Variation in ICU Risk-Adjusted Mortality

Kuzniewicz, Michael W.; Vasilevskis, Eduard E.; Lane, Rondall K.; Dean, Mitzi L.; Trivedi, Nisha G.; Rennie, Deborah J.; Clay, Ted; Kotler, Pamela L.; Dudley, R. Adams

doi:10.1378/chest.07-3061

Cited by 114 publications

(54 citation statements)

References 27 publications

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“…The ICUs with lower readmission or mortality can be viewed as best practices and ICUs with higher readmission or mortality could benefit from their views and experiences. The extent of this variation is consistent with that reported in studies on ICU length of stay and mortality [42, 43]. To study and to possibly explain the found variation, we subsequently studied the implementation of ICU discharge practices and their association with the occurrence of IC readmissions and post-ICU in hospital mortality rate.…”

Section: Discussionsupporting

confidence: 77%

Variation in rates of ICU readmissions and post-ICU in-hospital mortality and their association with ICU discharge practices

Sluisveld¹,

Bakhshi‐Raiez

Keizer

et al. 2017

BMC Health Serv Res

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BackgroundVariation in intensive care unit (ICU) readmissions and in-hospital mortality after ICU discharge may indicate potential for improvement and could be explained by ICU discharge practices. Our objective was threefold: (1) describe variation in rates of ICU readmissions within 48 h and post-ICU in-hospital mortality, (2) describe ICU discharge practices in Dutch hospitals, and (3) study the association between rates of ICU readmissions within 48 h and post-ICU in-hospital mortality and ICU discharge practices.MethodsWe analysed data on 42,040 admissions to 82 (91.1%) Dutch ICUs in 2011 from the Dutch National Intensive Care Evaluation (NICE) registry to describe variation in standardized ICU readmission and post-ICU mortality rates using funnel-plots. We send a questionnaire to all Dutch ICUs. 75 ICUs responded and their questionnaire data could be linked to 38,498 admissions in the NICE registry. Generalized estimation equations analyses were used to study the association between ICU readmissions and post-ICU mortality rates and the identified discharge practices, i.e. (1) ICU discharge criteria; (2) bed managers; (3) early discharge planning; (4) step-down facilities; (5) medication reconciliation; (6) verbal and written handover; (7) monitoring of post-ICU patients; and (8) consulting ICU nurses. In all analyses, the outcomes were corrected for patient-related confounding factors.ResultsThe standardized rate of ICU readmissions varied between 0.14 and 2.67 and 20.8% of the hospitals fell outside the 95% control limits and 3.6% outside the 99.8% control limits. The standardized rate of post-ICU mortality varied between 0.07 and 2.07 and 17.1% of the hospitals fell outside the 95% control limits and 4.9% outside the 99.8% control limits. We could not demonstrate an association between the eight ICU discharge practices and rates of ICU readmissions or post-ICU in-hospital mortality. Implementing a higher number of ICU discharge practices was also not associated with better patient outcomes.ConclusionsWe found both variation in patient outcomes and variation in ICU discharge practices between ICUs. However, we found no association between discharge practices and rates of ICU readmissions or post-ICU mortality. Further research is necessary to find factors, which may influence these patient outcomes, in order to improve quality of care.Electronic supplementary materialThe online version of this article (doi:10.1186/s12913-017-2234-z) contains supplementary material, which is available to authorized users.

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Section: Discussionsupporting

confidence: 77%

Variation in rates of ICU readmissions and post-ICU in-hospital mortality and their association with ICU discharge practices

Sluisveld¹,

Bakhshi‐Raiez

Keizer

et al. 2017

BMC Health Serv Res

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“…The over prediction of mortality is even greater for patients with specific diagnoses that had the largest mortality reductions between 1988/1989 and 2010/2012. The magnitude of these disease-specific changes may explain why recalibrating models that do not include specific diagnostic information often fails to improve calibration when tested in new populations [31-33]. …”

