Primary Care Appointment Completion Rates and Telemedicine Utilization Among Black and Non-Black Patients from 2019 to 2020

Telemedicine is associated with reduced socioeconomic disparities in outpatient clinic no-show rates

INTRODUCTION

The global pandemic caused by coronavirus (COVID-19) sped up the adoption of telemedicine. We aimed to assess whether factors associated with no-show differed between in-person and telemedicine visits. The focus is on understanding how social economic factors affect patient no-show for the two modalities of visits.

METHODS

We utilized electronic health records data for outpatient internal medicine visits at a large urban academic medical center, from February 1, 2020 to December 31, 2020. A mixed-effect logistic regression was used. We performed stratified analysis for each modality of visit and a combined analysis with interaction terms between exposure variables and visit modality.

RESULTS

A total of 111,725 visits for 72,603 patients were identified. Patient demographics (age, gender, race, income, partner), lead days, and primary insurance were significantly different between the two visit modalities. Our multivariable regression analyses showed that the impact of sociodemographic factors, such as Medicaid insurance (OR 1.23, p < 0.01 for in-person; OR 1.03, p = 0.57 for telemedicine; p < 0.01 for interaction), Medicare insurance (OR 1.11, p = 0.04 for in-person; OR 0.95, p = 0.32 for telemedicine; p = 0.03 for interaction) and Black race (OR 1.36, p < 0.01 for in-person; OR 1.20, p < 0.01 for telemedicine; p = 0.03 for interaction), on increased odds of no-show was less for telemedicine visits than for in-person visits. In addition, inclement weather and younger age had less impact on no-show for telemedicine visits.

DISCUSSION

Our findings indicated that if adopted successfully, telemedicine had the potential to reduce no-show rate for vulnerable patient groups and reduce the disparity between patients from different socioeconomic backgrounds.

Survivorship after adolescent and young adult cancer: models of care, disparities, and opportunities

Survivors of adolescent and young adult (AYA; age 15-39 years at diagnosis) cancer are a growing population with the potential to live for many decades after treatment completion. Survivors of AYA cancer are at risk for adverse long-term outcomes including chronic conditions, secondary cancers, impaired fertility, poor psychosocial health and health behaviors, and financial toxicity. Furthermore, survivors of AYA cancer from racially minoritized and low socioeconomic status populations experience disparities in these outcomes, including lower long-term survival. Despite these known risks, most survivors of AYA cancer do not receive routine survivorship follow-up care, and research on delivering high-quality, evidence-based survivorship care to these patients is lacking. The need for survivorship care was initially advanced in 2006 by the Institute of Medicine. In 2019, the Quality of Cancer Survivorship Care Framework (QCSCF) was developed to provide an evidence-based framework to define key components of optimal survivorship care. In this commentary focused on survivors of AYA cancer, we apply the QCSCF framework to describe models of care that can be adapted for their unique needs, multilevel factors limiting equitable access to care, and opportunities to address these factors to improve short- and long-term outcomes in this vulnerable population.

Telephone-Based Guideline-Directed Medical Therapy Optimization in Navajo Nation: The Hózhó Randomized Clinical Trial

Importance

Underutilization of guideline-directed medical therapy for heart failure with reduced ejection fraction is a major cause of poor outcomes. For many American Indian patients receiving care through the Indian Health Service, access to care, especially cardiology care, is limited, contributing to poor uptake of recommended therapy.

Objective

To examine whether a telehealth model in which guideline-directed medical therapy is initiated and titrated over the phone with remote telemonitoring using a home blood pressure cuff improves guideline-directed medical therapy use (eg, drug classes and dosage) in patients with heart failure with reduced ejection fraction in Navajo Nation.

Design, Setting, and Participants

The Heart Failure Optimization at Home to Improve Outcomes (Hózhó) randomized clinical trial was a stepped-wedge, pragmatic comparative effectiveness trial conducted from February to August 2023. Patients 18 years and older with a diagnosis of heart failure with reduced ejection fraction receiving care at 2 Indian Health Service facilities in rural Navajo Nation (defined as having primary care physician with 1 clinical visit and 1 prescription filled in the last 12 months) were enrolled. Patients were randomized to the telehealth care model or usual care in a stepped-wedge fashion, with 5 time points (30-day intervals) until all patients crossed over into the intervention. Data analyses were completed in January 2024.

