Postresidency Practice Setting and Clinical Care Features According to 3 Versus 4 Years of Training in Family Medicine: A Length of Training Pilot Study.

BACKGROUND AND OBJECTIVES: Factors associated with physician practice choice include residency location, training experiences, and financial incentives. How length of training affects practice setting and clinical care features postgraduation is unknown. METHODS: In this Length of Training Pilot (LoTP) study, we surveyed 366 graduates of 3-year (3YR) and 434 graduates of 4-year (4YR) programs 1 year after completion of training between 2013 and 2021. Variables assessed included reasons for practice setting choice, practice type, location, practice and community size, specialty mix, and clinical care delivery features (eg, integrated behavioral health, risk stratified care management). We compared different length of training models using χ2 or Fisher's exact tests for categorical variables and independent samples, and t test (unequal variances) for continuous variables. RESULTS: Response rates ranged from 50% to 88% for 3YR graduates and 68% to 95% for 4YR graduates. Scope of practice was a predominant reason for graduates choosing their eventual practice, and salary was a less likely reason for those completing 4 years versus 3 years of training (scope, 72% vs 55%, P=.001; salary, 15% vs 22%, P=.028). Community size, practice size, practice type, specialty mix, and practice in a federally designated underserved site did not differ between the two groups. We found no differences in patient-centered medical home features when comparing the practices of 3YR to 4YR graduates. CONCLUSIONS: Training length did not affect practice setting or practice features for graduates of LoTP programs. Future LoTP analyses will examine how length of training affects scope of practice and clinical preparedness, which may elucidate other elements associated with practice choice.

An Exploratory Study of Rural Parents' Knowledge and Attitudes About HPV Vaccination Following a Healthcare Visit With Their Child's Primary Care Provider.

INTRODUCTION/OBJECTIVES: Annually, HPV infections result in $775 million in direct medical costs and approximately 46 000 new cases of HPV-associated cancers. Safe and highly effective vaccines have been available to prevent HPV for children/adolescents since 2006. Vaccination rates remain low, especially in rural areas. Parental attitudes and beliefs affect HPV vaccination rates. METHODS: We developed, tested, and administered a survey that asked how parents and healthcare providers interacted about the HPV vaccine following a healthcare visit with an age-eligible child, as part of a multicomponent randomized controlled trial designed to improve HPV vaccination rates in rural Oregon. The 21-item survey assessed parents' information-seeking behavior, knowledge about HPV cancer risk reduction, the HPV vaccine series, and their vaccine confidence. RESULTS: Forty-three participants (59.7%) were in the intervention group; 29 (40.3%) were controls. Over 90% of healthcare visits were illness, injury, sports physical, or well-child visits (n = 67 or 93.1%), and 6.9% of visits were vaccine-specific. No statistically significant differences were found between study groups for healthcare visits. Over half the parents reported having discussions about HPV and the HPV vaccine (54.5%) with their care providers, 31.3% had recently learned about HPV, HPV risks, and the HPV vaccine prior to the visit, 83.1% were knowledgeable about cancers associated with HPV, and 79.2% were considering vaccinating their child(ren), which did not differ between study groups. CONCLUSIONS: Knowledge about HPV-related cancers and consideration for vaccinating children was higher than expected, but not associated with the intervention tested.

Resident Visit Productivity and Attitudes About Continuity According to 3 Versus 4 Years of Training in Family Medicine: A Length of Training Study.

BACKGROUND AND OBJECTIVES: Training models in the Length of Training Pilot (LOTP) vary. How innovations in training length affect patient visits and resident perceptions of continuity is unknown. METHODS: We analyzed resident in-person patient encounters (2013-2014 through 2018-2019) for each postgraduate year (PGY) and total visits at graduation derived from the Accreditation Council for Graduate Medical Education reports for each LOTP program. We collected data on residents' perceptions of continuity from annual surveys (2015-2019). We analyzed continuous variables using independent samples t tests with unequal variance and categorical variables using χ2 tests in comparing 3-year (3YR) versus 4-year (4YR) programs. RESULTS: PGY-1 and PGY-2 residents in 4YR programs saw statistically more patients than their counterparts in 3YR programs. In PGY3, 3YR program residents had statistically higher visit volume compared to 4YR program residents. Visits conducted in PGY4 ranged from 832 to 884. The additional year of training resulted in approximately 1,000 more total patient visits. Most residents in 3YR and 4YR programs rated their continuity clinic experience as somewhat or very adequate (range 86.3% to 93.7%), which did not statistically differ according to length of training. CONCLUSIONS: Resident visits were significantly different at each PGY level when comparing 3YR and 4YR programs in the LOTP and the additional year of training resulted in about 1,000 more total visits. Resident perspectives on the adequacy of their continuity clinic experience appeared to not be affected by length of training. Future research should explore how the volume of patient visits performed in residency affects scope of practice and clinical preparedness.

