Publications

BACKGROUND

Hospitals are subject to federal financial penalties for excessive 30-day hospital readmissions for acute myocardial infarction (AMI). Prospectively identifying patients hospitalized with AMI at high risk for readmission could help prevent 30-day readmissions by enabling targeted interventions. However, the performance of AMI-specific readmission risk prediction models is unknown.

METHODS AND RESULTS

We systematically searched the published literature through March 2017 for studies of risk prediction models for 30-day hospital readmission among adults with AMI. We identified 11 studies of 18 unique risk prediction models across diverse settings primarily in the United States, of which 16 models were specific to AMI. The median overall observed all-cause 30-day readmission rate across studies was 16.3% (range, 10.6%-21.0%). Six models were based on administrative data; 4 on electronic health record data; 3 on clinical hospital data; and 5 on cardiac registry data. Models included 7 to 37 predictors, of which demographics, comorbidities, and utilization metrics were the most frequently included domains. Most models, including the Centers for Medicare and Medicaid Services AMI administrative model, had modest discrimination (median C statistic, 0.65; range, 0.53-0.79). Of the 16 reported AMI-specific models, only 8 models were assessed in a validation cohort, limiting generalizability. Observed risk-stratified readmission rates ranged from 3.0% among the lowest-risk individuals to 43.0% among the highest-risk individuals, suggesting good risk stratification across all models.

CONCLUSIONS

Current AMI-specific readmission risk prediction models have modest predictive ability and uncertain generalizability given methodological limitations. No existing models provide actionable information in real time to enable early identification and risk-stratification of patients with AMI before hospital discharge, a functionality needed to optimize the potential effectiveness of readmission reduction interventions.

Men who have sex with men and transgender women are hard-to-reach populations for research. Social media-based tools may overcome certain barriers in accessing these groups and are being tested in an ongoing study exploring HIV home-test kit use to reduce risk behavior. We analyzed pre-screening responses about how volunteers learned about the study (n = 896) and demographic data from eligible participants who came for an initial study visit (n = 216) to determine the strengths and weaknesses of recruitment strategies. Social media-based strategies resulted in the highest number of individuals screened (n = 444, 26% eligible). Dating sites/apps reached large numbers of eligible participants. White-Hispanics and African-Americans were more likely to be recruited through personal contacts; community events successfully reached Hispanic volunteers. Incorporating recruitment queries into pre-screening forms can help modify recruitment strategies for greater efficacy and efficiency. Findings suggest that recruitment strategies need to be tailored to reach specific target populations.

PURPOSE

Primary care physicians (PCP) experience high rates of professional burnout. These symptoms may be magnified in underserved populations. This study explores relationships between clinic capacity to address patients' social needs (SN) and PCP burnout.

METHODS

We conducted a cross-sectional survey of PCPs from three delivery systems in San Francisco. Surveys included three components of burnout, measured by the Maslach Burnout Inventory (MBI) and a four-item instrument exploring attitudes, confidence, individual skills and organizational capacity to address patients' SN.

RESULTS

Provider perception of higher clinic capacity to address patients' SN was the strongest independent predictor of lower burnout. Providers who perceived high clinic capacity and resources to address SN reported significantly greater professional efficacy (p <.01), lower emotional exhaustion (p <.05), and lower cynicism (p <.05).

CONCLUSIONS

Provider perceptions of greater clinic capacity to address SN are significantly associated with lower burnout. Devoting organizational resources to address SN may reduce PCP burnout.

Understanding how HIV is acquired can inform interventions to prevent infection. We constructed a risk profile of 10-24 year olds participating in the 2012 Kenya AIDS Indicator Survey and classified them as perinatally infected if their biological mother was infected with HIV or had died, or if their father was infected with HIV or had died (for those lacking mother's data). The remaining were classified as sexually infected if they had sex, and the remaining as parenterally infected if they had a blood transfusion. Overall, 84 (1.6%) of the 5298 10-24 year olds tested HIV positive; 9 (11%) were aged 10-14 and 75 (89%) 15-24 years. Five (56%) 10-14 year olds met criteria for perinatal infection; 4 (44%) did not meet perinatal, sexual or parenteral transmission criteria and parental HIV status was not established. Of the 75 HIV-infected, 15 to 24 year olds, 5 (7%) met perinatal transmission, 63 (84%) sexual and 2 (3%) parenteral criteria; 5 (7%) were unclassified. Perinatal transmission likely accounted for 56% and sexual transmission for 84% of infections among 10-14 year olds and 15-24 year olds, respectively. Although our definitions may have introduced some uncertainty, and with the number of infected participants being small, our findings suggest that mixed modes of HIV transmission exist among adolescents and young people.