Validation of Administrative Coding and Clinical Notes for Hospital-Acquired Acute Kidney Injury in Adults

Jianqiu Zhang, Paul E Drawz, Ying Zhu, Gretchen Hultman, Gyorgy J Simon, Genevieve B. Melton

Research output: Contribution to journalArticlepeer-review

Abstract

Acute kidney injury (AKI) is potentially catastrophic and commonly seen among inpatients. In the United States, the quality of administrative coding data for capturing AKI accurately is questionable and needs to be updated. This retrospective study validated the quality of administrative coding for hospital-acquired AKI and explored the opportunities to improve the phenotyping performance by utilizing additional data sources from the electronic health record (EHR). A total of34570 patients were included, and overall prevalence of AKI based on the KDIGO reference standard was 10.13%, We obtained significantly different quality measures (sensitivity.-0.486, specificity:0.947, PPV.0.509, NPV:0.942 in the full cohort) of administrative coding from the previously reported ones in the U.S. Additional use of clinical notes by incorporating automatic NLP data extraction has been found to increase the AUC in phenotyping AKI, and AKI was better recognized in patients with heart failure, indicating disparities in the coding and management of AKI.

Original languageEnglish (US)
Pages (from-to)1234-1243
Number of pages10
JournalAMIA ... Annual Symposium proceedings. AMIA Symposium
Volume2021
StatePublished - 2021

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