Promise and Perils of Leader-Employee Check-ins in Reducing Emotional Exhaustion in Primary Care Clinics: Quasi-Experimental and Qualitative Evidence.

OBJECTIVE: To analyze the role of short (<30 minutes) and frequent (quarterly) check-ins between clinic leaders and employees in reducing emotional exhaustion. METHODS: Three interrelated studies were conducted: a 3-year repeated cross-sectional survey at 10 primary care clinics (n=505; we compared emotional exhaustion, perceived stress, and values alignment among employees of a clinic where check-ins were conducted vs 9 control clinics); interviews with leaders and employees (n=10) regarding the check-ins process and experiences; and interviews with leaders and employees (n=10) after replicating the check-ins at a new clinic. RESULTS: Outcomes were similar at baseline. After a year, emotional exhaustion was lower at the check-ins compared with control clinics (standardized mean difference, d, -0.71 [P<.05]). After 2 years, emotional exhaustion remained lower at the check-ins clinic, but this difference was not significant. The check-ins were associated with an increment in values alignment (2018 vs 2017, d=0.59 [P<.05]; 2019 vs 2017, d=0.76 [P<.05]). There were no differences for perceived job stress. Interviews indicated that work-life challenges were discussed in the check-ins. However, employees need confidentiality and to feel safe to do so. The replication suggested that the check-ins are feasible to implement even amid turbulent times. CONCLUSION: Periodic check-ins wherein leaders acknowledge and address work-life stressors might be a practical tactic to reduce emotional exhaustion in primary care clinics.

The Association Between Length of Training and Family Medicine Residents' Clinical Knowledge: A Report From the Length of Training Pilot Study.

BACKGROUND AND OBJECTIVE: The associations between training length and clinical knowledge are unknown. We compared family medicine in-training examination (ITE) scores among residents who trained in 3- versus 4-year programs and to national averages over time. METHODS: In this prospective case-control study, we compared the ITE scores of 318 consenting residents in 3-year programs to 243 who completed 4 years of training between 2013 through 2019. We obtained scores from the American Board of Family Medicine. The primary analyses involved comparing scores within each academic year according to length of training. We used multivariable linear mixed effects regression models adjusted for covariates. We performed simulation models to predict ITE scores after 4 years of training among residents who underwent only 3 years of training. RESULTS: At baseline postgraduate year-1 (PGY1), the estimated mean ITE scores were 408.5 for 4-year programs and 386.5 for 3-year programs, a 21.9 point difference (95% CI=10.1-33.8). At PGY2 and PGY3, 4-year programs scored 15.0 points higher and 15.6 points higher, respectively. When extrapolating an estimated mean ITE score for 3-year programs, 4-year programs would still score 29.4 points higher (95% CI=15.0-43.8). Our trend analysis revealed those in 4-year programs had a slightly lesser slope increase compared to 3-year programs in the first 2 years. Their drop-off in ITE scores is less steep in later years, though these differences were not statistically significant. CONCLUSIONS: While we found significantly higher absolute ITE scores in 4 versus 3-year programs, these increases in PGY2, PGY3 and PGY4 may be due to initial differences in PGY1 scores. Additional research is needed to support a decision to change the length of family medicine training.

Clinic-level differences in human papillomavirus vaccination rates among rural and urban Oregon primary care clinics.

