Utilization, quality, and spending for pediatric Medicaid enrollees with primary care in health centers vs non-health centers.

BACKGROUND: Limited research has explored the performance of health centers (HCs) compared to other primary care settings among children in the United States. We evaluated utilization, quality, and expenditures for pediatric Medicaid enrollees receiving care in HCs versus non-HCs. METHODS: This national cross-sectional study utilized 2012 Medicaid Analytic eXtract (MAX) claims to examine children 0-17 years with a primary care visit, stratified by whether majority (> 50%) of primary care visits were at HCs or non-HCs. Outcome measures include utilization (primary care visits, non-primary care outpatient visits, prescription claims, Emergency Department (ED) visits, hospitalizations) and quality (well-child visits, avoidable ED visits, avoidable hospitalizations). For children enrolled in fee-for-service Medicaid, we also measured expenditures. Propensity score-based overlap weighting was used to balance covariates. RESULTS: A total of 2,383,270 Medicaid-enrolled children received the majority of their primary care at HCs, while 18,540,743 did at non-HCs. In adjusted analyses, HC patients had 20% more primary care visits, 15% less non-primary care outpatient visits, and 21% less prescription claims than non-HC patients. ED visits were similar across the two groups, while HC patients had 7% lower chance of hospitalization than non-HC. Quality of care outcomes favored HC patients in main analyses, but results were less robust when excluding managed care beneficiaries. Total expenditures among the fee-for-service subpopulation were lower by $239 (8%) for HC patients. CONCLUSIONS: In this study of nationwide claims data to evaluate healthcare utilization, quality, and spending among Medicaid-enrolled children who receive primary care at HCs versus non-HCs, findings suggest primary care delivery in HCs may be associated with a more cost-effective model of healthcare for children.

Differences in Health Care Utilization of High-Need and High-Cost Patients of Federally Funded Health Centers Versus Other Primary Care Providers.

BACKGROUND: Primary care providers (PCP) differ in their ability to address the needs and reduce use of costly services among complex Medicaid beneficiaries. Among PCPs, Health Resources and Services Administration (HRSA)-funded health centers (HCs) are shown to provide high-value care. OBJECTIVE: We compared health care utilization of complex Medicaid managed care beneficiaries whose PCPs were HCs versus 3 other groups. RESEARCH DESIGN: Cross-sectional study using propensity score matching comparing health care use by provider type, controlling for demographics, health status, and other covariates. SUBJECTS: California Medicaid administrative data for complex adult managed care beneficiaries with at least 1 primary care visit in 2018. MEASURES: Primary and specialty care evaluation & management visits and services; emergency department (ED) visits; and hospitalizations. PCPs included HCs, clinics not funded by HRSA, solo, and group practice providers. RESULTS: HRSA-funded HCs had lower predicted rates of specialty evaluation & management and other services than all others; lower predicted probability of any ED visits than clinics not funded by HRSA [54% (95% CI: 53%-55%) vs. 56% (95% CI: 55%-57%)] and group practice providers [51% (95% CI: 51%-52%) vs. 52% (95% CI: 52%-53%)]; and lower PP of any hospitalizations than solo [20% (95% CI: 19%-20%) vs. 23% (95% CI: 22%-24%)] and group practice providers [21% (95% CI: 20%-21%) vs. 24% (95% CI: 23%-24%)]. CONCLUSIONS: Differences in HC care delivery and practices were associated with lower use of specialty, ED, and hospitalization visits compared with other PCPs for complex Medicaid managed care beneficiaries. Understanding the underlying reasons for these utilization differences may promote better outcomes among these patients.

Health centres and social determinants of health: an analysis of enabling services provision and clinical quality.