Intervention

A phone-based telehealth model in which guideline-directed medical therapy is initiated and titrated at home, using remote telemonitoring with a home blood pressure cuff.

Main Outcomes and Measures

The primary outcome was an increase in the number of guideline-directed classes of drugs filled from the pharmacy at 30 days postrandomization.

Results

Of 103 enrolled American Indian patients, 42 (40.8%) were female, and the median (IQR) age was 65 (53-77) years. The median (IQR) left ventricular ejection fraction was 32% (24%-36%). The primary outcome occurred significantly more in the intervention group (66.2% vs 13.1%), thus increasing uptake of guideline-directed classes of drugs by 53% (odds ratio, 12.99; 95% CI, 6.87-24.53; P < .001). The number of patients needed to receive the telehealth intervention to result in an increase of guideline-directed drug classes was 1.88.

Conclusions and Relevance

In this heart failure trial in Navajo Nation, a telephone-based strategy of remote initiation and titration for outpatients with heart failure with reduced ejection fraction led to improved rates of guideline-directed medical therapy at 30 days compared with usual care. This low-cost strategy could be expanded to other rural settings where access to care is limited.

Trial Registration

ClinicalTrials.gov Identifier: NCT05792085.

Trends in telemedicine visits among pediatric asthma patients during COVID-19

Background

Environmental and social factors, including lack of access to asthma care, contribute to persistent inequities in asthma outcomes among children from historically marginalized ethnoracial groups. Telemedicine, which expanded rapidly during the coronavirus disease 2019 (COVID-19) pandemic, may be an approach to augment access to pediatric asthma care.

Objectives

We sought to describe characteristics of pediatric (0-17 years) telemedicine users with asthma and characterize use trends throughout the COVID-19 pandemic.

Methods

We conducted a retrospective analysis using electronic health record data of pediatric patients with asthma seen at University of California, Los Angeles, Medical Center between March 2019 to March 2022 describing telemedicine user characteristics, trends of asthma-related telemedicine use, and associations between user characteristics and having a telemedicine visit.

Results

Among 6,777 patients with asthma, the percentage of asthma-related telemedicine visits peaked early in the pandemic, comprising 74.3% of visits, before decreasing to 13.6% in 2022. Compared to White patients, Black patients had lower odds of an asthma telemedicine visit (odds ratio [OR], 0.49; 95% confidence interval [CI], 0.26, 0.94). Those with public insurance (OR, 1.7; 95% CI, 1.19, 2.43), severe persistent asthma (OR, 3.03; 95% CI, 1.70, 5.42), or comorbidities (OR, 1.59; 95% CI, 1.08, 2.33) had higher odds. Time to first emergency department visit and hospitalization comparing those with at least one telemedicine visit to those with none were similar.

Conclusions

More pediatric asthma patients are using telemedicine since the COVID-19 pandemic, particularly those with medical complexity and comorbidities, and outcomes appear similar. However, Black patients at our institution have lower odds of using telemedicine.

Racial and Ethnic Disparities in Implantable Cardioverter-Defibrillator Utilization: A Contemporary Review

Purpose of review

Sudden cardiac arrest is associated with high morbidity and mortality. Despite having a disproportionate burden of sudden cardiac death (SCD), rates of primary and secondary prevention of SCD with implantable cardioverter-defibrillator (ICD) therapy are lower among eligible racially minoritized patients. This review highlights the racial and ethnic disparities in ICD utilization, associated barriers to ICD care, and proposed interventions to improve equitable ICD uptake.

Recent findings

Racially minoritized populations are disproportionately eligible for ICD therapy but are less likely to see cardiac specialists, be counseled on ICD therapy, and ultimately undergo ICD implantation, fueling disparate outcomes. Racial disparities in ICD utilization are multifactorial, with contributions at the patient, provider, health system, and structural/societal level.

Summary

Racial and ethnic disparities have been demonstrated in preventing SCD with ICD use. Proposed strategies to mitigate these disparities must prioritize care delivery and access to care for racially minoritized patients, increase the diversification of clinical and implementation trial participants and the healthcare workforce, and center reparative justice frameworks to rectify a long history of racial injustice.

