Table 2.

Using a Sociotechnical Systems Framework for the Application of Al in Health Care Delivery to Describe Participant Preferences on People, Process, and Technology

Domain	Themes and Subthemes	Salient Quotes
People	Who should have access to AI-derived social data? “Circle of care” team or anyone already having access to patient record Uncertainty whether clerical staff and/or patients should have access Appropriate to be accessed for quality improvement, practice-related purposes (eg, program planning/development, practice management, resource allocation) and research No access for private/third-party entities outside of circle of care (eg, insurance companies, housing agencies, any commercial organization)	“I think it’s very important to really understand those vulnerabilities linked to the social determinants to, kind of, allocate your resources as a provider, how much time investment is required to cater to the specific needs. So yeah, definitely, that information should be available to all the providers in the family health team, so they can provide that targeted, tailored care.”
People	Who should take action if a social need is identified through the AI tool? Should be led by most responsible provider (usually the family physician) Varying levels of action for different team members involved with patient care (eg, social workers, nurses) Many expressed the challenge of deciding when and how to act on an identified social need	“I think MRP is the most responsible. But I think anybody that sees that information could take a step to act on it. So you know, if they they’re meeting with nursing that day, and they notice something, and it’s something that might be appropriate for a referral to a social worker, the income program, you know, we get referrals from doc, from nurses, everybody does.”
Process	Start with pilot implementation Focus on 1 or 2 social determinants initially Verify AI response with patients to establish accuracy of the tool Anticipate guidance or management required according to AI output Obtain feedback from clinicians at end of pilot phase to measure satisfaction and usefulness	“How would I go about contacting the patient and saying, ‘Hey, the computer thinks you might have low income? What’s your income?’ How would that communication piece go?”
	Workflow considerations Patients were to verify/confirm social need once identified, but participants were uncertain how to do this without concerning their patients Additional staff time and resources needed Participants desired a balance between asking for SDOH information directly from patients (eg, surveys) and using AI to derive it where missing Participants indicated that consent should be sought from patients to use AI to derive social information (either direct or implied)	“I can’t imagine telling all my patients that AI is going to be reviewing their charts. They would absolutely never see me again.” “… for an individual social worker or physician, I think this would add work to our day. But probably provide better care. There’s a chance that we’d maybe solve their homelessness earlier and then later not have to deal with terrible mental health issues. So I guess that could be time gained. But overall, I suspect it would cause more work, which isn’t bad, because it’s probably for the best of the patient.”
	Activities or initiatives to support the adoption and integration of the AI tool Regularly scheduled meetings to discuss AI tool, implementation, and evaluation Use team to develop the algorithms alongside FHT staff who are ideally knowledgeable about the clinical environment Additional hours/staffing for nursing, physician assistant, and/or social work More staff for income and housing supports Ensure free tax clinics for patients are available Hire additional community health workers to conduct telephone checkins with vulnerable patients Ensure good connections and referral pathways to community agencies (ie, housing, income, gender transitioning) Plans or recommendations for physicians managing a large volume of messages flagging social needs or concerns identified by the AI tool, which would then need to be sorted and verified; this is especially pertinent for the FHT, as they provide care for a large proportion of patients who would potentially be flagged with social needs or concerns Meaningful and long-term engagement with patients and communities Support from leadership and clinic management	“But if you want it to be more actionable, then you’d have to have scheduled meetings and have people suited to the clinical environment to help develop algorithms with the staff. So [you’d need] personnel to help do that. And ideally, like nursing and social work hours or physician assistant hours, but that’s like in a dream world, because that’s a huge cost.” “It would be something I feel like management could be involved in supporting, whether it’s programs run by the nurses or something, but like we would need support from management and leadership.”
Technology	What SDOH data should be included in the AI tool? All participants agreed on housing and income insecurity as priorities Other SDOH suggested by participants: drug benefits/coverage and other medical coverage (eg, relevant to which medications are prescribed and allied health referrals, such as physiotherapy and massage therapy), sexual orientation, gender, country of origin, education, food insecurity, social isolation (particularly for elderly patients or immigrants), ability to navigate the health care system, health care access Date associated with each determinant	“Income is such a broad category, that kind of ties to so many different aspects like food security, housing, job security. And usually, it’s almost like, it’s so interchangeable, like, because of the health, you know, all these things are affected, or because of the income, the health is affected. So it just relates so well. So that [income] will be a very broad theme that should be given good focus.” “… Sure, it takes a lot of work and resources to get something like this going. So if we know that it’s this … and then maybe we move on to another one. We’d say like, ‘Oh, I really like housing and income, it’s really important. It’s helpful.’ And maybe the rest of it is like, we’re okay to do without or something, we can just figure that out. And it’s less critical or maybe down the road.” “Like the prescribing, you briefly glance at the side to see ‘Do they have insurance coverage?’, like ‘What did they do for work?’ all of like micro pieces of information that guide your decision with income and employment.”
Technology	How could this AI tool be most useful? Embedded in patient record/EHR AI tool to gather and summarize important information from patient record Ensure tool provides actionable output Monitor changes in patient status (eg, housing, income) and alert if potential challenge arises Automatic prompts for specific appointment or referral related to social work, income support, telephone support, or other resources AI tool output connected to local, evidence-based solutions	“I think kind of a change in status could also be interesting, you know, someone who’s kind of been as, let’s say, middle of the road, and then all of a sudden, the algorithm predicts that there’s been a significant drop in their income security, housing security, etcetera. And flagging that to the provider, kind of using that as a prompt to have a discussion around that. I think that could also be a pretty useful tool.” “But if we could use it for programming, like, if we find that like, a lot of our patients are low income and not filing their taxes, then we could send them directly to like tax clinics and make sure that those get done.”

AI = artificial intelligence; EHR = electronic health record; FHT = family health team; MRP = most responsible provider; SDOH = social determinants of health.
Note: Framework was developed by Salwei and Carayon.⁹