OBJECTIVE: It is well known that social determinants of health (SDOH), including poverty, education, transportation and housing, are important predictors of health outcomes. Health Resources and Services Administration (HRSA)-funded health centres serve a patient population with high vulnerability to barriers posed by SDOH and are required to provide services that enable health centre service utilisation and assist patients in navigating barriers to care. This study explores whether health centres with higher percentages of patients using these enabling services experience better clinical performance and outcomes. DESIGN AND SETTING: The analysis uses organisational characteristics, patient demographics and clinical quality measures from HRSA's 2018 Uniform Data System. Health centres (n=875) were sorted into quartiles with quartile 1 (Q1) representing the lowest utilisation of enabling services and quartile 4 (Q4) representing the highest. The researchers calculated a service area social deprivation score weighted by the number of patients for each health centre and used ordinary least squares to create adjusted values for each of the clinical quality process and outcome measures. Analysis of variance was used to test differences across enabling services quartiles. RESULTS: After adjusting for patient characteristics, health centre size and social deprivation, authors found statistically significant differences for all clinical quality process measures across enabling services quartiles, with Q4 health centres performing significantly better than Q1 health centres for several clinical process measures. However, these Q4 health centres performed poorer in outcome measures, including blood pressure and haemoglobin A1c control. CONCLUSION: These findings emphasise the importance of how enabling services (eg, translation services, transportation) can address unmet social needs, improve utilisation of health services and reaffirm the challenges inherent in overcoming SDOH to improve health outcomes.

Weight management practices of health center providers in the United States.

BACKGROUND: We examined weight management counseling practices of Health Resources and Services Administration-funded health center (HC) providers for patients with overweight (POW) and obesity (POB) status, focusing on weight-related conditions, risk factors, and health care utilization. METHOD: We used a nationally representative cross-sectional survey of HC patients and multilevel generalized structural equation logistic regression models to assess the association of provider counseling practices for POW and POB and by three obesity classes. Dependent variables included being told by the HC provider that weight was a problem, receiving a diet or exercise recommendation, referral to a nutritionist, or receiving weight loss prescriptions. Independent variables included weight-related conditions such as diabetes and hypertension, risk factors such as smoking, and health service utilization such as five or more primary care visits. RESULTS: All POB classes had higher odds of receiving all five counseling interventions than POW. Patients with diabetes and high cholesterol had higher odds of diet recommendations (OR = 1.8) and nutritionist referrals (OR = 2.3), while patients with cardiovascular disease had higher odds of nutritionist referral (OR = 2.0) and receiving weight loss prescriptions (OR = 2.6). Respondents with POB class III and diabetes had higher odds of receiving exercise recommendations (OR = 3.4), while POB class 1 and had hypertension had lower odds of nutritionist referral (OR = 0.3). CONCLUSIONS: Variations in HC primary care providers' weight management counseling practices between POW and POB present missed opportunities for consistent practice and early intervention. Assessing providers' counseling practices for patients with comorbid conditions is essential to the successful management of the obesity crisis.

Factors associated with frequent emergency department visits among health centre patients receiving primary care.

RATIONALE, AIMS AND OBJECTIVES: We sought to examine specific care-seeking behaviours and experiences, access indicators, and patient care management approaches associated with frequency of emergency department (ED) visits among patients of Health Resources and Services Administration-funded health centres that provide comprehensive primary care to low-income and uninsured patients. METHOD: We used cross-sectional data of a most recent nationally representative sample of health centre adult patients aged 18-64 (n = 4577) conducted between October 2014 and April 2015. These data were merged with the 2014 Uniform Data System to incorporate health centre characteristics. We measured care-seeking behaviours by whether the patient called the health centre afterhours, for an urgent appointment, or talked to a provider about a concern. Access to care indicators included health centre continuity of care and receipt of transportation or translation services. We included receipt of care coordination and specialist referral as care management indicators. We used a multilevel multinomial logistic regression model to identify the association of independent variables with number of ED visits (4 or more visits, 2-3 visits, 1 visit, vs. 0 visits), controlling for predisposing, enabling, and need characteristics. RESULTS: Calling the health centre after-hours (OR = 2.41) or for urgent care (OR = 2.53), and being referred to specialists (OR = 2.36) were associated with higher odds of four or more ED visits versus none. Three or more years of continuity with the health centre (OR = 0.32) was also associated with lower odds of four or more ED visits versus none. CONCLUSIONS: Findings underscore opportunities to reduce higher frequency of ED visits in health centres, which are primary care providers to many low-income populations. Our findings highlight the potential importance of improving patient retention, better access to providers afterhours or for urgent visits, and access to specialist as areas of care in need of improvement.

