National Hospital Care Survey Demonstration Projects: Examination of Maternal Health Outcomes by Housing Assistance Status.

Objectives-Objective-This report demonstrates the use of linked National Hospital Care Survey (NHCS) and U.S. Department of Housing and Urban Development (HUD) administrative data to examine demographic characteristics and maternal health outcomes among both patients who received and did not receive housing assistance. Methods-Administrative claims data and electronic health records data from the 2016 NHCS were linked to 2015-2017 HUD administrative data using patient identifiers. HUD administrative data for Housing Choice Voucher, Public Housing, and Multifamily housing program participation were used to identify patients who received housing assistance before, during, or after their delivery hospitalization. Exploratory analyses were conducted for patients who had a delivery hospitalization in 2016 and were eligible for linkage to HUD administrative data. Demographic characteristics and maternal health outcomes were compared by housing assistance status. The linked NHCS-HUD data are unweighted and not nationally representative. Results-In the 2016 NHCS, 146,672 patients had a delivery hospitalization and were eligible for linkage to 2015-2017 HUD administrative data (95.6% had a live birth, 1.0% had a stillbirth, and 3.4% were unspecified). Among this study population, 9,559 patients (6.5%) received housing assistance from 2015 to 2017. Among those who received housing assistance, 66.5% visited large metropolitan hospitals, 71.8% were insured by Medicaid, and 3.0% experienced severe maternal morbidity. Among patients who did not receive housing assistance, 74.0% visited large metropolitan hospitals, 35.6% were insured by Medicaid, and 1.9% experienced severe maternal morbidity. Nearly two-thirds of patients who received housing assistance from 2015 to 2017 were receiving housing assistance at the time of their delivery hospitalization (63.6%). Conclusion-Although these findings are not nationally representative, this report illustrates how linked NHCS-HUD data may provide insight into maternal health outcomes of patients who received housing assistance compared with those who did not.

Validation of the Enhanced Opioid Identification and Co-occurring Disorders Algorithms.

Objectives This report documents the results of a validation study conducted to assess the reliability of two algorithms applied to the 2016 National Hospital Care Survey. One algorithm identifies opioid-involved and opioid overdose hospital encounters, and the other identifies encounters with patients that have substance use disorders and selected mental health issues. These algorithms use both medical codes and natural language processing to identify encounters. Methods To validate the algorithms, medical record abstraction was performed on a stratified sample of 900 hospital encounters from the 2016 National Hospital Care Survey. The abstractors recorded their determinations of opioid involvement, opioid overdose, substance use disorder, and mental health issues on a standard form. Abstractors' determinations were compared with algorithm output to assess the overall performance using F-score and Matthews correlation coefficient. The latter provided a secondary measure of performance. The 2016 National Hospital Care Survey data are unweighted and not nationally representative. Results Overall algorithm performance varied by topic and by metric. The opioid-involvement algorithm achieved the highest performance, performing well with an F-score of 0.95, followed by the substance use disorder algorithm (F-score of 0.79), the mental health issues algorithm (F-score of 0.68), and the opioid overdose algorithm (F-score of 0.48). Assessment by Matthews correlation coefficient indicated an overall poorer level of performance, ranging from a high of 0.57 for the mental health issues algorithm to a low of 0.33 for the opioid-involvement algorithm. The causes of false positives and false negatives likewise varied, including both overly broad code and keyword inclusions as well as incompleteness of data submitted to the National Hospital Care Survey. Conclusion The validation study illustrates which aspects of the developed algorithms performed well and which aspects should be altered or discarded in future iterations. It further emphasizes the importance of data completeness, therefore laying the groundwork for improvements to future survey analyses.

Enhancing Capacity of Community-Academic Partnerships to Achieve Health Equity: Results From the CBPR Partnership Academy.

Community-based participatory research (CBPR) is an equitable partnership approach that links academic researchers, community organizations, and public health practitioners to work together to understand and address health inequities. Although numerous educational materials on CBPR exist, few training programs develop the skills and knowledge needed to establish effective, equitable partnerships. Furthermore, there are few professional development opportunities for academic researchers, practitioners, and community members to obtain these competencies in an experiential co-learning process. In response, the Detroit Community-Academic Urban Research Center developed the CBPR Partnership Academy, an innovative, yearlong capacity-building program facilitated by experienced community and academic partners, involving an intensive short course, partnership development, grant proposal preparation and funding, mentoring, online learning forums, and networking. Three diverse cohorts (36 teams) from 18 states and 2 tribal nations have participated. We describe the rationale and components of the training program and present results from the first two cohorts. Evaluation results suggest enhanced competence and efficacy in conducting CBPR. Outcomes include partnerships established, grant proposals submitted and funded, workshops and research conducted, and findings disseminated. A community-academic partner-based, integrated, applied program can be effective for professional development and establishing innovative linkages between academics and practitioners aimed at achieving health equity.