Strategy for ensuring the quality, fit-for-purpose, and usefulness of available knowledge.
Detailed Description
The clinical interoperability strategy will result in two general categories of data: 1) Data about tests as a class, e.g. the IVD name, mapped code, and device that produces it; and 2) Individual testing data, i.e. the actual results being produced for use. A quality assurance strategy should aim to assess the quality of both sorts of data.
“Class” data quality assurance:
Ensuring LIDR resources are generated according to defined practices
Assuring IVDs are uniquely identifiable
Assuring UDIs are generated according to defined practices
Allowing laboratories to assess whether their testing menu is conformant to LIDR resources
Allowing third parties to assess whether a laboratory’s menu is conformant to LIDR resources
“Instance” data quality assurance:
Maintaining a repository of traceability/harmonization information
Third party verification that individual testing data have mapping and harmonization elements required for interoperability
Third party verification that individual tests do not have unexpected variation by performing laboratory
Third party performance monitoring of devices and IVD kits
IV&V on harmonized terminology
Quality Assurance on knowledge representations
Knowledge can be reliably represented but how do we mitigate “bad” knowledge
Supporting Tactics
Tactic | Impact |
|---|---|
Reference Standard/Harmonization Hub | Contains information on what analytes have a traceable standard or harmonization procedure. |
Laboratory testing QC data repository | By monitoring individual testing data, a QC data hub would potentially 1) identify testing that can safely be treated as similar 2) identify incorrectly mapped tests |
Grouping determination re: standardization/harmonization | Primarily a governance problem: will there be a central location telling people if tests from two IVDs can be trended together, or will this be left to local judgment? |
Real World Evidence data hub | National database of testing data allowing performance monitoring of IVD and device-related issues. With linkages, could be used in evidence generation. |
Supporting Use Cases
Use Case |
|---|
Run APIs or other computational processes (idempotent) against the latest terminology release to assure no typographical errors in codes or displays. |
Check against current date to learn if this is the correct version release. |
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