Trends in Utilization of Electronic Consultations Associated With Patient Payer and Language Among US Academic Medical Centers During the COVID-19 Pandemic.

Importance: Electronic consultations (eConsultations) are increasingly used to obtain specialist guidance, avoiding unnecessary face-to-face patient visits for certain clinical questions. During the COVID-19 pandemic, when in-person care was limited, eConsultations may have helped clinicians obtain specialist input to guide patient care. Objective: To understand how the use of eConsultations changed during the COVID-19 pandemic and whether trends in eConsultation utilization differed based on patient's payer and primary language. Design, Setting, and Participants: This retrospective cohort study was conducted at 6 academic medical centers in the United States, all participating in the Association of American Colleges Coordinating Optimal Referral Experiences program. Participants included adult patients who had an outpatient visit, referral, or eConsultation during the study period. Data were analyzed from June 4, 2019, to July 28, 2020. Main Outcomes and Measures: The primary outcome was the eConsultation proportion of specialty contact, defined as the number of completed eConsultations divided by the sum of the number of completed eConsultations and specialty referrals, expressed as a percentage. eConsultation percentages of specialty contact were further stratified by payer type and language. Payers included commercial, Medicare, Medicaid, self-pay or uninsured, and other. Primary language included English and non-English languages. Results: A total of 14 545 completed eConsultations and 189 776 referrals were included. More eConsultations were completed for English-speaking patients (11 363 eConsultations [95.0%]) than non-English-speaking patients (597 eConsultations [5.0%]). Patients with commercial insurance represented the highest number of completed eConsultations (8848 eConsultations [60.8%]) followed by Medicare (3891 eConsultations [26.8%]), Medicaid (930 eConsultations [6.4%]), other insurance (745 eConsultations [5.1%]), and self-pay or no insurance (131 eConsultations [0.9%]). At the start of the pandemic, across all academic medical centers, the percentage of specialty contact conducted via eConsultation significantly increased by 6.21% (95% CI, 4.97%-7.44%; P < .001). When stratified by payer and language, the percentage of specialty contact conducted via eConsultation significantly increased at the beginning of the pandemic for both English-speaking patients (change, 6.09% (95% CI, 4.82% to 7.37%; P < .001) and non-English-speaking patients (change, 8.48% [95% CI, 5.79% to 11.16%]; P < .001) and for all payers, except self-pay and uninsured patients (change, -0.21% [95% CI, [-1.35% to 0.92%]; P = .70). Conclusions and Relevance: This retrospective cohort study found that eConsultations provided an accessible mechanism for clinicians to receive specialist input when in-person care was limited.

Neighbourhood walking tours for physicians-in-training.

Social and economic factors have a profound impact on patient health. However, education about these factors has been inconsistently incorporated into residency training. Neighbourhood walking tours may help physician-residents learn about the social determinants of health (SDoH). We assessed the impact of a neighbourhood walking tour on physician-residents' perceptions of SDoH, plans for counselling patients and knowledge of community resources. Using a community-based participatory research approach, in 2017 we implemented a neighbourhood walking tour curriculum for physician-residents in internal medicine, internal medicine/primary care, emergency medicine, paediatrics, combined internal medicine/paediatrics and obstetrics/gynaecology. In both pre-tour and post-tour, we asked participants to (1) rank the importance of individual-level and neighbourhood-level factors affecting patients' health, (2) describe strategies used to improve health behaviours and (3) describe knowledge of community resources. Eighty-one physician-residents participated in walks (pre-tour surveys (93% participation rate (n=75)), and post-tour surveys (53% participation rate (n=43)). Pre-tour, the factor ranked most frequently affecting patient health was 'access to primary care' (67%) compared with post-tour: 'income' (44%) and 'transportation' (44%). In describing ways to improve diet and exercise, among pre-tour survey respondents, 67% discussed individual-level strategies and 16% discussed neighbourhood-level, while among post-tour survey respondents, 39% of respondents discussed individual-level strategies and 37% discussed neighbourhood-level. Percentage of respondents aware of community resources changed from 5% to 76% (p<0.001). Walking tours helped physician-residents recognise the importance of SDoH and the value of community resources, and may have broadened frameworks for counselling patients on healthy lifestyles.

Do pregnant women living in higher well-being populations in the USA experience lower risk of preterm delivery? A cross-sectional study.

OBJECTIVE: To determine if preterm birth, defined as gestational age <37 weeks, is lower for women living in counties with higher well-being, after accounting for known individual risk factors. DESIGN: Cross-sectional study of all US births in 2011. PARTICIPANTS: We obtained birth data from the National Center for Health Statistics which included 3 938 985 individuals. MAIN OUTCOMES MEASURES: Primary outcome measure was maternal risk of preterm delivery by county; primary independent variable was county-level well-being as measured by the Gallup-Sharecare Well-Being Index (WBI). RESULTS: Women living in counties with higher population well-being had a lower rate of preterm delivery. The rate of preterm birth in counties in the lowest WBI quintile was 13.1%, while the rate of preterm birth in counties in the highest WBI quintile was 10.9%. In the model adjusted for maternal risk factors (age, race, Hispanic ethnicity, smoking status, timing of initiation of prenatal visits, multiparity, maternal insurance payer), the association was slightly attenuated with an absolute difference of 1.9% (95% CI 1.7% to 2.1%; p<0.001). CONCLUSIONS: Pregnant women who live in areas with higher population well-being have lower risk of preterm birth, even after accounting for individual risk factors.

