Ten-Year Outcomes: Community Health Center/Academic Medicine Partnership for Rural Family Medicine Training.

BACKGROUND AND OBJECTIVES: The widening gap between urban and rural health outcomes is exacerbated by physician shortages that disproportionately affect rural communities. Rural residencies are an effective mechanism to increase physician placement in rural and medically underserved areas yet are limited in number due to funding. Community health center/academic medicine partnerships (CHAMPs) can serve as a collaborative framework for expansion of academic primary care residencies outside of traditional funding models. This report describes 10-year outcomes of a rural training pathway developed as part of a CHAMP collaboration. METHODS: Using data from internal registries and public sources, our retrospective study examined demographic and postgraduation practice characteristics for rural pathway graduates. We identified the rates of postgraduation placement in rural (Federal Office of Rural Health Policy grant-eligible) and federally designated Medically Underserved Areas/Populations (MUA/Ps). We assessed current placement for graduates >3 years from program completion. RESULTS: Over a 10-year period, 25 trainees graduated from the two residency expansion sites. Immediately postgraduation, 84% (21) were in primary care Health Professional Shortage Areas (HPSAs), 80% (20) in MUA/Ps, and 60% (15) in rural locations. Sixteen graduates were >3 years from program completion, including 69% (11) in primary care HPSAs, 69% (11) in MUA/Ps, and 50% (5) in rural locations. CONCLUSIONS: This CHAMP collaboration supported development of a rural pathway that embedded family medicine residents in community health centers and effectively increased placement in rural and MUA/Ps. This report adds to national research on rural workforce development, highlighting the role of academic-community partnerships in expanding rural residency training outside of traditional funding models.

We Must Do Better: Addressing High Mortality After Release from Incarceration.

People who are incarcerated have high rates of mental illness, substance use disorder, suicide attempts, and chronic medical conditions. Mortality rates are also significantly elevated following release. Additional work needs to be done to understand the risk factors for increased morbidity and mortality of people impacted by incarceration to better inform future interventions and system changes.

The Transitions Clinic Network: Post Incarceration Addiction Treatment, Healthcare, and Social Support (TCN-PATHS): A hybrid type-1 effectiveness trial of enhanced primary care to improve opioid use disorder treatment outcomes following release from jail.

BACKGROUND: In 2016, at least 20% of people with opioid use disorder (OUD) were involved in the criminal justice system, with the majority of individuals cycling through jails. Opioid overdose is the leading cause of death and a common cause of morbidity after release from incarceration. Medications for OUD (MOUD) are effective at reducing overdoses, but few interventions have successfully engaged and retained individuals after release from incarceration in treatment. OBJECTIVE: To assess whether follow-up care in the Transitions Clinic Network (TCN), which provides OUD treatment and enhanced primary care for people released from incarceration, improves key measures in the opioid treatment cascade after release from jail. In TCN programs, primary care teams include a community health worker with a history of incarceration, and they attend to social needs, such as housing, food insecurity, and criminal legal system contact, along with patients' medical needs. METHODS AND ANALYSIS: We will bring together six correctional systems and community health centers with TCN programs to conduct a hybrid type-1 effectiveness/implementation study among individuals who were released from jail on MOUD. We will randomize 800 individuals on MOUD released from seven local jails (Bridgeport, CT; Niantic, CT; Bronx, NY; Caguas, PR; Durham, NC; Minneapolis, MN; Ontario County, NY) to compare the effectiveness of a TCN intervention versus referral to standard primary care to improve measures within the opioid treatment cascade. We will also determine what social determinants of health are mediating any observed associations between assignment to the TCN program and opioid treatment cascade measures. Last, we will study the cost effectiveness of the approach, as well as individual, organizational, and policy-level barriers and facilitators to successfully transitioning individuals on MOUD from jail to the TCN. ETHICS AND DISSEMINATION: Investigation Review Board the University of North Carolina (IRB Study # 19-1713), the Office of Human Research Protections, and the NIDA JCOIN Data Safety Monitoring Board approved the study. We will disseminate study findings through peer-reviewed publications and academic and community presentations. We will disseminate study data through a web-based platform designed to share data with TCN PATHS participants and other TCN stakeholders. Clinical trials.gov registration: NCT04309565.

Prevalence of Chronic Health Conditions Among Adults Released From the North Carolina Prison System, 2015-2016.

