The Evolution of Primary Care Telehealth Disparities During COVID-19: Retrospective Cohort Study.

BACKGROUND: Telehealth has become widely used as a novel way to provide outpatient care during the COVID-19 pandemic, but data about telehealth use in primary care remain limited. Studies in other specialties raise concerns that telehealth may be widening existing health care disparities, requiring further scrutiny of trends in telehealth use. OBJECTIVE: Our study aims to further characterize sociodemographic differences in primary care via telehealth compared to in-person office visits before and during the COVID-19 pandemic and determine if these disparities changed throughout 2020. METHODS: We conducted a retrospective cohort study in a large US academic center with 46 primary care practices from April-December 2019 to April-December 2020. Data were subdivided into calendar quarters and compared to determine evolving disparities throughout the year. We queried and compared billed outpatient encounters in General Internal Medicine and Family Medicine via binary logic mixed effects regression model and estimated odds ratios (ORs) with 95% CIs. We used sex, race, and ethnicity of the patient attending each encounter as fixed effects. We analyzed socioeconomic status of patients in the institution's primary county based on the patient's residence zip code. RESULTS: A total of 81,822 encounters in the pre-COVID-19 time frame and 47,994 encounters in the intra-COVID-19 time frame were analyzed; in the intra-COVID-19 time frame, a total of 5322 (11.1%) of encounters were telehealth encounters. Patients living in zip code areas with high utilization rate of supplemental nutrition assistance were less likely to use primary care in the intra-COVID-19 time frame (OR 0.94, 95% CI 0.90-0.98; P=.006). Encounters with the following patients were less likely to be via telehealth compared to in-person office visits: patients who self-identified as Asian (OR 0.74, 95% CI 0.63-0.86) and Nepali (OR 0.37, 95% CI 0.19-0.72), patients insured by Medicare (OR 0.77, 95% CI 0.68-0.88), and patients living in zip code areas with high utilization rate of supplemental nutrition assistance (OR 0.84, 95% CI 0.71-0.99). Many of these disparities persisted throughout the year. Although there was no statistically significant difference in telehealth use for patients insured by Medicaid throughout the whole year, subanalysis of quarter 4 found encounters with patients insured by Medicaid were less likely to be via telehealth (OR 0.73, 95% CI 0.55-0.97; P=.03). CONCLUSIONS: Telehealth was not used equally by all patients within primary care throughout the first year of the COVID-19 pandemic, specifically by patients who self-identified as Asian and Nepali, insured by Medicare, and living in zip code areas with low socioeconomic status. As the COVID-19 pandemic and telehealth infrastructure change, it is critical we continue to reassess the use of telehealth. Institutions should continue to monitor disparities in telehealth access and advocate for policy changes that may improve equity.

Transformation of the Doctor-Patient Relationship: Big Data, Accountable Care, and Predictive Health Analytics.

The medical profession is steeped in traditions that guide its practice. These traditions were developed to preserve the well-being of patients. Transformations in science, technology, and society, while maintaining a self-governance structure that drives the goal of care provision, have remained hallmarks of the profession. The purpose of this paper is to examine ethical challenges in health care as it relates to Big Data, Accountable Care Organizations, and Health Care Predictive Analytics using the principles of biomedical ethics laid out by Beauchamp and Childress (autonomy, beneficence, non-maleficence, and justice). Among these are the use of Electronic Health Records within stipulations of the Health Insurance Portability and Accountability Act. Clinicians are well-positioned to impact health policy development to address ethical issues associated with the use of Big Data, Accountable Care, and Health Care Predictive Analytics as we work to transform the doctor-patient relationship towards improving population health outcomes and creating a healthier society.

Pediatric Long COVID Subphenotypes: An EHR-based study from the RECOVER program.

Pediatric Long COVID has been associated with a wide variety of symptoms, conditions, and organ systems, but distinct clinical presentations, or subphenotypes, are still being elucidated. In this exploratory analysis, we identified a cohort of pediatric (age <21) patients with evidence of Long COVID and no pre-existing complex chronic conditions using electronic health record data from 38 institutions and used an unsupervised machine learning-based approach to identify subphenotypes. Our method, an extension of the Phe2Vec algorithm, uses tens of thousands of clinical concepts from multiple domains to represent patients' clinical histories to then identify groups of patients with similar presentations. The results indicate that cardiorespiratory presentations are most common (present in 54% of patients) followed by subphenotypes marked (in decreasing order of frequency) by musculoskeletal pain, neuropsychiatric conditions, gastrointestinal symptoms, headache, and fatigue.

Implementing the Better Starts For All Pilot Mobile and Telehealth Intervention in Ohio Appalachia: Improving Access to Maternal Healthcare.

INTRODUCTION: Women in Ohio Appalachia experience greater maternal health disparities relative to the general U.S. population, resulting in poorer health outcomes. This paper describes the Ohio Better Starts for All (BSFA) program that provides mobile maternal health services in rural Ohio. METHODS: This three-year intervention was delivered through a community-clinical partnership in Ohio Appalachia. The program's preliminary evaluation and opportunities were informed by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. RESULTS: Over six months, 86 patients were referred to the BSFA program, 54 (62.8 %) were seen by the maternal care team, and 14 out of 19 scheduled clinic days were held. Five clinics were canceled due to inclement weather, mobile unit breakdown, or provider COVID-19 infection. DISCUSSION: Maternal care providers must provide equitable care to patients, with particular attention to those who face substantial challenges accessing obstetric services. The BSFA program offers one promising solution to help women overcome barriers to accessing care.

A quality improvement collaborative increased preventive education and screening rates for women at high-risk for type 2 diabetes mellitus in primary care settings.

AIMS: Type 2 diabetes mellitus (T2DM) rates continue to increase across women of reproductive age in the United States. The Ohio Type 2 Diabetes Learning Collaborative aimed to improve education and screening for T2DM among women aged 18-44years at high risk for developing T2DM. METHODS: Fifteen primary care practices across Ohio participated in a 12-month quality improvement (QI) collaborative, which included monthly calls to share best practices, one-on-one QI coaching, and Plan-Do-Study-Act cycles. Monthly, practices submitted data on three outcome measures on preventive education and three measures on clinical screening for T2DM. RESULTS: Increases across each of the three preventive education rates (range of percent increase: 53.6% - 60.0%) and each of the three screening rates for T2DM (15.0% - 19.4%) were observed. Specifically, screening rates for high-risk women with two or more risk factors for T2DM (excluding gestational diabetes mellitus (GDM)) increased by 16.8% (60.5%-77.3%) while rates for T2DM among women with a history of GDM increased by 15.0% (75.0 - 90.0). CONCLUSIONS: A quality improvement collaborative increased preventive education and screening rates for women at high-risk for T2DM in primary care settings.

Engaging death: Narrative and constructed dialogue in Advance Care Planning discussions.

Advance Care Planning (ACP) remains extremely low in the US, due to numerous institutional and cultural barriers and discomfort in discussing death. There is a need for guidance about how patient and healthcare providers can effectively engage in ACP discussion. Here we analyze the linguistic strategies that focus-group participants use when discussing ACP in detailed ways. Prevalent linguistic structures in effective ACP discussions were loved ones' end-of-life narratives, hypothetical narratives, and constructed dialogue. In elucidating spontaneous, unprompted approaches to effective discussion of end-of-life issues, such research can help to dislodge communicative barriers to ACP so that more people are prepared to engage the process.