PURPOSE: Human papillomavirus (HPV) infection contributes to vaccine-preventable malignancies. Rural populations experience lower HPV vaccination rates despite similar rates of other childhood vaccinations. Individual- and clinic-level characteristics likely contribute to this disparity, but little is known about the separate roles of each. We compared clinic-level HPV vaccination rates among rural versus urban primary care clinics, identified factors associated with HPV vaccination, and separately assessed the impact of individual- and clinic-level characteristics on rural disparities in HPV vaccination. METHODS: This cross-sectional study included 537 Oregon primary care clinics participating in the Vaccines for Children (VFC) program during 2019. Vaccination status was assessed using Oregon's ALERT Immunization Information System and included HPV vaccine ≥ 1 dose for ages 11 and 12; HPV vaccination up to date (UTD) for ages 13-17, and coadministration with tetanus, diphtheria, and acellular pertussis (Tdap). Rural versus urban clinic-level outcomes were assessed using negative binomial regression. FINDINGS: Participating clinics were 24.5% rural and 75.6% urban. Family medicine clinics comprised 71.1%; pediatrics, 16.9%; and mixed, 12.1%. Across clinics, the average proportion of patients qualifying for VFC was 43%, and non-White patients were 14.1%. The mean rate of HPV vaccine ≥1 dose was lower among rural clinics (46.9% vs 51.1%, P = .039), as was vaccination UTD (40.5% vs 49.9%, P < .001). Adjusting for differences in individual- and clinic-level characteristics, rural disparities were no longer statistically significant. CONCLUSIONS: Both individual- and clinic-level characteristics play a role in rural disparities in HPV vaccination, and modifiable clinic-level differences may be opportune targets to address these disparities.

Impact of the Affordable Care Act Medicaid Expansion on Weight Loss among Community Health Center Patients with Obesity.

Context: Obesity affects over 40% of the US population and is linked to multiple preventable health conditions which can cause premature morbidity and mortality. Weight loss of at least 5% in patients with obesity reduces their risk of comorbid conditions and leads to improvement in some conditions, such as diabetes. Patients with obesity from underserved populations are less likely to access primary and preventive care services. The Affordable Care Act (ACA) improved access to care, which may in turn improve access to obesity prevention and treatment and assist with weight loss. Objective: Assess whether the proportion of patients with a weight loss ≥5% was higher in states that expanded Medicaid relative to non-expansion states among patients with obesity receiving care in community health centers (CHCs) which provide health care to underserved patients. Study Design: Retrospective observational cohort study. Setting: Electronic health record data from the ADVANCE (Advancing Data Value Across a National Community Health Center) clinical research network, during years 2012-2017. Population Studied: Patients from 346 CHCs age 19-64 with a body mass index of ≥ 30 kg/m2 during the pre-ACA period (n=34,027). Outcome measures: Proportion of patients with weight loss >5% (WL5+) from pre- to post-ACA. Medicaid expansion status (expansion vs. non-expansion states) stratified by pattern of insurance (uninsured, continuously insured, newly insured, discontinuously insured) and race and ethnicity. Results: The proportion of patients with WL5+ for newly insured patients was greater in expansion (26%) than non-expansion states (20%) (χ2=9.75, p=0.002). Among newly insured patients, Hispanic (22%) and Black (29%) patients residing in expansion states, had larger proportion of patients with WL5+ than those in non-expansion states (20% and 18%, respectively). No differences were observed among non-Hispanic White patients (expansion 28% vs non-expansion 27%). Conclusions: The findings suggest greater improvement in weight management among patients residing in expansion states than those in non-expansion states, especially among racial and ethnic minorities receiving care in CHCs.

Affordable Care Act Medicaid expansion and access to primary-care based smoking cessation assistance among cancer survivors: an observational cohort study.

