The Ability of Primary Care Practices to Measure and Report on Care Quality.

BACKGROUND: Creating useful clinical quality measure (CQM) reports in a busy primary care practice is known to depend on the capability of the electronic health record (EHR). Two other domains may also contribute: supportive leadership to prioritize the work and commit the necessary resources, and individuals with the necessary health information technology (IT) skills to do so. Here we describe the results of an assessment of the above 3 domains and their associations with successful CQM reporting during an initiative to improve smaller primary care practices' cardiovascular disease CQMs. METHODS: The study took place within an AHRQ EvidenceNOW initiative of external support for smaller practices across Washington, Oregon and Idaho. Practice facilitators who provided this support completed an assessment of the 3 domains previously described for each of their assigned practices. Practices submitted 3 CQMs to the study team: appropriate aspirin prescribing, use of statins when indicated, blood pressure control, and tobacco screening/cessation. RESULTS: Practices with advanced EHR reporting capability were more likely to report 2 or more CQMs. Only one-third of practices were "advanced" in this domain, and this domain had the highest proportion of practices (39.1%) assessed as "basic." The presence of advanced leadership or advanced skills did not appreciably increase the proportion of practices that reported 2 or more CQMs. CONCLUSIONS: Our findings support previous reports of limited EHR reporting capabilities within smaller practices but extend these findings by demonstrating that practices with advanced capabilities in this domain are more likely to produce CQM reports.

Medication-based treatment among rural, primary care patients diagnosed with opioid use disorder and alcohol use disorder.

INTRODUCTION: Opioid and alcohol use disorders are increasingly being addressed in primary care, yet how medications to treat these disorders are prescribed in rural regions is unknown. METHODS: We determined prevalence, types, and duration of medication prescription for opioid and/or alcohol use disorder among adult patients in rural primary clinics. The sample included 1874 adult patients who visited one of six rural primary care sites in the Northeastern and Northwestern United States at least once from October 2019 to January 2021 and had a diagnosis code for opioid use disorder (OUD), alcohol use disorder (AUD), or co-occurring opioid and alcohol use disorder (OUD + AUD) during that time. RESULTS: Patients with OUD + AUD were more likely to be prescribed medication for at least one of these disorders (85.3 %) than patients with OUD only (63.7 %) or AUD only (10.3 %). Further, the OUD + AUD group had the highest number of days on medication (M = 264.7), followed by OUD only (M = 220.5), then the AUD only group (M = 62.5). Only 8.8 % of patients with OUD + AUD were prescribed naltrexone or medication for OUD + AUD to treat both substance use disorders. CONCLUSIONS: Medications for treating AUD as well as OUD are available, but few patients with OUD + AUD and even fewer with AUD received pharmacological treatment for AUD. The current work highlights the need for rural clinicians to consider medications for AUD as an important treatment method for patients with AUD only or OUD + AUD.

Social Determinants of Health and Continuity of Medications for Opioid Use Disorder Among Patients Receiving Treatment in Rural Primary Care Settings.

OBJECTIVES: Factors associated with treatment retention on medications for opioid use disorder (MOUD) in rural settings are poorly understood. This study examines associations between social determinants of health (SDoH) and MOUD retention among patients with opioid use disorder (OUD) in rural primary care settings. METHODS: We analyzed patient electronic health records from 6 rural clinics. Participants (N = 575) were adult patients with OUD and had any prescription for MOUD from October 2019 to April 2020. MOUD retention was measured by MOUD days and continuity defined as continuous 180 MOUD days with no more than a 7-day gap. Mixed-effect regressions assessed associations between the outcomes and SDoH (Medicaid insurance, social deprivation index [SDI], driving time from home to the clinic), telehealth use, and other covariates. RESULTS: Mean patient MOUD days were 127 days (SD = 50.7 days). Living in more disadvantaged areas (based on SDI) (adjusted relative risk [aRR]: 0.98; 95% confidence interval [CI], 0.98-0.99) and having more than an hour (compared with an hour or less) driving time from home to clinic (aRR: 0.95; 95% CI, 0.93-0.97) were associated with fewer MOUD days. Using telehealth was associated with more MOUD days (aRR: 1.23; 95% CI, 1.21-1.26). In this cohort, 21.7% of the participants were retained on MOUD for at least 180 days. SDoH and use of telehealth were not associated with having continuity of MOUD. CONCLUSIONS: Addressing SDoH (eg, SDI) and providing telehealth (eg, improvements in public transportation, internet access) may improve MOUD days in rural settings.

