The COVID-19 pandemic presents an unprecedented risk for the 25+ million individuals in the United States who have asthma. Patients with chronic conditions such as asthma are more likely to have worse clinical outcomes due the respiratory complications of COVID-19. Furthermore, the risk of COVID-19 related ED visits and hospitalization is likely higher for patients with more severe asthma, minorities, and those of lower socioeconomic status. As routine care of chronic disease is declining and maintenance medications are unfilled, asthma patients are at even greater risk of exacerbations. It is widely established that good asthma control can help prevent asthma exacerbations and current clinical guidelines recommend frequent monitoring of asthma control in the ambulatory setting, but useful tools and practice models for symptom monitoring are unavailable. In prior work, we developed and tested a simple mobile health (mHealth) app that can be installed on patients' smartphones to track and self-report asthma symptoms using patient-reported outcomes (PRO) between visits, and a practice model for clinics to monitor the patient-reported symptoms as part of routine care. Based on the success of our feasibility study, we are currently scaling and spreading this intervention to primary care clinics that serves a diverse population, including Spanish-speaking and low health literacy patients. We are rigorously evaluating the effect of our clinically-integrated mHealth intervention in a randomized controlled trial which is soon to begin. In this supplement to our current project, we will make three enhancements to maximize health systems' and healthcare professionals' ability to respond to COVID-19. First, we will enhancement the mHealth app with a COVID-19 symptom screener and relevant educational materials. Second, we will use quantitative and qualitative methods to identify best practices, barriers, and facilitators for recruiting patients to our home monitoring intervention during the pandemic. Finally, we will develop and validate a predictive model to identify asthma patients who may benefit the most from our intervention, using data available from the electronic health record (EHR). Identifying, recruiting, and safely monitoring high-risk patients who could potentially utilize acute and critical care resources during the COVID- 19 pandemic are critical aspects of the healthcare system response. Our work will demonstrate how healthcare systems can use data-driven approaches to identify patients at risk for poor outcomes who would preferentially benefit from routine and remote monitoring of PROs via a clinically integrated digital interventions. The knowledge gained from these supplemental aims will provide a clearer understanding of how health systems might use health IT to keep the patients with chronic conditions, such as asthma, safe by improving compliance with guidelines. Doing so will not only mitigate the health effects of COVID-19 in this population, but also minimize the strain on acute and critical care capacity in future surges.

Public Health Relevance

As part of our existing effort to scale and spread the routine collection of asthma-related patient-reported outcomes, we will enhance our mobile app and practice model to address health system, patient, and clinician needs during the COVID-19 pandemic. The technology and knowledge that we generate from our study will also provide much insight into how health systems can efficiently and effectively identify and recruit high risk patients for digital home monitoring to prevents utilization of limited emergency and hospital resources during the COVID-19 pandemic. These approaches can be adapted to identify and recruit patients with other chronic medical conditions who are vulnerable during the pandemic and may benefit from home symptom monitoring.

Agency
National Institute of Health (NIH)
Institute
Agency for Healthcare Research and Quality (AHRQ)
Type
Research Demonstration and Dissemination Projects (R18)
Project #
3R18HS026432-03S1
Application #
10175400
Study Section
Special Emphasis Panel (ZHS1)
Program Officer
Dymek, Christine
Project Start
2018-09-30
Project End
2021-12-31
Budget Start
2021-01-01
Budget End
2021-12-31
Support Year
3
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Rand Corporation
Department
Type
DUNS #
006914071
City
Santa Monica
State
CA
Country
United States
Zip Code
90401