Using artificial intelligence to promote equitable care for inpatients with language barriers and complex medical needs: clinical stakeholder perspectives

Abstract

Objectives Inpatients with language barriers and complex medical needs suffer disparities in quality of care, safety, and health outcomes. Although in-person interpreters are particularly beneficial for these patients, they are underused. We plan to use machine learning predictive analytics to reliably identify patients with language barriers and complex medical needs to prioritize them for in-person interpreters. Materials and methods This qualitative study used stakeholder engagement through semi-structured interviews to understand the perceived risks and benefits of artificial intelligence (AI) in this domain. Stakeholders included clinicians, interpreters, and personnel involved in caring for these patients or for organizing interpreters. Data were coded and analyzed using NVIVO software. Results We completed 49 interviews. Key perceived risks included concerns about transparency, accuracy, redundancy, privacy, perceived stigmatization among patients, alert fatigue, and supply–demand issues. Key perceived benefits included increased awareness of in-person interpreters, improved standard of care and prioritization for interpreter utilization; a streamlined process for accessing interpreters, empowered clinicians, and potential to overcome clinician bias. Discussion This is the first study that elicits stakeholder perspectives on the use of AI with the goal of improved clinical care for patients with language barriers. Perceived benefits and risks related to the use of AI in this domain, overlapped with known hazards and values of AI but some benefits were unique for addressing challenges with providing interpreter services to patients with language barriers. Conclusion Artificial intelligence to identify and prioritize patients for interpreter services has the potential to improve standard of care and address healthcare disparities among patients with language barriers.

ChatGPT Usage and Attitudes are Driven by Perceptions of Usefulness, Ease of Use, Risks, and Psycho-Social Impact: A Study among University Students in the UAE

“…This association might indicate the interplay of cultural and demographic elements in the adoption of new technologies such as ChatGPT. For example, Arab students might exhibit more positive attitude to innovative AI technologies possibly due to its utility in overcoming language barriers(Barwise et al 2023;Chen 2023;Mijwil et al 2023b). Nevertheless, this justi cation remain tentative considering the studies showing inferior performance of ChatGPT in non-English languages (Żammit 2023; Sallam and Mousa 2024).…”