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Frequency, risk factors, and outcomes of early unplanned readmissions to PICUs.

ABSTRACT: To determine the rate of unplanned PICU readmissions, examine the characteristics of index admissions associated with readmission, and compare outcomes of readmissions versus index admissions.Retrospective cohort analysis.Ninety North American PICUs that participated in the Virtual Pediatric Intensive Care Unit Systems.One hundred five thousand four hundred thirty-seven admissions between July 2009 and March 2011.None.Unplanned PICU readmission within 48 hours of index discharge was the primary outcome. Summary statistics, bivariate analyses, and mixed-effects logistic regression model with random effects for each hospital were performed.There were 1,161 readmissions (1.2%). The readmission rate varied among PICUs (0-3.3%), and acute respiratory (56%), infectious (35%), neurological (28%), and cardiovascular (20%) diagnoses were often present on readmission. Readmission risk increased in patients with two or more complex chronic conditions (adjusted odds ratio, 1.72; p < 0.001), unscheduled index admission (adjusted odds ratio, 1.37; p < 0.001), and transfer to an intermediate unit (adjusted odds ratio, 1.29; p = 0.004, compared with ward). Trauma patients had a decreased risk of readmission (adjusted odds ratio, 0.67; p = 0.003). Gender, race, insurance, age more than 6 months, perioperative status, and nighttime transfer were not associated with readmission. Compared with index admissions, readmissions had longer median PICU length of stay (3.1 vs 1.7 d, p < 0.001) and higher mortality (4% vs 2.5%, p = 0.002).Unplanned PICU readmissions were relatively uncommon, but were associated with worse outcomes. Several patient and admission characteristics were associated with readmission. These data help identify high-risk patient groups and inform risk-adjustment for standardized readmission rates.

SUBMITTER: Edwards JD

PROVIDER: S-EPMC4327890 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

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Frequency, risk factors, and outcomes of early unplanned readmissions to PICUs.

Edwards Jeffrey D JD Lucas Adam R AR Stone Patricia W PW Boscardin W John WJ Dudley R Adams RA

Critical care medicine 20131201 12

<h4>Objectives</h4>To determine the rate of unplanned PICU readmissions, examine the characteristics of index admissions associated with readmission, and compare outcomes of readmissions versus index admissions.<h4>Design</h4>Retrospective cohort analysis.<h4>Setting</h4>Ninety North American PICUs that participated in the Virtual Pediatric Intensive Care Unit Systems.<h4>Patients</h4>One hundred five thousand four hundred thirty-seven admissions between July 2009 and March 2011.<h4>Intervention ...[more]

PMID: 23982030

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Project description:OBJECTIVE:To synthesise evidence on risk factors associated with paediatric unplanned hospital readmissions (UHRs). DESIGN:Systematic review. DATA SOURCE:CINAHL, EMBASE (Ovid) and MEDLINE from 2000 to 2017. ELIGIBILITY CRITERIA:Studies published in English with full-text access and focused on paediatric All-cause, Surgical procedure and General medical condition related UHRs were included. DATA EXTRACTION AND SYNTHESIS:Characteristics of the included studies, examined variables and the statistically significant risk factors were extracted. Two reviewers independently assessed study quality based on six domains of potential bias. Pooling of extracted risk factors was not permitted due to heterogeneity of the included studies. Data were synthesised using content analysis and presented in narrative form. RESULTS:Thirty-six significant risk factors were extracted from the 44 included studies and presented under three health condition groupings. For All-cause UHRs, ethnicity, comorbidity and type of health insurance were the most frequently cited factors. For Surgical procedure related UHRs, specific surgical procedures, comorbidity, length of stay (LOS), age, the American Society of Anaesthesiologists class, postoperative complications, duration of procedure, type of health insurance and illness severity were cited more frequently. The four most cited risk factors associated with General medical condition related UHRs were comorbidity, age, health service usage prior to the index admission and LOS. CONCLUSIONS:This systematic review acknowledges the complexity of readmission risk prediction in paediatric populations. This review identified four risk factors across all three health condition groupings, namely comorbidity; public health insurance; longer LOS and patients<12 months or between 13-18 years. The identification of risk factors, however, depended on the variables examined by each of the included studies. Consideration should be taken into account when generalising reported risk factors to other institutions. This review highlights the need to develop a standardised set of measures to capture key hospital discharge variables that predict unplanned readmission among paediatric patients.

