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AimTo explore whether there are racial/ethnic differences in diabetes management and outcomes among adult health center (HC) patients with type 2 diabetes.MethodsWe 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.ResultsWe 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.ConclusionHCs 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.

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.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.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).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.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.

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.

Introduction During the 2018–2019 influenza season, vaccination coverage among U.S. children was 62.6%. The purpose of this study was to estimate the prevalence of influenza vaccinations among pediatric patients seen in U.S. health centers, and to explore potential disparities in vaccination coverage among subpopulations. Funded by the Health Resources and Services Administration (HRSA) within the U.S. Department of Health and Human Services, these health centers provide primary and preventive care to underserved and vulnerable individuals and families in order to reduce health disparities based on economic, geographic, or cultural barriers. Methods Cross-sectional data, analyzed in 2019, came from the most recent waves of the Health Center Patient Survey (2009, 2014). The sample consisted of children ages 2–17 years receiving care from HRSA-funded health centers. The outcome of interest was self- or parent-reported receipt of influenza vaccine in the past year. Multivariable logistic regression was used to estimate the adjusted prevalence rate ratios for the association between demographic characteristics (age, sex, race/ethnicity, poverty level, urban/rural residence, geographic region), health-related variables (receipt of well-child check-up, asthma diagnosis), and influenza vaccination. Results Influenza vaccination coverage among pediatric health center patients increased from 46.6% in 2009 to 67.8% in 2014. In the adjusted model for 2014, there were few statistically significant differences in vaccination coverage among subpopulation groups, however American Indian/Alaska Native children had 31% increased vaccination coverage compared with non-Hispanic White children (aPRR: 1.31, 95% CI: 1.02–1.60) and children living in the South had 26% decreased vaccination coverage compared with those living in the Northeast (aPRR: 0.74, 95% CI: 0.54–0.93). Conclusions Influenza vaccination coverage among pediatric health center patients in 2014 exceeded the national average (as of 2018–2019), and few differences were found among at-risk subpopulations. HRSA-funded health centers are well-positioned to further increase the vaccination rate among children living in underserved communities.

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.

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 (

To describe the Health Resources and Services Administration's Quality Improvement Award (QIA) program, award patterns, and early lessons learned.1413 health centers were eligible for QIA from 2014 to 2018.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.Organizational and quality measures are reported in the Uniform Data System, QIA program data.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.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.

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).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).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).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.

ObjectiveThe 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.MethodsData 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.ResultsPatients 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%).ConclusionsColocating mental health staff at health centers increases the probability of patients' access to such treatment on site as well as from off-site providers.

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.

Author(s): Pourat, Nadereh; Chen, Xiao; Lu, Connie; Zhou, Weihao; Hoang, Hank; Hair, Brionna; Bolton, Joshua; Sripipatana, Alek | Abstract: ObjectivesHealth 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.MethodsThis 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 (nn=n5006) and used multilevel structural equation models with Poisson specification.ResultsLarger 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).DiscussionThe 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.

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.

This study sought to examine racial/ethnic variations in receipt of provider recommendations on weight loss, patient adherence, perception of weight, attempts at weight loss and actual weight loss among patients with overweight/obesity status at Health Resources and Services Administration-funded health centres (HC). We used a 2014 nationally representative survey of adult HC patients with overweight/obesity status (PwOW/OB) last year and reported the HC was their usual source of care (n = 3517). We used logistic regression models to assess the interaction of race/ethnicity and having obesity in (1) provider recommendations of diet or (2) exercise, (3) patient adherence to diet or (4) exercise, (5) perceptions of weight and (6) weight loss attempts. We used a multinomial regression model to examine (7) weight loss or gain vs no change and a linear regression model to evaluate (8) percent weight change. We found Black PwOW/OB (OR = 1.65) experienced greater odds of receiving diet recommendations than Whites. We found limited racial/ethnic disparities in adherence. Black (OR = 0.41), Hispanic/Latino (OR = 0.45), and American Indian/Alaska Native (OR = 0.41) PwOW/OB had lower odds of perceiving themselves as overweight. Black (OR = 1.68) and Hispanic (OR = 1.98) PwOW/OB had a greater odds of reporting weight gain, and Asian PwOW/OB (OR = 0.42) had lower odds of reporting weight loss than Whites. Disparities in provider diet recommendations among Blacks and Hispanics indicated the importance of personalized weight management recommendations. Understanding underlying reasons for discordance between self-perception and observed weight among different groups is needed. Overall increase in weight, despite current interventions, should be addressed through targeted racially/ethnically appropriate approaches.

