Can’t sign in? Forgot your password?
Enter your email address below and we will send you the reset instructions
If the address matches an existing account you will receive an email with instructions to reset your password.
Can’t sign in? Forgot your username?
Enter your email address below and we will send you your username
If the address matches an existing account you will receive an email with instructions to retrieve your username
Your password has been changed
Shortly after the COVID-19 pandemic began, the Centers for Disease Control and Prevention, health care providers, schools, and other organizations started offering digital symptom screeners to help individuals determine if they should be evaluated for infection. (Some screeners have since been removed.) The potential utility of such screeners as a public health intervention is the promise of early disease identification and use of timely preventative measures such as isolation to minimize spread of infection. Even as vaccination rates increase and states cautiously “re-open,” screeners remain a relevant tool for targeted outreach and risk mitigation efforts—particularly as new, more infectious variants perpetuate the spread of COVID-19.
Published usage data for screeners is sparse, limiting their critical evaluation. Mandated use of screeners, such as those deployed at entry to health care facilities or jobsites, is distinct from voluntary use. The latter requires the individual to proactively search for and select a COVID-19 screener online and determine if the screener appropriately considers their personal medical history or risk. As with many voluntary self-monitoring tools, these screeners are likely significantly underused.
We piloted a new approach to promote COVID-19 screener adoption for at-risk populations. Our approach enables integration of COVID-19 screening into a chronic disease symptom-monitoring intervention. By engaging patients in COVID-19 screening as part of routine care, this approach may have the potential to improve screening capacity and provide real-time, patient-reported data for research and disease surveillance.
Prior to the COVID-19 pandemic, we developed a clinically integrated mobile health intervention for monitoring asthma symptoms between visits and have recently adapted it for use in primary care. Consistent with guidelines that recommend routine symptom monitoring, English- and Spanish-speaking patients used an app to answer five questions weekly about their asthma control. If questionnaire symptom scores were declining or worse than their previously reported baseline scores, patients could request a call from a nurse from their primary care clinic. The app also let patients review their symptoms over time, enter notes, and watch educational videos. Patients’ health care providers could view the patient-reported symptoms from within the electronic health record and receive reminders to review the data before the patients’ visits. We demonstrated that this approach is feasible to implement and has high adherence rates. Others have shown similar results in other conditions, such as rheumatoid arthritis.
At the onset of the COVID-19 pandemic, we modified the asthma app to incorporate a COVID-19 symptom screener (exhibit 1) used at our health care institution that asks patients about COVID-19 symptoms and close contacts. Patients were reminded about the screener each week after they completed asthma symptom questionnaires. Patients with worsening or otherwise problematic asthma symptoms (many of which are also symptoms of COVID-19) received a prompt to use the COVID-19 screener. Positive responses prompted patients to call the institutional hotline associated with their primary care clinic for further evaluation.

Source: Authors.
Our preliminary analyses demonstrated high adoption of the integrated COVID-19 screener. Among 95 patients who used the app for asthma symptom monitoring during a three-month period (March 23–June 22, 2021), 65 (68.4 percent) completed the COVID-19 screener at least once (exhibit 2). In total, the COVID-19 screener was completed 183 times. Of those screener completions, 143 (78.14 percent) occurred in the context of worsening or otherwise problematic patient-reported symptoms; 29 (15.85 percent) occurred in the context of a weekly questionnaire used when patient-reported symptoms were close to or above baseline; and 11 (6.01 percent) occurred at times independent from weekly questionnaire use; in other words, the patient proactively used the screener without being prompted to do so.

Source: Authors’ analysis.
In an average week during this three-month period, asthma questionnaire completion rates were 74.8 percent (ranging from 64.9 percent to 83.1 percent). For patients who were prompted to complete the COVID-19 screener in response to problematic asthma symptoms, the average overall COVID-19 screener completion rate was 71.1 percent (range from 35.7 percent to 94.4 percent across weeks). For patients whose weekly questionnaire results did not prompt a nudge to complete the COVID-19 screener (that is, due to having symptoms closer to their baselines), the overall average COVID-19 screener completion rate was 4.1 percent (ranging from 0.0 to 10.9 percent across weeks). (See exhibit 3.)

Source: Authors’ analysis.
Our data suggest that COVID-19 screeners can be easily deployed as part of a clinically integrated symptom-monitoring intervention. Asthma serves as a strong use case for screener integration into a chronic disease symptom monitoring intervention: Screener completion rates were higher in the context of patient-reported worsening asthma symptoms.
As an integrated tool, screeners have the potential to reach individuals disproportionately impacted by chronic diseases with risk factors for worse outcomes from COVID-19 infection. Screeners may facilitate better data collection and COVID-19 management efforts for these individuals. Furthermore, when such chronic disease symptom-monitoring apps are optimized for patients with lower technology and health literacy, they may have potential to reach individuals from underserved and at-risk communities. This approach has the potential to provide more data compared to volunteer networks of individuals who track their symptoms over time, specifically for COVID-19 studies.
Additional efforts may be needed to enable adaptation of integrated COVID-19 screener design as new scientific knowledge or variant-related symptoms develop and to optimize integration to symptom-monitoring apps across a range of conditions. However, if between-visit symptom monitoring were part of routine care, as we have previously argued, COVID-19 screeners could become widely accessible, ensuring that patients, clinics, and the health care system are better prepared for pandemics.
This project was supported by Grant No. R18HS026432 from the Agency for Healthcare Research and Quality. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality.

source