37 research outputs found

    Preventive Care and Chronic Disease Management: Comparison of Appalachian and Non-Appalachian Community Health Centers in the United States

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    Introduction: The Appalachian region is often characterized by poor health outcomes and economic depression. Health centers (HCs) are community-based and patient-directed organizations that deliver comprehensive, culturally competent, high-quality primary healthcare services in high need areas, including Appalachia, where economic, geographic, or cultural factors can hinder access to healthcare services. Purpose: The study compares the clinical quality performance in preventive care and chronic disease management between Appalachian HCs and their non-Appalachian counterparts. Methods: Using 2015 Uniform Data System (UDS) health center data, bivariate and multivariate linear regression analyses examine the association of Appalachian HC with performance on preventive and chronic care clinical quality measures (CQMs). Results: In the multivariate analysis, patients served at Appalachian HCs are more likely to receive colorectal cancer screening and pediatric weight assessment and counseling than at non-Appalachian HCs. No statistically significant differences in performance observed among other CQMs. The percentage of Medicaid patients and total physician FTEs have positive associations with preventive care in colorectal and cervical cancer screening, pediatric weight assessment and counseling, and tobacco screening and cessation intervention as well as chronic disease management of aspirin therapy for ischemic vascular disease and hypertension control in the multivariate model. Implications: Overall Appalachian HCs perform as well as or better than non-Appalachian HCs in delivering preventive and chronic care services. Further examination of clinical quality improvement programs, insurance payer mix, and practice size among Appalachian HCs could advance the replication of clinical quality success for clinics in similar underserved communities

    Many Uninsured Children Qualify for Medi-Cal or Healthy Families

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    Examines the public health insurance eligibility of children in California who did not have health insurance coverage for some or all of the year in 2002, to highlight the geographic variations in children's uninsured eligibility rates

    Improving Access to Treatment for Opioid Use Disorder in High-Need Areas: The Role of HRSA Health Centers

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    Introduction: Despite the opioid epidemic adversely affecting areas across the U.S. for more than two decades and increasing evidence that medication-assisted treatment (MAT) is effective for patients with opioid use disorder (OUD), access to treatment is still limited. The limited access to treatment holds true in the Appalachia region despite being disproportionately affected by the crisis, particularly in rural, central Appalachia. Purpose: This research identifies opportunities for health centers located in high-need areas based on drug poisoning mortality to better meet MAT care gaps. We also provide an in-depth look at health center MAT capacity relative to need in the Appalachia region. Methods: The analysis included county-level drug poisoning mortality data (2013–2015) from the National Center for Health Statistics (NCHS)and Health Center Program Awardee and Look-Alike data (2017) on the number of providers with a DATA waiver to provide medication-assisted treatment (MAT) and the number of patients receiving MAT for the U.S. Several geospatial methods were used including an Empirical Bayes approach to estimate drug poisoning mortality, excess risk maps to identify outliers, and the Local Moran’s I tool to identify clusters of high drug poisoning mortality counties. Results: High-need counties were disproportionately located in the Appalachia region. More than 6 in 10 health centers in high-need counties have the potential to expand MAT delivery to patients. Implications: The results indicate an opportunity to increase health center capacity for providing treatment for opioid use disorder in high-need areas, particularly in central and northern Appalachia

    Clinical Quality Indicators of Asian American, Native Hawaiian, and Other Pacific Islander Patients Seen at Health Resources and Services Administration-Supported Community Health Centers

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    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

    Impact of health information technology optimization on clinical quality performance in health centers: A national cross-sectional study.

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    BackgroundDelivery of preventive care and chronic disease management are key components of a high functioning primary care practice. Health Centers (HCs) funded by the Health Resources and Services Administration (HRSA) have been delivering affordable and accessible primary health care to patients in underserved communities for over fifty years. This study examines the association between health center organization's health information technology (IT) optimization and clinical quality performance.Methods and findingsUsing 2016 Uniform Data System (UDS) data, we performed bivariate and multivariate analyses to study the association of Meaningful Use (MU) attestation as a proxy for health IT optimization, patient centered medical home (PCMH) recognition status, and practice size on performance of twelve electronically specified clinical quality measures (eCQMs). Bivariate analysis demonstrated performance of eleven out of the twelve preventive and chronic care eCQMs was higher among HCs attesting to MU Stage 2 or above. Multivariate analysis demonstrated that Stage 2 MU or above, PCMH status, and larger practice size were positively associated with performance on cancer screening, smoking cessation counseling and pediatric weight assessment and counseling eCQMs.ConclusionsOrganizational advancement in MU stages has led to improved quality of care that augments HCs patient care capacity for disease prevention, health promotion, and chronic care management. However, rapid technological advancement in health care acts as a potential source of disparity, as considerable resources needed to optimize the electronic health record (EHR) and to undertake PCMH transformation are found more commonly among larger HCs practices. Smaller practices may lack the financial, human and educational assets to implement and to maintain EHR technology. Accordingly, targeted approaches to support small HCs practices in leveraging economies of scale for health IT optimization, clinical decision support, and clinical workflow enhancements are critical for practices to thrive in the dynamic value-based payment environment

    Mental health status among women of reproductive age from underserved communities in the United States and the associations between depression and physical health. A cross-sectional study.

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    BACKGROUND:In 2017, 46.6 million U.S. adults aged 18 or older self-reported as having mental illness of which 52.0% or 24.2 million are women age 18-49. Perinatal depression and anxiety are linked to adverse outcomes concerning pregnancy, maternal functioning, and healthy child development. METHODS AND FINDINGS:Using the 2014 Health Center Patient Survey (HCPS), the objectives of the cross-sectional study are to assess the prevalence of self-reported mental health conditions among female patients of reproductive age and to examine the association between depression and physical health. Physical health conditions of interest included self-rated health, obesity, hypertension, smoking, and diabetes, which all have established associations with potential pregnancy complications and fetal health. The study found 40.8% of patients reported depression; 28.8% reported generalized anxiety; and 15.2% met the criteria for serious psychological distress on the Kessler 6 scale. Furthermore, patients with depression had two to three times higher odds of experiencing co-occurring physical health conditions. CONCLUSIONS:This study expands the discourse on maternal mental health, throughout the preconception, post-partum, and inter-conception care periods to improve understanding of the inter-correlated physical and mental health issues that could impact pregnancy outcomes and life course trajectory. From 2014 to 2018, the Health Resources and Services Administration (HRSA) has supported investments of nearly $750 million to improve and expand access to mental health and substance use disorder services for prevention, treatment, health education and awareness through comprehensive primary care integration. Moving forward, HRSA will implement strategic training and technical assistance (T/TA) framework that is designed to accelerate the adoption of science driven solutions in primary care in addressing depression for patients with co-occurring chronic conditions and advancing positive maternal outcomes

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

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    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
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