Ensuring Equitable Care in Diabetes Management Among Patients of Health Resources & Services Administration-Funded Health Centers in the United States.

Aim: To explore whether there are racial/ethnic differences in diabetes management and outcomes among adult health center (HC) patients with type 2 diabetes. Methods: We analyzed data from the 2014 Health Center Patient Survey, a national sample of HC patients. We examined indicators of diabetes monitoring (A1C testing, annual foot/eye doctor visits, and cholesterol checks) and care management (specialist referrals, individual treatment plan, and receipt of calls/appointments/home visits). We also examined diabetes-specific outcomes (blood glucose levels, diabetes-related emergency department [ED] visits/hospitalizations, and diabetes self-management confidence) and general outcomes (number of doctor visits, ED visits, and hospitalizations). We used multilevel logistic regression models to examine racial/ethnic disparities by the above indicators. Results: We found racial/ethnic parity in A1C testing, eye doctor visits, and diabetes-specific outcomes. However, Hispanics/Latinos (odds ratio [OR] 0.26), non-Hispanic African Americans (OR 0.25), and Asians (OR 0.11) were less likely to receive a cholesterol check than Whites. Non-Hispanic African Americans (OR 0.43) were less likely to have frequent doctor visits, while Hispanic/Latino patients (OR 0.45) were less likely to receive an individual treatment plan. Conclusion: HCs largely provide equitable diabetes care but have room for improvement in some indicators. Tailored efforts such as culturally competent care and health education for some racial/ethnic groups may be needed to improve diabetes management and outcomes.

Staffing transformation following Patient-Centered Medical Home recognition among Health Resources & Services Administration-funded health centers.

INTRODUCTION: Patient-Centered Medical Home (PCMH) recognition is designed to promote whole-person team-based and integrated care. PURPOSE: Our goal was to assess changes in staffing infrastructure that promoted team-based and integrated care delivery before and after PCMH recognition in Health Resources & Services Administration (HRSA)-funded health centers (HCs). METHODOLOGY/APPROACH: We identified changes in staffing 2 years before and 3 years after PCMH recognition using 2010-2019 Uniform Data System data among three cohorts of HCs that received PCMH recognition in 2013 ( n = 346), 2014 ( n = 207), and 2015 ( n = 115). Our outcomes were team-based ratio (full-time equivalent medical and nonmedical providers and staff to one primary care physician) and a multidisciplinary staff ratio (allied medical and nonmedical staff to 1,000 patients). We used mixed-effects Poisson regression models. RESULTS: The earlier cohorts served fewer complex patients and were larger before PCMH recognition. Three years following recognition, the 2013 and 2014 cohorts had significantly larger team-based ratios, and all three cohorts had significantly larger multidisciplinary staff ratios. Cohorts varied, however, in the type of staff that drove this change. Both ratios increased in the longer term. CONCLUSION: Our study suggests that growth in team-based and multidisciplinary staff ratios in each cohort may have been due to a combination of HCs' perceptions of need for specific services, HRSA funding, and technical assistance opportunities. POLICY IMPLICATIONS: Further research is needed to understand barriers such as costs of employing a multidisciplinary staff, particularly those that cannot directly bill for services as well as whether such changes lead to practice transformation and improved quality of care.

A Systematic Literature Review of Health Center Efforts to Address Social Determinants of Health.

Health centers (HCs) play a crucial and integral role in addressing social determinants of health (SDOH) among vulnerable and underserved populations, yet data on SDOH assessment and subsequent actions is limited. We conducted a systematic review to understand the existing evidence of integration of SDOH into HC primary-care practices. Database searches yielded 3,516 studies, of which 41 articles met the inclusion criteria. A majority of studies showed that HCs primarily captured patient-level rather than community-level SDOH data. Studies also showed that HCs utilized SDOH in electronic health records but capabilities varied widely. A few studies indicated that HCs measured health-related outcomes of integrating SDOH data. The review highlighted that many knowledge gaps exist in the collection, use, and assessment of impact of these data on outcomes, and future research is needed to address this knowledge gap.

