Initializing a hospital-wide data quality program. The AP-HP experience.

International audienceBackground and objectives: Data Quality (DQ) programs are recognized as a critical aspect of new-generation research platforms using electronic health record (EHR) data for building Learning Healthcare Systems. The AP-HP Clinical Data Repository aggregates EHR data from 37 hospitals to enable large-scale research and secondary data analysis. This paper describes the DQ program currently in place at AP-HP and the lessons learned from two DQ campaigns initiated in 2017.Materials and methods: As part of the AP-HP DQ program, two domains - patient identification (PI) and healthcare services (HS) - were selected for conducting DQ campaigns consisting of 5 phases: defining the scope, measuring, analyzing, improving and controlling DQ. Semi-automated DQ profiling was conducted in two data sets - the PI data set containing 8.8 M patients and the HS data set containing 13,099 consultation agendas and 2122 care units. Seventeen DQ measures were defined and DQ issues were classified using a unified DQ reporting framework. For each domain, actions plans were defined for improving and monitoring prioritized DQ issues.Results: Eleven identified DQ issues (8 for the PI data set and 3 for the HS data set) were categorized into completeness (n = 6), conformance (n = 3) and plausibility (n = 2) DQ issues. DQ issues were caused by errors from data originators, ETL issues or limitations of the EHR data entry tool. The action plans included sixteen actions (9 for the PI domain and 7 for the HS domain). Though only partial implementation, the DQ campaigns already resulted in significant improvement of DQ measures.Conclusion: DQ assessments of hospital information systems are largely unpublished. The preliminary results of two DQ campaigns conducted at AP-HP illustrate the benefit of the engagement into a DQ program. The adoption of a unified DQ reporting framework enables the communication of DQ findings in a well-defined manner with a shared vocabulary. Dedicated tooling is needed to automate and extend the scope of the generic DQ program. Specific DQ checks will be additionally defined on a per-study basis to evaluate whether EHR data fits for specific uses

Performance of AI-Based Automated Classifications of Whole-Body FDG PET in Clinical Practice: The CLARITI Project

Purpose: To assess the feasibility of a three-dimensional deep convolutional neural network (3D-CNN) for the general triage of whole-body FDG PET in daily clinical practice. Methods: An institutional clinical data warehouse working environment was devoted to this PET imaging purpose. Dedicated request procedures and data processing workflows were specifically developed within this infrastructure and applied retrospectively to a monocentric dataset as a proof of concept. A custom-made 3D-CNN was first trained and tested on an “unambiguous” well-balanced data sample, which included strictly normal and highly pathological scans. For the training phase, 90% of the data sample was used (learning set: 80%; validation set: 20%, 5-fold cross validation) and the remaining 10% constituted the test set. Finally, the model was applied to a “real-life” test set which included any scans taken. Text mining of the PET reports systematically combined with visual rechecking by an experienced reader served as the standard-of-truth for PET labeling. Results: From 8125 scans, 4963 PETs had processable cross-matched medical reports. For the “unambiguous” dataset (1084 PETs), the 3D-CNN’s overall results for sensitivity, specificity, positive and negative predictive values and likelihood ratios were 84%, 98%, 98%, 85%, 42.0 and 0.16, respectively (F1 score of 90%). When applied to the “real-life” dataset (4963 PETs), the sensitivity, NPV, LR+, LR− and F1 score substantially decreased (61%, 40%, 2.97, 0.49 and 73%, respectively), whereas the specificity and PPV remained high (79% and 90%). Conclusion: An AI-based triage of whole-body FDG PET is promising. Further studies are needed to overcome the challenges presented by the imperfection of real-life PET data

Fully automated opportunistic screening of vertebral fractures and osteoporosis on more than 150 000 routine computed tomography scans

International audienceAbstract Objective Osteoporosis is underdiagnosed and undertreated, although severe complications of osteoporotic fractures, including vertebral fractures, are well known. This study sought to assess the feasibility and results of an opportunistic screening of vertebral fractures and osteoporosis in a large database of lumbar or abdominal CT scans. Material and methods Data were analysed from CT scans obtained in 35 hospitals from patients aged 60 years or older and stored in a Picture Archiving and Communication System in Assistance-Publique-Hôpitaux de Paris, from 2007 to 2013. Dedicated software was used to analyse the presence or absence of at least 1 vertebral fracture (VF), and the radiodensity of the lumbar vertebrae was measured Hounsfield Units (HUs). A simulated T-score was calculated. Results Data were analysed from 152 268 patients [mean age (S.D.) = 73.2 (9.07) years]. Success rates for VF assessment and HUs measurements were 82 and 87%, respectively. The prevalence of VFs was 24.5% and increased with age. Areas under the receiver operating characteristic curves for the detection of VFs were 0.61 and 0.62 for the mean HUs of the lumbar vertebrae and the L1 HUs, respectively. In patients without VFs, HUs decreased with age, similarly in males and females. The prevalence of osteoporosis (sT-score ≤ –2.5) was 23.8% and 36.5% in patients without and with VFs, respectively. Conclusion It is feasible on a large scale to screen for VFs and osteoporosis during opportunistic screening in patients 60 years or older having lumbar or abdominal CT

