Introduction

At Mayo Clinic, product data has become a strategic asset for addressing some of healthcare’s most pressing challenges. From identifying clinically equivalent substitutes and standardizing product categorization to strengthening supply chain resilience during crises and improving patient safety through automated EHR workflows, trusted product information plays a critical role in enabling better decisions and better outcomes.

In a presentation at the GS1 Global Healthcare Summit, Mayo Clinic shared how it leveraged Innovit’s Product Information Management (PIM) platform to create a foundation of standardized, high-quality product data. The result is greater visibility, improved operational efficiency, enhanced clinical decision-making, and a more resilient healthcare supply chain.

Explore the four key use cases below to see how accurate product data is helping transform healthcare operations and patient care at Mayo Clinic.

Establishing Product Data Standardization for Substitutes Analysis

Healthcare providers are interested in maximizing clinical performance and improving patient experience.  So, choosing the right medical product for a given procedure is critical for caregivers to do their work effectively and deliver the best outcomes for patient wellness.  And while there are indeed products from different suppliers that seem to do the same job from a clinical perspective, clinicians must be assured that these products are truly “clinically‑equivalent” substitutes.  But substitute research can be a painstaking task which invariably takes caregivers away from spending more time with their patients.

For Mayo Clinic, their Supply Chain team needed to deliver two outcomes:

• Provide clinically‑equivalent substitute products when the primary product is not available
• Reduce cost of supply by identifying substitutes and alternatives at lower prices

Using Innovit’s PIM, the Mayo team was able to use standardized attributes and trusted product data within their supply chain operations to achieve both goals.

Enabling Consistency of Product Categorization to Facilitate Clinical Analysis

There are currently over 20 different Classification and Nomenclature Systems used across the world for the classification of products in the healthcare sector which are used to group products like Medical Devices and Pharmaceutical Drugs (example classification systems are GMDN, UNSPSC, GPC, eClass and ATC among others).

These classifications are intended to assist businesses with spend analysis, financial analysis, procurement and sourcing.  Unfortunately, it can be a tremendous challenge for hospitals to do any kinds of analysis since suppliers use different standards, versions and allocations / interpretations of these category codes and this was especially problematic during a pandemic.

The lack of categorization standards hit hardest with COVID-19.  As an enterprise, Mayo Clinic wanted to know the number of PPE products in total, inventory location and stock available at each location.  They saw the need for an industry standard product categorization method.

Mayo Clinic wanted to improve categorization of products through standardizing category codes and category attribution.  They also wanted the ability to group/categorize products that are clinically similar/equivalent.

Guaranteeing Supply for Critical Items During Extraordinary Events (e.g. COVID-19)

No matter what the circumstance – be it regional natural disaster or worldwide pandemic – healthcare providers must be prepared to tackle supply shortages or supply chain delays.  Doing so requires that these providers have a keen view and deep insight into inventories and where those products are manufactured.  Quite simply, ‘Country of Origin’ data is needed to better predict/estimate/determine potential medical device shortages especially during times of crisis.

A potential scenario…

Country A is a known supplier of PPE equipment providing products to a host of other countries, including Country B.  Country A experiences a devastating earthquake which severely hampers its manufacturing supply chain.  ‘Country of Origin’ data (via automation, with artificial intelligence and business intelligence) enables a healthcare provider in Country B to quickly change direction without affecting the clinical practice and their need for critical supplies.  They are better positioned to shift sourcing to a different suppliers and locations.

Triggering automated workflows in EHR systems with accurate clinical data to ensure patient safety and transparency

Electronic medical (or health) records (EMR/EHRs) have had a positive effect on patient care and the work lives of healthcare providers.  They can improve the ability to diagnose diseases and reduce—even prevent—medical errors.  For example, the EMR/EHR keeps record of a patient’s medications or allergies and will automatically check for problems whenever a new medication is prescribed.  If a potential conflict exists, the clinician will be alerted.  Behind the scenes of course, are a series of workflows that ensure the data is accessible and highly accurate.  Because we know that alerts within an EMR – which are designed to save a patient’s life – are only as good as the data that drives the alerts. The Mayo Clinic is devoted to providing the best care possible and continues its commitment working to build confidence in its product data.  One of the main ways they are doing this is through product category standardization.