Targeting ethical considerations tied to image-based mobile health diagnostic support specific to clinicians in low-resource settings: the Brocher proposition

Abstract

Background: mHealth applications assist workflow, help move towards equitable access to care, and facilitate care delivery. They have great potential to impact care in low-resource countries, but have significant ethical concerns pertaining to patient autonomy, safety, and justice.Objective: To achieve consensus among stakeholders on how to address concerns pertaining to autonomy, safety, and justice among mHealth developers and users in low-resource settings, in particular for the application of image-based consultation for diagnostic support.Methods: A consensus approach was taken during a three-day workshop using a purposive sample of global mHealth stakeholders (n = 27) professionally and geographically spread. Throughout a series of introductory talks, group brainstorming, plenary reviews, and synthesis by the moderators, lists of actions were generated that address the concerns engendered by mHealth applications on autonomy, justice and safety, taking into account the development, implementation, and scale-up phases of an mHealth application lifecycle.Results: Several types of actions were recommended; key ones among them included building in risk mitigation measures from the development stage, establishing inclusive consultation processes, using open sources platform whenever possible, training all clinical users, and bearing in mind that the gold standard of care is face-to-face consultation with the patient. Recommendations of patient, community and health system participation and of governance were identified as cutting across the mHealth lifecycle.Conclusion: Priorities agreed-upon at the meeting echo those put forward concerning other domains and locations of application of mHealth. Those more forcefully articulated are the need to adopt and maintain participatory processes as well as promoting self-governance. They are expected to cut across the mHealth lifecycle and are prerequisites to the safeguard of autonomy, safety and justice.

Emotion detection for supporting depression screening

“…In particular, data can be collected only if the users provide a consensus form and they understand what they are consenting to. 7 When systems collect passive data, as data provided by GPS and accelerometer, ethic concerns are particularly relevant because the daily activities of the user may be tracked [ 21 ]. EDApp does not track the patient because all the patient data, including multimedia contents, are taken while the questionnaire is filled in and stored on the clinician device without being transmitted.…”

Dos and don’ts for mHealth-based clinical support among clinicians in South Africa: Results from a 1-day workshop

“…[2] Use of clinician-to-clinician mHealth has proved particularly important during the COVID-19 pandemic, given movement restrictions, the risk of infection spread, and reduced clinical services. However, digital communication raises substantial ethical concerns [3][4][5][6][7][8][9] around the loss of privacy and self-determination inherent in how information is handled, and threats to patient safety emerging from weaknesses in the quality of the digital information deep-rooted in the iterative development process of mHealth apps. Errors and mischievous additions are silent and built in during the app development, [10,11] or result from issues such as clinical users' failure to use mHealth apps and/or devices appropriately, [11,12] or unstandardised and unsupervised environments of use.…”

“…The outcome was a list of actions aimed at reducing threats to autonomy, safety and justice implicit in digital technologies. The recommendations, compiled in the 'Brocher Proposition' , [8] were organised and disaggregated according to the three stages of the life cycle of mHealth applications (development, implementation and scale-up). Once the detailed recommendations had been published, they were synthesised in a set of seven 'pillars' that cut across the phases of technological development and the ethical principles, namely: (i) Be guided by the endpoint; (ii) Apply straightforward clinical standards; (iii) Integrate into existing healthcare system; (iv) Seek guidance from existing regulatory frameworks; (v) Build in protective solutions; (vi) Make ethics a quality assurance measure; and (vii) Focus on self-determination and governance [9] (Table 1).…”

Artificial intelligence, diagnostic imaging and neglected tropical diseases: ethical implications

“…5 However, careful consideration to several ethical concerns arising from artificial intelligence-driven diagnoses of neglected tropical diseases in low-resource settings is critical for maximizing the benefit of this technology. 6 Artificial intelligence applications focused on image-based diagnoses is still in its infancy and therefore, now is an opportune time to ensure that these applications develop within an ethical framework. Here, we outline important ethical challenges faced by low-and middle-income countries that may benefit from the implementation of these technologies.…”

“…Similarly, individuals must be notified of which personal information is being used and stored, where it is being stored, who has access to this data, how it is being accessed and how this personal information is being used or may be used in the future. 1,6 Given that much of this diagnosis technology has been developed in high-income countries for use in low-and middle-income countries, special attention is required. Therefore, the informed consent process…”