Background: Structural inequities have important implications for the health of marginalized groups. Neighborhood-level redlining and lending bias represent state-sponsored systems of segregation, potential drivers of adverse health outcomes. We sought to estimate the effect of redlining and lending bias on breast cancer mortality and explore differences by race. Methods: Using Georgia Cancer Registry data, we included 4,943 non-Hispanic White (NHW) and 3,580 non-Hispanic Black (NHB) women with a first primary invasive breast cancer diagnosis in metro-Atlanta (2010–2014). Redlining and lending bias were derived for census tracts using the Home Mortgage Disclosure Act database. We calculated hazard ratios and 95% confidence intervals (CI) for the associations of redlining, lending bias on breast cancer mortality and estimated race-stratified associations. Results: Overall, 20% of NHW and 80% of NHB women lived in redlined census tracts, and 60% of NHW and 26% of NHB women lived in census tracts with pronounced lending bias. Living in redlined census tracts was associated with a nearly 1.60-fold increase in breast cancer mortality (hazard ratio = 1.58; 95% CI, 1.37–1.82) while residing in areas with substantial lending bias reduced the hazard of breast cancer mortality (hazard ratio = 0.86; 95% CI, 0.75–0.99). Among NHB women living in redlined census tracts, we observed a slight increase in breast cancer mortality (hazard ratio = 1.13; 95% CI, 0.90–1.42); among NHW women the association was more pronounced (hazard ratio = 1.39; 95% CI, 1.09–1.78). Conclusions: These findings underscore the role of ecologic measures of structural racism on cancer outcomes. Impact: Place-based measures are important contributors to health outcomes, an important unexplored area that offers potential interventions to address disparities.

Primary care panel sizes are an important component of primary care practices. Determining the appropriate panel size has implications for patient access, physician workload, and care comprehensiveness and will have an impact on quality of care. An often quoted standard panel size is 2500. However, this number seems to arise in the literature anecdotally, without a basis in research. Subsequently, multiple studies observed that a panel size of 2500 is not feasible because of time constraints and results in incomplete preventive care and health care screening services. In this article we review the origins of a panel size of 2500, review the subsequent work examining this number and effectively debunking it as a feasible panel size, and discuss the importance of primary care physicians setting an appropriate panel size.

Purpose: Little is known about the attitudes toward and adoption of telehealth services among family physicians (FPs), the largest primary care physician group. We conducted a national survey of FPs, randomly sampled from membership organization files, to investigate use of and barriers to using telehealth services. Methods: Using bivariate analyses, we examined how telehealth usage affected FPs' identified barriers to using telehealth services. Logistic regressions show the factors associated both with using telehealth services and with barriers to using telehealth services. Results: Surveys reached 4980 FPs; 1557 surveys were eligible for analysis (31% response rate). Among FPs, 15% reported using telehealth services during 2014. After controlling for the characteristics of the physicians and their practice, FPs who were based in a rural setting, worked in a practice owned by an integrated health system or other ownership structure, and provided hospital/urgent/emergency care were more likely to use telehealth. Physician and practice characteristics by telehealth use status, sex of the physician, practice location, years in practice, care provided, and practice ownership were associated with the barriers identified. Conclusions: Telehealth use was limited among FPs. Many of the barriers to using telehealth services cited by FPs are amenable to policy modification.

Background: Telehealth has the potential to reduce health inequities and improve health outcomes among rural populations through increased access to physicians, specialists, and reduced travel time for patients. Introduction: Although rural telehealth services have expanded in several specialized areas, little is known about the attitudes, beliefs, and uptake of telehealth use in rural American primary care. This study characterizes the differences between rural and urban family physicians (FPs), their perceptions of telehealth use, and barriers to further adoption. Materials and Methods: Nationally representative randomly sampled survey of 5,000 FPs. Results: Among the 31.3% of survey recipients who completed the survey, 83% practiced in urban areas and 17% in rural locations. Rural FPs were twice as likely to use telehealth as urban FPs (22% vs. 10%). Logistic regressions showed rural FPs had greater odds of reporting telehealth use to connect their patients to specialists and to care for their patients. Rural FPs were less likely to identify liability concerns as a barrier to using telehealth. Discussion: Telemedicine allows rural patients to see specialists without leaving their communities and permits rural FPs to take advantage of specialist expertise, expand their scope of practice, and reduce the feeling of isolation experienced by rural physicians. Conclusion: Efforts to raise awareness of current payment policies for telehealth services, addressing the limitations of current reimbursement policies and state regulations, and creating new avenues for telehealth reimbursement and technological investments are critical to increasing primary care physician use of telehealth services.

The study sought to assess awareness, perceptions, and value of telehealth in primary care from the perspective of patients. We conducted a cross-sectional, Web-based survey of adults with access to telehealth services who visited healthcare providers for any of the 20 most-commonly seen diagnoses during telehealth visits. Three groups were studied: registered users (RUs) of telehealth had completed a LiveHealth Online (a health plan telehealth service provider) visit, registered nonusers (RNUs) registered for LiveHealth Online but had not conducted a visit, and nonregistered nonusers (NRNUs) completed neither step. Of 32 831 patients invited, 3219 (9.8%) responded and 766 met eligibility criteria and completed surveys: 390 (51%) RUs, 117 (15%) RNUs, and 259 (34%) NRNUs. RUs were least likely to have a primary care usual source of care (65.6% vs 78.6% for RNUs vs 80.0% for NRNUs; P < .001). Nearly half (46.8%) of RUs were unable to get an appointment with their doctor, and 34.8% indicated that their doctor’s office was closed. Among the 3 groups, RUs were most likely to be employed (89.5% vs 88.9% vs 82.2%; P = .007), have post–high school education (94.4% vs 93.2% vs 86.5%; P = .003), and live in urban areas (81.0% vs 69.2% vs 76.0%; P = .021). Telehealth users reported that they relied on live video for enhanced access and were less connected to primary care than nonusers were. Telehealth may expand service access but risks further fragmentation of care and undermining of the primary care function absent better coordination and information sharing with usual sources of patients’ care.

Background: “Financial toxicity” is a concern for patients, but little is known about how patients consider out‐of‐pocket cost in decisions. Sacubitril‐valsartan provides a contemporary scenario to understand financial toxicity. It is guideline recommended for heart failure with reduced ejection fraction, yet out‐of‐pocket costs can be considerable. Methods and Results: Structured interviews were conducted with 49 patients with heart failure with reduced ejection fraction at heart failure clinics and inpatient services. Patient opinions of the drug and its value were solicited after description of benefits using graphical displays. Descriptive quantitative analysis of closed‐ended responses was conducted, and qualitative descriptive analysis of text data was performed. Of participants, 92% (45/49) said that they would definitely or probably switch to sacubitril‐valsartan if their physician recommended it and out‐of‐pocket cost was $5 more per month than their current medication. Only 43% (21/49) would do so if out‐of‐pocket cost was $100 more per month ( P <0.001). At least 40% across all income categories would be unlikely to take sacubitril‐valsartan at $100 more per month. Participants exhibited heterogeneous approaches to cost in decision making and varied on their use and interpretation of probabilistic information. Few (20%) participants stated physicians had initiated a conversation about cost in the past year. Conclusions: Out‐of‐pocket cost variation reflective of contemporary cost sharing substantially influenced stated willingness to take sacubitril‐valsartan, a guideline‐recommended therapy with mortality benefit. These findings suggest a need for cost transparency to promote shared decision making. They also demonstrate the complexity of cost discussion and need to study how to incorporate out‐of‐pocket cost into clinical decisions.