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Objective: To describe telemedicine use patterns and understand clinic’s approaches to shifting care delivery during the COVID-19 pandemic.Methods: We used electronic health record data from 203 community health centers across 13 states between 01/01/2019 and 6/31/2021 to describe trends in telemedicine visit rates over time. Qualitative data were collected from 13 of those community health centers to understand factors influencing adoption and implementation of telemedicine.Results: Most clinics in our sample were in urban areas (n = 176) and served a majority of uninsured and publicly insured patients (12.8% and 44.4%, respectively) across racial and ethnic minority groups (16.6% Black and 29.3% Hispanic). During our analysis period there was a 791% increase in telemedicine visits from before the pandemic (.06% pre- vs 47.5% during). A latent class growth analysis was used to examine differences in patterns of adoption of telemedicine across the 203 CHCs. The model resulted in 6 clusters representing various levels of telemedicine adoption. A mixed methods approach streamlined these clusters into 4 final groups. Clinics that reported rapid adoption of telemedicine attributed this change to leadership prioritization of telemedicine, robust quality improvement processes (eg, using PDSA processes), and emphasis on training and technology support.Conclusions: In response to the COVID-19 pandemic, telemedicine adoption rates varied across clinics. Our study highlight that organizational factors contributed to the clinic’s ability to rapidly uptake and use telemedicine services throughout the pandemic. These approaches could inform future non-pandemic practice change and care delivery.

Aims: Children of parents with substance use and/or other mental health (SU/MH) diagnoses are at increased risk for health problems. It is unknown whether these children benefit from receiving primary care at the same clinic as their parents. Thus, among children of parents with >1 SU/MH diagnosis, we examined the association of parent-child clinic concordance with rates of well-child checks (WCCs) and childhood vaccinations.Design: Retrospective cohort study using electronic health record (EHR) data from the OCHIN network of community health organizations (CHOs), 2010-2018. Setting:280 CHOs across 17 states.Participants/Cases: 41,413 parents with >1 SU/MH diagnosis, linked to 65,417 children aged 0 to 17 years, each with >1 visit to an OCHIN clinic during the study period.Measurements: Dependent variables: rates of WCCs during (1) the first 15 months of life, and (2) ages 3 to 17 years; vaccine completeness (3) by the age of 2, and (4) before the age of 18. Estimates were attained using generalized estimating equations Poisson or logistic regression.Findings: Among children utilizing the same clinic as their parent versus children using a different clinic (reference group), we observed greater WCC rates in the first 15 months of life [adjusted rate ratio (aRR) = 1.06; 95% confidence interval (CI) = 1.02-1.10]; no difference in WCC rates in ages 3 to 17; higher odds for vaccine completion before age 2 [adjusted odds ratio (aOR) = 1.12; 95% CI = 1.03-1.21]; and lower odds for vaccine completion before age 18 (aOR = 0.88; 95% CI = 0.81-0.95).Conclusion: Among children whose parents have at least one SU/MH diagnosis, parent-child clinic concordance was associated with greater rates of WCCs and higher odds of completed vaccinations for children in the youngest age groups, but not the older children. This suggests the need for greater emphasis on family-oriented healthcare for young children of parents with SU/MH diagnoses; this may be less important for older children.