BACKGROUND: Smoking among cancer survivors can increase the risk of cancer reoccurrence, reduce treatment effectiveness and decrease quality of life. Cancer survivors without health insurance have higher rates of smoking and decreased probability of quitting smoking than cancer survivors with health insurance. This study examines the associations of the Affordable Care Act (ACA) Medicaid insurance expansion with smoking cessation assistance and quitting smoking among cancer survivors seen in community health centers (CHCs). METHODS: Using electronic health record data from 337 primary care community health centers in 12 states that expanded Medicaid eligibility and 273 CHCs in 8 states that did not expand, we identified adult cancer survivors with a smoking status indicating current smoking within 6 months prior to ACA expansion in 2014 and ≥ 1 visit with smoking status assessed within 24-months post-expansion. Using an observational cohort propensity score weighted approach and logistic generalized estimating equation regression, we compared odds of quitting smoking, having a cessation medication ordered, and having ≥6 visits within the post-expansion period among cancer survivors in Medicaid expansion versus non-expansion states. RESULTS: Cancer survivors in expansion states had higher odds of having a smoking cessation medication order (adjusted odds ratio [aOR] = 2.54, 95%CI = 1.61-4.03) and higher odds of having ≥6 office visits than those in non-expansion states (aOR = 1.82, 95%CI = 1.22-2.73). Odds of quitting smoking did not differ significantly between patients in Medicaid expansion versus non-expansion states. CONCLUSIONS: The increased odds of having a smoking cessation medication order among cancer survivors seen in Medicaid expansion states compared with those seen in non-expansion states provides evidence of the importance of health insurance coverage in accessing evidence-based tobacco treatment within CHCs. Continued research is needed to understand why, despite increased odds of having a cessation medication prescribed, odds of quitting smoking were not significantly higher among cancer survivors in Medicaid expansion states compared to non-expansion states.

Comparing ascertainment of chronic condition status with problem lists versus encounter diagnoses from electronic health records.

OBJECTIVE: To assess and compare electronic health record (EHR) documentation of chronic disease in problem lists and encounter diagnosis records among Community Health Center (CHC) patients. MATERIALS AND METHODS: We assessed patient EHR data in a large clinical research network during 2012-2019. We included CHCs who provided outpatient, older adult primary care to patients age ≥45 years, with ≥2 office visits during the study. Our study sample included 1 180 290 patients from 545 CHCs across 22 states. We used diagnosis codes from 39 Chronic Condition Warehouse algorithms to identify chronic conditions from encounter diagnoses only and compared against problem list records. We measured correspondence including agreement, kappa, prevalence index, bias index, and prevalence-adjusted bias-adjusted kappa. RESULTS: Overlap of encounter diagnosis and problem list ascertainment was 59.4% among chronic conditions identified, with 12.2% of conditions identified only in encounters and 28.4% identified only in problem lists. Rates of coidentification varied by condition from 7.1% to 84.4%. Greatest agreement was found in diabetes (84.4%), HIV (78.1%), and hypertension (74.7%). Sixteen conditions had <50% agreement, including cancers and substance use disorders. Overlap for mental health conditions ranged from 47.4% for anxiety to 59.8% for depression. DISCUSSION: Agreement between the 2 sources varied substantially. Conditions requiring regular management in primary care settings may have a higher agreement than those diagnosed and treated in specialty care. CONCLUSION: Relying on EHR encounter data to identify chronic conditions without reference to patient problem lists may under-capture conditions among CHC patients in the United States.

The Effects of Major Disruptions on Practice Participation in Facilitation During a Primary Care Quality Improvement Initiative.

BACKGROUND: Disruptions in primary care practices, like ownership change, clinician turnover, and electronic health record system implementation, can stall quality improvement (QI) efforts. However, little is known about the relationship between these disruptions and practice participation in facilitated QI. METHODS: We explore this relationship using data collected from EvidenceNOW in a mixed-methods convergent design. EvidenceNOW was a large-scale facilitation-based QI initiative in small and medium primary care practices. Data included practice surveys, facilitator time logs, site visit field notes, and interviews with facilitators and practices. Using multivariate regression, we examined associations between disruptions during interventions and practice participation in facilitation, measured by in-person facilitator hours in 987 practices. We analyzed qualitative data on 40 practices that described disruptions. Qualitative and quantitative teams iterated analyses based on each other's emergent findings. RESULTS: Many practices (51%) reported experiencing 1 or more disruptions during the 3- to 15-month interventions. Loss of clinicians (31.6%) was most prevalent. In adjusted analyses, disruptions were not significantly associated with participation in facilitation. Qualitative data revealed that practices that continued active participation were motivated, had some QI infrastructure, and found value in working with their facilitators. Facilitators enabled practice participation by doing EHR-related work for practices, adapting work for available staff, and helping address needs beyond the explicit aims of EvidenceNOW. CONCLUSIONS: Disruptions are prevalent in primary care, but practices can continue participating in QI interventions, particularly when supported by a facilitator. Facilitators may benefit from additional training in approaches for helping practices attenuate the effects of disruptions and adapting strategies to help interventions work to continue building QI capacity.

