What We Mean When We Talk About EvGen, Part 1

Laying the foundation for a national system for clinical evidence generation

Across the clinical research enterprise, there is a growing awareness of serious shortfalls in the current model for generating the scientific evidence that supports medical product evaluation and clinical care decisions. As a result the FDA seeks to modernize methods and satisfy expectations surrounding this evidence base.

We know, for instance, that most clinical-practice guideline recommendations are not based on high-quality evidence, which is typically derived from appropriately designed, randomized controlled trials. We also know that adherence to standards supported by such high-quality evidence results in better outcomes for patients.

There is reason to believe that we’ve arrived at a tipping point where previously separate, “siloed” efforts can be linked to create a national system for evidence generation (EvGen). In this first of a series of articles, we’ll take a look at the elements required to build such a national system, beginning with a pair of foundational concepts—interoperability and connectivity.

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Comments

Automotive "International Material Data System"

I'm in the auto industry, as a quality engineer on electronic components. I appreciate your need for an interconnected system, and I'd like to respond to the theory and the application of such as system.

Auto industry realized in the 90's that it would be better to internationally share hazardous materials testing in raw materials, showing the trace amounts of materials like mercury, internationally. The advantages manifested in reduced paperwork, the many different parts made with one batch of steel did not need that steel batch paperwork with each part, and better traceability, as long as the material makers input the data and lot number, you could trace back the lots all the way to the manufacturing point.

Application of the system is hard, and needs to be auditable. As I said above, the database relationship is a one batch to many products relationship, easy to think of conceptually in a SQL type database, but implementation requires some whizzes of the databasing indutstry. The more data you try to capture with each field increases your data exponetially because you have multiple locations the data is stored and accessed. Analyzing the data once it has been captured should just require the data manipulation skills of any social sciences or statistics person.

Auditing should be the explicit goal of an external body that monitors requirements. For IMDS, I am not a fan of the auditability of the system. An auditor of ISO14001 might be the person to dig up inconsistencies with PPAP (Production Part Approval Process), but I don't know of an organization that strictly audits IMDS requirements. The main thing an auditor should look for is when an Engineer or team approves the use of a certain material or part, that they keep and retain the material certifications for those items, and that they recertify on some regular basis. Similarly, when an organization in your system implements the use of a certain product, they should retain and reevaluate on a regular basis the raw components of that product.

You run into issues with proprietary products (especially in the plastics industry for auto) but it can be circumvented by setting key process indicators for the product (hardness, resistivity, specific mass). Drawing the analogy for your products, they could have key process indicators (percent active ingredient, time until effects felt, side effects).

The payoff of a system like you are suggesting is fantastic, the application will take some hard work from a good databasing team. I suggest you benchmark off of IMDS, but I would suggest taking it to the next level and making it auditable.

Cheers, this sounds like a great project.