Faculty Bibliography

Understanding patient characteristics associated with scheduling and completing telehealth visits can identify potential biases or latent preferences related to telehealth usage. We describe patient characteristics associated with being scheduled for and completing audio and video visits. We used data from patients at 17 adult primary care departments in a large, urban public healthcare system from August 1, 2020 to July 31, 2021. We used hierarchical multivariable logistic regression to generate adjusted odds ratios (aOR) for patient characteristics associated with having been scheduled for and completed telehealth (vs in-person) visits and for video (vs audio) scheduling and completion during two time periods: a telehealth transition period (N = 190,949) and a telehealth elective period (N = 181,808). Patient characteristics were significantly associated with scheduling and completion of telehealth visits. Many associations were similar across time periods, but others changed over time. Patients who were older (≥ 65 years old vs 18-44 years old: aOR for scheduling 0.53/completion 0.48), Black (0.86/0.71), Hispanic (0.76/0.62), or had Medicaid (0.93/0.84) were among those less likely to be scheduled for or complete video (vs audio) visits. Patients with activated patient portals (1.97/3.34) or more visits (≥ 3 scheduled visits vs 1 visit: 2.40/1.52) were more likely to be scheduled for or complete video visits. Variation in scheduling/completion explained by patient characteristics was 7.2%/7.5%, clustering by provider 37.2%/34.9%, and clustering by facility 43.1%/37.4%. Stable and dynamic associations suggest persistent gaps in access and evolving preferences/biases. Variation explained by patient characteristics was relatively low compared with that explained by provider and facility clustering.

BACKGROUND:Appointment non-attendance has clinical, operational, and financial implications for patients and health systems. How telehealth services are associated with non-attendance in primary care is not well-described, nor are patient characteristics associated with telehealth non-attendance. OBJECTIVE:We sought to compare primary care non-attendance for telehealth versus in-person visits and describe patient characteristics associated with telehealth non-attendance. DESIGN/METHODS:An observational study of electronic health record data. PARTICIPANTS/METHODS:Patients with primary care encounters at 23 adult primary care clinics at a large, urban public healthcare system from November 1, 2019, to August 31, 2021. MAIN MEASURES/METHODS:We analyzed non-attendance by modality (telephone, video, in-person) during three time periods representing different availability of telehealth using hierarchal multiple logistic regression to control for patient demographics and variation within patients and clinics. We stratified by modality and used hierarchal multiple logistic regression to assess for associations between patient characteristics and non-attendance in each modality. KEY RESULTS/RESULTS:There were 1,219,781 scheduled adult primary care visits by 329,461 unique patients: 754,149 (61.8%) in-person, 439,295 (36.0%) telephonic, and 26,337 (2.2%) video visits. Non-attendance for telephone visits was initially higher than that for in-person visits (adjusted odds ratio 1.04 [95% CI 1.02, 1.07]) during the early telehealth availability period, but decreased later (0.82 [0.81, 0.83]). Non-attendance for video visits was higher than for in-person visits during the early (4.37 [2.74, 6.97]) and later (2.02 [1.95, 2.08]) periods. Telephone visits had fewer differences in non-attendance by demographics; video visits were associated with increased non-attendance for patients who were older, male, had a primary language other than English or Spanish, and had public or no insurance. CONCLUSIONS:Telephonic visits may improve access to care and be more easily adoptable among diverse populations. Further attention to implementation may be needed to avoid impeding access to care for certain populations using video visits.

Telehealth services may improve access to care, but there are concerns around whether availability of telehealth may increase care utilization. We assessed whether usage of telehealth was associated with differential primary care utilization at a large, urban public healthcare system. Using electronic health record data from 23 primary care clinics, we categorized patients as telehealth users and non-users. Then, we compared the number of visits per patient between groups using Welch's t-tests while stratifying by comorbidity count. We used multivariable Poisson regression to test for associations between telehealth usage and visit count while controlling for other demographic factors. Compared with telehealth non-users, telehealth users had approximately 1 more primary care visit per patient over the year regardless of comorbidity count or other patient characteristics. Availability of telehealth services may be associated with increased primary care utilization in a safety-net setting, though further research on outcomes, costs of care, and patient and clinician experiences is needed to better inform decisions regarding provision and reimbursement of telehealth services.