Health Centers and Value-Based Payment: A Framework for Health Center Payment Reform and Early Experiences in Medicaid Value-Based Payment in Seven States.

Policy Points As essential access points to primary care for almost 29 million US patients, of whom 47% are Medicaid enrollees, health centers are positioned to implement the population health management necessary in value-based payment (VBP) contracts. Primary care payment reform requires multiple payment methodologies used together to provide flexibility to care providers, encourage investments in infrastructure and new services, and offer incentives for achieving better health outcomes. State policy and significant financial incentives from Medicaid agencies and Medicaid managed care plans will likely be required to increase health center participation in VBP, which is consistent with broader state efforts to expand investment in primary care. CONTEXT: Efforts are ongoing to advance value-based payment (VBP), and health centers serve as essential access points to comprehensive primary care services for almost 29 million people in the United States. Therefore, it is important to assess the levels of health center participation in VBP, types of VBP contracts, characteristics of health centers participating in VBP, and variations in state policy environments that influence VBP participation. METHODS: This mixed methods study combined qualitative research on state policy environments and health center participation in VBP with quantitative analysis of Uniform Data System and health center financial data in seven vanguard states: Oregon, Washington, California, Colorado, New York, Hawaii, and Kentucky. VBP contracts were classified into three layers: base payments being transformed from visit-based to population-based (Layer 1), infrastructure and care coordination payments (Layer 2), and performance incentive payments (Layer 3). FINDINGS: Health centers in all seven states participated in Layer 2 and Layer 3 VBP, with VBP participation growing from 35% to 58% of all health centers in these states from 2013 to 2017. Among participating health centers, the average percentage of Medicaid revenue received as Layer 2 and Layer 3 VBP rose from 6.4% in 2013 to 9.1% in 2017. Oregon and Washington health centers participating in Layer 1 payment reforms received most of their Medicaid revenue in VBP. In 2017, VBP participation was associated with larger health center size in four states (P <.05), and higher average number of days cash on hand (P <.05) in three states. CONCLUSIONS: A multilayer payment model is useful for implementing and monitoring VBP adoption among health centers. State policy, financial incentives from Medicaid agencies and Medicaid managed plans, and health center-Medicaid collaboration under strong primary care association and health center leadership will likely be required to increase health center participation in VBP.

The Relative Contribution of Social Determinants of Health Among Health Resources and Services Administration-Funded Health Centers.

Frameworks for identifying and assessing social determinants of health (SDOH) are effective for developing long-term societal policies to promote health and well-being, but may be less applicable in clinical settings. The authors compared the relative contribution of a specific set of SDOH indicators with several measures of health status among patients served by health centers (HCs). The 2014 Health Center Patient Survey was used to identify a sample of HC patient adults 18 years and older that reported the HC as their usual source of care (n = 5024). The authors examined the relationship between SDOH indicators organized in categories (health behaviors, access and utilization, social factors, economic factors, quality of care, physical environment) with health status measures (fair or poor health, diabetes, hypertension, cardiovascular disease, depression, or anxiety) using logistic regressions and predicted probabilities. Findings indicated that access to care and utilization indicators had the greatest relative contribution to all health status measures, but the relative contribution of other SDOH indicators varied. For example, access indicators had the highest predicted probability in the model with fair or poor health as the dependent variable (72.4%) and the model with hypertension as the dependent variable (47.4%). However, the second highest predicted probability was for social indicators (54.1%) in the former model and physical environment (44.7%) indicators in the latter model. These findings have implications for HCs that serve as the primary point of access to medical care in underserved communities and to mitigate SDOH particularly for patients with diabetes, depression, or anxiety.

Early experience of the quality improvement award program in federally funded health centers.

