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BackgroundPrevious studies of hospital readmission have focused on specific conditions or populations and generated complex prediction models.ObjectiveTo identify predictors of early hospital readmission in a diverse patient population and derive and validate a simple model for identifying patients at high readmission risk.DesignProspective observational cohort study.PatientsParticipants encompassed 10,946 patients discharged home from general medicine services at six academic medical centers and were randomly divided into derivation (n = 7,287) and validation (n = 3,659) cohorts.MeasurementsWe identified readmissions from administrative data and 30-day post-discharge telephone follow-up. Patient-level factors were grouped into four categories: sociodemographic factors, social support, health condition, and healthcare utilization. We performed logistic regression analysis to identify significant predictors of unplanned readmission within 30 days of discharge and developed a scoring system for estimating readmission risk.ResultsApproximately 17.5% of patients were readmitted in each cohort. Among patients in the derivation cohort, seven factors emerged as significant predictors of early readmission: insurance status, marital status, having a regular physician, Charlson comorbidity index, SF12 physical component score, ≥1 admission(s) within the last year, and current length of stay >2 days. A cumulative risk score of ≥25 points identified 5% of patients with a readmission risk of approximately 30% in each cohort. Model discrimination was fair with a c-statistic of 0.65 and 0.61 for the derivation and validation cohorts, respectively.ConclusionsSelect patient characteristics easily available shortly after admission can be used to identify a subset of patients at elevated risk of early readmission. This information may guide the efficient use of interventions to prevent readmission.

Burnout was strongly related to alcohol abuse/dependence among sampled medical students and increased educational debt predicted a higher risk. A multifaceted approach addressing burnout, medical education costs, and alcohol use is needed.

Physicians readily recalled multiple cases of diagnostic errors and were willing to share their experiences. Using a new taxonomy tool and aggregating cases by diagnosis and error type revealed patterns of diagnostic failures that suggested areas for improvement. Systematic solicitation and analysis of such errors can identify potential preventive strategies.

Objective The objective was to quantitatively and qualitatively examine the efficacy of DBT (e.g., decreasing life-threatening suicidal and parasuicidal acts, attrition, and depression) explicitly with borderline personality disorder (BPD) and using conservative assumptions and criteria, across treatment providers and settings. Method Five randomized controlled trials (RCTs) were identified in a systematic search that examined the efficacy of DBT in reducing suicide attempts, parasuicidal behavior, attrition during treatment, or symptoms of depression, in adult patients with BPD. Results Combining effect measures for suicide and parasuicidal behavior (five studies total) revealed a net benefit in favor of DBT (pooled Hedges’ g −0.622). DBT was only marginally better than treatment as usual (TAU) in reducing attrition during treatment in five RCTs (pooled risk difference −0.168). DBT was not significantly different from TAU in reducing depression symptoms in three RCTs (pooled Hedges’ g −0.896). Discussion DBT demonstrates efficacy in stabilizing and controlling self-destructive behavior and improving patient compliance.

Objective Several interventions promote axonal growth and functional recovery when initiated shortly after CNS injury, including blockade of myelin-derived inhibitors with soluble Nogo Receptor (NgR1, RTN4R) ‘decoy’ protein. We examined the efficacy of this intervention in the much more prevalent and refractory condition of chronic spinal cord injury. Methods We eliminated the NgR1 pathway genetically in mice by conditional gene targeting starting 8 weeks after spinal hemisection injury and monitored locomotion in the open field and by video kinematics over the ensuing 4 months. In a separate pharmacological experiment, intrathecal NgR1 decoy protein administration was initiated 3 months after spinal cord contusion injury. Locomotion and raphespinal axon growth were assessed during 3 months of treatment between 4 and 6 months after contusion injury. Results Conditional deletion of NgR1 in the chronic state results in gradual improvement of motor function accompanied by increased density of raphespinal axons in the caudal spinal cord. In chronic rat spinal contusion, NgR1 decoy treatment from 4–6 months after injury results in 29% (10 of 35) of rats recovering weight-bearing status compared to 0% (0 of 29) of control rats (P<0.05). Open field BBB locomotor scores showed a significant improvement in the NgR-treated group relative to the control group (P<0.005, repeated measures ANOVA). An increase in raphespinal axon density caudal to the injury is detected in NgR1-decoy-treated animals by immunohistology and by positron emission tomography using a serotonin reuptake ligand. Interpretation Antagonizing myelin-derived inhibitors signaling with NgR1 decoy augments recovery from chronic spinal cord injury.

BackgroundHealth information technology (HIT) systems have the potential to reduce delayed, missed or incorrect diagnoses. We describe and classify the current state of diagnostic HIT and identify future research directions.Methods A multi-pronged literature search was conducted using PubMed, Web of Science, backwards and forwards reference searches and contributions from domain experts. We included HIT systems evaluated in clinical and experimental settings as well as previous reviews, and excluded radiology computer-aided diagnosis, monitor alerts and alarms, and studies focused on disease staging and prognosis. Articles were organised within a conceptual framework of the diagnostic process and areas requiring further investigation were identified.ResultsHIT approaches, tools and algorithms were identified and organised into 10 categories related to those assisting: (1) information gathering; (2) information organisation and display; (3) differential diagnosis generation; (4) weighing of diagnoses; (5) generation of diagnostic plan; (6) access to diagnostic reference information; (7) facilitating follow-up; (8) screening for early detection in asymptomatic patients; (9) collaborative diagnosis; and (10) facilitating diagnostic feedback to clinicians. We found many studies characterising potential interventions, but relatively few evaluating the interventions in actual clinical settings and even fewer demonstrating clinical impact.ConclusionsDiagnostic HIT research is still in its early stages with few demonstrations of measurable clinical impact. Future efforts need to focus on: (1) improving methods and criteria for measurement of the diagnostic process using electronic data; (2) better usability and interfaces in electronic health records; (3) more meaningful incorporation of evidence-based diagnostic protocols within clinical workflows; and (4) systematic feedback of diagnostic performance.