Doctors on AI Adoption in Indian Medical Practice: A Sentiment and Feeler Survey

"Sentiments I see is that they were seeing AI from their own window of thought and trying to twist AI to fit in their bracket, not knowing that they might be forced to put themselves into AI frame of work and align their working routines in coming future."

Doctors' survey results on AI were enlightening, showing both excitement and uncertainty about its role in medicine. While AI has great potential in healthcare, doctors need to understand it fully to use it effectively. AI is already being used for personalized treatments, virtual assistants, remote monitoring, and more. To help doctors adopt AI, they need training on its benefits, real-case demonstrations, and ongoing education in digital health technologies. Real-world examples, like cancer detection algorithms and FDA-approved AI systems, and many more… can show AI's potential in healthcare.

The US FDA site lists some pointers on AI related authorizations

• 87% of devices on this list authorized in calendar year 2022 are in Radiology (122), followed by 7% in Cardiovascular (10) and 1% each in Neurology (2), Hematology (1), Gastroenterology/Urology (1), Ophthalmic (2), Clinical Chemistry (1) and Ear, Nose and Throat (1).?
• Through the end of July 2023, 79% of devices authorized in 2023 are in Radiology (85), 9% in Cardiovascular (10), 5% in Neurology (5), 4% in Gastroenterology/Urology (4), 2% in Anesthesiology (2), and 1% each in Ear, Nose and Throat (1), and Ophthalmic (1).
• In addition to having the largest number of submissions, Radiology has experienced the steadiest increase of AI/ML-enabled device submissions of any specialty.?
• In general, machine learning models have ranged in complexity from shallow (less than two hidden layers) models to more complex models (deep learning models).
• Models have generally trended toward more hybrid approaches, combining different algorithmic approaches to achieve the result of a safe and effective device (for example, using one model to generate features, and using another model to do classification).

(source:https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices )

The Survey

Despite the potential benefits, a considerable number of doctors have not yet embraced AI in their practice, indicating a lack of awareness or hesitation towards its implementation.

While there is a growing recognition of AI's potential in healthcare, the adoption rate among doctors in India remains modest. This survey was purely to capture sentiments and feelers in qualitative way with 46 respondents and not qualitative. The way to look at it is not by weightage and just by their current set of sentiments. The survey highlights both the opportunities and challenges associated with integrating AI into medical practice. Addressing concerns such as data privacy, skill gaps, and workflow integration will be crucial in realizing the full benefits of AI in improving patient care and operational efficiency. As AI continues to evolve, its role in healthcare delivery is expected to expand, driving positive transformation and ultimately enhancing the quality of healthcare services.

Q1) AI Tools Integration:

Among the 46 doctors surveyed in India, only a minority have integrated AI tools into their medical practice. The most integrated tools are Remote Monitoring and Predictive Analytics, indicating a recognition of the potential benefits of these technologies. These were from corporate hospitals. However, a significant portion stated that they do not currently use AI. This suggests a prevailing gap in AI adoption within the medical community. I see an insight here despite the potential benefits, a considerable number of doctors have not yet embraced AI in their practice, indicating a lack of awareness or hesitation towards its implementation. Sentiments were jumbled up as mixed sentiment with hints of curiosity and skepticism towards AI adoption in medical practice.

Q2) Effectiveness of AI Tools:

Of the respondents, 37% perceive AI tools as highly effective in improving patient care, while 26% find them moderately effective. However, a significant portion (27%) either do not use AI or are not aware of its impact, suggesting a need for more education and experience in this area. Insight here is there is a positive perception of AI's effectiveness in enhancing patient care among the majority of doctors who have integrated AI tools into their practice. But many doctors individual response if noted are not clear how. Generally positive sentiments towards the effectiveness of AI tools was seen, with room for improvement in awareness and understanding among some respondents.

Q3) Areas of Impact for AI:

The respondents believe that AI could have the most significant impact in the areas of Diagnostics (28 responses), Treatment and Decision Planning (22 responses), and Patient Engagement (26 responses). Interestingly, Administrative Tasks (24 responses) also emerged as a key area for potential AI impact. Doctors recognize the diverse applications of AI in healthcare, spanning from clinical decision-making to patient interaction and administrative tasks. However, sentiments were they were seeing AI from their own window of thought and trying to twist AI to fit in their bracket. Not knowing that they might be forced to put themselves into AI frame of work and align their working routines. Positive sentiment towards the potential of AI to revolutionize various aspects of medical practice, with an emphasis on improving efficiency and patient outcomes.

Q4) Factors Influencing Adoption:

The decision to adopt AI tools is primarily influenced by their potential to improve patient outcomes (28 responses) and increase efficiency (34 responses). Cost-effectiveness (17 responses) and peer recommendations (8 responses) also play significant roles. Doctors are motivated to adopt AI tools by their perceived benefits in enhancing patient care and operational efficiency, rather than solely by external factors like peer recommendations or regulatory pressure. Positive sentiment towards the perceived benefits of AI adoption, with a pragmatic approach focused on improving healthcare delivery.

Q5) Implementation Challenges:

The main challenges encountered in implementing AI tools include integration into existing workflows and habits with 26 responses (which corelated to what was asked and analysed in Q3…) and ?data privacy concerns, and the limitations of skilled staff for AI. These challenges underscore the importance of addressing infrastructure and skill gaps in AI adoption.

Despite recognizing the potential benefits, doctors face practical challenges in integrating AI into their medical practice, highlighting the need for supportive infrastructure and training programs. Specially, what I see it as they need someone who knows medicine and AI both to hand hold them were expressed with mixed sentiment reflecting both enthusiasm for AI adoption and concerns regarding its seamless integration and data security.

Q6) Mundane Tasks for AI Handling:

Doctors believe that AI could effectively handle mundane tasks such as Appointment Scheduling (31 responses), Documentation and EHR/EMR (27 responses), and Patient Follow-up Communication (27 responses). This reflects a desire to leverage AI for administrative efficiency and workflow optimization. A big insight I can see here is there is a clear recognition of the potential for AI to automate routine tasks, ?and not aware of to what level AI can do further for a doctor or a healthcare system. They seems to be happy with something that allows medical professionals to focus on more critical aspects of patient care and decision-making. Sentiments: Positive sentiment towards the prospect of AI streamlining administrative tasks, with an acknowledgment of its role in improving overall healthcare delivery.

Comments Insights:

• Positive Sentiments: Doctors recognize AI's potential to enhance healthcare delivery through improved patient engagement, personalized treatment plans, and administrative efficiency. There is optimism regarding AI's ability to revolutionize healthcare by facilitating early disease detection, enhancing diagnostic accuracy, and optimizing resource allocation.
• Negative Sentiments: Some express concerns about data privacy, integration challenges, and the need for skilled staff, highlighting potential barriers to AI adoption. There are reservations about replacing human expertise, particularly in complex medical procedures and patient management.
• Neutral Sentiments: Several comments express a willingness to learn and implement AI tools, indicating a balanced perspective on its potential benefits and challenges. Some respondents emphasize the importance of a gradual approach to AI implementation, starting with simpler tasks before advancing to more complex medical aspects.