Prevalent Multimorbidity Combinations Among Middle-Aged and Older Adults Seen in Community Health Centers.

BACKGROUND: Multimorbidity (≥ 2 chronic diseases) is associated with greater disability and higher treatment burden, as well as difficulty coordinating self-management tasks for adults with complex multimorbidity patterns. Comparatively little work has focused on assessing multimorbidity patterns among patients seeking care in community health centers (CHCs). OBJECTIVE: To identify and characterize prevalent multimorbidity patterns in a multi-state network of CHCs over a 5-year period. DESIGN: A cohort study of the 2014-2019 ADVANCE multi-state CHC clinical data network. We identified the most prevalent multimorbidity combination patterns and assessed the frequency of patterns throughout a 5-year period as well as the demographic characteristics of patient panels by prevalent patterns. PARTICIPANTS: The study included data from 838,642 patients aged ≥ 45 years who were seen in 337 CHCs across 22 states between 2014 and 2019. MAIN MEASURES: Prevalent multimorbidity patterns of somatic, mental health, and mental-somatic combinations of 22 chronic diseases based on the U.S. Department of Health and Human Services Multiple Chronic Conditions framework: anxiety, arthritis, asthma, autism, cancer, cardiac arrhythmia, chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD), congestive heart failure, coronary artery disease, dementia, depression, diabetes, hepatitis, human immunodeficiency virus (HIV), hyperlipidemia, hypertension, osteoporosis, post-traumatic stress disorder (PTSD), schizophrenia, substance use disorder, and stroke. KEY RESULTS: Multimorbidity is common among middle-aged and older patients seen in CHCs: 40% have somatic, 6% have mental health, and 24% have mental-somatic multimorbidity patterns. The most frequently occurring pattern across all years is hyperlipidemia-hypertension. The three most frequent patterns are various iterations of hyperlipidemia, hypertension, and diabetes and are consistent in rank of occurrence across all years. CKD-hyperlipidemia-hypertension and anxiety-depression are both more frequent in later study years. CONCLUSIONS: CHCs are increasingly seeing more complex multimorbidity patterns over time; these most often involve mental health morbidity and advanced cardiometabolic-renal morbidity.

Characterizing acute and chronic complications among patients with diabetes mellitus in community health centers.

Context: Diabetes mellitus affects about 10% of the world's population and can lead to serious complications, which reduce life quality and expectancy. People with low income have higher risk of diabetes complications than those with high income, but data on the trends of diabetes complications in underserved populations are scarce. Community health centers (CHCs) serve millions of patients in the United States regardless of their health insurance status and are an ideal setting for assessing the rate of diabetes complications in underserved populations. Objectives: To describe diabetes-related acute and chronic complications among patients served by CHCs. Study Design: Retrospective cohort study of electronic health record data from the ADVANCE clinical research network. Population studied: Patients with diabetes between ages 19 and 64 (excluding pregnant women) and ≥1 primary care ambulatory CHC visit in 2017 (N=85,442). Outcome Measures: Rates and type of diabetes-related acute and chronic complications recorded in 2017. Results: The incidence of acute complications among patients with diabetes in 2017 was 14%. Patients experiencing acute diabetes-related complications had on average 1.8 complications (range 1-33). The most common acute complications were infections (58.3%), abnormal blood glucose or related metabolic abnormalities (20.5%), and strokes or transient neurological deficits (6.8%). Patients with acute complications were proportionally more likely to be female, non-Hispanic white, have Medicaid insurance, out-of-control diabetes, a prescription for insulin, a diagnosis of substance use disorder, and co-occurring physical or mental conditions. For chronic complications, the prevalence in 2017 was 77% among patients with diabetes. Patients experiencing chronic diabetes-related complications had on average 2.3 complications (range 1-19). The most common chronic complications were cardiovascular disease (33.9%), endocrine/metabolic symptoms (22.8%), and neurological symptoms (13.0%). Patients with chronic complications were proportionally more likely to be male, non-Hispanic black, have health insurance, obesity, substance use disorder, longer period with diabetes diagnosis, and co-occurring conditions. Conclusions: The vast majority of patients with diabetes receiving care in CHCs had chronic complications. These findings are concerning, as diabetes-related complications are associated with greater healthcare utilization and patient morbidity.