The effect of methylphenidate on neurofibromatosis type 1: a randomised, double-blind, placebo-controlled, crossover trial

et Réseau NF1 Rhône Alpes Auvergne-FranceInternational audienceBackground: Neurofibromatosis type 1 (NF1) is an autosomal dominant disorder with an estimated prevalence of about 1/3000, independent of ethnicity, race, or gender. Attention Deficit Hyperactivity like Disorder (ADHD)-like characteristics are often reported in patients with NF1. We hypothesised that learning disabilities in NF1 children were related to ADHD symptoms. Treatment with methylphenidate (MPD) has improved learning disabilities in ADHD by acting on neurotransmitters. Our objective was to evaluate its efficacy on ADHD-like symptoms in neurofibromatosis type 1 children (7–12 years).Methods: This was a randomised, double blind, placebo controlled, and crossover trial comparing 0.5 to 0.8 mg/kg/d of MPD as it is indicated for ADHD to placebo in NF1 children with ADHD-like symptoms. Children aged 7 to 12 years were eligible when their IQ was between 80 and 120. The total follow-up was 9 weeks including 4 weeks for each period and 1 week wash out. Fifty subjects (25 for each period) were required for testing the primary study hypothesis. The main outcome was an improvement in scores on the simplified Conners' Parent Rating Scale.Results: Thirty-nine patients were included between April 2004 and December 2010. Twenty participants received MPD and 19 placebo during the first period. They all completed the trial. MPD decreased the simplified Conners by 3.9 points (±1.1, p = 0. 0003).Conclusions: This is the first randomised controlled trial showing the short-term benefit of MPD on simplified Conners scores in NF1 children

New cancer cases at the time of SARS-Cov2 pandemic and related public health policies: A persistent and concerning decrease long after the end of national lockdown

International audienceIntroductionThe dissemination of SARS-Cov2 may have delayed the diagnosis of new cancers. This study aimed at assessing the number of new cancers during and after the lockdown.MethodsWe prospectively collected the clinical data of the 11.4 million patients referred to the Assistance Publique Hôpitaux de Paris Teaching Hospital. We identified new cancer cases between 1st January 2018 and 31st September 2020 and compared indicators for 2018 and 2019 to 2020 with a focus on the French lockdown (17th March to 11th May 2020) across cancer types and patient age classes.ResultsBetween January and September, 28,348, 27,272 and 23,734 new cancer cases were identified in 2018, 2019 and 2020, respectively. The monthly median number of new cases reached 3168 (interquartile range, IQR, 3027; 3282), 3054 (IQR 2945; 3127) and 2723 (IQR 2085; 2,863) in 2018, 2019 and 2020, respectively. From March 1st to May 31st, new cancer decreased by 30% in 2020 compared to the 2018–19 average; then by 9% from 1st June to 31st September. This evolution was consistent across all tumour types: −30% and −9% for colon, −27% and −6% for lung, −29% and −14% for breast, −33% and −12% for prostate cancers, respectively. For patients aged <70 years, the decrease of colorectal and breast new cancers in April between 2018 and 2019 average and 2020 reached 41% and 39%, respectively.ConclusionThe SARS-Cov2 pandemic led to a substantial decrease in new cancer cases. Delays in cancer diagnoses may affect clinical outcomes in the coming years

