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 (< 1% vs. 13%) among SUD patients. The results indicate the utility of integration and related intervention services in primary care settings to improve service use and reduce ED and hospitalization among MH/SUD patients.

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.

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.

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.

Background

Millions 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.

Methods

We 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.

Results

Hypertension-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).

Conclusions

Our findings suggested that increased focus on these practices may lead to better hypertension outcomes among patients who are low-income and uninsured populations.

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.

Objectives

Existing literature indicates that multimorbidity, mental health (MH) conditions, substance use disorders (SUDs), and social determinants of health are hallmarks of high-need, high-cost patients. Health Resources and Services Administration-funded health centers (HCs) provide care to nearly 30 million patients, but data on their patients' complexity and utilization patterns are limited. We identified subgroups of HC patients based on latent concepts of complexity and utilization.

Study design

We used cross-sectional national data from the 2014 Health Center Patient Survey and latent class analyses to identify distinct and homogenous groups of complex high-utilizing patients aged 18 to 64 years.

Methods

We included indicators of chronic conditions (CCs), MH, SUD risk, and health behavior to measure complexity. We used number of outpatient and emergency department visits in the past year to measure utilization.

Results

HC patients were separated in 9 distinct groups based on 3 complexity latent classes (MH, multiple CCs, and low risk) and 3 utilization classes (low, high, and superutilizers). Conditions associated with each subgroup differed. The highest prevalence of bipolar disorder (45%) and high SUD risk (6%) was observed among MH superutilizers, whereas the highest prevalence of cardiovascular disease (48%) and obesity (96%) was seen among CC superutilizers. Most MH superutilizer patients concurrently had MH conditions and obesity and were smokers, but most CC superutilizer patients concurrently had hypertension, obesity, and cardiovascular disease.

Conclusions

Our examination of complexity and utilization indicated distinct HC patient populations. Managing the care of each group may require different targeted intervention approaches such as multidisciplinary care teams that include MH providers or specialists.

Background

Evidence 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).

Objective

We 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 design

We 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.

Sample

We 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.

Measures

Dependent 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.

Results

We 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.

Conclusions

HRSA 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.

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.

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.