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

Rupa MakadiaAzza ShoaibiGowtham A RaoAnna OstropoletsPeter R RijnbeekErica A Voss Talita Duarte SallesJuan Manuel Ramírez-AnguitaMiguel A MayerFilip MaljkovićSpiros Denaxas Fredrik Nyberg Vaclav Papez Anthony 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