Les non-usages des TIC

Les ENT (Environnements Numériques de Travail), les plates formes d'EAD (Enseignement A Distance) et les logiciels éducatifs sont généralement étudiés dans la perspective de rendre compte des transformations des situations d'enseignement-apprentissage dans lequelles ils sont utilisés. Les recherches occultent ainsi, de façon non intentionnelle, tout ce qui reste dans l'ombre de l'introduction désormais massive des TIC (Technologies de l'Information et de la Communication), et qui explique probablement la marginalité peristante des pratiques, au regard de l'accessibilité des ressources numériques et des mesures incitatives à tous les niveaux politiques. Ce numéro thématique rassemble des articles qui interrogent les non-usages de la part des enseignants, des étudiants et du grand public,dans le but de mieux comprendre pourquoi les supposés bénéficiaires rejettent ou se détournent de systèmes ou de ressources, qui ont pourtant été conçus pour eux. Il ne s'agit pas de faire le procès des TIC, mais bien d'identifier les obstacles qui subsistent encore, en vue d'une intégration raisonnée et justifiée des TIC dans les pratiques d'éducation et de formation. Il ressort que l'intelligibilité des non-usages des TIC, en tant qu'objet de recherche, exigerait des éclairages multiples, qui pour le moment dessinent les différentes facettes de cet objet. Chacune des études présentées semblerait justifier une approche particulière qui, sans doute, témoigne du manque dematurité conceptuelle de l'objet "non-usage". Ce numéro thématique apporte son lot de propositions théoriques des non-usages et permet aux lecteurs, spécialistes des TIC ou non, de les confronter à ses travaux ou à son expérience d'usager

Les non-usages des TIC

Les ENT (Environnements Numériques de Travail), les plates formes d'EAD (Enseignement A Distance) et les logiciels éducatifs sont généralement étudiés dans la perspective de rendre compte des transformations des situations d'enseignement-apprentissage dans lequelles ils sont utilisés. Les recherches occultent ainsi, de façon non intentionnelle, tout ce qui reste dans l'ombre de l'introduction désormais massive des TIC (Technologies de l'Information et de la Communication), et qui explique probablement la marginalité peristante des pratiques, au regard de l'accessibilité des ressources numériques et des mesures incitatives à tous les niveaux politiques. Ce numéro thématique rassemble des articles qui interrogent les non-usages de la part des enseignants, des étudiants et du grand public,dans le but de mieux comprendre pourquoi les supposés bénéficiaires rejettent ou se détournent de systèmes ou de ressources, qui ont pourtant été conçus pour eux. Il ne s'agit pas de faire le procès des TIC, mais bien d'identifier les obstacles qui subsistent encore, en vue d'une intégration raisonnée et justifiée des TIC dans les pratiques d'éducation et de formation. Il ressort que l'intelligibilité des non-usages des TIC, en tant qu'objet de recherche, exigerait des éclairages multiples, qui pour le moment dessinent les différentes facettes de cet objet. Chacune des études présentées semblerait justifier une approche particulière qui, sans doute, témoigne du manque dematurité conceptuelle de l'objet "non-usage". Ce numéro thématique apporte son lot de propositions théoriques des non-usages et permet aux lecteurs, spécialistes des TIC ou non, de les confronter à ses travaux ou à son expérience d'usager

External validation of prognostic scores for COVID-19: a multicenter cohort study of patients hospitalized in Greater Paris University Hospitals

International audiencePurposeThe Coronavirus disease 2019 (COVID-19) has led to an unparalleled influx of patients. Prognostic scores could help optimizing healthcare delivery, but most of them have not been comprehensively validated. We aim to externally validate existing prognostic scores for COVID-19.MethodsWe used “COVID-19 Evidence Alerts” (McMaster University) to retrieve high-quality prognostic scores predicting death or intensive care unit (ICU) transfer from routinely collected data. We studied their accuracy in a retrospective multicenter cohort of adult patients hospitalized for COVID-19 from January 2020 to April 2021 in the Greater Paris University Hospitals. Areas under the receiver operating characteristic curves (AUC) were computed for the prediction of the original outcome, 30-day in-hospital mortality and the composite of 30-day in-hospital mortality or ICU transfer.ResultsWe included 14,343 consecutive patients, 2583 (18%) died and 5067 (35%) died or were transferred to the ICU. We examined 274 studies and found 32 scores meeting the inclusion criteria: 19 had a significantly lower AUC in our cohort than in previously published validation studies for the original outcome; 25 performed better to predict in-hospital mortality than the composite of in-hospital mortality or ICU transfer; 7 had an AUC > 0.75 to predict in-hospital mortality; 2 had an AUC > 0.70 to predict the composite outcome.ConclusionSeven prognostic scores were fairly accurate to predict death in hospitalized COVID-19 patients. The 4C Mortality Score and the ABCS stand out because they performed as well in our cohort and their initial validation cohort, during the first epidemic wave and subsequent waves, and in younger and older patients