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An aligned framework of actively collected and passively monitored clinical outcome assessments (COAs) for measure selection.

Christine Manta CampbellCourtney WebsterMegan ParisiRoya Sherafat-KazemzadehJessica BraidThomas SwitzerMarcelo Alves FávaroCaprice SassanoAndrea Coravos
Published in: NPJ digital medicine (2024)
Regulators increasingly require clinical outcome assessment (COA) data for approval. COAs can be collected via questionnaires or digital health technologies (DHTs), yet no single resource provides a side-by-side comparison of tools that collect complementary or related COA measures. We propose how to align ontologies for actively collected and passively monitored COAs into a single framework to allow for rapid, evidence-based, and fit-for-purpose measure selection.
Keyphrases
  • healthcare
  • public health
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  • machine learning
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