Referral of patients from rural primary care clinics to telemedicine vendors for opioid use disorder treatment: A mixed-methods study.

INTRODUCTION: Rural primary care clinics can expand their medication treatment for opioid use disorder (MOUD) capacity by coordinating care with external telemedicine (TM) vendors specializing in addiction medicine. This study used mixed methods to identify factors that influence patient referrals from rural primary care clinics to TM vendors for MOUD. METHODS: Between July/August 2020 and January/February 2021, 582 patients with OUD were identified across six primary care sites; that included 68 referred to an external TM vendor to receive MOUD. Mixed effects logistic regression identified individual and site-level factors associated with being referred to the TM vendor. Clinic providers and staff participated in in-depth interviews and focus groups to discuss their considerations for referring patients to the TM vendor. RESULTS: Patient referrals were positively associated with local household broadband coverage (OR = 2.55, p < 0.001) and negatively associated with local population density (OR = 0.01, p = 0.003) and the number of buprenorphine prescribers in the county (OR = 0.85, p < 0.001). Clinic personnel expressed appreciation for psychiatric expertise and the flexibility to access MOUD brought by the TM vendor. Perceived concerns about TM referral included a lack of trust with external providers, uncertainty about TM service quality, workflow delays, and patients' technological and insurance challenges. CONCLUSION: This study revealed several clinic-level factors that may potentially influence patient referral to TM vendor services for MOUD. To facilitate the referral process and utilization of TM vendors, efforts should be made to foster open communication and trust between clinic providers and TM vendors, streamline workflows, and improve Internet access for patients.

Medication treatment for opioid use disorder among rural primary care patients.

PURPOSE: To investigate the prevalence of opioid use disorder (OUD) and medication treatment for OUD (MOUD) receipt in rural primary care settings and identify characteristics associated with MOUD among patients with OUD. METHODS: Secondary analyses based on electronic health records of all adult patients who visited 1 of the 6 rural primary care clinic sites from October 2019 to January 2021. Mixed effects logistic regression was conducted to assess MOUD receipt (Y/N) in relation to patient characteristics (eg, demographics, other substance use disorders [SUDs], mental health disorders, and chronic pain) and the number of MOUD prescribers per clinic. FINDINGS: The prevalence of OUD varied from 0.7% to 8.2% (Mean [SD] = 3.3% [95% CI: 0.4, 6.1]) among 36,762 primary care patients across 6 clinic sites. Among 1,164 patients with OUD, on average 50.1% received MOUD (95% CI: 28.0, 72.3). Patients in clinics with more than 3 MOUD prescribers had more than 3 times the odds of receiving MOUD (OR = 3.42; 95% CI, 1.22-9.62) as those in clinics with fewer than 3 prescribers. MOUD was positively associated with younger age (18-30 [OR = 6.97; 95% CI, 3.37-14.42], 31-64 [OR = 5.03; 95% CI, 2.64-9.57], relative to those 65 and older), having other co-occurring SUDs (OR = 3.77; 95% CI, 2.57-5.52), being male (OR = 1.50; 95% CI, 1.12-2.01), and negatively associated with having chronic pain disorders (OR = 0.69; 95% CI, 0.50-0.94). CONCLUSIONS: The prevalence of OUD and MOUD are high but vary considerably across rural primary care clinics; primary care MOUD prescribers play a key role on MOUD access in rural settings.

Identifying patients with opioid use disorder using International Classification of Diseases (ICD) codes: Challenges and opportunities.

