A qualitative study to inform the design and implementation of AI-driven diagnosis: Challenges, barriers, and clinical insights of physicians

Clinical Snapshot

Key Findings

• P Value: Not applicable for qualitative study

• Effect Size: Not applicable for qualitative study

• Primary Outcome: Four major themes: clinical experience and practice, diagnostic challenges, diagnostic parameters and decision-making, and AI integration in clinical practice

• Nnt Or Sensitivity: Not applicable for qualitative study

• Confidence Interval: Not applicable for qualitative study

Clinical Application

Findings may inform AI tool development but implementation feasibility requires further quantitative validation Limited direct applicability to Australian practice due to different disease epidemiology, though diagnostic support concepts may be relevant for tropical medicine specialists and infectious disease physicians Physicians managing tropical acute febrile illnesses, particularly in resource-limited settings with diagnostic challenges

Abstract

INTRODUCTION: Acute febrile illnesses are significant clinical challenge in tropical regions due to overlapping symptomatology among infections such as dengue, scrub typhus, and leptospirosis. This diagnostic dilemma leads to delays in appropriate treatment and negatively impacted patient outcome due to limited diagnostic tool availability. Recent advancement in artificial intelligence (AI) application in healthcare help in developing diagnostic aiding tool in such clinical dilemma. AIMS: Study aimed to explore physicians' perspectives on diagnostic challenges of tropical Acute-febrile-illnesses and assess perceived utility of AI as a supportive tool in clinical decision-making. METHODS: A qualitative interview was conducted using validated semi-structured interview guide using literature and expert opinion and validated by IPR method. To understand the physicians perspective on management infectious diseases in critical care, interview guide administered among ten physicians with 10-30 years of experience across different centres of India. Interviews were audio-recorded, transcribed verbatim, and thematically analyzed using ATLAS.ti software. RESULTS: Four major themes emerged: clinical experience and practice, diagnostic-challenges, diagnostic-parameters and decision-making, and AI integration in clinical-practice. However, no statistical test can be performed since study mainly focused to understand perception of physicians with respect to managing illness and hence prevalence cannot be determined. Diseases such as dengue, scrub typhus, and leptospirosis were reported as most prevalent, particularly during monsoon seasons. Key diagnostic challenges included overlapping symptoms, diagnostic delays, limited sensitivity/specificity of available tests, and cost constraints. Physicians primarily relied on clinical judgment and laboratory findings, despite the limitations. Most of the participants expressed positive attitudes toward the potential of AI as supportive tool, citing its ability to enhance diagnostic accuracy and streamline clinical workflow with proper validation. CONCLUSIONS: Growing in clinical dilemma AI has significant role in diagnosis of tropical fever with integration of the clinical data & physician perspective can successfully able to incorporate in clinical application.

References

1. 1.Chitrapady, S., Poojari, P. G., Rashid, M., Kunhikatta, V., Varma D, M., Acharya, R. V., K N, S., Devi, V., Acharya U, D., Khan, S., & Thunga, G. (2026). A qualitative study to inform the design and implementation of AI-driven diagnosis: Challenges, barriers, and clinical insights of physicians. PLoS One. https://doi.org/10.1371/journal.pone.0348519