INTRODUÇÃO: A doença diarréica aguda é ainda importante causa de morbidade no mundo. Sua elevada incidência e a aceitação de sua ocorrência como fato "normal" impõem desafios para seu registro e implantação de seus sistemas de vigilância. OBJETIVOS: Conhecer as características epidemiológicas da diarréia aguda e avaliar a capacidade de detecção de surtos pelo Programa de Monitorização da Doença Diarréica Aguda, no município de Avaré. MÉTODOS: De 27 de fevereiro a 16 de julho 2005, realizou-se estudo prospectivo da diarréia em unidade sentinela do programa. Os surtos identificados foram investigados por estudos descritivos e analíticos. Amostras de fezes foram coletadas para os casos envolvidos nos surtos. A avaliação dos propósitos do programa embasou-se em indicadores de utilidade, sensibilidade e oportunidade. RESULTADOS: Foram identificados 408 casos (Coeficiente de Incidência = 4,7/1000 habitantes); idade mediana de 7 anos (variação de 1 mês a 89 anos) e 54% do sexo masculino. Dos quatro surtos de diarréia confirmados, dois ocorreram em uma creche e em um orfanato, devido à Giárdia lamblia e Cryptosporidum spp.; um intradomiciliar de origem alimentar, sem identificação do agente, e uma epidemia na comunidade associada ao rotavírus. Dos casos atendidos, 63 (15,5%) pertenciam a surtos, identificando-se mais 56 casos, em um total de 119 casos (Coeficiente de Incidência de Surtos=1,4/1000 habitantes). CONCLUSÕES: O estudo mostrou que o programa responde ao seu principal propósito, respeitando-se as condições de regularidade na informação, análises dos padrões da diarréia e investigação criteriosa. Intensificar treinamentos para aumentar a habilidade das equipes locais nas avaliações e investigações é uma das principais recomendações deste estudo. / BACKGROUND: Acute diarrheal illness remains an important cause of morbidity worldwide. Its high incidence and the acceptance of its occurrence as “normal" fact impose challenges for its report and implantation of its surveillance systems. OBJECTIVES: To describe the epidemiologic characteristics of the acute diarrhea and to evaluate the capacity of the Monitoring Program of the Acute Diarrheal Illness for early detection of outbreaks, in the city of Avaré, State of São Paulo, Brazil. METHODS: From February 16 to July 28, 2005, was a prospective study of the diarrhea in a sentinel health service of the program. Descriptive and analytical studies were developed to investigate the potential outbreaks identified in this period. Stool samples were collected from the involved cases in the outbreaks. The evaluation of purpose of the program was based on indicators of usefulness, sensitivity and timeliness. RESULTS: A total of 408 cases were identified (incidence rate=4.7/1000 inhabitants). The median age was 7 years (range 1-89 years) and 54% were male. Among four confirmed diarrhea outbreaks, two occurred in a day nursery and orphanage, due to Giardia lamblia and Cryptosporidum spp., respectively; one was caused by food in dwelling-house, without identification of the agent, and one caused by rotavirus spread citywide. Of all monitored cases, 63 (15.5%) were involved in outbreaks, linked to more 56 cases, in a total of 119 cases (outbreaks incidence rate=1.4/1000 inhabitants). CONCLUSIONS: The study showed that the program enables prompt detection and investigation of outbreaks, respected the conditions of reliability of the information, evaluation of the acute diarrhea trends and careful inquiry. To intensify training to increase the ability of local professionals to recognize patterns of possible outbreaks and for suitable investigations is one of the major recommendations of this study.