BACKGROUND AND AIMS: International Classification of Diseases (ICD) diagnosis codes are often used in research to identify patients with opioid use disorder (OUD), but their accuracy for this purpose is not fully evaluated. This study describes application of ICD-10 diagnosis codes for opioid use, dependence and abuse from an electronic health record (EHR) data extraction using data from the clinics' OUD patient registries and clinician/staff EHR entries. DESIGN: Cross-sectional observational study. SETTING: Four rural primary care clinics in Washington and Idaho, USA. PARTICIPANTS: 307 patients. MEASUREMENTS: This study used three data sources from each clinic: (1) a limited dataset extracted from the EHR, (2) a clinic-based registry of patients with OUD and (3) the clinician/staff interface of the EHR (e.g. progress notes, problem list). Data source one included records with six commonly applied ICD-10 codes for opioid use, dependence and abuse: F11.10 (opioid abuse, uncomplicated), F11.20 (opioid dependence, uncomplicated), F11.21 (opioid dependence, in remission), F11.23 (opioid dependence with withdrawal), F11.90 (opioid use, unspecified, uncomplicated) and F11.99 (opioid use, unspecified with unspecified opioid-induced disorder). Care coordinators used data sources two and three to categorize each patient identified in data source one: (1) confirmed OUD diagnosis, (2) may have OUD but no confirmed OUD diagnosis, (3) chronic pain with no evidence of OUD and (4) no evidence for OUD or chronic pain. FINDINGS: F11.10, F11.21 and F11.99 were applied most frequently to patients who had clinical diagnoses of OUD (64%, 89% and 79%, respectively). F11.20, F11.23 and F11.90 were applied to patients who had a diagnostic mix of OUD and chronic pain without OUD. The four clinics applied codes inconsistently. CONCLUSIONS: Lack of uniform application of ICD diagnosis codes make it challenging to use diagnosis code data from EHR to identify a research population of persons with opioid use disorder.

Co-occurring substance use disorders among patients with opioid use disorder in rural primary care clinics.

BACKGROUND: Co-occurring substance use disorders (SUDs) among individuals with opioid use disorder (OUD) are associated with additional impairment, overdose, and death. This study examined characteristics of patients who have OUD with and without co-occurring SUDs in rural primary care clinics. METHODS: Secondary analysis used electronic health record (EHR) data from six rural primary care clinics, including demographics, diagnoses, encounters, and prescriptions of medication for OUD (MOUD), as well as EHR data from an external telemedicine vendor that provided MOUD to some clinic patients. The study population included all adult patients who had a visit to the participating clinics from October 2019 to January 2021. RESULTS: We identified 1164 patients with OUD; 72.6 % had OUD only, 11.5 % had OUD and stimulant use disorder (OUD + StUD), and 15.9 % had OUD and other non-stimulant substance use disorder (OUD + Other). The OUD + StUD group had the highest rates of hepatitis C virus (25.4 % for OUD + StUD, 17.8 % for OUD + Other, and 7.5 % for OUD Only; p < 0.001) and the highest rates of mental health disorders (78.4 %, 69.7 %, and 59.9 %, respectively; p < 0.001). Compared to the OUD Only group, patients in the OUD + StUD and OUD + Other groups were more likely to receive telehealth services provided by clinic staff, in-clinic behavioral health services, and in-clinic MOUD. The OUD + StUD group had the highest proportion of referrals to the external telemedicine vendor. CONCLUSIONS: More than 27 % of patients with OUD in rural primary care clinics had other co-occurring SUDs, and these patients received more healthcare services than those with OUD only. Future studies should examine variations in outcomes associated with these other services among patients with OUD and co-occurring SUDs.

Stakeholder perspectives on a telemedicine referral and coordination model to expand medication treatment for opioid use disorder in rural primary care clinics.

