This paper motivates institutional epistemic trust as an important ethical consideration informing the responsible development and implementation of artificial intelligence (AI) technologies (or AI-inclusivity) in healthcare. Drawing on recent literature on epistemic trust and public trust in science, we start by examining the conditions under which we can have institutional epistemic trust in AI-inclusive healthcare systems and their members as providers of medical information and advice. In particular, we discuss that institutional epistemic trust in AI-inclusive healthcare depends, in part, on the reliability of AI-inclusive medical practices and programs, its knowledge and understanding among different stakeholders involved, its effect on epistemic and communicative duties and burdens on medical professionals and, finally, its interaction and alignment with the public’s ethical values and interests as well as background sociopolitical conditions against which AI-inclusive healthcare systems are embedded. To assess the applicability of these conditions, we explore a recent proposal for AI-inclusivity within the Dutch Newborn Screening Program. In doing so, we illustrate the importance, scope, and potential challenges of fostering and maintaining institutional epistemic trust in a context where generating, assessing, and providing reliable and timely screening results for genetic risk is of high priority. Finally, to motivate the general relevance of our discussion and case study, we end with suggestions for strategies, interventions, and measures for AI-inclusivity in healthcare more widely.

Objectives: Congenital heart defects (CHD) are an important cause of death and morbidity in early childhood, but the effectiveness of alternative newborn screening strategies in preventing the collapse or death—before diagnosis—of infants with treatable but life-threatening defects is uncertain. We assessed their effectiveness and efficiency to inform policy and research priorities.

Methods: We compared the effectiveness of clinical examination alone and clinical examination with either pulse oximetry or screening echocardiography in making a timely diagnosis of life-threatening CHD or in diagnosing clinically significant CHD. We contrasted their cost-effectiveness, using a decision-analytic model based on 100,000 live births, and assessed future research priorities using value of information analysis.

Results: Clinical examination alone, pulse oximetry, and screening echocardiography achieved 34.0, 70.6, and 71.3 timely diagnoses per 100,000 live births, respectively. This finding represents an additional cost per additional timely diagnosis of £4,894 and £4,496,666 for pulse oximetry and for screening echocardiography. The equivalent costs for clinically significant CHD are £1,489 and £36,013, respectively. Key determinants of cost-effectiveness are detection rates and screening test costs. The false-positive rate is very high with screening echocardiography (5.4 percent), but lower with pulse oximetry (1.3 percent) or clinical examination alone (.5 percent).

Conclusions: Adding pulse oximetry to clinical examination is likely to be a cost-effective newborn screening strategy for CHD, but further research is required before this policy can be recommended. Screening echocardiography is unlikely to be cost-effective, unless the detection of all clinically significant CHD is considered beneficial and a 5 percent false-positive rate acceptable.