OBJECTIVES: To describe the Health Resources and Services Administration's Quality Improvement Award (QIA) program, award patterns, and early lessons learned. STUDY SETTING: 1413 health centers were eligible for QIA from 2014 to 2018. STUDY DESIGN: We assessed cumulative QIA funding earned and modified funding excluding payments for per-patient bonuses, electronic health record (EHR) use, patient-centered medical home (PCMH) accreditation, and health information technology. We compared health centers on rural/urban location, PCMH accreditation, EHR reporting, and size. DATA COLLECTION: Organizational and quality measures are reported in the Uniform Data System, QIA program data. PRINCIPAL FINDINGS: Average cumulative funding was higher for health centers that were not rural (USD 380,387 [± USD 233,467] vs. USD 303,526 [± USD 164,272]), had PCMH accreditation (USD 401,675 [± USD 218,246] vs. USD 250,784 [± USD 144,404]), used their EHR for quality reporting (USD 374,214 (± USD 222,866) vs. USD 331,150 (± USD 198,689)), and were large (USD 435,473 (± USD 238,193) vs. USD 270,681 (± USD 114,484) an USD 231,917 (± USD 97,847) for small and medium centers, respectively). There were similar patterns, with smaller differences, for average modified payments. CONCLUSIONS: QIA is an important feasible initiative to introduce value-based payment principles to health centers. Early lessons for program design include announcing award criteria in advance and focusing on a smaller number of priority targets.

Factors associated with federally qualified health center financial performance.

OBJECTIVES: To understand factors associated with federally qualified health center (FQHC) financial performance. STUDY DESIGN: We used multivariate linear regression to identify correlates of health center financial performance. We examined six measures of health center financial performance across four domains: margin (operating margin), liquidity (days cash on hand [DCOH], current ratio), solvency (debt-to-equity ratio), and others (net patient accounts receivable days, personnel-related expenses). We examined potential correlates of financial performance, including characteristics of the patient population, health center organization, and location/geography. DATA SOURCES: We use 2012-2017 Uniform Data System (UDS) files, financial audit data from Capital link, and publicly available data. DATA COLLECTION/EXTRACTION METHODS: We focused on health centers in the 50 US states and District of Columbia, which reported information to UDS for at least 1 year between 2012 and 2017 and had Capital link financial audit data. PRINCIPAL FINDINGS: FQHC financial performance generally improved over the study period, especially from 2015 to 2017. In multivariate regression models, a higher percentage of Medicaid patients was associated with better margins (operating margin: 0.06, p < 0.001), liquidity (DCOH: 0.67, p < 0.001; current ratio: 0.28, p = 0.001), and solvency (debt-to equity ratio: -0.08, p = 0.004). Moreover, a staffing mix comprised of more nonphysician providers was associated with better margin (operating margin: 0.21, p = 0.001) and liquidity (current ratio: 1.12, p < 0.001) measures. Patient-centered medical home (PCMH) recognition was also associated with better liquidity (DCOH: 19.01, p < 0.001; current ratio: 4.68, p = 0.014) and solvency (debt-to-equity ratio: -2.03, p < 0.001). CONCLUSIONS: The financial health of FQHCs improved with provisions of the Affordable Care Act, which included significant Medicaid expansion and direct funding support for health centers. FQHC financial health was also associated with key staffing and operating characteristics of health centers. Maintaining the financial health of FQHCs is critical to their ability to continuously provide affordable and high-quality care in medically underserved areas.

Disparities in smoking prevalence and associations with mental health and substance use disorders in underserved communities across the United States.