INTRODUCTION: Opioid overdose deaths are increasing rapidly in the United States. Medications for opioid use disorder (MOUD) are effective and can be delivered in primary care, but uptake has been limited in rural communities. Referral to and coordination with an external telemedicine (TM) vendor by rural primary care clinics for MOUD (TM-MOUD) may increase MOUD access for rural patients, but we know little about perspectives on this model among key stakeholders. As part of a TM-MOUD feasibility study, we explored TM-MOUD acceptability and feasibility among personnel and patients from seven rural primary care clinics and a TM-MOUD vendor. METHODS: We conducted virtual interviews or focus groups with clinic administrators (n = 7 interviews), clinic primary care and behavioral health providers (8 groups, n = 30), other clinic staff (9 groups, n = 37), patients receiving MOUD (n = 16 interviews), TM-MOUD vendor staff (n = 4 interviews), and vendor-affiliated behavioral health and prescribing providers (n = 17 interviews). We asked about experiences with and acceptability of MOUD (primarily buprenorphine) and telemedicine (TM) and a TM-MOUD referral and coordination model. We conducted content analysis to identify themes and participants quantitatively rated acceptability of TM-MOUD elements on a 4-item scale. RESULTS: Perceived benefits of vendor-based TM-MOUD included reduced logistical barriers, more privacy and less stigma, and access to services not available locally (e.g., counseling, pain management). Barriers included lack of internet or poor connectivity in patients' homes, limited communication and trust between TM-MOUD and clinic providers, and questions about the value to the clinic of TM-MOUD referral to external vendor. Acceptability ratings for TM-MOUD were generally high; they were lowest among frontline staff. CONCLUSIONS: Rural primary care clinic personnel, TM-MOUD vendor personnel, and patients generally perceived referral from primary care to a TM-MOUD vendor to hold potential for increasing access to MOUD in rural communities. Increasing TM-MOUD uptake requires buy-in and understanding among staff of the TM-MOUD workflow, TM services offered, requirements for patients, advantages over clinic-based or TM services from clinic providers, and identification of appropriate patients. Poverty, along with patient hesitation to initiate treatment, creates substantial barriers to MOUD treatment generally; insufficient internet availability creates a substantial barrier to TM-MOUD.

Primary Care Utilization and Cardiovascular Screening in Adult Survivors of Childhood Cancer.

Importance: Cardiovascular disease is the leading noncancer cause of premature death among survivors of childhood cancer. Adult survivors of childhood cancer are largely managed by primary care practitioners (PCPs), and health care utilization patterns related to cardiovascular screening are not well described. Objective: To examine screening and health care utilization among survivors of childhood cancer at high risk for cardiovascular complications. Design, Setting, and Participants: This multicenter cross-sectional study included participants enrolled in a randomized clinical trial from 2017 to 2021. Abstracted documentation of participants' cancer history, cardiotoxic treatment exposures, and survivorship care plans were obtained from participants' PCPs spanning 2 years preceding trial enrollment. Participants were members of the Childhood Cancer Survivor Study cohort at elevated risk for ischemic heart disease or heart failure, enrolled in a randomized trial focused on improving cardiovascular risk factor control. Data were analyzed from November 2022 to July 2023. Main Outcomes and Measures: Outcomes of interest were numbers of PCP and specialist visits, cardiovascular risk factors (hypertension, dyslipidemia, and diabetes), risk factor screening, and cardiac testing. Multivariable logistic regression assessed characteristics associated with up-to-date cardiac testing at enrollment. Results: Of 347 enrolled participants, 293 (84.4%) had evaluable medical records (median [range] age, 39.9 [21.5-65.0] years; 149 [50.9%] male) and were included in analyses. At baseline, 238 participants (81.2%) had a documented PCP encounter; 241 participants (82.3%) had undergone blood pressure screening, 179 participants (61.1%) had undergone lipid testing, and 193 participants (65.9%) had undergone diabetes screening. A total of 63 participants (21.5%) had echocardiography completed or planned. Only 198 participants (67.6%) had records referencing a cancer history. PCP documentation of prior cardiotoxic exposures was low compared with known exposures, including radiation therapy (103 participants [35.2%] vs 203 participants [69.3%]; P < .001) and anthracycline chemotherapy (27 participants [9.2%] vs 222 participants [75.8%]; P = .008). Few records referenced a need for cancer-related late effects surveillance (95 records [32.4%]). Independent factors associated with cardiac screening included documentation of increased cardiovascular disease risk (odds ratio [OR], 11.94; 95% CI, 3.37-42.31), a late-effects surveillance plan (OR, 3.92; 95% CI, 1.69-9.11), and existing cardiovascular risk factors (OR per each additional factor, 2.09; 95% CI, 1.32-3.31). Conclusions and Relevance: This cross-sectional study of adult survivors of childhood cancer at increased risk of cardiovascular disease found low adherence to recommended cardiac testing and documentation of risk for these individuals. Improving accuracy of reporting of survivors' exposures and risks within the medical record may improve screening.

