Evaluation of natural language processing from emergency department computerized medical records for intra-hospital syndromic surveillance

<p>Abstract</p> <p>Background</p> <p>The identification of patients who pose an epidemic hazard when they are admitted to a health facility plays a role in preventing the risk of hospital acquired infection. An automated clinical decision support system to detect suspected cases, based on the principle of syndromic surveillance, is being developed at the University of Lyon's Hôpital de la Croix-Rousse. This tool will analyse structured data and narrative reports from computerized emergency department (ED) medical records. The first step consists of developing an application (UrgIndex) which automatically extracts and encodes information found in narrative reports. The purpose of the present article is to describe and evaluate this natural language processing system.</p> <p>Methods</p> <p>Narrative reports have to be pre-processed before utilizing the French-language medical multi-terminology indexer (ECMT) for standardized encoding. UrgIndex identifies and excludes syntagmas containing a negation and replaces non-standard terms (abbreviations, acronyms, spelling errors...). Then, the phrases are sent to the ECMT through an Internet connection. The indexer's reply, based on Extensible Markup Language, returns codes and literals corresponding to the concepts found in phrases. UrgIndex filters codes corresponding to suspected infections. Recall is defined as the number of relevant processed medical concepts divided by the number of concepts evaluated (coded manually by the medical epidemiologist). Precision is defined as the number of relevant processed concepts divided by the number of concepts proposed by UrgIndex. Recall and precision were assessed for respiratory and cutaneous syndromes.</p> <p>Results</p> <p>Evaluation of 1,674 processed medical concepts contained in 100 ED medical records (50 for respiratory syndromes and 50 for cutaneous syndromes) showed an overall recall of 85.8% (95% CI: 84.1-87.3). Recall varied from 84.5% for respiratory syndromes to 87.0% for cutaneous syndromes. The most frequent cause of lack of processing was non-recognition of the term by UrgIndex (9.7%). Overall precision was 79.1% (95% CI: 77.3-80.8). It varied from 81.4% for respiratory syndromes to 77.0% for cutaneous syndromes.</p> <p>Conclusions</p> <p>This study demonstrates the feasibility of and interest in developing an automated method for extracting and encoding medical concepts from ED narrative reports, the first step required for the detection of potentially infectious patients at epidemic risk.</p

Evaluation of an automatic detection system of patients with potentially transmissible infectious disease from emergency department computerized record

Introduction. La détection précoce des infections par un système de surveillance efficace permet de mettre en œuvre des mesures de prévention et de contrôle adaptées. L’objectif de cette thèse était d’évaluer les performances d’un système de détection automatique, type syndromique, des patients à risque épidémique à partir des données du dossier médical informatisé des urgences. Population d’étude. 101001 patients ayant consulté aux urgences du groupement Nord des Hospices Civils de Lyon, entre le 01/06/2007 et le 31/03/2011, dont 10895 patients hospitalisés dans l’établissement à l’issue de la consultation. Méthode. Trois étapes ont été nécessaires. 1) Évaluation de la faisabilité d’utiliser les données structurées et textuelles, à l’aide d’une application de traitement automatisé des données textuelles. 2) Construction et évaluation d’algorithmes de repérage, pour les syndromes respiratoire, cutané et gastro-intestinal, de patients avec une infection à risque épidémique à partir des données du dossier médical informatisé des urgences. 3) Évaluation des données du dossier médical des urgences pour la détection d’épidémies communautaires de grippe, comparées aux données régionales de surveillance de la grippe. Résultats et Discussion. Cette thèse a montré que qu’il est possible de repérer des patients à risque épidémique avec une balance raisonnable entre la sensibilité et la spécificité pour des syndromes respiratoires et cutanés. Les algorithmes pour des syndromes gastro-intestinaux n'étaient pas assez spécifiques pour une utilisation de routine. Les données d’urgences ont permis aussi de détecter les épidémies communautaires dès le début de l’épidémie localeIntroduction. The early detection of the infections by an effective surveillance system allows implementing adapted measures of prevention and control. The objective of this thesis was to estimate the performances of an automatic system syndromic-like to detect the patients with potentially transmissible infectious diseases from the emergency department computerized medical record data. Study population. 101,001 adults, who were admitted to the emergency department and hospitalised of the North Hospital In University Hospital of Lyon, between 01/06/2007 and 30/03/2011. Method. Three steps were necessary. 1) Evaluation of the feasibility to use the structured and textual data with an application which automatically extracts and encodes information found in narrative reports. 2) Different algorithms were built for the detection of patients with infectious respiratory, cutaneous or gastrointestinal syndromes, and assessed. 3) Evaluation of the data of the electronic medical record of emergency department for the detection of flu community epidemics, compared with regional surveillance networks for flu. Results and discussion. This thesis showed that it is possible to detect patients with potentially transmissible infectious diseases with reasonable balance between sensitivity and specificity for respiratory and cutaneous syndromes. The algorithms for gastrointestinal syndromes were not specific enough for their routine use. Emergency department data enabled the detection of community outbreaks for fl