High Blood Pressure Reduction, Health Insurance Status, and Social Deprivation Index in U.S. Community Health Centers.

Introduction: Lack of health insurance is a risk factor for uncontrolled hypertension, but it is unknown whether health insurance or neighborhood-level social deprivation is associated with greater reductions in blood pressure over time. Methods: We estimated the association of health insurance and social deprivation index on blood pressure reduction over time using electronic health record data from 2012 to 2017. We included patients aged 19-64 years with an initial systolic blood pressure ≥150 mmHg or diastolic blood pressure ≥100 mmHg and ≥1 additional visit from 93 community health centers in states that expanded Medicaid in 2014. Results: We included 66,207 patients: 20.1% uninsured, 64.8% publicly insured, and 15.1% privately insured. Adjusting for patient characteristics and baseline blood pressure, systolic blood pressure/diastolic blood pressure declined over the study period by 21.3/11.2 mmHg, 22.0/11.4 mmHg, and 21.1/10.7 mmHg among uninsured, publicly insured, and privately insured individuals, respectively. There were small but significantly greater reductions in systolic blood pressure among patients with public insurance than among those who were uninsured (difference= -1.3, 95% CI= -1.6, -1.0) but none associated with social deprivation index. There were no differences in diastolic blood pressure reductions over time by insurance status or social deprivation index. Blood pressure control (systolic blood pressure <140 mmHg and diastolic blood pressure <90 mmHg) was significantly greater among publicly or commercially insured individuals than among uninsured individuals (51.7%, 51.5%, 44.6% respectively, both comparisons p<0.001), with no associations between blood pressure control and social deprivation index. Conclusions: Reductions in blood pressure were large but mostly not associated with insurance type or social deprivation index. Additional research is needed to understand the factors that lead to blood pressure reduction in community health center settings.

Changes in diabetes prescription patterns following Affordable Care Act Medicaid expansion.

INTRODUCTION: Most patients with diabetes mellitus are prescribed medications to control their blood glucose. The implementation of the Affordable Care Act (ACA) led to improved access to healthcare for patients with diabetes. However, impact of the ACA on prescribing trends by diabetes drug category is less clear. This study aims to assess if long-acting insulin and novel agents were prescribed more frequently following the ACA in states that expanded Medicaid compared with non-expansion states. RESEARCH DESIGN AND METHODS: In this analysis of a natural experiment, prescriptions reimbursed by Medicaid (US public insurance) for long-acting insulins, metformin, and novel agent medications (DPP4 inhibitors, sodium/glucose cotransporter 2 inhibitor antagonists, and glucagon-like peptide-1 receptor agonists) from 2012 to 2017 were obtained from public records. For each medication category, we performed difference-in-differences (DID) analysis modeling change in rate level from pre-ACA to post-ACA in Medicaid expansion states relative to Medicaid non-expansion states. RESULTS: Expansion and non-expansion states saw a decline in both metformin and long-acting insulin prescriptions per 100 enrollees from pre-ACA to post-ACA. These decreases were larger in non-expansion states relative to expansion states (metformin: absolute DID = +0.33, 95% CI=0.323 to 0.344) and long-acting insulin (absolute DID: +0.11; 95% CI=0.098 to 0.113). Novel agent prescriptions in expansion states (+0.08 per 100 enrollees) saw a higher absolute increase per 100 Medicaid enrollees than in non-expansion states (absolute DID= +0.08, 95% CI=0.079 to 0.086). CONCLUSIONS: There was a greater absolute increase for prescriptions of novel agents in expansion states relative to non-expansion states after accounting for number of enrollees. Reducing administrative barriers and improving the ability of providers to prescribe such newer therapies will be critical for caring for patients with diabetes-particularly in Medicaid non-expansion states.

Effectiveness of an insurance enrollment support tool on insurance rates and cancer prevention in community health centers: a quasi-experimental study.

