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Developing and validating an algorithm to identify incident chronic dialysis patients using administrative data.

Dino GibertoniClaudio VociMarica IommiBenedetta D'ErcoleMarcora MandreoliAntonio SantoroElena Mancini
Published in: BMC medical informatics and decision making (2020)
Algorithms relying on retrieval of administrative records have high sensitivity and positive predictive value for the identification of incident chronic dialysis patients. Algorithm 1, which showed the higher accuracy and has a simpler case definition, can be used in place of regional dialysis registries when they are not present or sufficiently developed in a region, or to improve the accuracy and timeliness of existing registries.
Keyphrases
  • end stage renal disease
  • chronic kidney disease
  • peritoneal dialysis
  • machine learning
  • ejection fraction
  • newly diagnosed
  • cardiovascular disease
  • prognostic factors
  • drug induced
  • neural network
  • data analysis