In early March 2020 an outbreak of coronavirus disease 2019 (COVID-19) in New York City exerted sudden and extreme pressures on emergency medical services and quickly changed public health policy and clinical guidance. Recognizing this, New York City Health + Hospitals established a clinician-staffed COVID-19 hotline for all New Yorkers. The hotline underwent three phases as the health crisis evolved. As of May 1, 2020, the hotline had received more than ninety thousand calls and was staffed by more than a thousand unique clinicians. Hotline clinicians provided callers with clinical assessment and guidance, registered them for home symptom monitoring, connected them to social services, and provided a source of up-to-date answers to COVID-19 questions. By connecting New Yorkers with hotline clinicians, regardless of their regular avenues of accessing care, the hotline aimed to ease the pressures on the city's overtaxed emergency medical services. Future consideration should be given to promoting easy access to clinician hotlines by disadvantaged communities early in a public health crisis and to evaluating the impact of clinician hotlines on clinical outcomes.

Ascending to the peak of the novel coronavirus disease (COVID-19) pandemic in New York City, NYC Health + Hospitals (NYC H+H), the City's public health care system, rapidly expanded capacity across its 11 acute-care hospitals and three new field hospitals. To meet the unprecedented demand for patient care, NYC H+H redeployed staff to the areas of greatest need and redesigned recruiting, onboarding, and training processes. The hospital system engaged private staffing agencies, partnered with the U.S Department of Defense, and recruited volunteers throughout the country. A centralized onboarding team created a single-source portal for medical providers requiring credentialing and established new staff positions to increase efficiency. Using new educational tools focused on COVID-19 content, the hospital system trained 20,000 staff, including nearly 9,000 nurses, within a two-month period. Creation of multidisciplinary teams, frequent enterprise-wide communication, willingness to shift direction in response to changing needs, and innovative use of technology were the key factors that enabled the hospital system to meet its goals. [Editor's Note: This Fast Track Ahead Of Print article is the accepted version of the manuscript. The final edited version will appear in an upcoming issue of Health Affairs.].

NYC Health + Hospitals (NYC H+H) is the largest safety net health care delivery system in the United States. Prior to the novel coronavirus disease (COVID-19) pandemic, NYC H+H served over one million patients, including the most vulnerable New Yorkers, and billed fewer than 500 telehealth visits monthly. Once the pandemic struck, we established a strategy to allow us to continue to serve existing patients and treat the surge of new patients. Starting in March 2020 we were able to transform the system using virtual care platforms through which we conducted almost 83,000 billable televisits in one month and more than 30,000 behavioral health encounters via telephone and video. Telehealth also enabled us to support patient-family communication, post-discharge follow-up, and palliative care for COVID-19 patients. Expanded Medicaid coverage and insurance reimbursement for telehealth played a pivotal role in this transformation. As we move to a new blend of virtual and in-person care, it is vital that the major regulatory and insurance changes undergirding our COVID-19 telehealth response be sustained to protect access for our most vulnerable patients. [Editor's Note: This Fast Track Ahead Of Print article is the accepted version of the manuscript. The final edited version will appear in an upcoming issue of Health Affairs.].

Increased investment in primary care is associated with lower healthcare costs and improved population health. The allocation of scarce resources should be driven by robust models that adequately describe primary care activities and spending within a health system, and allow comparisons within and across health systems. However, disparate definitions result in wide variations in estimates of spending on primary care. We propose a new model that allows for a dynamic assessment of primary care spending (PC Spend) within the context of a system's total healthcare budget. The model articulates varied definitions of primary care through a tiered structure which includes overall spending on primary care services, spending on services delivered by primary care professionals and spending delivered by providers that can be characterised by the '4Cs' (first contact, continuous, comprehensive and coordinated care). This unifying framework allows a more refined description of services to be included in any estimate of primary care spend and also supports measurement of primary care spending across nations of varying economic development, accommodating data limitations and international health system differences. It provides a goal for best accounting while also offering guidance, comparability and assessments of how primary care expenditures are associated with outcomes. Such a framework facilitates comparison through the creation of standard definitions and terms, and it also has the potential to foster new areas of research that facilitate robust policy analysis at the national and international levels.