BACKGROUND: Following the ACA, millions of people gained Medicaid insurance. Most electronic health record (EHR) tools to date provide clinical-decision support and tracking of clinical biomarkers, we developed an EHR tool to support community health center (CHC) staff in assisting patients with health insurance enrollment documents and tracking insurance application steps. The objective of this study was to test the effectiveness of the health insurance support tool in (1) assisting uninsured patients gaining insurance coverage, (2) ensuring insurance continuity for patients with Medicaid insurance (preventing coverage gaps between visits); and (3) improving receipt of cancer preventive care. METHODS: In this quasi-experimental study, twenty-three clinics received the intervention (EHR-based insurance support tool) and were matched to 23 comparison clinics. CHCs were recruited from the OCHIN network. EHR data were linked to Medicaid enrollment data. The primary outcomes were rates of uninsured and Medicaid visits. The secondary outcomes were receipt of recommended breast, cervical, and colorectal cancer screenings. A comparative interrupted time-series using Poisson generalized estimated equation (GEE) modeling was performed to evaluate the effectiveness of the EHR-based tool on the primary and secondary outcomes. RESULTS: Immediately following implementation of the enrollment tool, the uninsured visit rate decreased by 21.0% (Adjusted Rate Ratio [RR] = 0.790, 95% CI = 0.621-1.005, p = .055) while Medicaid-insured visits increased by 4.5% (ARR = 1.045, 95% CI = 1.013-1.079) in the intervention group relative to comparison group. Cervical cancer preventive ratio increased 5.0% (ARR = 1.050, 95% CI = 1.009-1.093) immediately following implementation of the enrollment tool in the intervention group relative to comparison group. Among patients with a tool use, 81% were enrolled in Medicaid 12 months after tool use. For the 19% who were never enrolled in Medicaid following tool use, most were uninsured (44%) at the time of tool use. CONCLUSIONS: A health insurance support tool embedded within the EHR can effectively support clinic staff in assisting patients in maintaining their Medicaid coverage. Such tools may also have an indirect impact on evidence-based practice interventions, such as cancer screening. TRIAL REGISTRATION: This study was retrospectively registered on February 4th, 2015 with Clinicaltrials.gov (#NCT02355262). The registry record can be found at https://www.clinicaltrials.gov/ct2/show/NCT02355262 .

Measurement of American Indian and Alaska Native Racial Identity Among Medical School Applicants, Matriculants, and Graduates, 1996-2017.

Importance: Accurate racial/ethnic identity measurement is needed to understand the effectiveness of outreach, recruitment, and programs to support American Indian and Alaska Native (AIAN) people becoming physicians. Objective: To examine how changes in race/ethnicity data collection by the American Medical College Application System are associated with trends in applicants, matriculants, and graduates self-reporting as AIAN. Design, Setting, and Participants: In this cohort study, interrupted time series regression was conducted using data from the American Medical College Application system identifying medical school applicants and graduates between January 1, 1996, and December 31, 2017, who identified as AIAN. The number of students identifying as AIAN was compared before and after the American Medical College Application System changed how it collected race/ethnicity data in 2002. Data analyses were conducted between December 2019 and May 2019. Exposures: Applicants could select only 1 racial identity from 1996 to 2001 and could select more than 1 racial identity from 2002 to 2017. Main Outcomes and Measures: Rates of AIAN groups before and after changing how race/ethnicity data were collected. Covariates were age, sex, and Medical College Admission Test scores. Results: The total number of individuals identifying as AIAN in the study was 8361; the mean (SD) number of applicants per year was 380.0 (89.9) overall: 257.3 (39.6) in 1996 to 2001, with a mean (SD) age of 26.6 (5.5) years and 830 (54.0%) male individuals, and 426.1 (50.1) in 2002 to 2017, with a mean (SD) age of 25.5 (5.6) years and 3441 (50.5%) female individuals. Before the change, there was a decrease of 5% per year (relative rate [RR] of 0.95; 95% CI, 0.91-0.98; P < .001) in the rate of AIAN applicants. In 2002, the change in data collection was associated with an immediate 78% relative increase in applicants (RR, 1.78; 95% CI, 1.55-2.06; P < .001). From 2002 to 2017 there was a 10% increase in applicants per year (RR, 1.10; 95% CI, 1.06-1.14; P < .001). For matriculants, yearly trends indicated a nonsignificant 3% decrease before the change, whereas the change was associated with an immediate 62% relative increase in matriculants (RR, 1.62; 95% CI, 1.35-1.95; P < .001), with no difference in trend after the change. For graduates, a nonsignificant yearly decrease of 2% was found in the mean number of graduates before the change, whereas the change was associated with an immediate 94% relative increase (RR, 1.94; 95% CI, 1.57-2.38; P < .001), followed by no change in trend after the modification. Conclusions and Relevance: Changing the method of race/ethnicity data collection captured more AIAN applicants, matriculants, and graduates. Yearly trends indicate concerning although nonsignificant differences after the change for AIAN graduates. These findings should inform diversity efforts.

