Login / Signup

Evaluating the impact of alternative phenotype definitions on incidence rates across a global data network.

Rupa MakadiaAzza ShoaibiGowtham A RaoAnna OstropoletsPeter R RijnbeekErica A VossTalita Duarte SallesJuan Manuel Ramírez-AnguitaMiguel A MayerFilip MaljkovićSpiros DenaxasFredrik NybergVaclav PapezAnthony G SenaThamir M AlshammariLana Y H LaiKevin HaynesMarc A SuchardGeorge HripcsakPatrick B Ryan
Published in: JAMIA open (2023)
Characterization of outcomes across a network of databases yields insights into sensitivity and specificity trade-offs when definitions are altered. Outcomes should be thoroughly evaluated prior to use for background rates for their plausibility for use across a global network.
Keyphrases
  • big data
  • risk factors
  • type diabetes
  • metabolic syndrome
  • glycemic control