Objectives (1) To evaluate the relationship between Patient-centered Medical Home (PCMH) recognition and quality of clinical care among health centers, and (2) to determine whether the duration of recognition is positively associated with cumulative quality improvement over time. Methods Data came from the 2012 to 2015 Uniform Data System, health centers' PCMH recognition status, and the Area Resource File. Health center was the unit of observation. The outcome variables included 11 measures of clinical quality. We pooled all years of data and modeled longitudinal data with generalized estimating equations to examine the degree of improvement in health care quality in health centers with and without PCMH recognition over the years 2012-2015. Results Health centers with PCMH recognition generally performed better on clinical quality measures than health centers that did not have PCMH recognition for all years studied. After accounting for health center and county-level potential confounders, health centers with longer periods of PCMH recognition were more likely to have improved their clinical quality on 9 of 11 measures, than health centers with fewer years of PCMH recognition. Conclusions Health centers' length of time with PCMH recognition was positively associated with additive quality improvement. Adoption of the PCMH model of care may serve as a strategy to enhance quality of primary care services.

BACKGROUND Colorectal cancer (CRC) screening rates are low among underserved populations. High-quality patient-physician communication potentially influences patients' willingness to undergo CRC screening. Community health centers (HCs) provide comprehensive primary health care to underserved populations. This study's objectives were to ascertain national CRC screening rates and to explore the relations between sociodemographic characteristics and patient-provider communication on the receipt of CRC screening among HC patients. METHODS Using 2014 Health Center Patient Survey data, bivariate and multivariate analyses examined the association of sociodemographic variables (sex, race/ethnicity, age, geography, preferred language, household income, insurance, and employment status) and patient-provider communication with the receipt of CRC screening. RESULTS Patients between the ages of 65 and 75 years (adjusted odds ratio [aOR], 2.49; 95% confidence interval [CI], 1.33-4.64) and patients not in the labor force (aOR, 2.32; 95% CI, 1.37-3.94) had higher odds of receiving CRC screening, whereas patients who were uninsured (aOR, 0.33; 95% CI, 0.18-0.61) and patients who were non–English-speaking (aOR, 0.42; 95% CI, 0.18-0.99) had lower odds. Patient-provider communication was not associated with the receipt of CRC screening. CONCLUSIONS The CRC screening rate for HC patients was 57.9%, whereas the rate was 65.1% according to the 2012 Behavioral Risk Factor Surveillance System and 58.2% according to the 2013 National Health Interview Survey. The high ratings of patient-provider communication, regardless of the screening status, suggest strides toward a patient-centered medical home practice transformation that will assist in a positive patient experience. Addressing the lack of insurance, making culturally and linguistically appropriate patient education materials available, and training clinicians and care teams in cultural competency are critical for increasing future CRC screening rates. Cancer 2017;123:4185–4192. © 2017 American Cancer Society.

Background The opioid epidemic and subsequent mortality is a national concern in the U.S. The burden of this problem is disproportionately high among low-income and uninsured populations who are more likely to experience unmet need for substance use services. We assessed the impact of two Health Resources and Services Administration (HRSA) substance use disorder (SUD) service capacity grants on SUD staffing and service use in HRSA -funded health centers (HCs). Methods and findings We conducted cross-sectional analyses of the Uniform Data System (UDS) from 2010 to 2017 to assess HC (n = 1,341) trends in capacity measured by supply of SUD and medication-assisted treatment (MAT) providers, utilization of SUD and MAT services, and panel size and visit ratio measured by the number of patients seen and visits delivered by SUD and MAT providers. We merged mortality and national survey data to incorporate SUD mortality and SUD treatment services availability, respectively. From 2010 to 2015, 20% of HC organizations had any SUD staff, had an average of one full-time equivalent SUD employee, and did not report an increase in SUD patients or SUD services. SUD capacity grew significantly in 2016 (43%) and 2017 (22%). MAT capacity growth was measured only in 2016 and 2017 and grew by 29% between those years. Receipt of both supplementary grants increased the probability of any SUD capacity by 35% (95% CI: 26%, 44%) and service use, but decreased the probability of SUD visit ratio by 680 visits (95% CI: -1,013, -347), compared to not receiving grants. Conclusions The significant growth in HC specialized SUD capacity is likely due to supplemental SUD-specific HRSA grants and may vary by structure of grants. Expanding SUD capacity in HCs is an important step in increasing SUD access for low income and uninsured populations broadly and for patients of these organizations.

BackgroundIn 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 findingsWe 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.ConclusionsFindings 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.

