Non-decision time: The Higgs Boson of decision.

Asthma disproportionately affects low-income Black and Hispanic residents of the Bronx in New York, where mortality rates are triple that of the state average []. Contributing factors include suboptimal self-management skills, environmental exposures, poverty, and other social determinants of health (SDoH) []. Effective asthma management requires addressing SDoH and incorporating patient-reported outcomes (PROs) to support self-management and shared decision-making []. Yet, the outpatient setting of U.S. healthcare systems faces barriers to collecting, assessing, and responding to SDoH and implementing PROs due to factors such as time constraints and the lack of personnel (e.g. health educators) []. Mobile health (mHealth) applications (apps) have the potential to support asthma self-management through features such as guideline-based patient education, personalized management algorithms, push notifications, and provider-facing portals for remote care coordination. Yet, there is a shortage of individualized and rigorously studied mHealth apps to support patient-centered asthma interventions []. This research team previously developed and evaluated ASTHMAXcel PRO, an interactive and personalized mHealth app designed to educate and improve self-management in adults with asthma []. Building upon this success, we created ASTHMAXcel Voice, a next-generation mHealth app for asthma that incorporates voice biomarkers for early detection of asthma exacerbations, and collection of SDoH data, to further facilitate shared decision-making and referrals to respiratory specialists for low-income populations. This paper reports a user needs assessment study that we conducted while developing ASTHMAXcel Voice. The objectives of the study were twofold: (1) to solicit user feedback of the app particularly its innovative feature utilizing voice biomarkers, and (2) to identify and understand potential barriers to the adoption and long-term use of the app when it is deployed in real-world settings. ASTHMAXcel Voice incorporates a voice-based asthma exacerbation early detection feature that is based on a voice biomarker platform developed by Sonde Health (Sonde Health, Inc., Boston, Massachusetts, U.S.). The feature assesses the patient’s respiratory dysfunction from a 6-second voice sample using machine learning techniques. The resultant asthma risk score is combined with the SDoH data collected within the app to provide more accurate exacerbation assessments in addition to shared decision-making capabilities between patients and providers. As such, ASTHMAXcel Voice takes a holistic patient-centered approach to asthma management by integrating personalized digital data (e.g., SDoH, PROs, voice biomarkers) and supporting the collaboration between patients and various health services and stakeholders.