Project description:To determine the frequency, mortality, cost, and risk factors associated with readmission after index hospitalization with severe sepsis.Observational cohort study of Healthcare Cost and Utilization Project data.All nonfederal hospitals in three U.S. states.Severe sepsis survivors (n = 43,452) in the first two quarters of 2011.None.We measured readmission rates and the associated cost and mortality of readmissions in severe sepsis survivors. We used multivariable logistic regression to identify patient and hospitalization characteristics associated with readmission. Of 43,452 sepsis survivors, 26% required readmission within 30 days and 48% within 180 days. The cumulative mortality rate of sepsis survivors attributed to readmissions was 8%, and the estimated cost was over $1.1 billion. Among survivors, 25% required multiple readmissions within 180 days and accounted for 77% of all readmissions. Age younger than 80 years (odds ratio, 1.14; 95% CI, 1.08-1.21), black race (odds ratio, 1.18; 95% CI, 1.10-1.26), and Medicare or Medicaid payor status (odds ratio, 1.21; 95% CI, 1.13-1.30; odds ratio, 1.34; 95% CI, 1.23-1.46, respectively) were associated with greater odds of 30-day readmission while female gender was associated with reduced odds (odds ratio, 0.92; 95% CI, 0.87-0.96). Comorbidities including malignancy (odds ratio, 1.34; 95% CI, 1.24-1.45), collagen vascular disease (odds ratio, 1.30; 95% CI, 1.15-1.46), chronic kidney disease (odds ratio, 1.24; 95% CI, 1.18-1.31), liver disease (odds ratio, 1.22; 95% CI, 1.11-1.34), congestive heart failure (odds ratio, 1.14; 95% CI, 1.08-1.19), lung disease (odds ratio, 1.12; 95% CI, 1.06-1.18), and diabetes (odds ratio, 1.12; 95% CI, 1.07-1.17) were associated with greater odds of 30-day readmission. Index hospitalization characteristics including longer length of stay, discharge to a care facility, higher hospital annual severe sepsis case volume, and higher hospital sepsis mortality rate were also positively associated with readmission rates.The 30-day and 180-day readmissions are common in sepsis survivors with significant resultant cost and mortality. Patient sociodemographics and comorbidities as well as index hospitalization characteristics are associated with 30-day readmission rates.

Project description:RationaleIn the United States, approximately 20% of patients hospitalized with pneumonia are readmitted to a hospital within 30 days. Given the significant costs and healthcare system use resulting from unplanned readmissions, pneumonia readmission rates are a target of national quality measures. Patient do-not-resuscitate (DNR) status strongly influences hospital pneumonia mortality measures; however, associations between DNR status and 30-day readmissions after pneumonia are unclear.ObjectivesDetermine the effect of accounting for patient DNR status on hospital readmission measures for pneumonia.MethodsAfter excluding patients with missing data, those who died during the index hospitalization, those who were discharged against medical advice, those who did not reside in California, and those admitted to low pneumonia case-volume hospitals, we identified 30-day unplanned readmissions after an index pneumonia hospitalization from the 2011 California State Inpatient Database. We used hierarchical logistic regression to determine the association between early DNR status (within 24 hours of admission) and 30-day readmission and hospital risk-adjusted readmission rates.Measurements and main resultsWe identified 68,691 hospitalizations for pneumonia across 321 hospitals. Patients with early DNR orders were less likely to be readmitted within 30 days (20.0% vs. 22.5%, adjusted odds ratio [aOR], 0.93; 95% confidence interval [CI], 0.88-0.99). Patients with pneumonia admitted to high-versus-low DNR rate hospitals were at lower risk for readmission (DNR rate quartile 4 vs. quartile 1, aOR, 0.62; 95% CI, 0.55-0.70), regardless of individual DNR status. Higher hospital risk-adjusted DNR rates were strongly associated with lower risk-adjusted readmission rates (r?=?-0.44; P?<?0.0001). Inclusion of early DNR status in risk-adjusted readmission models changed ranking categories for 7/321 (2.2%) hospitals, with 2 hospitals no longer labeled as "under-performing outliers."ConclusionsPatients with an early DNR order have a lower risk for readmission after a pneumonia hospitalization. Unmeasured DNR status weakly confounds hospital readmission measures; accounting for patient DNR status would alter readmission ratings for a small number of hospitals.

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Frequency, risk factors, and outcomes of early unplanned readmissions to PICUs.

Publications

Frequency, risk factors, and outcomes of early unplanned readmissions to PICUs.

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