Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare.

OBJECTIVE: The complexity and rapid pace of development of algorithmic technologies pose challenges for their regulation and oversight in healthcare settings. We sought to improve our institution's approach to evaluation and governance of algorithmic technologies used in clinical care and operations by creating an Implementation Guide that standardizes evaluation criteria so that local oversight is performed in an objective fashion. MATERIALS AND METHODS: Building on a framework that applies key ethical and quality principles (clinical value and safety, fairness and equity, usability and adoption, transparency and accountability, and regulatory compliance), we created concrete guidelines for evaluating algorithmic technologies at our institution. RESULTS: An Implementation Guide articulates evaluation criteria used during review of algorithmic technologies and details what evidence supports the implementation of ethical and quality principles for trustworthy health AI. Application of the processes described in the Implementation Guide can lead to algorithms that are safer as well as more effective, fair, and equitable upon implementation, as illustrated through 4 examples of technologies at different phases of the algorithmic lifecycle that underwent evaluation at our academic medical center. DISCUSSION: By providing clear descriptions/definitions of evaluation criteria and embedding them within standardized processes, we streamlined oversight processes and educated communities using and developing algorithmic technologies within our institution. CONCLUSIONS: We developed a scalable, adaptable framework for translating principles into evaluation criteria and specific requirements that support trustworthy implementation of algorithmic technologies in patient care and healthcare operations.

Costs and effectiveness of ximelagatran for stroke prophylaxis in chronic atrial fibrillation.

CONTEXT: Recent trials have found that ximelagatran and warfarin are equally effective in stroke prevention for patients with atrial fibrillation. Because ximelagatran can be taken in a fixed, oral dose without international normalized ratio monitoring and may have a lower risk of hemorrhage, it might improve quality-adjusted survival compared with dose-adjusted warfarin. OBJECTIVE: To compare quality-adjusted survival and cost among 3 alternative therapies for patients with chronic atrial fibrillation: ximelagatran, warfarin, and aspirin. DESIGN: Semi-Markov decision model. PATIENTS: Hypothetical cohort of 70-year-old patients with chronic atrial fibrillation, varying risk of stroke, and no contraindications to anticoagulation therapy. MAIN OUTCOME MEASURES: Quality-adjusted life-years (QALYs) and costs in US dollars. RESULTS: For patients with atrial fibrillation but no additional risk factors for stroke, both ximelagatran and warfarin cost more than 50,000 dollars per QALY compared with aspirin. For patients with additional stroke risk factors and low hemorrhage risk, ximelagatran modestly increased quality-adjusted survival (0.12 QALY) at a substantial cost (116,000 dollars per QALY) compared with warfarin. For ximelagatran to cost less than 50,000 dollars per QALY it would have to cost less than 1100 dollars per year or be prescribed to patients who have an elevated risk of intracranial hemorrhage (>1.0% per year of warfarin) or a low quality of life with warfarin therapy. CONCLUSION: Assuming equal effectiveness in stroke prevention and decreased hemorrhage risk, ximelagatran is not likely to be cost-effective in patients with atrial fibrillation unless they have a high risk of intracranial hemorrhage or a low quality of life with warfarin.