Within strata of medical and surgical hospitalizations, we identified risk factors associated with extracorporeal membrane oxygenation use through multivariate logistic regression.SettingTertiary-care children's hospitals.PatientsNeonates through adults with cardiac disease.InterventionsNone.Measurements and main resultsThere were 14,526 eligible hospitalizations from August 1, 2014, to June 30, 2016; 449 (3.1%) included at least one extracorporeal membrane oxygenation run. Extracorporeal membrane oxygenation was used in 329 surgical (3.5%) and 120 medical (2.4%) hospitalizations. Systemic circulatory failure and extracorporeal cardiopulmonary resuscitation were the most common extracorporeal membrane oxygenation indications. In the surgical group, risk factors associated with postoperative extracorporeal membrane oxygenation use included younger age, extracardiac anomalies, preoperative comorbidity, higher Society of Thoracic Surgeons-European Association for Cardiothoracic Surgery category, bypass time, postoperative mechanical ventilation, and arrhythmias (all p < 0.05). Bleeding requiring reoperation (25%) was the most common extracorporeal membrane oxygenation complication in the surgical group. In the medical group, risk factors associated with extracorporeal membrane oxygenation use included acute heart failure and higher Vasoactive Inotropic Score at cardiac ICU admission (both p < 0.0001). Stroke (15%) and renal failure (15%) were the most common extracorporeal membrane oxygenation complications in the medical group. Hospital mortality was 49% in the surgical group and 63% in the medical group; mortality rates for hospitalizations including extracorporeal cardiopulmonary resuscitation were 50% and 83%, respectively.ConclusionsThis is the first multicenter study describing extracorporeal membrane oxygenation use and outcomes specific to the cardiac ICU and inclusive of surgical and medical cardiac disease. Mortality remains high, highlighting the importance of identifying levers to improve care. These data provide benchmarks for hospitals to assess their outcomes in extracorporeal membrane oxygenation patients and identify unique high-risk subgroups to target for quality initiatives.

Dataset Information

Variation in Adjusted Mortality for Medical Admissions to Pediatric Cardiac ICUs.

Publications

Variation in Adjusted Mortality for Medical Admissions to Pediatric Cardiac ICUs.

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