Literature DB >> 35308921

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

Jianqiu Zhang1, Paul E Drawz2, Ying Zhu1, Gretchen Hultman1, Gyorgy Simon1, Genevieve B Melton1,3.   

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. ©2021 AMIA - All rights reserved.

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Year:  2022        PMID: 35308921      PMCID: PMC8861756     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  20 in total

1.  Combining billing codes, clinical notes, and medications from electronic health records provides superior phenotyping performance.

Authors:  Wei-Qi Wei; Pedro L Teixeira; Huan Mo; Robert M Cronin; Jeremy L Warner; Joshua C Denny
Journal:  J Am Med Inform Assoc       Date:  2015-09-02       Impact factor: 4.497

2.  KDIGO clinical practice guidelines for acute kidney injury.

Authors:  Arif Khwaja
Journal:  Nephron Clin Pract       Date:  2012-08-07

3.  Validation of electronic medical record-based phenotyping algorithms: results and lessons learned from the eMERGE network.

Authors:  Katherine M Newton; Peggy L Peissig; Abel Ngo Kho; Suzette J Bielinski; Richard L Berg; Vidhu Choudhary; Melissa Basford; Christopher G Chute; Iftikhar J Kullo; Rongling Li; Jennifer A Pacheco; Luke V Rasmussen; Leslie Spangler; Joshua C Denny
Journal:  J Am Med Inform Assoc       Date:  2013-03-26       Impact factor: 4.497

4.  World incidence of AKI: a meta-analysis.

Authors:  Paweena Susantitaphong; Dinna N Cruz; Jorge Cerda; Maher Abulfaraj; Fahad Alqahtani; Ioannis Koulouridis; Bertrand L Jaber
Journal:  Clin J Am Soc Nephrol       Date:  2013-06-06       Impact factor: 8.237

Review 5.  Choice of Reference Serum Creatinine in Defining Acute Kidney Injury.

Authors:  Edward D Siew; Michael E Matheny
Journal:  Nephron       Date:  2015-09-02       Impact factor: 2.847

Review 6.  Epidemiology of cardiac surgery-associated acute kidney injury.

Authors:  Eric A J Hoste; Wim Vandenberghe
Journal:  Best Pract Res Clin Anaesthesiol       Date:  2017-11-08

Review 7.  Acute Kidney Injury in Diabetes Mellitus.

Authors:  D Patschan; G A Müller
Journal:  Int J Nephrol       Date:  2016-11-15

8.  Improved nephrology referral of chronic kidney disease patients: potential role of smartphone apps.

Authors:  Nestor Oliva-Damaso; Elena Oliva-Damaso; Jose C Rodriguez-Perez; Juan Payan
Journal:  Clin Kidney J       Date:  2019-09-28

9.  NLP-PIER: A Scalable Natural Language Processing, Indexing, and Searching Architecture for Clinical Notes.

Authors:  Reed McEwan; Genevieve B Melton; Benjamin C Knoll; Yan Wang; Gretchen Hultman; Justin L Dale; Tim Meyer; Serguei V Pakhomov
Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2016-07-20

10.  Trends in Hospitalizations for Acute Kidney Injury - United States, 2000-2014.

Authors:  Meda E Pavkov; Jessica L Harding; Nilka R Burrows
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2018-03-16       Impact factor: 17.586

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