A Cluster Randomized Trial of Primary Care Practice Redesign to Integrate Behavioral Health for Those Who Need It Most: Patients With Multiple Chronic Conditions.

PURPOSE: Patient outcomes can improve when primary care and behavioral health providers use a collaborative system of care, but integrating these services is difficult. We tested the effectiveness of a practice intervention for improving patient outcomes by enhancing integrated behavioral health (IBH) activities. METHODS: We conducted a pragmatic, cluster randomized controlled trial. The intervention combined practice redesign, quality improvement coaching, provider and staff education, and collaborative learning. At baseline and 2 years, staff at 42 primary care practices completed the Practice Integration Profile (PIP) as a measure of IBH. Adult patients with multiple chronic medical and behavioral conditions completed the Patient-Reported Outcomes Measurement Information System (PROMIS-29) survey. Primary outcomes were the change in 8 PROMIS-29 domain scores. Secondary outcomes included change in level of integration. RESULTS: Intervention assignment had no effect on change in outcomes reported by 2,426 patients who completed both baseline and 2-year surveys. Practices assigned to the intervention improved PIP workflow scores but not PIP total scores. Baseline PIP total score was significantly associated with patient-reported function, independent of intervention. Active practices that completed intervention workbooks (n = 13) improved patient-reported outcomes and practice integration (P ≤ .05) compared with other active practices (n = 7). CONCLUSION: Intervention assignment had no effect on change in patient outcomes; however, we did observe improved patient outcomes among practices that entered the study with greater IBH. We also observed more improvement of integration and patient outcomes among active practices that completed the intervention compared to active practices that did not. Additional research is needed to understand how implementation efforts to enhance IBH can best reach patients.

Integrated Behavioral Health in Primary Care Residency and Nonresidency Practices.

BACKGROUND AND OBJECTIVES: Integrated behavioral health (BH) is becoming a preferred model of care for primary care because it improves patient outcomes and satisfaction. Little is known about whether residency practices are consistently modeling this preferred care model relative to real-world nonresidency practices. The study compared levels of BH integration, patient health outcomes, and satisfaction with care between residency practices and nonresidency practices with colocated BH providers. METHODS: Baseline data were collected in 2018-2019 from 44 practices and their adult patients with chronic conditions participating in a cluster-randomized, pragmatic trial to improve BH integration. The sample included 18 (40.9%) residency and 26 (59.1%) nonresidency practices, with 1,817 (45.3%) patients from residency practices and 2,190 (54.7%) patients from nonresidency practices. Outcomes including BH integration levels (the Practice Integration Profile), patient health outcomes (the PROMIS-29), and patient satisfaction with care (the Consultation and Relational Empathy scale) were compared between residency and nonresidency practices using multivariate regression analyses. RESULTS: No differences were found between BH integration levels, patient health outcomes, and patient satisfaction with care between residency and nonresidency practices. In a sample of primary care practices with colocated BH providers, residencies had BH integration and patient outcomes similar to real-world practices. CONCLUSIONS: Primary care practices with residency programs reported comparable levels of BH integration, patient health outcomes, and patient satisfaction compared to practices without residency programs. Both types of practices require interventions and resources to help them overcome challenges associated with dissemination of high levels of BH integration.

