Does the implementation of a novel intensive care discharge risk score and nurse-led inpatient review tool improve outcome? A prospective cohort study in two intensive care units in the UK.
ABSTRACT: To develop a clinical prediction model for poor outcome after intensive care unit (ICU) discharge in a large observational data set and couple this to an acute post-ICU ward-based review tool (PIRT) to identify high-risk patients at the time of ICU discharge and improve their acute ward-based review and outcome.Retrospective patient cohort of index ICU admissions between June 2006 and October 2011 receiving routine inpatient review. Prospective cohort between March 2012 and March 2013 underwent risk scoring (PIRT) which subsequently guided inpatient ward-based review.Two UK adult ICUs.4212 eligible discharges from ICU in the retrospective development cohort and 1028 patients included in the prospective intervention cohort.Multivariate analysis was performed to determine factors associated with poor outcome in the retrospective cohort and used to generate a discharge risk score. A discharge and daily ward-based review tool incorporating an adjusted risk score was introduced. The prospective cohort underwent risk scoring at ICU discharge and inpatient review using the PIRT.The primary outcome was the composite of death or readmission to ICU within 14 days of ICU discharge following the index ICU admission.PIRT review was achieved for 67.3% of all eligible discharges and improved the targeting of acute post-ICU review to high-risk patients. The presence of ward-based PIRT review in the prospective cohort did not correlate with a reduction in poor outcome overall (P=0.876) or overall readmission but did reduce early readmission (within the first 48?hours) from 4.5% to 3.6% (P=0.039), while increasing the rate of late readmission (48?hours to 14 days) from 2.7% to 5.8% (P=0.046).PIRT facilitates the appropriate targeting of nurse-led inpatient review acutely after ICU discharge but does not reduce hospital mortality or overall readmission rates to ICU.
Project description:INTRODUCTION: The discharge of patients from the intensive care unit (ICU) to a hospital ward is a common transition of care that is associated with error and adverse events. Risk stratification tools may help identify high-risk patients for targeted interventions, but it is unclear if proper tools have been developed. METHODS: We searched Ovid EMBASE, Ovid MEDLINE, CINAHL, PUBMED and Cochrane Central Register of Controlled Trials from the earliest available date through March 2013, plus reference lists and citations of all studies included in the systematic review. Cohort studies were selected that described the derivation, validation or clinical impact of tools for predicting medical emergency team activation, ICU readmission or mortality following patient discharge from the ICU. Data were extracted on the study design, setting, population, sample size, tool (components, measurement properties) and outcomes. RESULTS: The literature search identified 9,926 citations, of which eight studies describing eight tools met the inclusion criteria. Reported outcomes included ICU readmission (n=4 studies), hospital mortality (n=3 studies) and both ICU readmission and hospital mortality (n=1 studies). Seven of the tools were comprised of distinct measurable component variables, while one tool used subjective scoring of patient risk by intensive care physicians. The areas under receiver operator curves were reported for all studies and ranged from 0.66 to 0.92. A single study provided a direct comparative analysis between two tools. We did not find any studies evaluating the impact of risk prediction on processes and outcomes of care. CONCLUSIONS: Eight risk stratification tools for predicting severe adverse events following patient discharge from ICU have been developed, but have undergone limited comparative evaluation. Although risk stratification tools may help clinician decision-making, further evaluation of the existing tools' effects on care is required prior to clinical implementation.
Project description:INTRODUCTION: Early discharge from the ICU is desirable because it shortens time in the ICU and reduces care costs, but can also increase the likelihood of ICU readmission and post-discharge unanticipated death if patients are discharged before they are stable. We postulated that, using eICU® Research Institute (eRI) data from >400 ICUs, we could develop robust models predictive of post-discharge death and readmission that may be incorporated into future clinical information systems (CIS) to assist ICU discharge planning. METHODS: Retrospective, multi-center, exploratory cohort study of ICU survivors within the eRI database between 1/1/2007 and 3/31/2011. EXCLUSION CRITERIA: DNR or care limitations at ICU discharge and discharge to location external to hospital. Patients were randomized (2?1) to development and validation cohorts. Multivariable logistic regression was performed on a broad range of variables including: patient demographics, ICU admission diagnosis, admission severity of illness, laboratory values and physiologic variables present during the last 24 hours of the ICU stay. Multiple imputation was used to address missing data. The primary outcomes were the area under the receiver operator characteristic curves (auROC) in the validation cohorts for the models predicting readmission and death within 48 hours of ICU discharge. RESULTS: 469,976 and 234,987 patients representing 219 hospitals were in the development and validation cohorts. Early ICU readmission and death was experienced by 2.54% and 0.92% of all patients, respectively. The relationship between predictors and outcomes (death vs readmission) differed, justifying the need for separate models. The models for early readmission and death produced auROCs of 0.71 and 0.92, respectively. Both models calibrated well across risk groups. CONCLUSIONS: Our models for death and readmission after ICU discharge showed good to excellent discrimination and good calibration. Although prospective validation is warranted, we speculate that these models may have value in assisting clinicians with ICU discharge planning.
