David Kagen

Risk Prediction Models for Hospital Readmission: A Systematic Review

CONTEXT Predicting hospital readmission risk is of great interest to identify which patients would benefit most from care transition interventions, as well as to risk-adjust readmission rates for the purposes of hospital comparison. OBJECTIVE To summarize validated readmission risk prediction models, describe their performance, and assess suitability for clinical or administrative use. DATA SOURCES AND STUDY SELECTION The databases of MEDLINE, CINAHL, and the Cochrane Library were searched from inception through March 2011, the EMBASE database was searched through August 2011, and hand searches were performed of the retrieved reference lists. Dual review was conducted to identify studies published in the English language of prediction models tested with medical patients in both derivation and validation cohorts. DATA EXTRACTION Data were extracted on the population, setting, sample size, follow-up interval, readmission rate, model discrimination and calibration, type of data used, and timing of data collection. DATA SYNTHESIS Of 7843 citations reviewed, 30 studies of 26 unique models met the inclusion criteria. The most common outcome used was 30-day readmission; only 1 model specifically addressed preventable readmissions. Fourteen models that relied on retrospective administrative data could be potentially used to risk-adjust readmission rates for hospital comparison; of these, 9 were tested in large US populations and had poor discriminative ability (c statistic range: 0.55-0.65). Seven models could potentially be used to identify high-risk patients for intervention early during a hospitalization (c statistic range: 0.56-0.72), and 5 could be used at hospital discharge (c statistic range: 0.68-0.83). Six studies compared different models in the same population and 2 of these found that functional and social variables improved model discrimination. Although most models incorporated variables for medical comorbidity and use of prior medical services, few examined variables associated with overall health and function, illness severity, or social determinants of health. CONCLUSIONS Most current readmission risk prediction models that were designed for either comparative or clinical purposes perform poorly. Although in certain settings such models may prove useful, efforts to improve their performance are needed as use becomes more widespread.

Treatment of anemia in patients with heart disease: A systematic review

BACKGROUND The benefits of anemia treatment in patients with heart disease are uncertain. PURPOSE To evaluate the benefits and harms of treatments for anemia in adults with heart disease. DATA SOURCES MEDLINE, EMBASE, and Cochrane databases; clinical trial registries; reference lists; and technical advisors. STUDY SELECTION English-language trials of blood transfusions, iron, or erythropoiesis-stimulating agents in adults with anemia and congestive heart failure or coronary heart disease and observational studies of transfusion. DATA EXTRACTION Data on study design, population characteristics, hemoglobin levels, and health outcomes were extracted. Trials were assessed for quality. DATA SYNTHESIS Low-strength evidence from 6 trials and 26 observational studies suggests that liberal transfusion protocols do not improve short-term mortality rates compared with less aggressive protocols (combined relative risk among trials, 0.94 [95% CI, 0.61 to 1.42]; I2 = 16.8%), although decreased mortality rates occurred in a small trial of patients with the acute coronary syndrome (1.8% vs. 13.0%; P = 0.032). Moderate-strength evidence from 3 trials of intravenous iron found improved short-term exercise tolerance and quality of life in patients with heart failure. Moderate- to high-strength evidence from 17 trials of erythropoiesis-stimulating agent therapy found they offered no consistent benefits, but their use may be associated with harms, such as venous thromboembolism. LIMITATIONS Few trials have examined transfusions in patients with heart disease, and observational studies are potentially confounded by indication. Data supporting iron use come mainly from 1 large trial, and long-term effects are unknown. CONCLUSION Higher transfusion thresholds do not consistently improve mortality rates, but large trials are needed. Intravenous iron may help to alleviate symptoms in patients with heart failure and iron deficiency and also warrants further study. Erythropoiesis-stimulating agents do not seem to benefit patients with mild to moderate anemia and heart disease and may be associated with serious harms. PRIMARY FUNDING SOURCE U.S. Department of Veterans Affairs.

So many options, where do we start? An overview of the care transitions literature.

BACKGROUND Health systems are faced with a large array of transitional care interventions and patient populations to whom such activities might apply. PURPOSE To summarize the health and utilization effects of transitional care interventions, and to identify common themes about intervention types, patient populations, or settings that modify these effects. DATA SOURCES PubMed and Cochrane Database of Systematic Reviews (January 1950-May 2014), reference lists, and technical advisors. STUDY SELECTION Systematic reviews of transitional care interventions that reported hospital readmission as an outcome. DATA EXTRACTION We extracted transitional care procedures, patient populations, settings, readmissions, and health outcomes. We identified commonalities and compiled a narrative synthesis of emerging themes. DATA SYNTHESIS Among 10 reviews of mixed patient populations, there was consistent evidence that enhanced discharge planning and hospital-at-home interventions reduced readmissions. Among 7 reviews in specific patient populations, transitional care interventions reduced readmission in patients with congestive heart failure and general medical populations. In general, interventions that reduced readmission addressed multiple aspects of the care transition, extended beyond hospital stay, and had the flexibility to accommodate individual patient needs. There was insufficient evidence on how caregiver involvement, transition to sites other than home, staffing, patient selection practices, or care settings modified intervention effects. CONCLUSIONS Successful interventions are comprehensive, extend beyond hospital stay, and have the flexibility to respond to individual patient needs. The strength of evidence should be considered low because of heterogeneity in the interventions studied, patient populations, clinical settings, and implementation strategies.