Using State All-Payer Claims Data to Identify the Active Primary Care Workforce: A Novel Study in Virginia.

PURPOSE: Primary care is the foundation of the health care workforce and the only part that extends life and improves health equity. Previous research on the geographic and specialty distribution of physicians has relied on the American Medical Association's Masterfile, but these data have limitations that overestimate the workforce. METHODS: We present a pragmatic, systematic, and more accurate method for identifying primary care physicians using the National Plan and Provider Enumeration System (NPPES) and the Virginia All-Payer Claims Database (VA-APCD). Between 2015 and 2019, we identified all Virginia physicians and their specialty through the NPPES. Active physicians were defined by at least 1 claim in the VA-APCD. Specialty was determined hierarchically by the NPPES. Wellness visits were used to identify non-family medicine physicians who were providing primary care. RESULTS: In 2019, there were 20,976 active physicians in Virginia, of whom 5,899 (28.1%) were classified as providing primary care. Of this primary care physician workforce, 52.4% were family medicine physicians; the remaining were internal medicine physicians (18.5%), pediatricians (16.8%), obstetricians and gynecologists (11.8%), and other specialists (0.5%). Over 5 years, the counts and relative percentages of the workforce made up by primary care physicians remained relatively stable. CONCLUSIONS: Our novel method of identifying active physicians with a primary care scope provides a realistic size of the primary care workforce in Virginia, smaller than some previous estimates. Although the method should be expanded to include advanced practice clinicians and to further delineate the scope of practice, this simple approach can be used by policy makers, payers, and planners to ensure adequate primary care capacity.

Chronic Opioid Prescribing in Primary Care: Factors and Perspectives.

BACKGROUND: Primary care clinicians write 45% of all opioid prescriptions in the United States, but little is known about the characteristics of patients who receive them and the clinicians who prescribe opioids in primary care settings. Our study aimed to describe the patient and clinician characteristics and clinicians' perspectives of chronic opioid prescribing in primary care. METHODS: Using a mixed methods approach, we completed an analysis of 2016 electronic health records from 21 primary care practices to identify patients who had received chronic opioids, which we defined as in receipt of an opioid prescription for at least 3 consecutive months. We compared those receiving chronic opioids with those not in terms of their demographics, prescribing clinician characteristics, and risk factors for opioid-related harms, as identified by the Centers for Disease Control and Prevention Guideline on Opioid Prescribing for Chronic Pain. We then interviewed 16 primary care clinicians about their perspectives on chronic opioid prescribing. RESULTS: Of 84,029 patients, 1.1% (902/84,929) received chronic opioid prescriptions. Characteristics associated with being prescribed chronic opioids include being female, being of black or African American race, and having risks for opioid-related harms, such as mental health diagnoses, substance use disorder, and concurrent benzodiazepine use. Clinicians report multiple difficulties in weaning patients from chronic opioids, including medical contraindications of nonopioid alternatives and difficulty justifying weaning by stable long-term patients. CONCLUSION: Although patients prescribed opioids in primary care have higher risks of opioid-related harms, clinicians report multiple barriers in deprescribing chronic opioids. Future studies should examine strategies to mitigate these harms and engage patients in shared decision making about their chronic opioid use.

Feasibility of Patient Navigation for Care Planning in Primary Care.

OBJECTIVES: To help better control chronic conditions we need to address root causes of poor health like unhealthy behaviors, mental health, and social needs. However, addressing these needs in primary care is difficult. One solution may be connecting patients with a navigator for support creating a personal care goal. METHODS: As part of an RCT to evaluate a feasible approach to care planning, 24 clinicians from 12 practices in the Virginia Ambulatory Care Outcomes Research Network (ACORN) and 87 intervention patients with uncontrolled chronic conditions participated in a care planning intervention. We had a structured process to guide patients, train navigators, and adapt the navigation process to meet the needs of each practice. RESULTS: Only 1 practice had bandwidth for staff to serve as a patient navigator, even for extra pay. For the other 11 practices, a research team member needed to provide navigation services. On average, patients wanted 25 weeks of support to complete care plans. The average time patients needed to speak with navigators on the phone was 7 min and 3 s. In exit interviews, patients consistently shared how motivational it was to have a caring person check in on them, offer help, and hold them accountable. CONCLUSION: Patient navigation to address care plans should be feasible. The time commitment is minimal. It does not require intensive training, and primary care is already doing much of this work. Yet, given the burden and competing demands in primary care, this help cannot be offered without additional resources.

Enhanced care planning and clinical-community linkages versus usual care to address basic needs of patients with multiple chronic conditions: a clinician-level randomized controlled trial.