BACKGROUND: Smoking contributes to the top 3 deadliest cancers, cancers of the lung, colon, and pancreas, which account for nearly 40% of all cancer-related deaths in the United States. Despite historicly low smoking rates, substantial disparities remain among people with mental health conditions and substance use disorders (SUDs). METHODS: The study examined the prevalence of smoking among adults from underserved communities who are served at federally qualified health centers through an analysis of the 2014 Health Center Patient Survey. Furthermore, the study assessed associations of smoking with co-occurring mental health conditions and SUDs among adult smokers (n = 1735). RESULTS: The prevalence of smoking among health center patients was 28.1%. Among current smokers, 59.1% had depression and 45.4% had generalized anxiety. Non-Hispanic Black smokers had more than 2 times the odds of reporting SUDs (adjusted odds ratio [aOR], 2.13; 95% confidence interval [CI], 1.06-4.30). Individuals at or below 100% of the federal poverty level had more than 2 times the odds of having mental health conditions (aOR, 2.55; 95% CI, 1.58-4.11), and those who were unemployed had more than 3 times the odds for SUDs (aOR, 3.21; 95% CI, 1.27-8.10). CONCLUSIONS: The prevalence of smoking in underserved communities is nearly double the national prevalence. In addition, the study underscores important socioeconomic determinants of health in smoking cessation behavior and the marked disparities among individuals with mental health conditions and SUDs. Finally, the findings illuminate the unique need for tailored treatments supporting cancer prevention care to address challenges confronted by vulnerable populations.

Trends in access to care among rural patients served at HRSA-funded health centers.

PURPOSE: Nearly one-fifth of Americans live in rural areas and experience multiple socioeconomic and health disparities. Health Resources and Services Administration (HRSA)-funded health centers (HCs) provide comprehensive primary care in rural communities. However, no prior research has examined trends in access to care in rural HC patients. We examined the change in access to care among patients served at rural HRSA-funded HCs in the United States between 2009 and 2014. METHODS: We compared patients by year to examine measures of access using multilevel generalized structural equation logistic regression models with random effects. We used the 2009 and 2014 cross-sectional Health Center Patient Surveys and identified 2,625 adult rural HC patients. Dependent variables were subjective (unmet need/delay in medical care, mental health, dental care, and prescription medications) and objective measures (preventive care and other health care utilization) in access to care. Our independent variable of interest was time, comparing access in 2009 and 2014. RESULTS: Rural HC patients reported higher predicted probability of influenza vaccine receipt (37% vs 51%), and lower unmet (25% vs 14%) and delayed medical care (36% vs 18%) between 2009 and 2014. Any emergency department visits in the last year increased (32% vs 46%) and mammogram (70% vs 55%) and Pap test (83% vs 72%) screening rates decreased. CONCLUSIONS: Observed increases in access to care among rural HC patients are positive developments but the challenges to access care still persist. Remote services, such as telehealth, could be cost-effective means of improving access to care among rural patients with limited provider supply.

Exploring the association of social determinants of health and clinical quality measures and performance in HRSA-funded health centres.

OBJECTIVE: This paper explores the impact of service area-level social deprivation on health centre clinical quality measures. DESIGN: Cross-sectional data analysis of Health Resources and Services Administration (HRSA)-funded health centres. We created a weighted service area social deprivation score for HRSA-funded health centres as a proxy measure for social determinants of health, and then explored adjusted and unadjusted clinical quality measures by weighted service area Social Deprivation Index quartiles for health centres. SETTINGS: HRSA-funded health centres in the USA. PARTICIPANTS: Our analysis included a subset of 1161 HRSA-funded health centres serving more than 22 million mostly low-income patients across the country. RESULTS: Higher levels of social deprivation are associated with statistically significant poorer outcomes for all clinical quality outcome measures (both unadjusted and adjusted), including rates of blood pressure control, uncontrolled diabetes and low birth weight. The adjusted and unadjusted results are mixed for clinical quality process measures as higher levels of social deprivation are associated with better quality for some measures including cervical cancer screening and child immunisation status but worse quality for other such as colorectal cancer screening and early entry into prenatal care. CONCLUSIONS: This research highlights the importance of incorporating community characteristics when evaluating clinical outcomes. We also present an innovative method for capturing health centre service area-level social deprivation and exploring its relationship to health centre clinical quality measures.

Mental Health Staffing at HRSA-Funded Health Centers May Improve Access to Care.

