Transdisciplinary Collaboration: Harnessing AI in Healthcare for Holistic Solutions - Part 1

Artificial Intelligence (AI) is transforming healthcare (if not revolutionizing it), offering unprecedented opportunities to enhance patient care, improve diagnostics, and streamline operations. However, the successful implementation of AI in healthcare is not straightforward and requires a nuanced approach that leverages the strengths of various disciplines.

In a three-part article series, I explore the three key approaches to integrating AI in healthcare—Multidisciplinary, Interdisciplinary, and Transdisciplinary, how they should be managed, and the process for Transdisciplinary design and implementation.

Understanding the Three Approaches

1. Multidisciplinary Approach: This method involves multiple disciplines working in parallel. Each discipline contributes its expertise independently, focusing on specific aspects of a problem. While this approach brings diverse perspectives to a project, it often lacks integration and holistic understanding.
2. Interdisciplinary Approach: In this approach, disciplines work collaboratively, blending their knowledge and methods to create integrated solutions. This leads to more cohesive outcomes but still within the confines of their specific expertise.
3. Transdisciplinary Approach: This approach transcends traditional disciplinary boundaries, fostering a holistic perspective that integrates knowledge from various fields and stakeholders. It is particularly suited for complex, real-world problems where a unified, cohesive solution is essential.

Comparison of Approaches

Examples of AI in Healthcare

AI-Enhanced MRI Machine (Multidisciplinary Approach):

In a multidisciplinary project, the smart pill dispenser would involve electrical engineers designing the hardware, software developers creating the app interface, and clinical pharmacologists defining medication schedules. Each team works independently, contributing their expertise without significant integration. The AI component helps in reminding patients to take their medication and notifies caregivers if doses are missed.

AI-Based Glucose Monitoring System (Interdisciplinary Approach):

An interdisciplinary approach to developing an AI-based glucose monitoring system would involve biomedical engineers, endocrinologists, and software developers working closely together. They blend their knowledge to design sensors, develop predictive algorithms, and create a user-friendly interface. This collaboration ensures that the device not only accurately monitors glucose levels but also provides actionable insights to users.

Comprehensive Telehealth Platform (Transdisciplinary Approach):

A transdisciplinary approach is exemplified by the development of a comprehensive telehealth platform. This project involves biomedical engineers, healthcare informatics experts, social scientists, public health policymakers, and community representatives working together from the outset. By integrating their diverse perspectives, they create a holistic solution that addresses technological, social, and regulatory challenges. The platform uses AI to provide remote diagnostics, continuous patient monitoring, and health education, ensuring it is culturally appropriate, accessible, and effective.

The need for Transdisciplinary approach to Healthcare AI

Implementing AI in healthcare is a complex process that benefits significantly from a transdisciplinary approach. By transcending traditional boundaries and integrating diverse perspectives, healthcare solutions can be more innovative, effective, and holistic. The examples of the AI-enhanced MRI machine, AI-based glucose monitoring system, and comprehensive telehealth platform illustrate how different approaches influence the design and impact of AI in healthcare.

Embracing a transdisciplinary approach not only enhances the potential of AI but also ensures that healthcare innovations are sustainable and truly transformative.

Shayan Mshatian

Founder, Silverberry.ai

PS. Correction: I had mentioned MRI as an example of a Multidisciplinary approach, however, I received feedback from Kouhyar Tavakolian that MRI is one of the most integrated imaging systems ever created, the hardware and software design is totally intertwined, and teams can not possibly work independently. The example is replaced by a Smart Pill Dispenser. It seems I need to take a course on medical imaging!