BACKGROUND: Many patients with poorly controlled multiple chronic conditions (MCC) also have unhealthy behaviors, mental health challenges, and unmet social needs. Medical management of MCC may have limited benefit if patients are struggling to address their basic life needs. Health systems and communities increasingly recognize the need to address these issues and are experimenting with and investing in new models for connecting patients with needed services. Yet primary care clinicians, whose regular contact with patients makes them more familiar with patients' needs, are often not included in these systems. METHODS: We are starting a clinician-level cluster-randomized controlled trial to evaluate how primary care clinicians can participate in these community and hospital solutions and whether doing so is effective in controlling MCC. Sixty clinicians in the Virginia Ambulatory Care Outcomes Research Network will be matched by age and sex and randomized to usual care (control condition) or enhanced care planning with clinical-community linkage support (intervention). From the electronic health record we will identify all patients with MCC, including cardiovascular disease or risks, diabetes, obesity, or depression. A baseline assessment will be mailed to up to 50 randomly selected patients for each clinician (3000 total). Ten respondents per clinician (600 patients total) with uncontrolled MCC will be randomly selected for study inclusion, with oversampling of minorities. The intervention includes two components. First, we will use an enhanced care planning tool, My Own Health Report (MOHR), to screen patients for health behavior, mental health, and social needs. Patients will be supported by a patient navigator, who will help patients prioritize needs, create care plans, and write a personal narrative to guide the care team. Patients will update care plans every 1 to 2 weeks. Second, we will create community-clinical linkage to help address patients' needs. The linkage will include community resource registries, personnel to span settings (patient navigators and a community health worker), and care team coordination across team members through MOHR. DISCUSSION: This study will help inform efforts by primary care clinicians to help address unhealthy behaviors, mental health needs, and social risks as a strategy to better control MCC. TRIAL REGISTRATION: ClinicalTrials.gov: NCT03885401. Registered on 19 September 2019.

Clinician Experiences with Screening for Social Needs in Primary Care.

BACKGROUND: Despite clear evidence demonstrating the influence of social determinants on health, whether and how clinicians should address these determinants remain unclear. We aimed to understand primary care clinicians' experiences of administering a social needs screening instrument. METHODS: Using a prospective, observational design, we identified patients living in communities with lower education and income seen by 17 clinicians from 12 practices in northern Virginia. Before office visits, patients completed social needs surveys, which probed about their quality of life, education, housing, finances, substance use, transportation, social connections, physical activity, and food access. Clinicians then reviewed the completed surveys with patients. Concurrently, clinicians participated in a series of learning collaboratives to consider how to address social needs as part of care and completed diary entries about how knowing the patient's social needs influenced care after seeing each patient. RESULTS: Out of a total of 123 patients, 106 (86%) reported a social need. Excluding physical activity, 71% reported a social need, although only 3% wanted help. Clinicians reported that knowing the patient had a social need changed care delivery in 23% of patients and helped improve interactions with and knowledge of the patient in 53%. Clinicians reported that assessing social needs is difficult and resource intensive and that there were insufficient resources to help patients with identified needs. CONCLUSIONS: Clinicians reported that knowing patients' social needs changed what they did and improved communication for many patients. However, more evidence is needed regarding the benefit of social needs screening in primary care before widespread implementation.

MyPreventiveCare: implementation and dissemination of an interactive preventive health record in three practice-based research networks serving disadvantaged patients--a randomized cluster trial.

BACKGROUND: Evidence-based preventive services for early detection of cancer and other health conditions offer profound health benefits, yet Americans receive only half of indicated services. Policy initiatives promote the adoption of information technologies to engage patients in care. We developed a theory-driven interactive preventive health record (IPHR) to engage patients in health promotion. The model defines five levels of functionality: (1) collecting patient information, (2) integrating with electronic health records (EHRs), (3) translating information into lay language, (4) providing individualized, guideline-based clinical recommendations, and (5) facilitating patient action. It is hypothesized that personal health records (PHRs) with these higher levels of functionality will inform and activate patients in ways that simpler PHRs cannot. However, realizing this vision requires both technological advances and effective implementation based upon clinician and practice engagement. METHODS/DESIGN: We are starting a two-phase, mixed-method trial to evaluate whether the IPHR is scalable across a large number of practices and how its uptake differs for minority and disadvantaged patients. In phase 1, 40 practices from three practice-based research networks will be randomized to add IPHR functionality to their PHR versus continue to use their existing PHR. Throughout the study, we will engage intervention practices to locally tailor IPHR content and learn how to integrate new functions into their practice workflow. In phase 2, the IPHR to all nonintervention practices to observe whether the IPHR can be implemented more broadly (Scalability). Phase 1 will feature an implementation assessment in intervention practices, based on the RE-AIM model, to measure Reach (creation of IPHR accounts by patients), Adoption (practice decision to use the IPHR), Implementation (consistency, fidelity, barriers, and facilitators of use), and Maintenance (sustained use). The incremental effect of the IPHR on receipt of cancer screening tests and shared decision-making compared to traditional PHRs will assess Effectiveness. In phase 2, we will assess similar outcomes as phase 1 except for effectiveness. DISCUSSION: This study will yield information about the effectiveness of new health information technologies designed to actively engage patients in their care as well as information about how to effectively implement and disseminate PHRs by engaging clinicians. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02138448.