OBJECTIVE: The study objective was to examine the association between mental health staffing at health centers funded by the Health Resources and Services Administration (HRSA) and patients' receipt of mental health treatment. METHODS: Data were from the 2014 HRSA-funded Health Center Patient Survey and the 2013 Uniform Data System. Colocation of any mental health staff, including psychiatrists, psychologists, and other licensed staff, was examined. The outcomes of interest were whether a patient received any mental treatment and received any such treatment on site (at the health center). Analyses were conducted with multilevel generalized structural equation logistic regression models for 4,575 patients ages 18-64. RESULTS: Patients attending health centers with at least one mental health full-time equivalent (FTE) per 2,000 patients had a higher predicted probability of receiving mental health treatment (32%) compared with those attending centers with fewer than one such FTE (24%) or no such staffing (22%). Among patients who received this treatment, those at health centers with no staffing had a significantly lower predicted probability of receiving such treatment on site (28%), compared with patients at health centers with fewer than one such FTE (49%) and with at least one such FTE (65%). The predicted probability of receiving such treatment on site was significantly higher if there was a colocated psychiatrist versus no psychiatrist (58% versus 40%). CONCLUSIONS: Colocating mental health staff at health centers increases the probability of patients' access to such treatment on site as well as from off-site providers.

Patient-Provider Communication and Adherence to Cholesterol Management Advice: Findings from a Cross-Sectional Survey.

High cholesterol is a preventable risk factor for heart disease. This study examines which aspects of patient-provider communication are associated with patient report of increased adherence to cholesterol management advice in a diverse, low-income patient population accessing the health care safety net, using the 2014 Health Center Patient Survey. Patient-provider communication measures included patient report of: how often a provider listened carefully, gave easy-to-understand information, knew important information about the patient's medical history, showed respect, and spent enough time with the patient. Outcome measures were patient report of following provider advice to eat fewer high fat or high cholesterol foods, manage weight, increase physical activity, or take prescribed medicine. In adjusted analyses, when patients perceived their provider always knew their medical history, patients were more likely to report taking prescribed medication (adjusted odds ratio [aOR]: 3.2; 95% confidence interval [CI]: 1.6, 6.6). Knowledge of medical history (aOR: 2.8, 95% CI: 1.4, 5.8), spending enough time (aOR: 2.3, 95% CI: 1.2, 4.4), and providing easily understandable information (aOR: 2.2, 95% CI: 1.0, 4.7) were significantly associated with report of following physical activity advice. Knowledge of medical history (aOR: 2.3, 95% CI: 1.0, 5.2) and providing easily understandable information (aOR: 3.3, 95% CI: 1.4, 7.9) were significantly associated with report of following weight management advice. This study indicates different components of patient-provider communication influence patient adherence to lifestyle modification advice and medication prescription. These results suggest a tailored approach to optimize the impact of patient-provider communication on cholesterol management advice adherence.

Blood Lead Testing Among Medically Underserved and Socially Vulnerable Children in the United States 2012-2017.

CONTEXT: Lead poisoning can affect intellectual development, growth, hearing, and other health problems. Children 6 years or younger are particularly susceptible to lead poisoning. Health Resources and Services Administration (HRSA)-funded health centers (HCs) serve lower-income, minority, and vulnerable populations across the United States, who may be at a higher risk for lead exposure. At HCs, blood lead testing is monitored; however, little is known about testing rates and characteristics of children tested by HCs. OBJECTIVES: We assessed the prevalence and characteristics of children who received a blood lead test at HCs from 2012 to 2017. DESIGN: We assessed characteristics of children 12 to 60 months of age who had a blood lead test using available self-reported data from HRSA's Health Center Patient Survey (2014-2015). In addition, using HRSA's Uniform Data System, an administrative performance data set, we calculated the annual percentage change of blood lead testing from 2012 to 2017. RESULTS: During 2014-2015, 1.1 million (72.9%; 95% CI, 64.6-81.3) out of the 1.5 million (n = 365 unweighted) eligible children 12 to 60 months of age self-reported receiving a blood lead test at an HRSA-funded HC. There was a significant higher proportion of children with a blood lead test among urban HCs (74.1%; 95% CI, 59.4-88.8) and among those who reported HCs as their usual source of care (99.9%; 95% CI, 99.7-100) (P ≤ .05).The total HC population of children younger than 72 months increased from 2 674 500 in 2012 to 2 989 184 in 2017, and we observed a 34.4% increase in blood lead testing at HRSA-funded HCs over the same time period. CONCLUSIONS: HCs play an important role in providing access to blood lead testing in underserved communities in the United States. While HRSA-funded HCs have made substantial efforts to screen and educate patients on lead exposure, nonetheless continued screening and education efforts with both health providers at HCs and parents/guardians are warranted to continue to improve blood lead screening rates among high-risk groups.

