Faculty Bibliography

The recent Ebola outbreak in West Africa was an exemplar for the need to rapidly measure population-level health-seeking behaviors, in order to understand healthcare utilization during emergency situations. Taking advantage of the high prevalence of mobile phones, we deployed a national SMS-poll and collected data about individual-level health and health-seeking behavior throughout the outbreak from 6694 individuals from March to June 2015 in Liberia. Using propensity score matching to generate balanced subsamples, we compared outcomes in our survey to those from a recent household survey (the 2013 Liberian Demographic Health Survey). We found that the matched subgroups had similar patterns of delivery location in aggregate, and utilizing data on the date of birth, we were able to show that facility-based deliveries were significantly decreased during, compared to after the outbreak (p < 0.05) consistent with findings from retrospective studies using healthcare-based data. Directly assessing behaviors from individuals via SMS also enabled the measurement of public and private sector facility utilization separately, which has been a challenge in other studies in countries including Liberia which rely mainly on government sources of data. In doing so, our data suggest that public facility-based deliveries returned to baseline values after the outbreak. Thus, we demonstrate that with the appropriate methodological approach to account for different population denominators, data sourced via mobile tools such as SMS polling could serve as an important low-cost complement to existing data collection strategies especially in situations where higher-frequency data than can be feasibly obtained through surveys is useful.

Background: Understanding the development of post-traumatic stress disorder (PTSD) is a precondition for efficient risk assessment and prevention planning. Studies to date have been site and sample specific. Towards developing generalizable models of PTSD development and prediction, the International Consortium to Predict PTSD (ICPP) compiled data from 13 longitudinal, acute-care based PTSD studies performed in six different countries. Objective: The objectives of this study were to describe the ICPP's approach to data pooling and harmonization, and present cross-study descriptive results informing the longitudinal course of PTSD after acute trauma. Methods: Item-level data from 13 longitudinal studies of adult civilian trauma survivors were collected. Constructs (e.g. PTSD, depression), measures (questions or scales), and time variables (days from trauma) were identified and harmonized, and those with inconsistent coding (e.g. education, lifetime trauma exposure) were recoded. Administered in 11 studies, the Clinician Administered PTSD Scale (CAPS) emerged as the main measure of PTSD diagnosis and severity. Results: The pooled data set included 6254 subjects (39.9% female). Studies' average retention rate was 87.0% (range 49.1-93.5%). Participants' baseline assessments took place within 2 months of trauma exposure. Follow-up durations ranged from 188 to 1110 days. Reflecting studies' inclusion criteria, the prevalence of baseline PTSD differed significantly between studies (range 3.1-61.6%), and similar differences were observed in subsequent assessments (4.3-38.2% and 3.8-27.0% for second and third assessments, respectively). Conclusion: Pooling data from independently collected studies requires careful curation of individual data sets for extracting and optimizing informative commonalities. However, it is an important step towards developing robust and generalizable prediction models for PTSD and can exceed findings of single studies. The large differences in prevalence of PTSD longitudinally cautions against using any individual study to infer trauma outcome. The multiplicity of instruments used in individual studies emphasizes the need for common data elements in future studies.

