Applied clinical informatics · 2026
Co-designing an Outpatient Clinical Decision Support Prototype for Managing Social Risks in Patients Living with Dementia.
СтатьяПоддержка NIH: внешняя программаНазвание и аннотация: Перевод пока не подготовлен
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Alfaqih Miad Ahemd, Haessner Philipp, LeLaurin Jennifer H, Guo Jingchuan, Hammer Nicole C, Ike-Okpe Onyekachi, Pappa Michael J, He Xing, Salloum Ramzi G, Bian Jiang, Gregory Megan E
Аннотация
BACKGROUND: Patients living with dementia (PLWD) require attention to social determinants of health (SDoH), but social information is often unavailable or incomplete during care encounters, and clinicians report uncertainty about how to act on this information.
OBJECTIVE: This study aimed to co-design the Intelligent Social Risk Management in Alzheimer's Disease and Alzheimer's Disease-Related Dementias Patients (iSMART) clinical decision support (CDS) prototype, which integrates an AI-driven individualized polysocial risk score (iPsRS) to identify PLWD at high social risk for hospitalization.
METHODS: We conducted a qualitative user-centered design study with nine outpatient providers and clinical staff who care for PLWD at a large academic health system. Participants completed semi-structured interviews to explore perceived social risks in dementia care, gather feedback on the iSMART prototype and its features, and identify implementation considerations. Interview transcripts were coded and analyzed via rapid qualitative and thematic analysis.
RESULTS: Nine participants (six providers, two nurses, and one social worker) were interviewed. Lack of caregiver or family support was identified as the most important social factor to consider for PLWD, followed by financial strain and transportation issues. Participants described the iSMART prototype as helpful for identifying social risks among PLWD, summarizing and prioritizing factors contributing to hospitalization risk, and connecting patients to relevant social resources. Participants suggested primary care providers and social workers should be the primary users. Recommended improvements included auto-populated (as opposed to manual entry) but editable SDoH fields for model input, incorporating caregiver presence as a model input, and providing clearer visual representations of risk.
CONCLUSION: Outpatient providers and staff viewed the iSMART prototype as a promising approach to support social risk screening, resource connection, and referral support in dementia care. These findings inform practical strategies for integrating iPsRS-informed CDS tools into routine workflows in dementia clinics.
OBJECTIVE: This study aimed to co-design the Intelligent Social Risk Management in Alzheimer's Disease and Alzheimer's Disease-Related Dementias Patients (iSMART) clinical decision support (CDS) prototype, which integrates an AI-driven individualized polysocial risk score (iPsRS) to identify PLWD at high social risk for hospitalization.
METHODS: We conducted a qualitative user-centered design study with nine outpatient providers and clinical staff who care for PLWD at a large academic health system. Participants completed semi-structured interviews to explore perceived social risks in dementia care, gather feedback on the iSMART prototype and its features, and identify implementation considerations. Interview transcripts were coded and analyzed via rapid qualitative and thematic analysis.
RESULTS: Nine participants (six providers, two nurses, and one social worker) were interviewed. Lack of caregiver or family support was identified as the most important social factor to consider for PLWD, followed by financial strain and transportation issues. Participants described the iSMART prototype as helpful for identifying social risks among PLWD, summarizing and prioritizing factors contributing to hospitalization risk, and connecting patients to relevant social resources. Participants suggested primary care providers and social workers should be the primary users. Recommended improvements included auto-populated (as opposed to manual entry) but editable SDoH fields for model input, incorporating caregiver presence as a model input, and providing clearer visual representations of risk.
CONCLUSION: Outpatient providers and staff viewed the iSMART prototype as a promising approach to support social risk screening, resource connection, and referral support in dementia care. These findings inform practical strategies for integrating iPsRS-informed CDS tools into routine workflows in dementia clinics.