Section: Discussionmentioning

confidence: 99%

Changes in hospital mortality for United States intensive care unit admissions from 1988 to 2012

2013

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IntroductionA decrease in disease-specific mortality over the last twenty years has been reported for patients admitted to United States (US) hospitals, but data for intensive care patients are lacking. The aim of this study was to describe changes in hospital mortality and case-mix using clinical data for patients admitted to multiple US ICUs over the last 24 years.MethodsWe carried out a retrospective time series analysis of hospital mortality using clinical data collected from 1988 to 2012. We also examined the impact of ICU admission diagnosis and other clinical characteristics on mortality over time. The potential impact of hospital discharge destination on mortality was also assessed using data from 2001 to 2012.ResultsFor 482,601 ICU admissions there was a 35% relative decrease in mortality from 1988 to 2012 despite an increase in age and severity of illness. This decrease varied greatly by diagnosis. Mortality fell by >60% for patients with chronic obstructive pulmonary disease, seizures and surgery for aortic dissection and subarachnoid hemorrhage. Mortality fell by 51% to 59% for six diagnoses, 41% to 50% for seven diagnoses, and 10% to 40% for seven diagnoses. The decrease in mortality from 2001 to 2012 was accompanied by an increase in discharge to post-acute care facilities and a decrease in discharge to home.ConclusionsHospital mortality for patients admitted to US ICUs has decreased significantly over the past two decades despite an increase in the severity of illness. Decreases in mortality were diagnosis specific and appear attributable to improvements in the quality of care, but changes in discharge destination and other confounders may also be responsible.

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“…22 Reported areas under the curve for MediQual Atlas mortality prediction in medical patients range from 0.837 to 0.874, which are comparable to other common ICU risk-adjustment systems. 23, 24 The MediQual Atlas score is automatically calculated by PHC4 on patients admitted to Pennsylvania hospitals but may be absent due to missing clinical data.…”

Section: Methodsmentioning

confidence: 99%

The Effect of Multidisciplinary Care Teams on Intensive Care Unit Mortality

et al. 2010

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Background Critically ill patients are medically complex and may benefit from a multidisciplinary approach to care. Methods We conducted a population-based retrospective cohort study of medical patients admitted to Pennsylvania acute hospitals (N=169) from July 1, 2004 to June 30, 2006, linking a statewide hospital organizational survey to hospital discharge data. Multivariate logistic regression was used to determine the independent relationship between daily multidisciplinary rounds and 30-day mortality. Results 112 hospitals and 107,324 patients were included in the final analysis. Overall 30-day mortality was 18.3%. After adjusting for patient and hospital characteristics, multidisciplinary care was associated with significant reductions in the odds of death (OR=0.84, 95% CI: 0.76–0.93, p=0.001). When stratifying by intensivist physician staffing, the lowest odds of death were in ICUs with high-intensity physician staffing and multidisciplinary care teams (OR=0.78, 95% CI: 0.68–0.89, p<0.0001), followed by ICUs with low intensity physician staffing and multidisciplinary care teams (OR=0.88, 95%CI: 0.79–0.97, p=0.014), compared to hospitals with low intensity physician staffing but without multidisciplinary care teams. The effects of multidisciplinary care were consistent across key subgroups including patients with sepsis, patients requiring invasive mechanical ventilation, and patients in the highest quartile of severity of illness Conclusions Daily rounds by a multidisciplinary team are associated with lower mortality among medical ICU patients. The survival benefit of intensivist physician staffing is in part explained by the presence of multidisciplinary teams in high-intensity staffed ICUs.

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Variation in ICU Risk-Adjusted Mortality

Cited by 114 publications

References 27 publications

Variation in rates of ICU readmissions and post-ICU in-hospital mortality and their association with ICU discharge practices

Variation in rates of ICU readmissions and post-ICU in-hospital mortality and their association with ICU discharge practices

Changes in hospital mortality for United States intensive care unit admissions from 1988 to 2012

The Effect of Multidisciplinary Care Teams on Intensive Care Unit Mortality

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