Using generative AI, knowledge graphs and natural language processing in MedTech product and code matching A

Business Challenges

Medical supplies include a wide range of products, from surgical instruments to bandages, that are used in healthcare facilities. Properly classifying and assigning codes to these medical supplies is critical for sourcing, tracking, billing, ordering, inventory management, and patient safety.

Key challenges include the high cost of healthcare supply-chain transactions (up to 4x higher compared to other industries), significant waste incurred e.g. $5Bn worth of COVID-19 PPE deemed ‘unusable’. In addition globally, 10% to 34% of health care spendings of OCED countries were wasted on inappropriate care.

What classifications are we talking about?

We have broken down the challenge into code-to-code, code-to-product, product-to-product, product-to-evidence, and product-to-opportunity. More specifically

• Code-to-code: suppose you have one code such as CPV and you want to match this to your own internal code or other codes such as UNSPSC.
• Code-to-product: imagine as a buyer you onboard a new supplier with 30,000 items or items that you need to assign categories to. As a supplier I need to filter or assign buyer code to my products.
• Product-to-product: as a buyer I have lots of products in my basket of goods, of different brands or suppliers, how can you compare the products to find similar ones? As a supplier how can I understand the market landscape.
• Product-to-evidence: now as a buyer you want to screen the clinical evidence of many items, how do you do this at the moment? as a supplier I want to see what my competitors are doing
• Product-to-opportunity: as a buyer I want to see the supplier products, or as a supplier I want to see the opportunities I can participate in or my competitors are doing

Why is this so complex?

Here is a selection of complexities involved in classification:

• Complexity, Diversity, and Standardisation Issues: The sheer variety of medical supplies, each with its unique specifications, makes classification intricate. Differentiating between products with minor variations can be challenging. There may be a lack of standardised naming conventions and categorisations for medical supplies, especially across different manufacturers or countries. Different vendors might use different names, codes, or specifications for similar products, making it challenging to maintain a standardised classification.
• Continuous Evolution of Products: As medical technology advances, new products are constantly introduced to the market. Keeping classification systems up-to-date becomes an ongoing task.
• Overlapping Categories: Some medical supplies can fit into multiple categories, leading to confusion about proper classification.
• Human Errors, Scale and Skill: Mistakes can occur in manual entry or categorisation processes, leading to misclassifications. Staff needs to be trained to understand and use the classification system correctly, and this training has to be updated as the system evolves.
• Regulatory and Compliance Requirements: Different regions or countries might have different regulations concerning medical supplies, which can affect how they need to be classified or coded. In multinational settings, translation and localisation can introduce further complexity to classification.
• Interoperability and Integration: Different systems within a healthcare facility, like billing, electronic health records, and inventory management, need to communicate seamlessly. Discrepancies in code classifications can lead to issues in this integration. Legacy systems in hospitals or facilities might still rely on outdated classification systems, leading to discrepancies when integrating with newer systems or vendors. Classification systems need to be compatible with inventory management systems to ensure seamless tracking of medical supplies usage and restocking needs.

Addressing these challenges requires a combination of technology, training, and careful planning. Solutions might include investing in modern inventory management systems, providing ongoing staff training, collaborating with vendors for standardisation, and regularly reviewing and updating classification systems. Doing this manually globally for all healthcare products and services is not possible and this needs an automated tracking and monitoring solution, luckily with the emergence of big data, generative AI, and graph analytics this is possible.