Patient Perceptions of Artificial Intelligence–Supported Shared Decision-Making in UK Primary Care for Multiple Long-Term Conditions: Qualitative Study - Scorecard - MDSpire
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Patient Perceptions of Artificial Intelligence–Supported Shared Decision-Making in UK Primary Care for Multiple Long-Term Conditions: Qualitative Study
Clinical Scorecard: Exploring Patient Views on AI-Enhanced Shared Decision-Making in UK Primary Care for Multiple Chronic Conditions: A Qualitative Analysis
At a Glance
Category
Detail
Condition
Multiple Long-Term Conditions (MLTCs)
Key Mechanisms
Shared decision-making (SDM) supported by artificial intelligence (AI) for personalized care.
Target Population
Patients with multiple chronic conditions in UK primary care.
Care Setting
Primary care consultations.
Key Highlights
MLTCs are defined as the coexistence of 2 or more chronic conditions.
SDM is a collaborative approach that incorporates patient preferences and evidence.
AI can enhance SDM by providing personalized information and decision aids.
Challenges in SDM include patient readiness, power dynamics, and organizational support.
Concerns exist regarding medicolegal vulnerability in SDM practices.
Guideline-Based Recommendations
Diagnosis
Recognize the complexity of MLTCs and the need for tailored diagnostic approaches.
Management
Implement shared decision-making strategies in managing MLTCs.
Monitoring & Follow-up
Utilize AI tools for ongoing assessment of treatment efficacy and patient engagement.
Risks
Be aware of the risks associated with polypharmacy and inappropriate prescribing.
Patient & Prescribing Data
Patients with multiple chronic conditions experiencing polypharmacy.
AI can optimize treatment choices by analyzing patient data to minimize risks.
Clinical Best Practices
Enhance clinical communication skills to facilitate effective SDM.
Incorporate AI tools to support medication decisions and patient engagement.
by Charlotte Spurway, Sarah Flanagan, Jenny Cooper, Francesca L Crowe, Shamil Haroon, Tom Marshall, Leah Fitzsimmons, Eleanor Hathaway, Krishnarajah Nirantharakumar, Thomas Jackson, Sheila Greenfield, Louise Jackson