BACKGROUND In the United States each year nearly 570,000 people return from state prisons to the community. Prevalence data of chronic health problems for this population are lacking, impeding planning of health care programs to serve people with chronic conditions who are re-entering the community.METHOD We used medication dispensing records as a proxy for diagnoses in assessing the prevalence of 10 major and 20 substituent health conditions among incarcerated people released from the North Carolina state prison system from July 2015 through June 2016.RESULTS Among 20,585 released people, 13% were female; 50% were black; 43% were white; and 4% were aged 55 years or older. Thirty-three percent had ≥ 1 condition and 13% had two or more. The prevalence of chronic health conditions was the following: psychiatric, 15%; cardiovascular, 15%; neurologic, 7%; pulmonary, 6%; diabetes mellitus, 3%; and infectious, 3%. Seventy-one percent of those aged 55 years or older had a chronic medical condition. Among those with a psychiatric condition, 56% had another chronic illness.LIMITATIONS We could not identify unmedicated health conditions; medications prescribed across multiple disease categories were excluded from our analysis.CONCLUSION In North Carolina, at least one in three people released from the state prison system had a chronic health condition, and among those with psychiatric conditions, most had comorbid medical disease. Coordination of health care after release from incarceration is essential to avoid preventable complications and unnecessary utilization of acute care services. Greater eligibility for Medicaid is needed to scale up transition programs for this population.

Overwhelming Need, Insufficient Health Care for Justice-involved North Carolinians.

AJ was a 34-year-old African American male who was incarcerated for eight years for drug-related convictions. He suffered from diabetes, hypertension, chronic kidney failure, depression, and substance use disorder. Upon release from prison he was not connected with health services and he was uninsured, which was an additional barrier to accessing medical care. His own perceived need for care was limited as he had significant cognitive deficits with extremely low health literacy. Two years following his release from prison, an aunt concerned about his health brought him to clinic. His clinical course was fraught with complications that would likely have been preventable if he had been connected to care upon release. With treatment, his depression eventually improved and his substance use disorder was under better control. However, he endured multiple amputations from diabetic foot infections, partial vision loss, severe pain from diabetic neuropathy, temporary dialysis for end stage kidney disease, and two months of a feeding tube for severe gastroparesis. AJ's story is not unique, and it highlights the terrible personal costs of inadequately addressing the health needs of people during periods of incarceration and following their release.

Cost of Incremental Expansion of an Existing Family Medicine Residency Program.

BACKGROUND AND OBJECTIVES: Expanding residency training programs to address shortages in the primary care workforce is challenged by the present graduate medical education (GME) environment. The Medicare funding cap on new GME positions and reductions in the Health Resources and Services Administration (HRSA) Teaching Health Center (THC) GME program require innovative solutions to support primary care residency expansion. Sparse literature exists to assist in predicting the actual cost of incremental expansion of a family medicine residency program without federal or state GME support. METHODS: In 2011 a collaboration to develop a community health center (CHC) academic medical partnership (CHAMP), was formed and created a THC as a training site for expansion of an existing family medicine residency program. The cost of expansion was a critical factor as no Federal GME funding or HRSA THC GME program support was available. Initial start-up costs were supported by a federal grant and local foundations. Careful financial analysis of the expansion has provided actual costs per resident of the incremental expansion of the residencyRESULTS: The CHAMP created a new THC and expanded the residency from eight to ten residents per year. The cost of expansion was approximately $72,000 per resident per year. CONCLUSIONS: The cost of incremental expansion of our residency program in the CHAMP model was more than 50% less than that of the recently reported cost of training in the HRSA THC GME program.

Using Natural Language Processing to Extract Abnormal Results From Cancer Screening Reports.

OBJECTIVES: Numerous studies show that follow-up of abnormal cancer screening results, such as mammography and Papanicolaou (Pap) smears, is frequently not performed in a timely manner. A contributing factor is that abnormal results may go unrecognized because they are buried in free-text documents in electronic medical records (EMRs), and, as a result, patients are lost to follow-up. By identifying abnormal results from free-text reports in EMRs and generating alerts to clinicians, natural language processing (NLP) technology has the potential for improving patient care. The goal of the current study was to evaluate the performance of NLP software for extracting abnormal results from free-text mammography and Pap smear reports stored in an EMR. METHODS: A sample of 421 and 500 free-text mammography and Pap reports, respectively, were manually reviewed by a physician, and the results were categorized for each report. We tested the performance of NLP to extract results from the reports. The 2 assessments (criterion standard versus NLP) were compared to determine the precision, recall, and accuracy of NLP. RESULTS: When NLP was compared with manual review for mammography reports, the results were as follows: precision, 98% (96%-99%); recall, 100% (98%-100%); and accuracy, 98% (96%-99%). For Pap smear reports, the precision, recall, and accuracy of NLP were all 100%. CONCLUSIONS: Our study developed NLP models that accurately extract abnormal results from mammography and Pap smear reports. Plans include using NLP technology to generate real-time alerts and reminders for providers to facilitate timely follow-up of abnormal results.