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ObjectiveTo describe the participation of racial and ethnic minority groups (REMGs) in gynecologic oncology trials.MethodsGynecologic oncology studies registered on ClinicalTrials.gov between 2007 and 2020 were identified. Trials with published results were analyzed based on reporting of race/ethnicity in relation to disease site and trial characteristics. Expected enrollment by race/ethnicity was calculated and compared to actual enrollment, adjusted for 2010 US Census population data.Results2146 gynecologic oncology trials were identified. Of published trials (n = 252), 99 (39.3%) reported race/ethnicity data. Recent trials were more likely to report these data (36% from 2007 to 2009; 51% 2013-2015; and 53% from 2016 to 2018, p = 0.01). Of all trials, ovarian cancer trials were least likely to report race/ethnicity data (32.1% vs 39.3%, p = 0.011). Population-adjusted under-enrollment for Blacks was 7-fold in ovarian cancer, Latinx 10-fold for ovarian and 6-fold in uterine cancer trials, Asians 2.5-fold in uterine cancer trials, and American Indian and Alaska Native individuals 6-fold in ovarian trials. Trials for most disease sites have enrolled more REMGs in recent years - REMGs made up 19.6% of trial participants in 2007-2009 compared to 38.1% in 2016-2018 (p

PurposeNearly 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.MethodsWe 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.ResultsRural 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.ConclusionsObserved 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.

ObjectivesExisting 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 designWe 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.MethodsWe 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.ResultsHC 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.ConclusionsOur 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.

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.

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 (n = 5006) 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.

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.

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.

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.

Policy makers are increasingly investing in programs focused on identifying and addressing the nonmedical needs of high-utilizing Medicaid beneficiaries, yet little is known about these programs' implementation. This study provides an overview of early progress in and strategies used to implement California's Whole Person Care (WPC) Pilot Program, a $3 billion Medicaid Section 1115(a) waiver demonstration project focused on improving the integrated delivery of health, behavioral health, and social services for Medicaid beneficiaries who use acute and costly services in multiple service sectors. WPC pilots reported significant progress in developing partnerships, data-sharing infrastructure, and services needed to coordinate care for identified patient populations. We also identified major barriers to WPC implementation, such as difficulty identifying and engaging eligible beneficiaries and the lack of affordable housing. Our findings offer insights to leaders and policy makers interested in testing new approaches for improving the health and well-being of medically and socially complex patients.

BackgroundThe 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 findingsWe 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.ConclusionsThe 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.

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.

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.

A series of actinide-transition metal heterobimetallics has been prepared, featuring thorium, uranium and cobalt. Complexes incorporating the binucleating ligand N[-(NHCH2PiPr2)C6H4]3 and Th(IV) (4) or U(IV) (5) with a carbonyl bridged [Co(CO)4]- unit were synthesized from the corresponding actinide chlorides (Th: 2; U: 3) and Na[Co(CO)4]. Irradiation of the isocarbonyls with ultraviolet light resulted in the formation of new species containing actinide-metal bonds in good yields (Th: 6; U: 7); this photolysis method provides a new approach to a relatively rare class of complexes. Characterization by single-crystal X-ray diffraction revealed that elimination of the bridging carbonyl is accompanied by coordination of a phosphine arm from the N4P3 ligand to the cobalt center. Additionally, actinide-cobalt bonds of 3.0771(5) and 3.0319(7) for the thorium and uranium complexes, respectively, were observed. The solution state behavior of the thorium complexes was evaluated using 1H, 1H-1H COSY, 31P and variable-temperature NMR spectroscopy. IR, UV-Vis/NIR, and variable-temperature magnetic susceptibility measurements are also reported.

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. [ABSTRACT FROM AUTHOR]