Author(s): Nguyen, Vy; Daniel, Marlon; Joskow, Renee; Lu, Connie; Chen, Xiao; Zhou, Weihao; Lin, Sue; Sripipatana, Alek; Nair, Suma; Pourat, Nadereh | Abstract: ObjectivesThis study aims to assess the impact of Health Resources and Services Administration (HRSA) investment in oral health through the HRSA FY16 Oral Health Service Expansion (OHSE) funding on workforce, access, and quality in health centers (HCs) from 2015 to 2017.MethodsAnalyses were conducted using data from the Uniform Data System from 2015 and 2017, and the 2015 Area Health Resource File. Change in indicators of oral health workforce, access, and quality of care by the receipt of OHSE funding received by HCs in 2016 were examined. Regression models for 1,345 HCs were developed to conduct a difference-in-difference analyses of the comparative change from 2015 to 2017 in the dependent variables among OHSE and non-OHSE awardees while controlling for confounders.ResultsOHSE awardees showed a significant difference in the oral health workforce with a higher mean number increase by 0.6 full time equivalent (FTE) dentists, 0.4 dental hygienists, 1.1 dental assistants, and 2.3 for other dental staff compared to non-OHSE awardees. Compared to non-OHSE awardees, OHSE awardees showed a mean increase of 712 dental patients served who received 1,402 dental visits, representing a 9-percentage point increase in the percentage of HCs that had an oral health program and a 3-percentage point increase in the ratio of dental patients to total patients.ConclusionsFunding dedicated to oral health service expansion in HCs may result in outcomes ranging from increasing workforce to reduction in access and financial barriers. Retrospective analysis demonstrated improved capacity for oral healthcare delivery attributable to HRSA support to HCs.

BackgroundEvidence indicates the unmet need for primary care services including medical, mental health, and dental care is greater among uninsured and Medicaid beneficiaries than privately insured individuals, many of whom use Health Resources and Services Administration-funded health centers (HRSA HCs).ObjectiveWe examined differences in rates of unmet need between low-income uninsured and Medicaid patients of HRSA HCs and safety-net clinics in general or private physicians.Research designWe used logistic regression models to compare the predicted probabilities of unmet need for uninsured and Medicaid individuals whose usual source of care is HRSA HCs versus clinics in general or private physicians.SampleWe used a nationally representative survey of low income, adult patients who identified HRSA HCs as their usual source of care. We used the National Health Interview Survey to independently identify low-income individuals whose usual source of care was clinics (National Health Interview Survey clinics) or physicians (National Health Interview Survey physicians) in the general population.MeasuresDependent variables were unmet need and delay in medical care, and unmet need for prescription medications, mental health, and dental care. The primary independent variable of interest was the usual source of care. We controlled for potential confounders.ResultsWe found the probability of unmet need for medical and dental care to be lower among HRSA HC patients than individuals whose usual source of care were not HRSA HCs.ConclusionsHRSA HC patients have lower probabilities of unmet need for medical and dental care. This is likely because HRSA HCs provide accessible, affordable, and comprehensive primary care services. Expanding capacity of these organizations will help reduce unmet need and its consequences.

Enabling services address a combination of social determinants of health and barriers to access to primary care and are intended to reduce health disparities. They include care coordination; health education; transportation; and assistance with obtaining food, shelter, and benefits. Empirical evidence of enabling services' potential contribution to health outcomes is limited, which impedes their widespread dissemination. We examined how the receipt of enabling services influenced patient health care outcomes based on a nationally representative survey of patients served in 2014 at health centers funded by the Health Resources and Services Administration. We compared enabling services users and nonusers and found that enabling services were associated with 1.92 more health center visits, an 11.78-percentage-point higher probability of getting a routine checkup, a 16.34-percentage-point higher likelihood of having had a flu shot, and a 7.63-percentage-point higher probability of patient satisfaction. Our results confirm the value of systematic delivery of enabling services in reducing access barriers and improving patient satisfaction.

The rising prevalence of mental health conditions and substance use disorders (MH/SUD) underscores the important role of health centers (HCs) in caring for low-income and uninsured MH/SUD patients. This study used the 2014 Health Center Patient Survey and 2014 Uniform Data System to determine the independent association between delivery of MH/SUD integration and related interventions to patients that reported a MH/SUD condition (n=2714) with the number of HC visits, emergency department (ED) visits, and hospitalizations last year. Results showed that health education was associated with fewer predicted ED visits (1.8 vs. 2.3) and lower likelihood of hospitalizations (16% vs. 24%) among MH patients. Medical enabling services was associated with lower rates of ED visits (0.3 vs.1.9) and hospitalizations (

Some racial/ethnic minorities are more likely to have hypertension and experience increased hypertension-related morbidity and mortality compared to whites. Health Resources and Services Administration-funded health centers care for over 27 million patients, 62 percent of whom are racial/ethnic minorities. We assessed the presence of racial/ethnic disparities in (a) hypertension management and (b) hypertension outcomes among health center patients. We used data from the 2014 Health Center Patient Survey and performed multilevel logistic regression models to predict hypertension management counseling, patient adherence to counseling and medication regimen, management plan receipt, high blood pressure at last clinical visit, confidence in hypertension self-management, and hypertension-related emergency department (ED) episodes or hospitalizations in the past year. We controlled for patient characteristics including age, sex, education, nativity, health behaviors, health care access, and comorbidities. We found significantly higher odds of diet counseling (African Americans, OR: 1.87; Asian Americans, OR: 3.02, AIAN, OR: 2.01), reduced sodium intake (African American, OR: 2.42), and adherence to exercise counseling (African American, OR: 3.52; Asian Americans, OR: 2.93). We also found lower odds of taking hypertension control medication (AIAN, OR: 0.50) and higher odds of hypertension-related ED visits (African Americans, OR: 3.61, AIAN, OR: 5.31). These results highlight the success of health centers in managing hypertension by race/ethnicity but found adverse hypertension outcomes for some groups. Racial/ethnically tailored efforts might be required to manage hypertension and improve outcomes.

