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Hospital Readmissions in Patients with Cirrhosis: A Systematic Review.

ABSTRACT: BACKGROUND:Hospital readmission is a significant problem for patients with complex chronic illnesses such as liver cirrhosis. PURPOSE:We aimed to describe the range of readmission risk in patients with cirrhosis and the impact of the model for end-stage liver disease (MELD) score. DATA SOURCES:We conducted a systematic review of studies identified in Ovid MEDLINE, PubMed, EMBASE, CINAHL, the Cochrane Library, Scopus, Google Scholar, and ClinicalTrials.gov from 2000 to May 2017. STUDY SELECTION:We examined studies that reported early readmissions (up to 90 days) in patients with cirrhosis. Studies were excluded if they did not examine the association between readmission and at least 1 variable or intervention. DATA EXTRACTION:Two reviewers independently extracted data on study design, setting, population, interventions, comparisons, and detailed information on readmissions. DATA SYNTHESIS:Of the 1363 records reviewed, 26 studies met the inclusion and exclusion criteria. Of these studies, 21 were retrospective, and there was significant variation in the inclusion and exclusion criteria. The pooled estimate of 30-day readmissions was 26%(95% confidence interval [CI], 22%-30%). Few studies examined readmission preventability or the relationship between readmissions and social determinants of health. Reasons for readmission were highly variable. An increased MELD score was associated with readmissions in most studies. Readmission was associated with increased mortality. CONCLUSIONS:Hospital readmissions frequently occur in patients with cirrhosis and are associated with liver disease severity. The impact of functional and social factors on readmissions is unclear.

SUBMITTER: Orman ES

PROVIDER: S-EPMC6202277 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Hospital Readmissions in Patients with Cirrhosis: A Systematic Review.

Orman Eric S ES Ghabril Marwan M Emmett Thomas W TW Chalasani Naga N

Journal of hospital medicine 20180701 7

<h4>Background</h4>Hospital readmission is a significant problem for patients with complex chronic illnesses such as liver cirrhosis.<h4>Purpose</h4>We aimed to describe the range of readmission risk in patients with cirrhosis and the impact of the model for end-stage liver disease (MELD) score.<h4>Data sources</h4>We conducted a systematic review of studies identified in Ovid MEDLINE, PubMed, EMBASE, CINAHL, the Cochrane Library, Scopus, Google Scholar, and ClinicalTrials.gov from 2000 to May 2 ...[more]

PMID: 29694458

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Project description:ObjectivesTo identify and synthesise available evidence on the impact of transitional care interventions with both predischarge and postdischarge elements on readmission rates in older medical patients.DesignA systematic review.MethodInclusion criteria were: medical patients ≥65 years or mean age in study population of ≥75 years; interventions were transitional care interventions between hospital and home with both predischarge and postdischarge components; outcome was hospital readmissions. Studies were excluded if they: included other patient groups than medical patients, included patients with only one diagnosis or patients with only psychiatric disorders. PubMed, The Cochrane Library, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Web of Science were searched from January 2008 to August 2019. Study selection at title level was undertaken by one author; the remaining selection process, data extraction and methodological quality assessment were undertaken by two authors independently. A narrative synthesis was performed, and effect sizes were estimated.ResultWe identified 1951 records and included 11 studies: five randomised trials, four non-randomised controlled trials and two pre-post cohort studies. The 11 studies represent 15 different interventions and 29 outcome results measuring readmission rates within 7-182 days after discharge. Twenty-two of the 29 outcome results showed a drop in readmission rates in the intervention groups compared with the control groups. The most significant impact was seen when interventions were of high intensity, lasted at least 1 month and targeted patients at risk. The methodological quality of the included studies was generally poor.ConclusionTransitional care interventions reduce readmission rates among older medical patients although the impact varies at different times of outcome assessment. High-quality studies examining the impact of interventions are needed, preferably complimented by a process evaluation to refine and improve future interventions.Prospero registration numberCRD42019121795.

