Abstract
he BMJ Health & Care Informatics presented two editors’ choice papers highlighting artificial intelligence (AI) and the challenges to properly evaluating AI-driven implementation tools associated with healthcare improvement at the system level.
The study from Kueper et al1 focused on AI challenges in the primary care setting in Ontario, Canada. They provided lessons learnt and guidance for future opportunities to improve primary care using AI for resource management. The authors engaged multistakeholders in collaborative consultations. Nine priorities were identified that centred on system-level considerations, such as practice context, organisation and a performance domain devoted to health service delivery and quality of care. The paper highlighted concerns around equity and the digital divide, system capacity and culture, data accessibility and quality, legal and ethical considerations, user-centred design, patient-centredness, and appropriate assessment of AI application.
The study from Kueper et al1 focused on AI challenges in the primary care setting in Ontario, Canada. They provided lessons learnt and guidance for future opportunities to improve primary care using AI for resource management. The authors engaged multistakeholders in collaborative consultations. Nine priorities were identified that centred on system-level considerations, such as practice context, organisation and a performance domain devoted to health service delivery and quality of care. The paper highlighted concerns around equity and the digital divide, system capacity and culture, data accessibility and quality, legal and ethical considerations, user-centred design, patient-centredness, and appropriate assessment of AI application.
| Original language | English |
|---|---|
| Article number | 100650 |
| Pages (from-to) | 1-2 |
| Number of pages | 2 |
| Journal | BMJ Health and Care Informatics |
| Volume | 29 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Aug 2022 |
| Externally published | Yes |