Author(s): Chuang, Emmeline; Pourat, Nadereh; Chen, Xiao; Lee, Christopher; Zhou, Weihao; Daniel, Marlon; Hoang, Hank; Sripipatana, Alek | Abstract: INTRODUCTION:Community health centers provide care to underserved populations least likely to adhere to cancer screening guidelines, but vary in their ability to ensure eligible patients are identified and screened. This study examines organizational factors associated with cervical and colorectal cancer screening rates among health centers funded by the Health Resources and Services Administration (HRSA). METHODS:Data were drawn from the 2015 Uniform Data System and analyzed using negative binomial regression. RESULTS:On average, 53% of eligible health center patients were screened for cervical cancer and 37% for colorectal cancer. Organizational characteristics positively associated with cancer screening rates include provider-patient staffing ratios, electronic health record status, percentage revenue from public capitated managed care, and local primary care provider availability. Percentage of homeless patients was negatively associated with screening. CONCLUSION:Efforts to improve cancer screening among underserved populations should address organizational factors that may contribute to disparities in screening uptake.

Author(s): Pourat, Nadereh; Chen, Xiao; Lee, Christopher; Zhou, Weihao; Daniel, Marlon; Hoang, Hank; Sripipatana, Alek | Abstract: BackgroundMillions of Americans have uncontrolled hypertension and are low-income or uninsured populations. Health Resources and Services Administration-funded health centers (HCs) are primary providers of care to these patients and a majority have adopted the patient-centered medical home (PCMH). PCMH includes principles of care coordination or integration and care management-support important to the treatment of hypertension. We examined whether the receipt of PCMH concordant care by HC patients improved hypertension outcomes.MethodsWe used a nationally representative survey of adult HC patients with hypertension (n = 2,280) conducted between October 2014 and April 2015. We included data from the 2013 and 2014 Uniform Data System to include characteristics of the HCs where these patients received their care. Our outcome measures included flu shots, number of primary care visits, normal blood pressure at last visit, emergency department (ED) visits, confidence in self-care, and compliance with provider recommendations. The primary independent variables were (i) whether the HC coordinated and referred patients to specialists; (ii) provided counseling, health education, coaching, treatment plans, and advice on hypertension control; and (iii) helped patients to obtain government benefits, medical transportation, and basic needs such as housing and food. Logistic and negative binomial multivariate regression models were performed.ResultsHypertension-focused coaching was associated with normal blood pressure at last visit (odds ratio (OR) = 1.47) and fewer ED visits (incidence rate ratio = 0.81). Behavioral health counseling was associated with increased self-efficacy in self-care management (OR = 3.20).ConclusionsOur findings suggested that increased focus on these practices may lead to better hypertension outcomes among patients who are low-income and uninsured populations.

Aims This paper examines the association of multimorbidity, mental health (MH) conditions, and obesity severity among health center (HC) patients in the United States. Methods We used cross-sectional data from the 2014 Health Center Patient Survey (n = 5370). We examined the independent association of multimorbidity and MH conditions with obesity severity using a multinomial logistic regression model, controlling for potential confounders. Results More than half (50.4%) of HC patients had obesity, including 15% with severe obesity. In addition, 41% had multimorbidity and 49% had one of five diagnosed MH conditions. We found higher odds of having mild (OR = 4.06), moderate (OR = 3.39), and severe (OR = 4.93) obesity with the presence of both multimorbidity and MH conditions. Multimorbidity alone was also associated with higher odds of obesity, but MH conditions alone were only associated with having moderate obesity. Conclusions Findings show a higher burden of comorbidity and MH conditions given the severity of obesity among HC patients. This complex patient profile highlights the need for innovative approaches in effective care delivery and management of HC patients who are primarily low-income or uninsured. Approaches may include further integration of behavioral health and social services with primary care and the need for targeted practice guidelines for providers managing such patients.

