Sourcing for quality demands standards

What if making sourcing decisions in healthcare were more like buying a new car or major appliance, with a Consumer Reports-like service to provide data on real world performance? That’s essentially the question explored by the Product Quality Outcomes Analytics (PQOA) Working Group of the Medical Device Innovation Consortium (MDIC) Case for Quality Program. MDIC is the public-private partnership that was recently awarded $3 million to create the coordinating center for the Medical Device National Evaluation System for health Technology (NEST). The NEST will focus on improving the quality of data on medical device performance to help inform sourcing decisions, improve patient safety and guide the introduction of new medical technology to the market.

In October, the PQOA Working Group released its first report, focused on whether it is even feasible to create a system that can effectively compare products across manufacturers. The answer, as with so many things in healthcare, came down in large part to standardization— in how products are identified, how quality is defined and measured, and how data is collected and reported. Once again, variation is the challenge.

The working group, made up of regulators, data scientists, subject matter experts and medical device manufacturers, first agreed upon the factors to evaluate quality. With input from value analysis committees (VACs) and the MDIC community at large, they came up with seven quality domains and corresponding definitions.

Factors to Evaluate Medical Device Quality

 
The biggest concern with creating a comparative system was data. Does it exist? Is it publicly available? Is it accurate? Unbiased? Complete? Consistently reported? The working group acknowledged the importance of the U.S. Food and Drug Administration (FDA) requirement that manufacturers assign unique device identifiers (UDIs) to their products and publish those UDIs and additional product data to the FDA’s Global UDI Database (GUDID). But that begged the question as to the quality of the data in the GUDID.

The working group also found variation in how VACs approach their work — from how they are structured, what data they consider, where they source the data and how they format and summarize it for decision making. But there was broad agreement that there is a need for reliable data from independent sources.

To test the feasibility of such a cross-manufacturer comparability system, the working group ran a pilot. Step one was to gather data from sources including:

• Peer-reviewed, published studies
• Clinical trials
• Medical device recalls and reports
• Device registries
• Online user forums

The working group then created dashboards that provided company rankings by specific data sources and aggregate rankings for companies and for products and companies. VACs surveyed liked the ease of use of the dashboards and the availability of data beyond just safety and efficacy information. Manufacturers also said there is value in unbiased data to help compare themselves to other companies with similar products and to improve their product quality. On the other hand, there was considerable concern among manufacturers regarding the consistency and validity of the data and metrics used. As an example, different manufacturers often use different criteria to trigger voluntary recalls.

In general, there is agreement among a variety of stakeholders that an independent and objective means to evaluate product quality based on real world evidence makes sense. But there was also a strong belief that the feasibility of such a system depends itself on the quality — of the source data, the definitions, and the reporting and analysis.

You can read the full report at this url: http://mdic.org/cfq/resource-center-for-sustained-quality.