The Affordable Care Act: Effects of Insurance on Diabetes Biomarkers.

OBJECTIVE: We sought to understand how Affordable Care Act (ACA) Medicaid expansion insurance coverage gains are associated with changes in diabetes-related biomarkers. RESEARCH DESIGN AND METHODS: This was a retrospective observational cohort study using electronic health record data from 178 community health centers (CHCs) in the ADVANCE (Accelerating Data Value Across a National Community Health Center Network) network. We assessed changes in diabetes-related biomarkers among adult patients with diabetes in 10 Medicaid expansion states (n = 25,279), comparing newly insured with continuously insured, discontinuously insured, and continuously uninsured patients pre- to post-ACA expansion. Primary outcomes included changes from 24 months pre- to 24 months post-ACA in glycosylated hemoglobin (HbA1c), systolic (SBP) and diastolic (DBP) blood pressure, and LDL cholesterol levels. RESULTS: Newly insured patients exhibited a reduction in adjusted mean HbA1c levels (8.24% [67 mmol/mol] to 8.17% [66 mmol/mol]), which was significantly different from continuously uninsured patients, whose HbA1c levels increased (8.12% [65 mmol/mol] to 8.29% [67 mmol/mol]; difference-in-differences [DID] -0.24%; P < 0.001). Newly insured patients showed greater reductions than continuously uninsured patients in adjusted mean SBP (DID -1.8 mmHg; P < 0.001), DBP (DID -1.0 mmHg; P < 0.001), and LDL (DID -3.3 mg/dL; P < 0.001). Among patients with elevated HbA1c in the 3 months prior to expansion, newly insured patients were more likely than continuously uninsured patients to have a controlled HbA1c measurement by 24 months post-ACA (hazard ratio 1.25; 95% CI 1.02-1.54]. CONCLUSIONS: Post-ACA, newly insured patients had greater improvements in diabetes-related biomarkers than continuously uninsured, discontinuously insured, or continuously insured patients. Findings suggest that health insurance gain via ACA facilitates access to appropriate diabetes care, leading to improvements in diabetes-related biomarkers.

Disparities in Biomarkers for Patients With Diabetes After the Affordable Care Act.

BACKGROUND: Racial and ethnic minorities are disproportionately affected by diabetes and at greater risk of experiencing poor diabetes-related outcomes compared with non-Hispanic whites. The Affordable Care Act (ACA) was implemented to increase health insurance coverage and reduce health disparities. OBJECTIVE: Assess changes in diabetes-associated biomarkers [hemoglobin A1c (HbA1c) and low-density lipoprotein] 24 months pre-ACA to 24 months post-ACA Medicaid expansion by race/ethnicity and insurance group. RESEARCH DESIGN: Retrospective cohort study of community health center (CHC) patients. SUBJECTS: Patients aged 19-64 with diabetes living in 1 of 10 Medicaid expansion states with ≥1 CHC visit and ≥1 HbA1c measurement in both the pre-ACA and the post-ACA time periods (N=13,342). METHODS: Linear mixed effects and Cox regression modeled outcome measures. RESULTS: Overall, 33.5% of patients were non-Hispanic white, 51.2% Hispanic, and 15.3% non-Hispanic black. Newly insured Hispanics and non-Hispanic whites post-ACA exhibited modest reductions in HbA1c levels, similar benefit was not observed among non-Hispanic black patients. The largest reduction was among newly insured Hispanics versus newly insured non-Hispanic whites (P<0.05). For the subset of patients who had uncontrolled HbA1c (HbA1c≥9%) within 3 months of the ACA Medicaid expansion, non-Hispanic black patients who were newly insured gained the highest rate of controlled HbA1c (hazard ratio=2.27; 95% confidence interval, 1.10-4.66) relative to the continuously insured group. CONCLUSIONS: The impact of the ACA Medicaid expansion on health disparities is multifaceted and may differ across racial/ethnic groups. This study highlights the importance of CHCs for the health of minority populations.