Introduction America's community health centers (HCs) are uniquely poised to implement the patient-centered medical home (PCMH) model, as they are effective in providing comprehensive, accessible, and continuous primary care. This study aims to evaluate the relationship between PCMH recognition in HCs and clinical performance. Methods Data for this study came from the 2012 Uniform Data System (UDS) as well as a survey of HCs' PCMH recognition achievement. The dependent variables included all 16 measures of clinical performance collected through UDS. Control measures included HC patient, provider, and practice characteristics. Bivariate analyses and multiple logistic regressions were conducted to compare clinical performance between HCs with and without PCMH recognition. Findings Health centers that receive PCMH recognition generally performed better on clinical measures than HCs without PCMH recognition. After controlling for HC patient, provider, and practice characteristics, HCs with PCMH recognition reported significantly better performance on asthma-related pharmacologic therapy, diabetes control, pap testing, prenatal care, and tobacco cessation intervention. Conclusion This study establishes a positive association between PCMH recognition and clinical performance in HCs. If borne out in future longitudinal studies, policy makers and practices should advance the PCMH model as a strategy to further enhance the quality of primary care.

Telehealth services have the potential to improve access to care, especially in rural or urban areas with scarce health care resources. Despite the potential benefits, telehealth has not been fully adopted by health centers. This study examined factors associated with and barriers to telehealth use by federally funded health centers. We analyzed data for 2016 from the Uniform Data System using a mixed-methods approach. Our findings suggest that rural location, operational factors, patient demographic characteristics, and reimbursement policies influence health centers' decisions about using telehealth. Cost, reimbursement, and technical issues were described as major barriers. Medicaid reimbursement policies promoting live video and store-and-forward services were associated with a greater likelihood of telehealth adoption. Many health centers were implementing telehealth or exploring its use. Our findings identified areas that policy makers can address to achieve greater telehealth adoption by health centers.

The Health Resources and Services Administration supports federally qualified health centers that provide health care services to more than 21.7 million low-income and medically underserved patients, the majority being racial/ethnic minorities. Nationally, Native Hawaiians and Pacific Islanders (NHPIs) represent 1.3 percent of all health center patients; however, NHPIs constitute more than half of the patients for some health centers. National data of health center clinical quality indicators were analyzed to explore potential differences between Native Hawaiian, Pacific Islander, and Asian American patients. Even among a group of medically underserved patients, health disparities were found in NHPIs, illustrating the relevance of disaggregating data in identifying idiosyncratic differences deserving culturally appropriate interventions.

Cross-sectional 2009 Health Center Patient Survey data describe the mental health status of health center patients, utilization of mental health services, and factors associated with unmet need for mental health treatment. One in five health center patients accessed mental health services in the past year, and over half of the patients who received counseling received this treatment at a health center. Patients who were unable to access mental health care cited affordability as a concern. Unmet need for mental health treatment was reported by one in three patients. Multivariate analysis found that the odds of reporting unmet need were higher for patients who lacked a usual source of care and patients with serious mental illness.

We obtained the prevalence of overweight/obesity, weight-loss attempts, and weight-related counseling and treatment among U.S. adults who sought care in federally funded community health centers. We investigated whether racial/ethnic and gender disparities existed for these measures.Data came from the 2009 Health Center Patient Survey. Measures included body mass index (BMI), self-perceived weight, weight-loss attempts, being told of a weight problem, receipt of weight-related counseling, nutritionist referrals, weight-loss prescriptions, and cholesterol checks. We conducted bivariate analyses to determine distributions by race/ethnicity and gender, then ran logistic regressions to examine the effects of several sociodemographic factors on weight-loss attempts and on being told of a weight problem.Overall, 76% of adult patients seen in health centers were overweight or obese (BMI ≥ 25.0 kg/m(2)); 55% of overweight patients, and 87% of obese patients correctly perceived themselves as overweight. There were no racial/ethnic differences in BMI categories or self-perceptions of weight. Females were more likely than males to be obese and also more likely to perceive themselves as overweight. About 60% of overweight/obese patients reported trying to lose weight in the past year. There were no racial/ethnic disparities favoring non-Hispanic White patients in weight-related treatment. Women were more likely than men to receive referrals to a nutritionist or weight-loss prescriptions. Overweight/obese patients had higher adjusted odds of a past-year weight-loss attempt if they perceived themselves as overweight (OR = 3.30, p0.0001), were female (OR = 1.95, p0.05), African American (OR = 3.34, p0.05), or Hispanic/Latino (OR = 2.14, p0.05). Overweight/obese patients had higher odds of being told they had a weight problem if they were Hispanic/Latino (OR = 2.56, p0.05) or if they had two or more chronic conditions (OR = 2.77, p0.01).Patients seen in community health centers have high rates of overweight and obesity, even higher than the general U.S. population. Efforts to address weight problems during primary care visits are needed to reduce the burden of obesity and its sequellae among health center patients.

