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Improving Accuracy of Administrative Data for Perforated Appendicitis Classification.

Authors :
Ingram MC
Hu A
Lewit R
Arshad SA
Witte A
Keane OA
Dantes G
Mehl SC
Evans PT
Santore MT
Huang EY
Lopez ME
Tsao K
Van Arendonk K
Blakely ML
Raval MV
Source :
The Journal of surgical research [J Surg Res] 2024 Jul; Vol. 299, pp. 120-128. Date of Electronic Publication: 2024 May 14.
Publication Year :
2024

Abstract

Introduction: Reliance on International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis codes may misclassify perforated appendicitis with resultant research, fiscal, and public health implications. We aimed to improve the accuracy of administrative data for perforated appendicitis classification relying on ICD-10-CM codes from 2015 to 2018.<br />Methods: We conducted a retrospective study of randomly sampled patients aged ≤18 years diagnosed with acute appendicitis from eight children's hospitals. Patients were identified using the Pediatric Health Information System, and true perforation status was determined by medical record review. We developed two algorithms by leveraging Pediatric Health Information System data elements and data mining (DM) approaches. The two developed algorithm performance was compared against algorithms that exclusively relied on ICD-10-CM codes using area under the curve and other measures.<br />Results: Of 1051 clinically validated encounters that were included, 383 (36.4%) patients were identified to have perforated appendicitis. The two algorithms developed using DM approaches primarily leveraged ICD-10-CM codes and length of stay. DM-developed algorithms had a significantly higher accuracy than algorithms relying exclusively on ICD-10-CM (P value < 0.01): sensitivity and specificity for DM-developed algorithms were 0.86-0.88 and 0.95-0.97, respectively, which were overall higher than algorithms that relied on only ICD-10-CM.<br />Conclusions: This study provides an algorithm that can improve the accuracy of perforated appendicitis classification using commonly available elements in administrative data. We recommend that this algorithm is used in future appendicitis classification to ensure valid reporting, hospital-level benchmarking, and fiscal or public health assessments.<br /> (Copyright © 2024 Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1095-8673
Volume :
299
Database :
MEDLINE
Journal :
The Journal of surgical research
Publication Type :
Academic Journal
Accession number :
38749315
Full Text :
https://doi.org/10.1016/j.jss.2024.03.041