Evaluation of an automatic detection system of patients with potentially transmissible infectious disease from emergency department computerized record

Introduction. La détection précoce des infections par un système de surveillance efficace permet de mettre en œuvre des mesures de prévention et de contrôle adaptées. L’objectif de cette thèse était d’évaluer les performances d’un système de détection automatique, type syndromique, des patients à risque épidémique à partir des données du dossier médical informatisé des urgences. Population d’étude. 101001 patients ayant consulté aux urgences du groupement Nord des Hospices Civils de Lyon, entre le 01/06/2007 et le 31/03/2011, dont 10895 patients hospitalisés dans l’établissement à l’issue de la consultation. Méthode. Trois étapes ont été nécessaires. 1) Évaluation de la faisabilité d’utiliser les données structurées et textuelles, à l’aide d’une application de traitement automatisé des données textuelles. 2) Construction et évaluation d’algorithmes de repérage, pour les syndromes respiratoire, cutané et gastro-intestinal, de patients avec une infection à risque épidémique à partir des données du dossier médical informatisé des urgences. 3) Évaluation des données du dossier médical des urgences pour la détection d’épidémies communautaires de grippe, comparées aux données régionales de surveillance de la grippe. Résultats et Discussion. Cette thèse a montré que qu’il est possible de repérer des patients à risque épidémique avec une balance raisonnable entre la sensibilité et la spécificité pour des syndromes respiratoires et cutanés. Les algorithmes pour des syndromes gastro-intestinaux n'étaient pas assez spécifiques pour une utilisation de routine. Les données d’urgences ont permis aussi de détecter les épidémies communautaires dès le début de l’épidémie localeIntroduction. The early detection of the infections by an effective surveillance system allows implementing adapted measures of prevention and control. The objective of this thesis was to estimate the performances of an automatic system syndromic-like to detect the patients with potentially transmissible infectious diseases from the emergency department computerized medical record data. Study population. 101,001 adults, who were admitted to the emergency department and hospitalised of the North Hospital In University Hospital of Lyon, between 01/06/2007 and 30/03/2011. Method. Three steps were necessary. 1) Evaluation of the feasibility to use the structured and textual data with an application which automatically extracts and encodes information found in narrative reports. 2) Different algorithms were built for the detection of patients with infectious respiratory, cutaneous or gastrointestinal syndromes, and assessed. 3) Evaluation of the data of the electronic medical record of emergency department for the detection of flu community epidemics, compared with regional surveillance networks for flu. Results and discussion. This thesis showed that it is possible to detect patients with potentially transmissible infectious diseases with reasonable balance between sensitivity and specificity for respiratory and cutaneous syndromes. The algorithms for gastrointestinal syndromes were not specific enough for their routine use. Emergency department data enabled the detection of community outbreaks for fl