Colorectal cancer (CRC) screening rates are low among underserved populations. High-quality patient-physician communication potentially influences patients' willingness to undergo CRC screening. Community health centers (HCs) provide comprehensive primary health care to underserved populations. This study's objectives were to ascertain national CRC screening rates and to explore the relations between sociodemographic characteristics and patient-provider communication on the receipt of CRC screening among HC patients.Using 2014 Health Center Patient Survey data, bivariate and multivariate analyses examined the association of sociodemographic variables (sex, race/ethnicity, age, geography, preferred language, household income, insurance, and employment status) and patient-provider communication with the receipt of CRC screening.Patients between the ages of 65 and 75 years (adjusted odds ratio [aOR], 2.49; 95% confidence interval [CI], 1.33-4.64) and patients not in the labor force (aOR, 2.32; 95% CI, 1.37-3.94) had higher odds of receiving CRC screening, whereas patients who were uninsured (aOR, 0.33; 95% CI, 0.18-0.61) and patients who were non-English-speaking (aOR, 0.42; 95% CI, 0.18-0.99) had lower odds. Patient-provider communication was not associated with the receipt of CRC screening.The CRC screening rate for HC patients was 57.9%, whereas the rate was 65.1% according to the 2012 Behavioral Risk Factor Surveillance System and 58.2% according to the 2013 National Health Interview Survey. The high ratings of patient-provider communication, regardless of the screening status, suggest strides toward a patient-centered medical home practice transformation that will assist in a positive patient experience. Addressing the lack of insurance, making culturally and linguistically appropriate patient education materials available, and training clinicians and care teams in cultural competency are critical for increasing future CRC screening rates. Cancer 2017;123:4185-4192. © 2017 American Cancer Society.

This study examined access to care and satisfaction among health center patients with chronic conditions. Data for this study were obtained from the 2009 Health Center Patient Survey. Dependent variables of interest included 5 measures of access to and satisfaction with care, whereas the main independent variable was number of chronic conditions. Results of bivariate analysis and multiple logistic regressions showed that patients with chronic conditions had significantly higher odds of reporting access barriers than those without chronic conditions. Our results suggested that additional efforts and resources are necessary to address the needs of health center patients with chronic conditions.

To examine health status and health care experiences of homeless patients in health centers and to compare them with their nonhomeless counterparts.Nationally representative data from the 2009 Health Center Patient Survey.Cross-sectional analyses were limited to adults (n = 2,683). We compared sociodemographic characteristics, health conditions, access to health care, and utilization of services among homeless and nonhomeless patients. We also examined the independent effect of homelessness on health care access and utilization, as well as factors that influenced homeless patients' health care experiences.Computer-assisted personal interviews were conducted with health center patients.Homeless patients had worse health status-lifetime burden of chronic conditions, mental health problems, and substance use problems-compared with housed respondents. In adjusted analyses, homeless patients had twice the odds as housed patients of having unmet medical care needs in the past year (OR = 1.98, 95 percent CI: 1.24-3.16) and twice the odds of having an ED visit in the past year (OR = 2.00, 95 percent CI: 1.37-2.92).There is an ongoing need to focus on the health issues that disproportionately affect homeless populations. Among health center patients, homelessness is an independent risk factor for unmet medical needs and ED use.

Objectives. We examined primary care and public health activities among federally funded health centers, to better understand their successes, the barriers encountered, and the lessons learned.Methods. We used qualitative and quantitative methods to collect data from 9 health centers, stratified by administrative division, urban–rural location, and race/ethnicity of patients served. Descriptive data on patient and institutional characteristics came from the Uniform Data System, which collects data from all health centers annually. We administered questionnaires and conducted phone interviews with key informants.Results. Health centers performed well on primary care coordination and community orientation scales and reported conducting many essential public health activities. We identified specific needs for integrating primary care and public health: (1) more funding for collaborations and for addressing the social determinants of health, (2) strong leadership to champion collaborations, (3) trust building...

