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.

Health literacy and not race was an independent predictor of end-of-life preferences after hearing a verbal description of advanced dementia. In addition, after viewing a video of a patient with advanced dementia there were no longer any differences in the distribution of preferences according to race and health literacy. These findings suggest that clinical practice and research relating to end-of-life preferences may need to focus on a patient education model incorporating the use of decision aids such as video to ensure informed decision-making.

BACKGROUND: We conducted a cluster randomized controlled trial to examine the effectiveness of computerized decision support (CDS) designed to improve hypertension care and outcomes in a racially diverse sample of primary care patients. METHODS:We randomized 2,027 adult patients receiving hypertension care in 14 primary care practices to either 18 months of their physicians receiving CDS for each hypertensive patient or to usual care without computerized support for the control group. We assessed prescribing of guideline-recommended drug therapy and levels of blood pressure control for patients in each group and examined if the effects of the intervention differed by patients' race/ethnicity using interaction terms. MEASUREMENTS AND MAIN RESULTS:Rates of blood pressure control were 42% at baseline and 46% at the outcome visit with no significant differences between groups. After adjustment for patients' demographic and clinical characteristics, number of prior visits, and levels of baseline blood pressure control, there were no differences between intervention groups in the odds of outcome blood pressure control. The use of CDS to providers significantly improved Joint National Committee ( JNC) guideline adherent medication prescribing compared to usual care (7% versus 5%, P< 0.001); the effects of the intervention remained after multivariable adjustment (odds ratio [OR] 1.39 [CI,) and the effects of the intervention did not differ by patients' race and ethnicity.CONCLUSIONS: CDS improved appropriate medication prescribing with no improvement in disparities in care and overall blood pressure control. Future work focusing on improvement of these interventions and the study of other practical interventions to reduce disparities in hypertension-related outcomes is needed. INTRODUCTIONMeasuring and improving the quality of hypertension care has become a national priority in recent years. Prior studies have demonstrated substantial problems in the quality of hypertension treatment and low rates of blood pressure control, as well as racial and socioeconomic disparities. [1][2][3][4][5][6][7][8][9][10][11][12][13][14] Hypertension is particularly burdensome among racial/ethnic minority groups 7-14 and hypertension-related cardiovascular disease has been shown to be the greatest contributor to racial differences in mortality. 12 Several reviews have emphasized the importance of designing pragmatic interventions to improve care and reduce disparities in outcomes of chronic diseases [15][16][17] ; one such intervention may be the use of computerized decision support (CDS). In a prior randomized trial, we found that CDS for diabetes and coronary artery disease care were effective for improving provider adherence with recommended processes of care. 18 Other studies have also demonstrated that computer-based reminders are effective in improving measures of process of care, but intermediate clinical outcomes, such as blood pressure control, are rarely examined and when studied are frequently not improved. [19][20][21][22][2...

IMPORTANCE Falls represent a leading cause of preventable injury in hospitals and a frequently reported serious adverse event. Hospitalization is associated with an increased risk for falls and serious injuries including hip fractures, subdural hematomas, or even death. Multifactorial strategies have been shown to reduce falls in acute care hospitals, but evidence for fall-related injury prevention in hospitals is lacking. OBJECTIVE To assess whether a fall-prevention tool kit that engages patients and families in the fallprevention process throughout hospitalization is associated with reduced falls and injurious falls. DESIGN, SETTING, AND PARTICIPANTSThis nonrandomized controlled trial using stepped wedge design was conducted between November 1, 2015, and October 31, 2018, in 14 medical units within 3 academic medical centers in Boston and New York City. All adult inpatients hospitalized in participating units were included in the analysis. INTERVENTIONS A nurse-led fall-prevention tool kit linking evidence-based preventive interventions to patient-specific fall risk factors and designed to integrate continuous patient and family engagement in the fall-prevention process. MAIN OUTCOMES AND MEASURES The primary outcome was the rate of patient falls per 1000 patient-days in targeted units during the study period. The secondary outcome was the rate of falls with injury per 1000 patient-days. RESULTS During the interrupted time series, 37 231 patients were evaluated, including 17 948 before the intervention (mean [SD] age, 60.56 [18.30] years; 9723 [54.17%] women) and 19 283 after the intervention (mean [SD] age, 60.92 [18.10] years; 10 325 [53.54%] women). There was an overall adjusted 15% reduction in falls after implementation of the fall-prevention tool kit compared with before implementation (2.92 vs 2.49 falls per 1000 patient-days [95% CI, 2.06-3.00 falls per 1000 patient-days]; adjusted rate ratio 0.85; 95% CI, 0.75-0.96; P = .01) and an adjusted 34% reduction in injurious falls (0.73 vs 0.48 injurious falls per 1000 patient-days [95% CI, 0.34-0.70 injurious falls per 1000 patient-days]; adjusted rate ratio, 0.66; 95% CI, 0.53-0.88; P = .003). CONCLUSIONS AND RELEVANCEIn this nonrandomized controlled trial, implementation of a fallprevention tool kit was associated with a significant reduction in falls and related injuries. A patientcare team partnership appears to be beneficial for prevention of falls and fall-related injuries.

We evaluated potential modulators of alert acceptance by assessing content and human factors issues, and quantified the impact of a number of specific factors which influence alert acceptance. This information may help improve clinical decision support systems design.

Background: Advance care planning is a process by which patients plan for future medical care under circumstances of impaired decision-making. Central to this process is the patient's understanding and ability to imagine future health states. Methods: A before and after oral survey was used to compare the effect of a video depiction with that of a verbal description of a patient with advanced dementia for individuals selecting level of medical care at 7 primary care clinics at 2 US medical centers. The study enrolled 120 adults, half of whom were nonwhite. Results: A total of 120 subjects completed the interview. Before watching the video, 60 (50.0%) subjects preferred comfort care, 25 (20.8%) desired life-prolonging care, 22 (18.3%) chose limited care, and 13 (10.8%) were unsure of their preferences. Subject preferences changed significantly after the video: 107 (89.2%) of the subjects chose comfort care, none desired life-prolonging care, 10

No abstract

No abstract