Digital health innovations have been rapidly implemented and scaled to provide solutions to health delivery challenges posed by the coronavirus disease (COVID-19) pandemic. This has provided people with ongoing access to vital health services while minimizing their potential exposure to infection and allowing them to maintain social distancing. However, these solutions may have unintended consequences for health equity. Poverty, lack of access to digital health, poor engagement with digital health for some communities, and barriers to digital health literacy are some factors that can contribute to poor health outcomes. We present the Digital Health Equity Framework, which can be used to consider health equity factors. Along with person-centered care, digital health equity should be incorporated into health provider training and should be championed at the individual, institutional, and social levels. Important future directions will be to develop measurement-based approaches to digital health equity and to use these findings to further validate and refine this model.

Currently, relatively few patients and psychiatrists use telepsychiatry. In addition, patients scarcely access telepsychiatry for posthospitalisation follow-up. This study, which serves as a preliminary baseline for telepsychiatry in Ontario, demonstrates that telepsychiatry has not evolved systematically to address need and highlights the importance of system-level planning when implementing telepsychiatry to optimise access to care.

Background Telepsychiatry is an increasingly used model of mental health care that connects patients with psychiatrists at a distance via videoconference. Telepsychiatry is an effective clinical intervention that improves access to quality care in regions with limited resources or in clinical situations where in-person care is unavailable. Objective This study aims to develop a validated survey tool to measure patient experience and satisfaction with telepsychiatry based on the quality of care domains. This study also seeks to understand which health service outcomes were most strongly correlated with overall satisfaction in the context of telepsychiatry. Methods The survey created in this study was developed and validated with a panel of subject matter and process experts and was piloted with 274 patients who received clinical consultations through the TeleMental Health Program at the Centre for Addiction and Mental Health. Factor analysis was used to determine correlations between questions and quality of care domains and was also used to assess model fit. Results The study provides a validated survey to measure patient satisfaction and experience with telepsychiatry across 4 domains: access and timeliness, appropriateness, effectiveness, and safety. Both safety and access and timeliness were found to be statistically significant predictors of satisfaction in our sample. Conclusions By situating patient satisfaction and experience within this framework, the survey facilitates patient data collection and interpretation through a clinical quality lens.

UNSTRUCTURED Digital health innovations have been rapidly implemented and scaled to provide solutions to some health delivery challenges posed by the Covid-19 pandemic. This has enabled ongoing access to vital health services while minimizing potential exposure to infection and maintaining social distancing. However, these solutions may have unintended consequences on health equity. Poverty, access to digital health, poor engagement with digital health for some communities, and barriers to digital health literacy are some of the factors that can contribute to poor health outcomes. We present the Digital Health Equity Framework, which can be used to consider health equity factors. Along with person-centered care, digital health equity should be incorporated into health provider training, and should be championed the individual, institutional, and social levels. Important future directions will be to develop measurement-based approaches to digital health equity, and to use these findings to further validate and refine this model.