Clinicians' roles and necessary levels of understanding in the use of artificial intelligence: A qualitative interview study with German medical students.

BACKGROUND: Artificial intelligence-driven Clinical Decision Support Systems (AI-CDSS) are being increasingly introduced into various domains of health care for diagnostic, prognostic, therapeutic and other purposes. A significant part of the discourse on ethically appropriate conditions relate to the levels of understanding and explicability needed for ensuring responsible clinical decision-making when using AI-CDSS. Empirical evidence on stakeholders' viewpoints on these issues is scarce so far. The present study complements the empirical-ethical body of research by, on the one hand, investigating the requirements for understanding and explicability in depth with regard to the rationale behind them. On the other hand, it surveys medical students at the end of their studies as stakeholders, of whom little data is available so far, but for whom AI-CDSS will be an important part of their medical practice. METHODS: Fifteen semi-structured qualitative interviews (each lasting an average of 56 min) were conducted with German medical students to investigate their perspectives and attitudes on the use of AI-CDSS. The problem-centred interviews draw on two hypothetical case vignettes of AI-CDSS employed in nephrology and surgery. Interviewees' perceptions and convictions of their own clinical role and responsibilities in dealing with AI-CDSS were elicited as well as viewpoints on explicability as well as the necessary level of understanding and competencies needed on the clinicians' side. The qualitative data were analysed according to key principles of qualitative content analysis (Kuckartz). RESULTS: In response to the central question about the necessary understanding of AI-CDSS tools and the emergence of their outputs as well as the reasons for the requirements placed on them, two types of argumentation could be differentiated inductively from the interviewees' statements: the first type, the clinician as a systemic trustee (or "the one relying"), highlights that there needs to be empirical evidence and adequate approval processes that guarantee minimised harm and a clinical benefit from the employment of an AI-CDSS. Based on proof of these requirements, the use of an AI-CDSS would be appropriate, as according to "the one relying", clinicians should choose those measures that statistically cause the least harm. The second type, the clinician as an individual expert (or "the one controlling"), sets higher prerequisites that go beyond ensuring empirical evidence and adequate approval processes. These higher prerequisites relate to the clinician's necessary level of competence and understanding of how a specific AI-CDSS works and how to use it properly in order to evaluate its outputs and to mitigate potential risks for the individual patient. Both types are unified in their high esteem of evidence-based clinical practice and the need to communicate with the patient on the use of medical AI. However, the interviewees' different conceptions of the clinician's role and responsibilities cause them to have different requirements regarding the clinician's understanding and explicability of an AI-CDSS beyond the proof of benefit. CONCLUSIONS: The study results highlight two different types among (future) clinicians regarding their view of the necessary levels of understanding and competence. These findings should inform the debate on appropriate training programmes and professional standards (e.g. clinical practice guidelines) that enable the safe and effective clinical employment of AI-CDSS in various clinical fields. While current approaches search for appropriate minimum requirements of the necessary understanding and competence, the differences between (future) clinicians in terms of their information and understanding needs described here can lead to more differentiated approaches to solutions.

Treatment recommendations within the leeway of clinical guidelines: A qualitative interview study on oncologists' clinical deliberation.

BACKGROUND: Recommending the optimal treatment for an individual patient requires a well-balanced consideration of various medical, social and ethical factors. The interplay of these factors, interpretation of the patient's situation and understanding of the existing clinical guidelines can lead to divergent therapy recommendations, depending on the attending physician. Gaining a better understanding of the individual process of medical decision-making and the differences occurring will support the delivery of optimal individualized care within the clinical setting. METHODS: A case vignette of a 64-year-old patient with locally advanced pancreatic adenocarcinoma was discussed with oncologists in 14 qualitative, semi-structured interviews at two academic institutions. Relevant factors that emerged were ranked by the participants using the Q card sorting method. Qualitative data analysis and descriptive statistics were performed. RESULTS: Oncologists recommend different therapeutic approaches within the leeway of the relevant clinical guidelines. One group of participants endorses a rather aggressive and potentially curative approach with a combination chemotherapy following the FOLFIRINOX protocol to provide the patient with the best chances of resectability. The second group suggests a milder chemotherapy approach with gemcitabine, highlighting the palliative approach and the patient's quality of life. Clinical guidelines are generally seen as an important point of reference, but are complicated to apply in highly individual cases. CONCLUSION: The physician's individual assessment of factors, such as biological age, general condition or prognosis, plays a decisive role in treatment recommendations, particularly in those cases which are not fully covered by guidelines. Judgment and discretion remain crucial in clinical decision-making and cannot and should not be fully ruled out by evidence-based guidelines. Therefore, a more comprehensive reflection on the interaction between evidence-based medicine and the physician's estimation of each individual case is desirable. Knowledge of existing barriers can enhance the implementation of guidelines, for example, through medical education.

'One also needs a bit of trust in the doctor ... ': a qualitative interview study with pancreatic cancer patients about their perceptions and views on information and treatment decision-making.

BACKGROUND: Information about diagnosis, treatment options and prognosis has been emphasized as a key to empower cancer patients to make treatment decisions reflecting their values. However, surveys indicate that patients' preferences regarding information and treatment decision-making differ. In this qualitative interview study, we explored pancreatic cancer patients' perceptions and preferences on information and treatment decision-making. PATIENTS AND METHODS: Qualitative in-depth interviews with patients with pancreatic cancer. Purposive sampling and qualitative analysis were carried out. RESULTS: We identified two stages of information and treatment decision-making. Patients initially emphasize trust in their physician and indicate rather limited interest in details about surgical and medical treatment. In the latter stage of disease, patients perceive themselves more active regarding information seeking and treatment decision-making. All patients discuss their poor prognosis. Reflecting on their own situation, all patients interviewed pointed out that hope was an important driver to undergo further treatment also in advanced stages of the disease. Interviewees unanimously emphasized the difficulty of anticipating the time at which stopping cancer treatment would be the right decision. CONCLUSIONS: The findings can serve as starting point for reflection on professional decision-making in pancreatic cancer and larger representative surveys on ethical issues in treatment decision-making in pancreatic cancer.