Project description:Importance:The safety of discharging adult patients recovering from critical illness directly home from the intensive care unit (ICU) is unknown. Objective:To compare the health care utilization and clinical outcomes for ICU patients discharged directly home from the ICU with those of patients discharged home via the hospital ward. Design, Setting, and Participants:Retrospective population-based cohort study of adult patients admitted to the ICU of 9 medical-surgical hospitals from January 1, 2014, to January 1, 2016, with 1-year follow-up after hospital discharge. All adult ICU patients were discharged home alive from hospital, and the propensity score matched cohort (1:1) was based on patient characteristics, therapies received in the ICU, and hospital characteristics. Exposures:Patient disposition on discharge from the ICU: directly home vs home via the hospital ward. Main Outcomes and Measures:The primary outcome was readmission to the hospital within 30 days of hospital discharge. The secondary outcomes were emergency department visit within 30 days and death within 1 year. Results:Among the 6732 patients included in the study, 2826 (42%) were female; median age, 56 years (interquartile range, 41-67 years); 922 (14%) were discharged directly home, with significant variation found between hospitals (range, 4.4%-44.0%). Compared with patients discharged home via the hospital ward, patients discharged directly home were younger (median age 47 vs 57 years; P < .001), more likely to be admitted with a diagnosis of overdose, substance withdrawal, seizures, or metabolic coma (32%  vs 10% ; P < .001), to have a lower severity of acute illness on ICU admission (median APACHE II score 15 vs 18; P < .001), and receive less than 48 hours of invasive mechanical ventilation (42%  vs 34% ; P < .001). In the propensity score matched cohort (n = 1632), patients discharged directly home had similar length of ICU stay (median, 3.1 days vs 3.0 days; P = .42) but significantly shorter length of hospital stay (median, 3.3 days vs 9.2 days; P < .001) compared with patients discharged home via the hospital ward. There were no significant differences between patients discharged directly home or home via the hospital ward for readmission to the hospital (10% [n = 81] vs 11% [n = 92]; hazard ratio [HR], 0.88; 95% CI, 0.64-1.20) or emergency department visit (25% [n = 200] vs 26% [n = 212]; HR, 0.94; 95% CI, 0.81-1.09) within 30 days of hospital discharge. Four percent of patients in both groups died within 1 year of hospital discharge (n = 31 and n = 34 in the discharged directly home and discharged home via the hospital ward groups, respectively) (HR, 0.90; 95% CI, 0.60-1.35). Conclusions and Relevance:The discharge of select adult patients directly home from the ICU is common, and it is not associated with increased health care utilization or increased mortality.
Project description:Discharge location is associated with short-term readmission rates after hospitalization for several medical and surgical diagnoses. We hypothesized that discharge location: home, home health, skilled nursing facility (SNF), long-term acute care (LTAC), or inpatient rehabilitation, independently predicted the risk of 30-day readmission and severity of first readmission after orthotopic liver transplantation.We performed a retrospective cohort review using Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases for Florida and California. Patients who underwent orthotopic liver transplantation from 2009 to 2011 were included and followed for 1 year. Mixed-effects logistic regression was used to model the effect of discharge location on 30-day readmission controlling for demographic, socioeconomic, and clinical factors. Total cost of first readmission was used as a surrogate measure for readmission severity and resource use.A total of 3,072 patients met our inclusion criteria. The overall 30-day readmission rate was 29.6%. Discharge to inpatient rehabilitation (adjusted odds ratio [aOR] 0.43, p = 0.013) or LTAC/SNF (aOR 0.63, p = 0.014) were associated with decreased odds of 30-day readmission when compared with home. The severity of 30-day readmissions for patients discharged to inpatient rehabilitation were the same as those discharged home or home with home health. Severity was increased for those discharged to LTAC/SNF. The time to first readmission was longest for patients discharged to inpatient rehabilitation (17 days vs 8 days, p < 0.001).When compared with other locations of discharge, inpatient rehabilitation reduces the risk of 30-day readmission and increases the time to first readmission. These benefits come without increasing the severity of readmission. Increased use of inpatient rehabilitation after orthotopic liver transplantation is a strategy to improve 30-day readmission rates.