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:ObjectiveTo describe the discrimination and calibration of clinical prediction models, identify characteristics that contribute to better predictions and investigate predictors that are associated with unplanned hospital readmissions.DesignSystematic review and meta-analysis.Data sourceMedline, EMBASE, ICTPR (for study protocols) and Web of Science (for conference proceedings) were searched up to 25 August 2020.Eligibility criteria for selecting studiesStudies were eligible if they reported on (1) hospitalised adult patients with acute heart disease; (2) a clinical presentation of prediction models with c-statistic; (3) unplanned hospital readmission within 6 months.Primary and secondary outcome measuresModel discrimination for unplanned hospital readmission within 6 months measured using concordance (c) statistics and model calibration. Meta-regression and subgroup analyses were performed to investigate predefined sources of heterogeneity. Outcome measures from models reported in multiple independent cohorts and similarly defined risk predictors were pooled.ResultsSixty studies describing 81 models were included: 43 models were newly developed, and 38 were externally validated. Included populations were mainly patients with heart failure (HF) (n=29). The average age ranged between 56.5 and 84 years. The incidence of readmission ranged from 3% to 43%. Risk of bias (RoB) was high in almost all studies. The c-statistic was <0.7 in 72 models, between 0.7 and 0.8 in 16 models and >0.8 in 5 models. The study population, data source and number of predictors were significant moderators for the discrimination. Calibration was reported for 27 models. Only the GRACE (Global Registration of Acute Coronary Events) score had adequate discrimination in independent cohorts (0.78, 95% CI 0.63 to 0.86). Eighteen predictors were pooled.ConclusionSome promising models require updating and validation before use in clinical practice. The lack of independent validation studies, high RoB and low consistency in measured predictors limit their applicability.Prospero registration numberCRD42020159839.

Project description:ImportanceReducing early (<30 days) hospital readmissions is a policy priority aimed at improving health care quality. The cumulative complexity model conceptualizes patient context. It predicts that highly supportive discharge interventions will enhance patient capacity to enact burdensome self-care and avoid readmissions.ObjectiveTo synthesize the evidence of the efficacy of interventions to reduce early hospital readmissions and identify intervention features--including their impact on treatment burden and on patients' capacity to enact postdischarge self-care--that might explain their varying effects.Data sourcesWe searched PubMed, Ovid MEDLINE, Ovid EMBASE, EBSCO CINAHL, and Scopus (1990 until April 1, 2013), contacted experts, and reviewed bibliographies.Study selectionRandomized trials that assessed the effect of interventions on all-cause or unplanned readmissions within 30 days of discharge in adult patients hospitalized for a medical or surgical cause for more than 24 hours and discharged to home.Data extraction and synthesisReviewer pairs extracted trial characteristics and used an activity-based coding strategy to characterize the interventions; fidelity was confirmed with authors. Blinded to trial outcomes, reviewers noted the extent to which interventions placed additional work on patients after discharge or supported their capacity for self-care in accordance with the cumulative complexity model.Main outcomes and measuresRelative risk of all-cause or unplanned readmission with or without out-of-hospital deaths at 30 days postdischarge.ResultsIn 42 trials, the tested interventions prevented early readmissions (pooled random-effects relative risk, 0.82 [95% CI, 0.73-0.91]; P < .001; I² = 31%), a finding that was consistent across patient subgroups. Trials published before 2002 reported interventions that were 1.6 times more effective than those tested later (interaction P = .01). In exploratory subgroup analyses, interventions with many components (interaction P = .001), involving more individuals in care delivery (interaction P = .05), and supporting patient capacity for self-care (interaction P = .04) were 1.4, 1.3, and 1.3 times more effective than other interventions, respectively. A post hoc regression model showed incremental value in providing comprehensive, postdischarge support to patients and caregivers.Conclusions and relevanceTested interventions are effective at reducing readmissions, but more effective interventions are complex and support patient capacity for self-care. Interventions tested more recently are less effective.

Dataset Information

Hospital Readmissions in Patients with Cirrhosis: A Systematic Review.

Publications

Hospital Readmissions in Patients with Cirrhosis: A Systematic Review.

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