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Updated: Jun 23, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
[Quantifying errors in the identification of patients' medical records in an active filing]
Alexis Hautemanière1, Catherine Quantin, Philippe Hartemann
1Département d'Information Médicale, d'Epidémiologie et de Sante Publique Centre Hospitalier de Dieppe, avenue pasteur, 76202 Dieppe cedex.
Abstract:
The aim of this study was to quantify and qualify mistaken identities in a current medical records archive. The medical records are classified by identification indexes (day and month of birth, the first letter of their surname) by category where their placement is a function of the record's status defined as "current", "semi-current" or "dead". All of the medical records marked as "current" (n=43,592), dating between 12 February 2004 to 11 March 2004, were analysed. 1397 (3.2%) contained at least one error, totalling 1456 errors, or an average of 1.04 errors per record. The errors were classified into two types: misidentification (1254 or 86.1%) and logistical errors (202 or 13.9%). 256 serious mistakes were identified as representing 17.6% of the cases. The staff costs associated with managing these errors totalled 12,408 Euro, corresponding to a cost of 8.88 Euro per error. The immediate impact is a reduction in the workload of staff directly due to the absence of the missing file. The depth of this problem was more significant than had been suggested by the indicators, both qualitatively and quantitatively. These results should be used to advocate for the implementation of a policy on continuous quality assessment (scoring the quality of the creation of the record, and scoring the intervention).
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