Care coordination between rural primary care and telemedicine to expand medication treatment for opioid use disorder: Results from a single-arm, multisite feasibility study.

PURPOSE: The use of telemedicine (TM) has accelerated in recent years, yet research on the implementation and effectiveness of TM-delivered medication treatment for opioid use disorder (MOUD) has been limited. This study investigated the feasibility of implementing a care coordination model involving MOUD delivered via an external TM provider for the purpose of expanding access to MOUD for patients in rural settings. METHODS: The study tested a care coordination model in 6 rural primary care sites by establishing referral and coordination between the clinic and a TM company for MOUD. The intervention spanned approximately 6 months from July/August 2020 to January 2021, coinciding with the peak of the COVID-19 pandemic. Each clinic tracked patients with OUD in a registry during the intervention period. A pre-/post-intervention design (N = 6) was used to assess the clinic-level outcome as patient-days on MOUD based on patient electronic health records. FINDINGS: All clinics implemented critical components of the intervention, with an overall TM referral rate of 11.7% among patients in the registry. Five of the 6 sites showed an increase in patient-days on MOUD during the intervention period compared to the 6-month period before the intervention (mean increase per 1,000 patients: 132 days, P = .08, Cohen's d = 0.55). The largest increases occurred in clinics that lacked MOUD capacity or had a greater number of patients initiating MOUD during the intervention period. CONCLUSIONS: To expand access to MOUD in rural settings, the care coordination model is most effective when implemented in clinics that have negligible or limited MOUD capacity.

Lessons from the implementation of a trauma center-based program to support primary care providers in managing opioids and pain after trauma hospitalization.

Background: Decreasing exposure to prescription opioids is critical to lowering risk of opioid misuse, overdose and opioid use disorder. This study reports a secondary analysis of a randomized controlled trial implementing an opioid taper support program directed to primary care providers (PCPs) of patients discharged from a level I trauma center to their homes distant from the center, and shares lessons for trauma centers in supporting these patients. Methods: This longitudinal descriptive mixed-methods study uses quantitative/qualitative data from trial intervention arm patients to examine implementation challenges and outcomes: adoption, acceptability, appropriateness, feasibility, fidelity. In the intervention, a physician assistant (PA) contacted patients after discharge to review their discharge instructions and pain management plan, confirm their PCP's identity and encourage PCP follow-up. The PA reached out to the PCP to review the discharge instructions and offer ongoing opioid taper and pain management support. Results: The PA reached 32 of 37 patients randomized to the program. Of these 32, 81% discussed topics not targeted by the intervention (eg, social/financial). The PA identified and reached a PCP's office for only 51% of patients. Of these, all PCP offices (100% adoption) received one to four consults (mean 1.9) per patient (fidelity). Few consults were with PCPs (22%); most were with medical assistants (56%) or nurses (22%). The PA reported that it was not routinely clear to patients or PCPs who was responsible for post-trauma care and opioid taper, and what the taper instructions were. Conclusions: This level I trauma center successfully implemented a telephonic opioid taper support program during COVID-19 but adapted the program to allow nurses and medical assistants to receive it. This study demonstrates a critical need to improve care transition from hospitalization to home for patients discharged after trauma. Level of evidence: Level IV.

Tailoring Implementation Strategies for Cardiovascular Disease Risk Calculator Adoption in Primary Care Clinics.

