Addressing the Primary Challenge in the Medical Device Sector through Generative AI Solutions

Revolutionising Healthcare Supply Chain Management with AI-driven Nomenclature and Classification Solutions

In the realm of healthcare, the spectrum of medical supplies is vast, encompassing everything from surgical instruments to bandages, playing a crucial role in the operations of healthcare facilities. Accurate classification, naming, and coding of these supplies are paramount for various functions, including sourcing, tracking, billing, ordering, inventory management, and most importantly, ensuring patient safety.

However, the medical supply chain faces significant challenges, such as exorbitant transaction costs (up to 4 times higher than other industries), substantial waste (e.g., $5 billion worth of deemed ‘unusable’ COVID-19 PPE), and global overspending on inappropriate care (ranging from 10% to 34% of healthcare spending in OCED countries2).

Nomenclature and classification complexities arise from various factors:

1. Complexity, Diversity, and Standardisation Issues: The diverse nature of medical supplies, coupled with unique specifications, complicates classification. The lack of standardised naming conventions and categorisations across manufacturers or countries further adds to the challenge.

2. Continuous Evolution of Products: Advances in medical technology introduce new products regularly, demanding constant updates to classification systems.

3. Overlapping Categories: Some supplies may fit into multiple categories, leading to confusion in proper classification.

4. Human Errors, Scale, and Skill: Manual errors in entry and categorization, along with the need for continuous staff training, contribute to misclassifications.

5. Regulatory and Compliance Requirements: Varying regulations across regions or countries impact classification, requiring compatibility with different systems.

6. Interoperability and Integration: Seamless communication between healthcare facility systems necessitates compatible classification systems, especially with the presence of legacy systems.

Addressing these challenges involves a combination of technology, training, and meticulous planning. Solutions include investing in modern inventory management systems, ongoing staff training, collaboration with vendors for standardization, and regular review and update of classification systems. Automating this process on a global scale is essential, and emerging technologies like big data, generative AI, and graph analytics offer viable solutions.

While ChatGPT-4 may excel in text summarisation, its application for code-to-code matching has proven ineffective, leading to the assignment of incorrect classification codes—referred to as hallucination3. Vamstar, however, presents a solution that combines generative AI, natural language processing, and knowledge graphs to address these challenges effectively.

Vamstar’s innovative platforms utilise deep data science and AI in the Healthcare and MedTech sectors. With expertise, funding, and collaborations, Vamstar has developed solutions for standardising and automating healthcare product catalogues, leveraging information from diverse sources to enhance contracting, tendering and procurement decision-making.

The heart of Vamstar’s solution lies in the creation of the world’s largest healthcare and life sciences knowledge base. By interconnecting buyers, suppliers, products, services, and medical devices globally, Vamstar’s platform facilitates auto-matching of code and product assignments and classifications with unprecedented accuracy and scalability.

The benefits of Vamstar’s approach include highly scalable and accurate code-to-code matching, code-to-product assignment, product-to-product comparison, product-to-evidence summarisation, and product-to-opportunity matching. By seamlessly integrating generative AI, NLP, and knowledge graphs, Vamstar empowers stakeholders in the healthcare industry to make informed decisions and streamline supply chain processes.

In conclusion, Vamstar stands as a leading AI-powered B2B Healthcare and Lifesciences solution, revolutionising healthcare supply chain management. Through big data and machine learning, Vamstar facilitates intelligent sourcing, faster tendering, simplified contracting, real-time opportunities, and embedded intelligence, ultimately driving efficiency and cost savings across the healthcare ecosystem.