Evaluation de différentes méthodes de repérage des infections nosocomiales dans un service de chirurgie et un service d'obstétrique des Hospices Civils de Lyon

LYON1-BU Santé (693882101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Addressing Risk Assessment for Patient Safety in Hospitals through Information Extraction in Medical Reports

Hospital Acquired Infections (HAI) is a real burden for doctors and risk surveillance experts. The impact on patients ’ health and related healthcare cost is very significant and a major concern even for rich countries. Furthermore required data to evaluate the threat is generally not available to experts and that prevents from fast reaction. However, recent advances in Computationa

Heat map for data visualization in infection control epidemiology: An application describing the relationship between hospital-acquired infections, Simplified Acute Physiological Score II, and length of stay in adult intensive care units

International audienceBackgroundHospital-acquired infections (HAIs) in intensive care units (ICUs) are associated with increased length of stay (LOS). The objective of this study was to graphically describe by heat mapping LOS of patients hospitalized in ICUs related to the occurrence of HAI and severity at admission measured by the Simplified Acute Physiological Score II (SAPSII).MethodsAdult patients hospitalized in ICUs of Lyon University Hospitals (France) were included in an active standardized surveillance study of HAI from January 1, 1995-December 31, 2012. Surveillance included adult patients aged ≥18 years hospitalized ≥2 days. Patient follow-up ended at ICU discharge or death. LOS was calculated in days from differences between dates of entry and discharge from ICUs. HAIs recorded were pneumonia, bacteremia, and urinary tract infection. The heat map was designed with a spreadsheet software.ResultsA total of 34,694 patients were analyzed. Among infected patients, 72.3% had 1 infected site (IS), 23% had 2 ISs, and 4.7% had 3 ISs. Median LOS was 24 days in infected patients (20.4 days among patients with 1 IS, 34.2 days among patients with 2 ISs, and 45.3 days among patients with 3 ISs) and 5 days in noninfected patients (P < .001). Two groups of multi-infected patients with long LOSs were identified with the heat map.ConclusionsThe heat map facilitated easy-to-implement semi-quantitative visualization of increasing LOS through the SAPSIIs and number of ISs

Estimation of Extra Length of Stay Attributable to Hospital-Acquired Infections in Adult ICUs Using a Time-Dependent Multistate Model*:

International audienceObjectives: The objective of the study was to estimate the length of stay of patients with hospital-acquired infections hospitalized in ICUs using a multistate model. Design: Active prospective surveillance of hospital-acquired infection from January 1, 1995, to December 31, 2012. Setting: Twelve ICUs at the University of Lyon hospital (France). Patients: Adult patients age greater than or equal to 18 years old and hospitalized greater than or equal to 2 days were included in the surveillance. All hospital-acquired infections (pneumonia, bacteremia, and urinary tract infection) occurring during ICU stay were collected. Interventions: None. Measurements and Main Results: The competitive risks of in-hospital death, transfer, or discharge were considered in estimating the change in length of stay due to infection(s), using a multistate model, time of infection onset. Thirty-three thousand four-hundred forty-nine patients were involved, with an overall hospital-acquired infection attack rate of 15.5% (n = 5,176). Mean length of stay was 27.4 (+/- 18.3) days in patients with hospital-acquired infection and 7.3 (+/- 7.6) days in patients without hospital-acquired infection. A multistate model-estimated mean found an increase in length of stay by 5.0 days (95% CI, 4.6-5.4 d). The extra length of stay increased with the number of infected site and was higher for patients discharged alive from ICU. No increased length of stay was found for patients presenting late-onset hospital-acquired infection, more than the 25th day after admission. Conclusions: An increase length of stay of 5 days attributable to hospital-acquired infection in the ICU was estimated using a multistate model in a prospective surveillance study in France. The dose-response relationship between the number of hospital-acquired infection and length of stay and the impact of early-stage hospital-acquired infection may strengthen attention for clinicians to focus interventions on early preventions of hospital-acquired infection in ICU