The role of dentist supply, need for care and long-term continuity in Health Resources and Services Administration-funded health centres in the United States.

OBJECTIVES: Health Resources and Services Administration-funded health centres (HCs) are an important source of dental services for low-income and vulnerable patients in the United States. About 82% of HCs in 2018 had dental workforce, but it is unclear whether this workforce meets the oral health needs of HC patients. Thus, we first examined (a) whether dental workforce was associated with any dental visits vs none and (b) whether HC patients with any visits were more likely to have a visit at the HC vs elsewhere. We then examined (c) if need for oral health care and long-term continuity at the HC were associated with dental visits and visits at the HC. METHODS: This study used the 2014 Health Center Patient Survey, a nationally representative study of US HC patients, and the 2013 Uniform Data System, an administrative dataset of HC characteristics. We also used the 2013 Area Health Resource File to measure the contribution of local supply of dentists. We included working-age adult patients (n = 5006) and used multilevel structural equation models with Poisson specification. RESULTS: Larger dental workforce at the HC was significantly associated with 1% higher likelihood (relative risk [RR]: 1.01, 1.00-1.02) of any visits and 10% higher likelihood of a visit at the HC among those with a visit (RR: 1.10, 1.06-1.14). Patient self-reported oral health need was positively associated with 157% higher likelihood of dental visits (RR: 2.57, 2.29-2.88), and 42% higher likelihood of dental visit at the HC vs elsewhere (RR: 1.42, 1.19-1.69). Long-term continuity with the HC was not significantly associated with likelihood of dental visits, but was associated with 26% higher likelihood of visits at the HC among those who had any visits (RR: 1.26, 1.02-1.56). DISCUSSION: The findings highlight the potential impact of increasing dental workforce at HCs to promote access; the high level of need for oral health care at HCs; and the increased effort required to promote access among newer patients who may be less familiar with the availability of oral health care at HCs. Together, these findings reinforce the importance of addressing barriers of use of oral health services among low-income and uninsured patients.

Assessing clinical quality performance and staffing capacity differences between urban and rural Health Resources and Services Administration-funded health centers in the United States: A cross sectional study.

BACKGROUND: In the United States, there are nearly 1,400 Health Resources and Services Administration-funded health centers (HCs) serving low-income and underserved populations and more than 600 of these HCs are located in rural areas. Disparities in quality of medical care in urban vs. rural areas exist but data on such differences between urban and rural HCs is limited in the literature. We examined whether urban and rural HCs differed in their performance on clinical quality measures before and after controlling for patient, organizational, and contextual characteristics. METHODS AND FINDINGS: We used the 2017 Uniform Data System to examine performance on clinical quality measures between urban and rural HCs (n = 1,373). We used generalized linear regression models with the logit link function and binomial distribution, controlling for confounding factors. After adjusting for potential confounders, we found on par performance between urban and rural HCs in all but one clinical quality measure. Rural HCs had lower rates of linking patients newly diagnosed with HIV to care (74% [95% CI: 69%, 80%] vs. 83% [95% CI: 80%, 86%]). We identified control variables that systematically accounted for eliminating urban vs. rural differences in performance on clinical quality measures. We also found that both urban and rural HCs had some clinical quality performance measures that were lower than available national benchmarks. Main limitations included potential discrepancy of urban or rural designation across all HC sites within a HC organization. CONCLUSIONS: Findings highlight HCs' contributions in addressing rural disparities in quality of care and identify opportunities for improvement. Performance in both rural and urban HCs may be improved by supporting programs that increase the availability of providers, training, and provision of technical resources.