OBJECTIVES/SPECIFIC AIMS: Determine timing of risk of readmissions within 30 days among patients first discharged to a skilled nursing facilities (SNF) after heart failure hospitalization and subsequently discharged home. METHODS/STUDY POPULATION: This was a retrospective cohort study of patients with SNF stays of 30 days or less following discharge from a heart failure hospitalization. Patients were followed for 30 days following discharge from SNF. We categorized patients based on SNF length of stay (LOS): 1-6 days, 7-13 days, 14-30 days. We then fit a piecewise exponential Bayesian model with the outcome as time to readmission after discharge from SNF for each group. Our event of interest was unplanned readmission; death and planned readmissions were considered as competing risks. Our model examined 2 different time intervals following discharge from SNF: 0-3 days post SNF discharge and 4-30 days post SNF discharge. We reported the hazard rate (credible interval) of readmission for each time interval. We examined all Medicare fee-for-service (FFS) patients 65 and older admitted from July 2012 to June 2015 with a principal discharge diagnosis of HF, based on methods adopted by the Centers for Medicare and Medicaid Services (CMS) for hospital quality measurement. RESULTS/ANTICIPATED RESULTS: Our study included 67,585 HF hospitalizations discharged to SNF and subsequently discharged home [median age, 84 years (IQR; 78-89); female, 61.0%]; 13,257 (19.2%) were discharged with home care, 54,328 (80.4%) without. Median length of SNF admission was 17 days (IQR; 11-22). In total, 16,333 (24.2%) SNF discharges to home were readmitted within 30 days of SNF discharge; median time to readmission was 9 days (IQR; 3-18). The hazard rate of readmission for each group was significantly increased on days 0-3 after discharge from SNF compared with days 4-30 after discharge from SNF. In addition, the hazard rate of readmission during the first 0-3 days after discharge from SNF decreased as the LOS in SNF increased. DISCUSSION/SIGNIFICANCE OF IMPACT: The hazard rate of readmission after SNF discharge following heart failure hospitalization is highest during the first 6 days home. Length of stay at SNF also has an effect on risk of readmission immediately after discharge from SNF; patients with a longer length of stay in SNF were less likely to be readmitted in the first 3 days after discharge from SNF.

BACKGROUND:Interprofessional education is increasingly recognized as essential for health education worldwide. Although effective management, innovation, and entrepreneurship are necessary to improve health systems, business schools have been underrepresented in global health education. Central America needs more health professionals trained in health management and innovation to respond to health disparities, especially in rural communities. OBJECTIVE:This paper explores the impact of the Health Innovation Fellowship (HIF), a new training program for practicing health professionals offered jointly by the Central American Healthcare Initiative and INCAE Business School, Costa Rica. Launched in 2014, HIF's goal is to create a network of highly trained interdisciplinary health professionals in competencies to improve health of Central American communities through better health management. METHODS:The program's fellows carried out innovative healthcare projects in their local regions. The first three annual cohorts (total of 43 fellows) represented all health-related professions and sectors (private, public, and civil society) from six Central American countries. All fellows attended four 1-week, on-site modular training sessions, received ongoing mentorship, and stayed connected through formal and informal networks and webinars through which they exchange knowledge and support each other. CAHI stakeholders supported HIF financially. RESULTS:Impact evaluation of the three-year pilot training program is positive: fellows improved their health management skills and more than 50% of the projects found either financial or political support for their implementation. CONCLUSIONS:HIF's strengths include that both program leaders and trainees come from the Global South, and that HIF offers a platform to collaborate with partners in the Global North. By focusing on promoting innovation and management at a top business school in the region, HIF constitutes a novel capacity-building effort within global health education. HIF is a capacity-building effort that can be scaled up in the region and other low- and middle-income countries.

The social environment influences health outcomes for older adults and could be an important target for interventions to reduce costly medical care. We sought to understand which elements of the social environment distinguish communities that achieve lower health care utilization and costs from communities that experience higher health care utilization and costs for older adults with complex needs. We used a sequential explanatory mixed methods approach. We classified community performance based on three outcomes: rate of hospitalizations for ambulatory care sensitive conditions, all-cause risk-standardized hospital readmission rates, and Medicare spending per beneficiary. We conducted in-depth interviews with key informants (N = 245) from organizations providing health or social services. Higher performing communities were distinguished by several aspects of social environment, and these features were lacking in lower performing communities: 1) strong informal support networks; 2) partnerships between faith-based organizations and health care and social service organizations; and 3) grassroots organizing and advocacy efforts. Higher performing communities share similar social environmental features that complement the work of health care and social service organizations. Many of the supportive features and programs identified in the higher performing communities were developed locally and with limited governmental funding, providing opportunities for improvement.