INTRODUCTION: When implementing interventions in primary care, tailoring implementation strategies to practice barriers can be effective, but additional work is needed to understand how to best select these strategies. This study sought to identify clinicians' contributions to the process of tailoring implementation strategies to barriers in clinical settings. METHODS: We conducted a modified nominal group exercise involving 8 implementation scientists and 26 primary care clinicians in the WWAMI region Practice and Research Network. Each group identified implementation strategies it felt would best address barriers to using a cardiovascular disease (CVD) risk calculator previously identified across 44 primary care clinics from the Healthy Hearts Northwest pragmatic trial (2015 to 2018). These barriers had been mapped beforehand to the Consolidated Framework for Implementation Research (CFIR) domains. We examined similarities and differences in the strategies that 30% or more of each group identified (agreed-on strategies) for each barrier and for barriers in each CFIR domain. We used the results to demonstrate how strategies might be tailored to individual clinics. RESULTS: Clinicians selected 23 implementation strategies to address 1 or more of the 13 barriers; implementation scientists selected 35. The 2 groups agreed on at least 1 strategy for barriers in each CFIR domain: Inner Setting, Outer Setting, Intervention Characteristics, Characteristics of Individuals, and Process. Conducting local needs assessment and assessing for readiness/identifying barriers and facilitators were the 2 most common implementation strategies chosen only by clinicians. CONCLUSIONS: Clinician stakeholders identified implementation strategies that augmented those chosen by implementation scientists, suggesting that codesign of implementation processes between implementation scientists and clinicians may strengthen the process of tailoring strategies to overcome implementation barriers.

Payment strategies for behavioral health integration in hospital-affiliated and non-hospital-affiliated primary care practices.

Recent value-based payment reforms in the U.S. called for empirical data on how primary care practices of varying characteristics fund their integrated behavioral health services. To describe payment strategies used by U.S. primary care practices to fund behavioral health integration and compare strategies between practices with and without hospital affiliation.Baseline data were used and collected from 44 practices participating in a cluster-randomized, pragmatic trial of behavioral health integration. Data included practice characteristics and payment strategies-fee-for-service payment, pay-for-performance incentives, grants, and graduate medical education funds. Descriptive and comparative analyses using Fisher's exact tests and independent T-tests were conducted. The sample had 26 (59.1%) hospital-affiliated (hospital/health system-owned, academic medical centers and hospital-affiliated practices) and 18 (40.9%) non-hospital-affiliated practices (community health centers/federally qualified health centers and privately-owned practices). Most practices (88.6%) received payments through fee-for-service; 63.6% received pay-for-performance incentives; 31.8% received grant funds. Collaborative Care Management billing (CPT) codes were used in six (13.6%) practices. Over half (53.8%) of hospital-affiliated practices funded their behavioral health services through fee-for-service and pay-for-performance incentives only, as opposed to two-thirds (66.7%) of non-hospital-affiliated practices required additional support from grants and/or general medical education funds. Primary care practices support behavioral health integration through diverse payment strategies. More hospital-affiliated practices compared to non-hospital-affiliated practices funded integrated behavioral health services through fee-for-service and pay-for-performance incentives. Practices without hospital affiliation relied on multiple funding streams including grants and/or general medical education funds, suggesting their approach to financial sustainment may be more precarious or challenging, compared to hospital-affiliated practices.

Underdiagnosis and Undertreatment of Modifiable Cardiovascular Risk Factors Among Survivors of Childhood Cancer.

Background Determine the prevalence and predictors associated with underdiagnosis and undertreatment of modifiable cardiovascular disease (CVD) risk factors (hypertension, dyslipidemia, glucose intolerance/diabetes) among adult survivors of childhood cancer at high risk of premature CVD. Methods and Results This was a cross-sectional study of adult-aged survivors of childhood cancer treated with anthracyclines or chest radiotherapy, recruited across 9 US metropolitan regions. Survivors completed questionnaires and in-home clinical assessments. The comparator group was a matched sample from the National Health and Nutrition Examination Survey. Multivariable logistic regression estimated the risk (odds ratios) of CVD risk factor underdiagnosis and undertreatment among survivors compared with the National Health and Nutrition Examination Survey. Survivors (n=571; median age, 37.7 years and 28.5 years from cancer diagnosis) were more likely to have a preexisting CVD risk factor than the National Health and Nutrition Examination Survey (n=345; P<0.05 for all factors). While rates of CVD risk factor underdiagnosis were similar (27.1% survivors versus 26.1% National Health and Nutrition Examination Survey; P=0.73), survivors were more likely undertreated (21.0% versus 13.9%, P=0.007; odds ratio, 1.8, 95% CI, 1.2-2.7). Among survivors, the most underdiagnosed and undertreated risk factors were hypertension (18.9%) and dyslipidemia (16.3%), respectively. Men and survivors who were overweight/obese were more likely to be underdiagnosed and undertreated. Those with multiple adverse lifestyle factors were also more likely undertreated (odds ratio, 2.2, 95% CI, 1.1-4.5). Greater health-related self-efficacy was associated with reduced undertreatment (odds ratio, 0.5; 95% CI, 0.3-0.8). Conclusions Greater awareness of among primary care providers and cardiologists, combined with improving self-efficacy among survivors, may mitigate the risk of underdiagnosed and undertreated CVD risk factors among adult-aged survivors of childhood cancer. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT03104543.