Project description:Background:The relationship between postoperative intensive care (ICU) admission following emergency general surgery (EGS) and emergency hospital readmission has not been widely investigated. Methods:Retrospective analysis of registry data for patients undergoing EGS in Scotland, 2005-2007. Exposure of interest was ICU admission status (direct from theatre; indirect after initial care on ward; no ICU admission). The primary outcome was emergency hospital readmission within 30 days of discharge. Results:Thirty-seven thousand one hundred seventy-three patients were included in the analysis. Overall emergency readmission rate was 8% (n = 2983): 2756 (7.8%) in patients without postoperative ICU admission; 155 (12.1%) with direct ICU admission and 65 (14.7%) with indirect ICU admission. Indirect ICU admission was associated with increased hospital readmission rates (HR 1.24 [1.03, 1.49]; p = 0.024) compared with direct ICU admission. ICU admission was associated with increased three-year readmission rates (p = 0.006) and costs (p < 0.001) compared with initial ward care. Conclusion:Indirect ICU admission is associated with increased emergency hospital readmission and healthcare costs for patients undergoing EGS.
Project description:Comparisons of early discharge and outpatient postchemotherapy supportive care in pediatric acute myeloid leukemia (AML) patients are limited. We used data from the Pediatric Health Information System on a cohort of children treated for newly diagnosed AML to compare course-specific mortality and resource utilization in patients who were discharged after chemotherapy to outpatient management during neutropenia relative to patients who remained hospitalized. Patients were categorized at each course as early or standard discharge. Discharges within 3 days after chemotherapy completion were considered "early". Resource utilization was determined based on daily billing data and reported as days of use per 1000 hospital days. Inpatient mortality, occurrence of intensive care unit (ICU)-level care, and duration of hospitalization were compared using logistic, log-binomial and linear regression methods, respectively. Poisson regression with inpatient days as offset was used to compare resource use by discharge status. The study population included 996 patients contributing 2358 treatment courses. Fewer patients were discharged early following Induction I (7%) than subsequent courses (22-24%). Across courses, patients discharged early experienced high readmission rates (69-84%), yet 9-12 fewer inpatient days (all P < 0.001). Inpatient mortality was low across courses and did not differ significantly by discharge status. The overall risk for ICU-level care was 116% higher for early compared to standard discharge patients (adjusted risk ratio: 2.16, 95% confidence interval: 1.50, 3.11). Rates of antibiotic, vasopressor, and supplemental oxygen use were consistently elevated for early discharge patients. Despite similar inpatient mortality to standard discharge patients, early discharge patients may be at greater risk for life-threatening chemotherapy-related complications, including infections.
Project description:Early discharge from the intensive care unit (ICU) may constitute a strategy of resource consumption optimization; however, unplanned readmission of hospitalized patients to an ICU is associated with a worse outcome. We aimed to compare the effectiveness of the Stability and Workload Index for Transfer score (SWIFT), Sequential Organ Failure Assessment score (SOFA) and simplified Therapeutic Intervention Scoring System (TISS-28) in predicting unplanned ICU readmission or unexpected death in the first 48 hours after discharge from the ICU.We conducted a prospective cohort study in a single tertiary hospital in southern Brazil. All adult patients admitted to the ICU for more than 24 hours from January 2008 to December 2009 were evaluated. SWIFT, SOFA and TISS-28 scores were calculated on the day of discharge from the ICU. A stepwise logistic regression was conducted to evaluate the effectiveness of these scores in predicting unplanned ICU readmission or unexpected death in the first 48 hours after discharge from the ICU. Moreover, we conducted a direct accuracy comparison among SWIFT, SOFA and TISS-28 scores.A total of 1,277 patients were discharged from the ICU during the study period. The rate of unplanned ICU readmission or unexpected death in the first 48 hours after discharge from the ICU was 15% (192 patients). In the multivariate analysis, age (P = 0.001), length of ICU stay (P = 0.01), cirrhosis (P = 0.03), SWIFT (P = 0.001), SOFA (P = 0.01) and TISS-28 (P<0.001) constituted predictors of unplanned ICU readmission or unexpected death. The SWIFT, SOFA and TISS-28 scores showed similar predictive accuracy (AUC valueswere 0.66, 0.65 and 0.67, respectively; P = 0.58) [corrected].SWIFT, SOFA and TISS-28 on the day of discharge from the ICU have only moderate accuracy in predicting ICU readmission or death. The present study did not find any differences in accuracy among the three scores.