The Bureau of Primary Health Care (BPHC), in the Health Resources and Services Administration (HRSA), funds over 1,100 health centers to provide primary and preventive care to about 19 million underserved patients throughout the nation (Health Resources and Services Administration). Under Section 330 of the Public Health Service Act, the federal Health Center Program has been serving vulnerable populations since 1965 and has been championed as a model delivery system for improving access to care and reducing disparities (Shi et al. 2001a,b; Shi et al. 2004, 2009; Proser 2005; Hadley, Cunningham, and Hargraves 2006; Shi, Stevens, and Politzer 2007). The year 2008 marked the beginning of a program-wide clinical quality improvement initiative to measure and demonstrate quality of care across all BPHC-funded health centers (Health Resources and Services Administration). As part of this initiative, the Health Center Program now incorporates an array of performance measures into its annual data reporting activities, emphasizing a combination of indicators measuring both processes of care and health outcomes. The performance measures tracked by HRSA are consistent with those endorsed by the National Quality Forum, AQA Alliance (formerly the Ambulatory Care Quality Alliance), and other national quality organizations; are designed to address priority health conditions of HRSA safety-net populations throughout the life cycle; and are amenable to quality improvement. For instance, quality measures include indicators of screening for cervical cancer, which disproportionately affects vulnerable populations served by HRSA-funded health centers and for which early detection and care can significantly decrease mortality and improve 5-year survival. Other measures include access to prenatal care, low birth weight, age-appropriate immunizations, and chronic disease management indicators for diabetes and hypertension. In years past, a number of studies have evaluated health centers' performance on quality-related indicators. This prior research found that health centers performed quite well with respect to prenatal care outcomes; specifically, rates of low birth weight in health centers were comparable or lower than other provider settings nationwide, despite the fact that health centers serve higher-risk groups (Politzer et al. 2001; Regan et al. 2003; Haq 2007). In addition, cervical cancer screening rates in health centers exceeded national rates, overall and for specific racial/ethnic and insurance groups (Regan, Lefkowitz, and Gaston 1999; Politzer et al. 2001; Regan et al. 2003; Shi and Stevens 2007; Dor et al. 2008; Shin et al. 2008; Shi et al. 2009). Health centers have also generally shown comparable performance in terms of childhood immunization rates (Schempf, Politzer, and Wulu 2003). However, past research found room for improvement in performance in the management of chronic diseases. Studies of health center patients conducted 10 years ago suggested that only about 50 percent of patients with hypertension, and 40–60 percent of patients with diabetes, received appropriate care (Chin et al. 2000; Hicks et al. 2006). Quality improvement efforts, such as the various Health Disparities Collaboratives implemented within health centers, showed progress in diabetes-related prevention, screening, treatment, and monitoring activities, as well as cancer screening, while the collaboratives were in operation; however, no improvements were demonstrated in hypertension (Chin et al. 2004, 2007; Chien, Walters, and Chin 2007; Landon et al. 2007). There was also mixed evidence regarding the impact of these interventions on longer-term patient outcomes, such as control of glycated hemoglobin levels for diabetes and control of blood pressure for hypertension (Chien, Walters, and Chin 2007; Landon et al. 2007). While informative, these studies may not serve as the best preface to the current state of clinical quality in health centers. Prior data sources date back at least 5 years, preceding the current quality improvement initiative at HRSA, and previous analyses often included regional rather than national data, possibly limiting the generalizability of the findings. To address this gap in the health center literature, this study sought to provide the most recent national analyses of clinical quality performance across health centers, using 2009 Uniform Data System (UDS) data from HRSA. While informative, these studies may not serve as the best preface to the current state of clinical quality in health centers. Prior data sources date back at least 5 years, preceding the current quality improvement initiative at HRSA, and previous analyses often included regional rather than national data, possibly limiting the generalizability of the findings. To address this gap in the health center literature, this study sought to provide the most recent national analyses of clinical quality performance across health centers, using 2009 Uniform Data System (UDS) data from HRSA. While informative, these studies may not serve as the best preface to the current state of clinical quality in health centers. Prior data sources date back at least 5 years, preceding the current quality improvement initiative at HRSA, and previous analyses often included regional rather than national data, possibly limiting the generalizability of the findings. To address this gap in the health center literature, this study sought to provide the most recent national analyses of clinical quality performance across health centers, using 2009 Uniform Data System (UDS) data from HRSA. While informative, these studies may not serve as the best preface to the current state of clinical quality in health centers. Prior data sources date back at least 5 years, preceding the current quality improvement initiative at HRSA, and previous analyses often included regional rather than national data, possibly limiting the generalizability of the findings. To address this gap in the health center literature, this study sought to provide the most recent national analyses of clinical quality performance across health centers, using 2009 Uniform Data System (UDS) data from HRSA. While informative, these studies may not serve as the best preface to the current state of clinical quality in health centers. Prior data sources date back at least 5 years, preceding the current quality improvement initiative at HRSA, and previous analyses often included regional rather than national data, possibly limiting the generalizability of the findings. To address this gap in the health center literature, this study sought to provide the most recent national analyses of clinical quality performance across health centers, using 2009 Uniform Data System (UDS) data from HRSA. While informative, these studies may not serve as the best preface to the current state of clinical quality in health centers. Prior data sources date back at least 5 years, preceding the current quality improvement initiative at HRSA, and previous analyses often included regional rather than national data, possibly limiting the generalizability of the findings. To address this gap in the health center literature, this study sought to provide the most recent national analyses of clinical quality performance across health centers, using 2009 Uniform Data System (UDS) data from HRSA. The purpose of this study was to provide a description of the current status of clinical quality among the nation's health centers, to compare the status with similar national measures, and to examine health center patient, provider, and institutional characteristics associated with performance excellence. We utilized 2009 data from the UDS, to which all health centers are required to submit a variety of aggregated information on an annual basis. Other studies have often included nonrandom and/or regional samples of health centers, but use of the UDS data enables the calculation of national estimates. Finally, previous studies tended to focus on processes of care as indicators of quality rather than both processes of care and health outcomes.