Dissemination and implementation science resources, training, and scientific activities provided through CTSA programs nationally: Opportunities to advance D&I research and training capacity.

Introduction: Clinical and Translational Science Award (CTSA) Program hubs are well-positioned to advance dissemination and implementation (D&I) research and training capacity nationally, though little is known about what D&I research support and services CTSAs provide. To address this gap, the CTSA Dissemination, Implementation, and Knowledge Transfer Working Group conducted an environmental scan of CTSAs (2017-2018). Methods: Of 67 CTSA institutions, we contacted 43 that previously reported delivering D&I research services. D&I experts from these institutions were emailed a survey assessing D&I resources, services, training, and scientific projects. Responses were categorized and double-coded by study authors using a content analysis approach. Results: Thirty-five of the 43 D&I experts (81.4%) responded. Challenges to CTSAs in developing and supporting D&I science activities were related to inadequate D&I science workforce (45.7%) and lack of understanding of D&I science (25.7%). Services provided included consultation/mentoring programs (68%), pilot funding/grants (50%), and workshops/seminars/conferences (46%). Training and workforce development in D&I were frequently identified as future priorities. Recommendations included increase training to meet demand (68.6%), accessible D&I tools/resources (34.3%), greater visibility/awareness of D&I methods (34.3%), consultation services (22.9%), and expand D&I science workforce (22.9%). Conclusions: CTSAs have tremendous potential to support the advancement and impact of D&I science across the translational continuum. Despite the growing presence of D&I science in CTSAs, continued commitment and prioritization are needed from CTSA and institutional leadership to raise awareness of D&I science and its value, meet training demands, and develop necessary infrastructure for conducting D&I science.

Early Response of Primary Care Practices to COVID-19 Pandemic.

INTRODUCTION: The emergence of the COVID-19 pandemic and subsequent public health mitigation strategies resulted in rapid and significant changes to delivery of primary care. The field of primary care faced an unprecedented dual challenge of providing routine care to patients while ensuring patient and staff safety and managing patients with a highly transmissible disease. This study describes how a diverse group of primary care practices addressed these challenges at the start of the COVID-19 pandemic, in Spring 2020. METHODS: A cross-sectional electronic survey of representatives from primary care practices in the WWAMI region Practice and Research Network (WPRN). Survey topics included clinical workforce, operations, and use of telemedicine in the first 3 months of the COVID-19 pandemic. RESULTS: To safely manage patients with COVID-19 symptoms all clinics modified operations; 81.3% diverted patients with respiratory symptoms to a telemedicine evaluation, 68.8% diverted these patients to be seen in-person at another location, and 75% made in-clinic changes to maintain safety. The set of operational changes employed by clinics was diverse. To continue to provide routine patient care, all clinics employed telemedicine. Over 80% of clinics had never used telemedicine prior to March 2020. CONCLUSIONS: A diverse group of primary care clinics all rapidly implemented a variety of operational adaptations to address patient needs and maintain patient and staff safety at the onset of the COVID- 19 pandemic. Telemedicine, together with other measures, provided critical pathways for maintaining delivery of care.