Titre :

Combining information from a clinical data warehouse and a pharmaceutical database to generate a framework to detect comorbidities in electronic health records

Auteur(s) :

Sylvestre, Emmanuelle [Auteur]
Centre d'Investigation Clinique [Rennes] [CIC]
Centre Hospitalier Universitaire de Rennes [CHU Rennes] = Rennes University Hospital [Pontchaillou]
Bouzille, Guillaume [Auteur]
Centre d'Investigation Clinique [Rennes] [CIC]
Centre Hospitalier Universitaire de Rennes [CHU Rennes] = Rennes University Hospital [Pontchaillou]
Chazard, Emmanuel [Auteur]
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS]
His-Mahier, Cecil [Auteur]
Centre d'Investigation Clinique [Rennes] [CIC]
Centre Hospitalier Universitaire de Rennes [CHU Rennes] = Rennes University Hospital [Pontchaillou]
Riou, Christine [Auteur]
Centre d'Investigation Clinique [Rennes] [CIC]
Centre Hospitalier Universitaire de Rennes [CHU Rennes] = Rennes University Hospital [Pontchaillou]
Cuggia, Marc [Auteur]
Centre d'Investigation Clinique [Rennes] [CIC]
Centre Hospitalier Universitaire de Rennes [CHU Rennes] = Rennes University Hospital [Pontchaillou]

Titre de la revue :

BMC medical informatics and decision making

Nom court de la revue :

BMC Med. Inform. Decis. Mak.

Numéro :

18

Date de publication :

2018-01-24

ISSN :

1472-6947

Mot(s)-clé(s) en anglais :

Billing codes
Pharmaceutical
Databases
Drug prescriptions
Laboratory test results
Clinical data warehouse
Comorbidity

Discipline(s) HAL :

Sciences du Vivant [q-bio]

Résumé en anglais : [en]

Medical coding is used for a variety of activities, from observational studies to hospital billing. However, comorbidities tend to be under-reported by medical coders. The aim of this study was to develop an algorithm to ...
Lire la suite >Medical coding is used for a variety of activities, from observational studies to hospital billing. However, comorbidities tend to be under-reported by medical coders. The aim of this study was to develop an algorithm to detect comorbidities in electronic health records (EHR) by using a clinical data warehouse (CDW) and a knowledge database. We enriched the Theriaque pharmaceutical database with the French national Comorbidities List to identify drugs associated with at least one major comorbid condition and diagnoses associated with a drug indication. Then, we compared the drug indications in the Theriaque database with the ICD-10 billing codes in EHR to detect potentially missing comorbidities based on drug prescriptions. Finally, we improved comorbidity detection by matching drug prescriptions and laboratory test results. We tested the obtained algorithm by using two retrospective datasets extracted from the Rennes University Hospital (RUH) CDW. The first dataset included all adult patients hospitalized in the ear, nose, throat (ENT) surgical ward between October and December 2014 (ENT dataset). The second included all adult patients hospitalized at RUH between January and February 2015 (general dataset). We reviewed medical records to find written evidence of the suggested comorbidities in current or past stays. Among the 22,132 Common Units of Dispensation (CUD) codes present in the Theriaque database, 19,970 drugs (90.2%) were associated with one or several ICD-10 diagnoses, based on their indication, and 11,162 (50.4%) with at least one of the 4878 comorbidities from the comorbidity list. Among the 122 patients of the ENT dataset, 75.4% had at least one drug prescription without corresponding ICD-10 code. The comorbidity diagnoses suggested by the algorithm were confirmed in 44.6% of the cases. Among the 4312 patients of the general dataset, 68.4% had at least one drug prescription without corresponding ICD-10 code. The comorbidity diagnoses suggested by the algorithm were confirmed in 20.3% of reviewed cases. This simple algorithm based on combining accessible and immediately reusable data from knowledge databases, drug prescriptions and laboratory test results can detect comorbidities.Lire moins >

Langue :

Anglais

Audience :

Internationale

Vulgarisation :

Non

Établissement(s) :

CHU Lille
Université de Lille

Collections :

• METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694

Date de dépôt :

2019-12-09T18:17:48Z
2020-04-15T10:02:11Z
2020-04-16T09:12:11Z