Project description:To examine risk factors for transfer of bronchiolitis patients from the ward to the intensive care unit (ICU) and/or initiation of critical care interventions.We performed a 16-center, prospective cohort study of hospitalized children age <2 years with bronchiolitis. During the winters of 2007 to 2010, researchers collected clinical data and nasopharyngeal aspirates from study participants. The primary outcome was late intensive care use, defined as a transfer to the ICU and/or use of mechanical ventilation (regardless of location) after the child's first inpatient day.Among 2104 children hospitalized with bronchiolitis, 1762 (84%) were identified as initial ward patients, comprising the analysis cohort. The median age was 4 months (interquartile range, 2-9 months), and 1048 (59%) were boys. The most frequently detected pathogens were respiratory syncytial virus (72%) and rhinovirus (25%). After the first inpatient day, 47 (3%; 95% confidence interval, 2-4) were subsequently transferred to the ICU or required mechanical ventilation. In the multivariable logistic regression model predicting subsequent transfer to the ICU or mechanical ventilation use, the significant predictors were birth weight <5 pounds (odds ratio, 2.28; 95% confidence interval, 1.30-4.02; P = .004) and respiratory rate high of ? 70 breaths/min on the first inpatient day (odds ratio, 4.64; 95% confidence interval, 2.86-7.53; P < .001).In this multicenter study of children hospitalized with bronchiolitis, low birth weight and tachypnea were significantly associated with subsequent transfer to the ICU and/or use of mechanical ventilation.
Project description:Discharge from an intensive care unit (ICU) out of hours is common. We undertook a systematic review and meta-analysis to explore the association between time of discharge and mortality/ICU readmission.We searched Medline, Embase, Web of Knowledge, CINAHL, the Cochrane Library and OpenGrey to June 2017. We included studies reporting in-hospital mortality and/or ICU readmission rates by ICU discharge "out-of-hours" and "in-hours". Inclusion was limited to patients aged???16 years discharged alive from a non-specialist ICU to a lower level of hospital care. Studies restricted to specific diseases were excluded. We assessed study quality using the Newcastle Ottowa Scale. We extracted published data, summarising using a random-effects meta-analysis.Our searches identified 1961 studies. We included unadjusted data from 1,191,178 patients from 18 cohort studies (presenting data from 1994 to 2014). "Out of hours" had multiple definitions, beginning between 16:00 and 22:00 and ending between 05:59 and 09:00. Patients discharged out of hours had higher in-hospital mortality [relative risk (95% CI) 1.39 (1.24, 1.57) p?<?0.0001] and readmission rates [1·30 (1.19, 1.42), p?<?0.001] than patients discharged in hours. Heterogeneity was high (I2 90.1% for mortality and 90.2% for readmission), resulting from differences in effect size rather than the presence of an effect.Out-of-hours discharge from an ICU is strongly associated with both in-hospital death and ICU readmission. These effects persisted across all definitions of "out of hours" and across healthcare systems in different geographical locations. Whether these increases in mortality and readmission result from patient differences, differences in care, or a combination remains unclear.
Project description:PURPOSE: The objectives of this study were to find factors related to medical intensive care unit (ICU) readmission and to develop a prediction index for determining patients who are likely to be readmitted to medical ICUs. MATERIALS AND METHODS: We performed a retrospective cohort study of 343 consecutive patients who were admitted to the medical ICU of a single medical center from January 1, 2008 to December 31, 2012. We analyzed a broad range of patients' characteristics on the day of admission, extubation, and discharge from the ICU. RESULTS: Of the 343 patients discharged from the ICU alive, 33 (9.6%) were readmitted to the ICU unexpectedly. Using logistic regression analysis, the verified factors associated with increased risk of ICU readmission were male sex [odds ratio (OR) 3.17, 95% confidence interval (CI) 1.29-8.48], history of diabetes mellitus (OR 3.03, 95% CI 1.29-7.09), application of continuous renal replacement therapy during ICU stay (OR 2.78, 95% CI 0.85-9.09), white blood cell count on the day of extubation (OR 1.13, 95% CI 1.07-1.21), and heart rate just before ICU discharge (OR 1.03, 95% CI 1.01-1.06). We established a prediction index for ICU readmission using the five verified risk factors (area under the curve, 0.76, 95% CI 0.66-0.86). CONCLUSION: By using specific risk factors associated with increased readmission to the ICU, a numerical index could be established as an estimation tool to predict the risk of ICU readmission.