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Objective: When prescribed with opioids, sedative-hypnotics substantially increase the risk of overdose. The objective of this paper was to describe characteristics and trends in opioid sedative-hypnotic co-prescribing in a network of safety-net clinics serving low-income, publicly insured, and uninsured individuals.Methods: This retrospective longitudinal analysis of prescription orders examined opioid sedative-hypnotic co-prescribing rates between 2009 and 2018 in the OCHIN network of safety-net community health centers. Sedative-hypnotics included benzodiazepine and non-benzodiazepine sedatives (eg, zolpidem). Co-prescribing patterns were assessed overall and across patient demographic and co-morbidity characteristics.Results: From 2009 to 2018, 240 587 patients had ≥1 opioid prescriptions. Most were White (65%), female (59%), and had Medicaid insurance (43%). One in 4 were chronic opioid users (25%). During this period, 55 332 (23%) were co-prescribed a sedative-hypnotic. The prevalence of co-prescribing was highest for females (26% vs 19% for males), non-Hispanic Whites (28% vs 13% for Hispanic to 20% for unknown), those over 44 years of age (25% vs 20% for <44 years), Medicare insurance (30% vs 21% for uninsured to 22% for other/unknown), and among those on chronic opioid therapy (40%). Co-prescribing peaked in 2010 (32%) and declined steadily through 2018 (20%). Trends were similar across demographic subgroups. Co-prescribed sedative-hypnotics remained elevated for those with chronic opioid use (27%), non-Hispanic Whites (24%), females (23%), and those with Medicare (23%) or commercial insurance (22%).Conclusions: Co-prescribed sedative-hypnotic use has declined steadily since 2010 across all demographic subgroups in the OCHIN population. Concurrent use remains elevated in several population subgroups.

Objective: To identify the patient- and clinic-level correlates of any prescription opioid use, chronic use, and high-dose opioid use in a multi-state network of Community Health Centers (CHCs).Methods: We used electronic health record data from 337 primary care clinics serving 610 983 patients across 15 states in 2018. The primary outcomes were prescription of any opioid, chronic opioid, and high-dose opioid.Results: Overall, 6.5% of patients were prescribed an opioid; of these, 31% were chronic users and 5% were high-dose users. Males had 5% lower odds (Odds Ratio [OR] = 0.95; 95% Confidence Interval = 0.93-0.97) of being prescribed an opioid but 16% higher odds (OR = 1.16; 95% CI = 1.10-1.21) of being chronic users and 48% (OR = 1.48; 95% CI = 1.36-1.64) higher odds of being high-dose users than females. Rural clinics had higher rates of chronic opioid (rate ratio = 1.86; 95% CI = 1.20, 2.88) and high-dose users (rate ratio = 2.95; 95% CI = 1.81-4.81).Conclusions: Our study highlights variations in opioid prescribing with regard to patient-level and clinic-level factors. Targeted efforts and resources may be required to support rural CHCs who seek to reduce high-risk opioid prescribing.

To examine trends in health insurance type among US children and their parents.

Despite its focus on adults, the Affordable Care Act (ACA) Medicaid expansion led to increased health insurance enrollment for children in the United States. Previous studies looked at parent and child insurance changes separately, or used a single survey response item to understand changes in health insurance for parents and children. It is, however, important to understand the connection between parent and child insurance changes together (not individually) using data sources that account for insurance over time. Therefore, to understand the association of parental health insurance on their children’s coverage, leveraging a cohort of linked families seen in community health centers (CHCs), we used electronic health records to link a cohort of parents and children with ≥1 visit to a CHC in a Medicaid expansion state pre- (1/1/2012–12/31/2013) and ≥1 visit post-ACA (1/1/2014–12/31/2018) and determined primary payer type for all visits. This observational, cohort study assessed the rate of insured visits for children pre- to post-ACA across four parental insurance groups (always insured, gained Medicaid, discontinuously insured, never insured) using Poisson mixed effects models. We included 335 CHCs across 7 United States. Insurance rates were highest (~95 insured visits/100 visits) for children of parents who were always insured; rates were lowest for children of parents who were never insured (~83 insured visits/100 visits). Children with a parent who gained Medicaid had 4.4% more insured visits post- compared to pre-ACA (adjusted relative rates  = 1.044, 95% confidence interval: 1.014, 1.074). When comparing changes from pre- to post-ACA between parent insurance groups, children’s insured visit rates were significantly higher for children of parents who gained Medicaid (reference) compared to children of parents who were always insured (adjusted ratio of rate ratio: 0.963, confidence interval: 0.935–0.992). Despite differences in Medicaid eligibility for children and adults, health insurance patterns were similar for linked families seen in CHCs. Findings suggest consideration should be paid to parent health insurance options when trying to increase children’s coverage.