Health Disparities, Clinical Trials, and the Digital Divide

In the past few years, there have been rapid advances in technology and the use of digital tools in health care and clinical research. Although these innovations have immense potential to improve health care delivery and outcomes, there are genuine concerns related to inadvertent widening of the digital gap consequentially exacerbating health disparities. As such, it is important that we critically evaluate the impact of expansive digital transformation in medicine and clinical research on health equity. For digital solutions to truly improve the landscape of health care and clinical trial participation for all persons in an equitable way, targeted interventions to address historic injustices, structural racism, and social and digital determinants of health are essential. The urgent need to focus on interventions to promote health equity was made abundantly clear with the coronavirus disease 2019 pandemic, which magnified long-standing social and racial health disparities. Novel digital technologies present a unique opportunity to embed equity ideals into the ecosystem of health care and clinical research. In this review, we examine racial and ethnic diversity in clinical trials, historic instances of unethical research practices in biomedical research and its impact on clinical trial participation, and the digital divide in health care and clinical research, and we propose suggestions to achieve digital health equity in clinical trials. We also highlight key digital health opportunities in cardiovascular medicine and dermatology as exemplars, and we offer future directions for development and adoption of patient-centric interventions aimed at narrowing the digital divide and mitigating health inequities.

Visit and Between-Visit Interaction Frequency Before and After COVID-19 Telehealth Implementation

Importance

Telehealth implementation associated with the COVID-19 public health emergency (PHE) affected patient-clinical team interactions in numerous ways. Yet, studies have narrowly examined billed patient-clinician visits rather than including visits with other team members (eg, pharmacists) or between-visit interactions.

Objective

To evaluate rates of change over time in visits (in-person, telehealth) and between-visit interactions (telephone calls, patient portal messages) overall and by key patient characteristics.

Design, Setting, and Participants

This retrospective cohort study included adults with diabetes receiving primary care at urban academic (University of California San Francisco [UCSF]) and safety-net (San Francisco Health Network [SFHN]) health care systems. Encounters from April 2019 to March 2021 were analyzed.

Exposure

Telehealth implementation over 3 periods: pre-PHE (April 2019 to March 2020), strict shelter-in-place (April to June 2020), and hybrid-PHE (July 2020 to March 2021).

Main Outcomes and Measures

The main outcomes were rates of change in monthly mean number of total encounters, visits with any health care team member, visits with billing clinicians, and between-visit interactions. Key patient-level characteristics were age, race and ethnicity, language, and neighborhood socioeconomic status (nSES).

Results

Of 15 148 patients (4976 UCSF; 8975 SFHN) included, 2464 (16%) were 75 years or older, 7734 (51%) were female patients, 9823 (65%) self-identified as racially or ethnically minoritized, 6223 (41%) had a non-English language preference, and 4618 (31%) lived in the lowest nSES quintile. After accounting for changes to care delivery through an interrupted time-series analysis, total encounters increased in the hybrid-PHE period (UCSF: 2.3% per patient/mo; 95% CI, 1.6%-2.9% per patient/mo; SFHN: 1.8% per patient/mo, 95% CI, 1.3%-2.2% per patient/mo), associated primarily with growth in between-visit interactions (UCSF: 3.1% per patient/mo, 95% CI, 2.3%-3.8% per patient/mo; SFHN: 2.9% per patient/mo, 95% CI, 2.3%-3.4% per patient/mo). In contrast, rates of visits were stable during the hybrid-PHE period. Although there were fewer differences in visit use by key patient-level characteristics during the hybrid-PHE period, pre-PHE differences in between-visit interactions persisted during the hybrid-PHE period at SFHN. Asian and Chinese-speaking patients at SFHN had fewer monthly mean between-visit interactions compared with White patients (0.46 [95% CI, 0.42-0.50] vs 0.59 [95% CI, 0.53-0.66] between-visit interactions/patient/mo; P < .001) and English-speaking patients (0.52 [95% CI, 0.47-0.58] vs 0.61 [95% CI, 0.56-0.66] between-visit interactions/patient/mo; P = .03).

Conclusions and Relevance

In this study, pre-PHE growth in overall patient-clinician encounters persisted after PHE-related telehealth implementation, driven in both periods by between-visit interactions. Differential utilization based on patient characteristics was observed, which may indicate disparities. The implications for health care team workload and patient outcomes are unknown, particularly regarding between-visit interactions. Therefore, to comprehensively understand care utilization for patients with chronic diseases, research should expand beyond billed visits.