The State of Education and Training for Antimicrobial Stewardship Programs in Indian Hospitals-A Qualitative and Quantitative Assessment.

Background: To understand the role of infrastructure, manpower, and education and training (E&T) in relation to Antimicrobial Stewardship (AMS) in Indian healthcare organizations. Methods: Mixed method approach using quantitative survey and qualitative interviews was applied. Through key informants, healthcare professionals from 69 hospitals (public & private) were invited to participate in online survey and follow up qualitative interviews. Thematic analysis was applied to identify the key emerging themes from the interviews. The survey data were analyzed using descriptive statistics. Results: 60 healthcare professionals from 51 hospitals responded to the survey. Eight doctors participated in semi-structured telephone interviews. 69% (27/39) of the respondents received E&T on AMS during undergraduate or postgraduate training. 88% (15/17) had not received any E&T at induction or during employment. In the qualitative interviews three key areas of concern were identified: (1) need for government level endorsement of AMS activities; (2) lack of AMS programs in hospitals; and, (3) lack of postgraduate E&T in AMS for staff. Conclusion: No structured provision of E&T for AMS currently exists in India. Stakeholder engagement is essential to the sustainable design and implementation of bespoke E&T for hospital AMS in India.

Identifying county characteristics associated with resident well-being: A population based study.

BACKGROUND: Well-being is a positively-framed, holistic assessment of health and quality of life that is associated with longevity and better health outcomes. We aimed to identify county attributes that are independently associated with a comprehensive, multi-dimensional assessment of individual well-being. METHODS: We performed a cross-sectional study examining associations between 77 pre-specified county attributes and a multi-dimensional assessment of individual US residents' well-being, captured by the Gallup-Sharecare Well-Being Index. Our cohort included 338,846 survey participants, randomly sampled from 3,118 US counties or county equivalents. FINDINGS: We identified twelve county-level factors that were independently associated with individual well-being scores. Together, these twelve factors explained 91% of the variance in individual well-being scores, and they represent four conceptually distinct categories: demographic (% black); social and economic (child poverty, education level [

Association of the Overall Well-being of a Population With Health Care Spending for People 65 Years of Age or Older.

Importance: New US health care payment models have increasingly incentivized health care systems to promote health and reduce health care spending at the population level, with Medicare beneficiaries representing one of the largest populations affected by new payment models. Identifying novel strategies to promote health and reduce health care spending is necessary. Objective: To assess whether the overall well-being of a population is associated with health care spending for people 65 years of age or older. Design, Setting, and Participants: This US national, population-based cross-sectional study examined the association between county well-being and Medicare fee-for-service (FFS) spending. Population well-being, a holistic assessment of the overall health of the population comprising interrelated domains, including physical, mental, and social health, as measured by the Gallup-Sharecare Well-Being Index (2010), was linked to the mean spending per Medicare FFS beneficiary (2010) and county characteristics data for all US counties assessed. The data were adjusted for prevalence of 4 low-variation conditions (hip fracture, stroke, colorectal cancer, and acute myocardial infarction) and regional penetration of Medicare Advantage. Data analyses were conducted October 13, 2016, to October 31, 2017. Main Outcomes and Measures: Mean spending per Medicare FFS beneficiary per county. Results: In total, 2998 counties were assessed using county-level mean values, with 4 to 7317 participants (mean [SD] number of participants, 755 [1220]) per county. The mean (SD) values of the demographic characteristics of the participants were 50.8% (1.3%) female, 74.9% (16.5%) white, 12.1% (13.0%) black, 4.0% (5.3%) Asian, and 13.7% (14.8%) Hispanic with a mean (SD) of the median county age of 38.2 (4.4) years. Medicare spent a mean (SE) of $992 ($110) less per Medicare FFS beneficiary in counties in the highest quintile of well-being compared with counties in the lowest well-being quintile. This inverse association persisted after accounting for key population characteristics such as median household income and contextual factors such as urbanicity and health care system capacity. Medicare spent a mean (SE) of $1233 ($104) less per Medicare FFS beneficiary in counties with the greatest access to basic needs than in those with the lowest access. Conclusions and Relevance: In this US national study, the overall well-being of a geographically defined population was inversely associated with its health care spending for people 65 years and older. Identifying this association between well-being and health care spending at the population level may help to lay the foundation for further study to first illuminate the mechanisms underlying the association and to second study interventions aimed at creating greater well-being and lower health care spending at the population level.

Population Well-Being Measures Help Explain Geographic Disparities In Life Expectancy At The County Level.

Geographic disparities in life expectancy are substantial and not fully explained by differences in race and socioeconomic status. To develop policies that address these inequalities, it is essential to identify other factors that account for this variation. In this study we investigated whether population well-being-a comprehensive measure of physical, mental, and social health-helps explain geographic variation in life expectancy. At the county level, we found that for every 1-standard-deviation (4.2-point) increase in the well-being score, life expectancy was 1.9 years higher for females and 2.6 years higher for males. Life expectancy and well-being remained positively associated, even after race, poverty, and education were controlled for. In addition, well-being partially mediated the established associations of race, poverty, and education with life expectancy. These findings highlight well-being as an important metric of a population's health and longevity and as a promising focus for intervention.