The Patient-centered Medical Home (PCMH) model of care dates back to the 1960s, when it was originally conceived to improve care for children with special needs. The 7 core features of PCMH are: (1) a personal primary care physician, (2) a physician-directed medical practice, (3) whole person orientation, (4) coordinated or integrated care, (5) quality and safety, (6) enhanced access, and (7) payment reform.1 In the recent years, support for the expansion of PCMH has rapidly increased.2,3 Currently, the model is being applied through a growing number of demonstration projects, each with its own evaluation of effectiveness.4,5 One such application is through health centers (HCs), which receive funds from the Health Resources and Services Administration (HRSA) to provide primary care services to medically underserved populations.6 As of 2012, >21 million patients were served by HRSA-supported HCs.7 HCs are poised to implement the PCMH model as they have proven to be effective in providing comprehensive, accessible, and continuous primary care.8,9 HRSA’s PCMH initiative supports HCs’ efforts to adopt PCMH features and gain recognition by the National Committee for Quality Assurance, by providing education, training, technical assistance, and fee waivers for gaining recognition.10 By the end of fiscal year 2014, HRSA aims to have approximately 40% of HCs recognized.11 Although preliminary evaluations show that PCMHs promote improvements in health care access and quality,12–14 most report inconclusive results because of insufficient sample sizes to detect significant effects or lack of association between PCMH measures and clinical outcome.3 Large-scale evaluations of the PCMH model, particularly in safety-net settings like HCs, are needed. To address this gap, the current study evaluated the relationship between PCMH model adoption in HCs [as determined by the Safety Net Medical Home Scale (SNMHS)] and clinical performance measures, to determine if adoption of PCMH characteristics is associated with better clinical performance.

We compared preventive counseling services provided by health centers versus other physician offices. Cross-sectional data came from the 2008 National Ambulatory Medical Care Survey, including 25,177 patient visits in physician offices and 3,345 patient visits in health centers. Despite serving disproportionately more vulnerable patients, health centers provided comparable rates of preventive counseling services, compared with other physician offices: health education (39% vs. 36%), disease management (34% vs. 41%), asthma education (21% vs. 13%), tobacco education (19% for both), and weight reduction education (6% vs. 9%) (p>.05 for all). Adjusted analyses showed no association between health care setting and preventive counseling.

Over the last 50 years, the incidence of cervical cancer has dramatically decreased. However, health disparities in cervical cancer screening (CCS) persist for women from racial and ethnic minorities and those residing in rural and poor communities. For more than 45 years, federally funded health centers (HCs) have been providing comprehensive, culturally competent, and quality primary health care services to medically underserved communities and vulnerable populations. To enhance the quality of care and to ensure more women served at HCs are screened for cervical cancer, over eight HCs received funding to support patient-centered medical home (PCMH) transformation with goals to increase CCS rates. The study conducted a qualitative analysis using Atlas.ti software to describe the barriers and challenges to CCS and PCMH transformation, to identify potential solutions and opportunities, and to examine patterns in barriers and solutions proposed by HCs. Interrater reliability was assessed using Cohen’s Kappa. The findings indicated that HCs more frequently described patient-level barriers to CCS, including demographic, cultural, and health belief/behavior factors. System-level barriers were the next commonly cited, particularly failure to use the full capability of electronic medical records (EMRs) and problems coordinating with external labs or providers. Provider-level barriers were least frequently cited.

U.S. health centers provide primary and preventive care to underserved populations, including low-income and uninsured patients. The purpose of this study is to examine patterns of publicly funded health center use according to patient insurance status (private, public, none), prior to implementation of the Affordable Care Act.National data came from the 2009 Health Center Patient Survey, and were analyzed in 2013. Descriptive analysis of health center patient insurance coverage and health center utilization variables was conducted, followed by adjusted multivariate analysis.About 91% of uninsured patients received at least half their annual healthcare visits at a health center, and 86% had at least one usual source of care that included a health center; these rates were not significantly different from those for publicly or privately insured patients. About half of uninsured patients (48%) had long tenures at the health center (≥3 years since first visit), not significantly different from the publicly insured (52%), but lower than the privately insured (63%, p0.01). Uninsured patients highlighted affordability as the main reason for visiting a health center, whereas insured patients emphasized convenient location and quality of care.Insured patients used health centers for the majority of their care, and in similar proportions to their uninsured counterparts. The primary motivation for visiting a health center differed based on insurance type. Future studies should be able to examine whether health center demand across insurance categories follows a similar pattern following the Affordable Care Act insurance coverage expansions.