L'abattoir est un observatoire privilégié de la santé des bovins, permettant d'envisager une surveillance de la population bovine à partir des données d'inspection sanitaire qui y sont collectées. Mais la valorisation épidémiologique de ces données fait face à des difficultés (complexité des données, nombreux mouvements des bovins de leur naissance à l'abattoir). Afin de gérer cette complexité, une approche statistique (analyse multifactorielle et classification mixte) associée à des avis d'experts ont permis d'établir une typologie des lésions observées à l'abattoir. Une dizaine de groupes lésionnels ont été identifiés qui relèvent de divers domaines tels que la santé animale, la protection animale ou la santé publique. Les données d'abattoir peuvent être utilisées pour la surveillance de maladies ciblées telles que la cysticercose bovine. Des indicateurs de surveillance robustes ont été élaborés pour permettre la comparaison des prévalences de cette zoonose dans le temps et l'espace. Une méthode innovante de prise en compte de l'incertitude liée au lieu d'infestation des animaux a été mise en oeuvre pour identifier les zones à risque plus élevé d'infestation. Un tel outil sera mobilisable pour la mise en oeuvre ultérieure d'une inspection basée sur le risque visant à améliorer l'efficience de l'inspection en abattoir. L'utilisation des données d'abattoir pour la mise en place d'un dispositif de surveillance syndromique a par ailleurs été investiguée par modélisation de la proportion hebdomadaire de bovins ayant fait l'objet d'une saisie totale. Une évaluation des performances de plusieurs algorithmes de détection d'anomalies temporelles a été menée sur données simulées / The slaughterhouse is a unique dedicated vantage point from which to observe bovine health, making it possible to consider implementation of bovine surveillance based on meat inspection data. But the exploitation of these data for epidemiological purposes is not without difficulties (data complexity, large number of cattle movements from birth to slaughter). In order to deal with the data complexity issue, a statistical approach (multiple factor analysis in combination with clustering methods), in addition to the gathering of expert opinions, enables us to create a typology of the lesions detected at the slaughterhouse. Approximately ten lesion groups were identified which cover various areas including animal heath, animal welfare and public health. Meat inspection data can be used for the surveillance of targeted diseases such as bovine cysticercosis. Robust surveillance indicators have been created to enable prevalence comparisons of this zoonosis over time and space. An innovative approach that takes into account uncertainty regarding the location where the animal became infected was implemented to identify areas of higher risk of infection. A similar method could be used for the implementation of a future risk-based meat inspection initiative so as to improve meat inspection efficiency. The use of meat inspection data for the implementation of a syndromic surveillance system was investigated using a temporal analysis of the weekly proportion of whole carcass condemnations, and assessment of the performance of several algorithms for temporal aberration detection was conducted on simulated data

INTRODUÇÃO: A doença diarréica aguda é ainda importante causa de morbidade no mundo. Sua elevada incidência e a aceitação de sua ocorrência como fato "normal" impõem desafios para seu registro e implantação de seus sistemas de vigilância. OBJETIVOS: Conhecer as características epidemiológicas da diarréia aguda e avaliar a capacidade de detecção de surtos pelo Programa de Monitorização da Doença Diarréica Aguda, no município de Avaré. MÉTODOS: De 27 de fevereiro a 16 de julho 2005, realizou-se estudo prospectivo da diarréia em unidade sentinela do programa. Os surtos identificados foram investigados por estudos descritivos e analíticos. Amostras de fezes foram coletadas para os casos envolvidos nos surtos. A avaliação dos propósitos do programa embasou-se em indicadores de utilidade, sensibilidade e oportunidade. RESULTADOS: Foram identificados 408 casos (Coeficiente de Incidência = 4,7/1000 habitantes); idade mediana de 7 anos (variação de 1 mês a 89 anos) e 54% do sexo masculino. Dos quatro surtos de diarréia confirmados, dois ocorreram em uma creche e em um orfanato, devido à Giárdia lamblia e Cryptosporidum spp.; um intradomiciliar de origem alimentar, sem identificação do agente, e uma epidemia na comunidade associada ao rotavírus. Dos casos atendidos, 63 (15,5%) pertenciam a surtos, identificando-se mais 56 casos, em um total de 119 casos (Coeficiente de Incidência de Surtos=1,4/1000 habitantes). CONCLUSÕES: O estudo mostrou que o programa responde ao seu principal propósito, respeitando-se as condições de regularidade na informação, análises dos padrões da diarréia e investigação criteriosa. Intensificar treinamentos para aumentar a habilidade das equipes locais nas avaliações e investigações é uma das principais recomendações deste estudo. / BACKGROUND: Acute diarrheal illness remains an important cause of morbidity worldwide. Its high incidence and the acceptance of its occurrence as “normal” fact impose challenges for its report and implantation of its surveillance systems. OBJECTIVES: To describe the epidemiologic characteristics of the acute diarrhea and to evaluate the capacity of the Monitoring Program of the Acute Diarrheal Illness for early detection of outbreaks, in the city of Avaré, State of São Paulo, Brazil. METHODS: From February 16 to July 28, 2005, was a prospective study of the diarrhea in a sentinel health service of the program. Descriptive and analytical studies were developed to investigate the potential outbreaks identified in this period. Stool samples were collected from the involved cases in the outbreaks. The evaluation of purpose of the program was based on indicators of usefulness, sensitivity and timeliness. RESULTS: A total of 408 cases were identified (incidence rate=4.7/1000 inhabitants). The median age was 7 years (range 1-89 years) and 54% were male. Among four confirmed diarrhea outbreaks, two occurred in a day nursery and orphanage, due to Giardia lamblia and Cryptosporidum spp., respectively; one was caused by food in dwelling-house, without identification of the agent, and one caused by rotavirus spread citywide. Of all monitored cases, 63 (15.5%) were involved in outbreaks, linked to more 56 cases, in a total of 119 cases (outbreaks incidence rate=1.4/1000 inhabitants). CONCLUSIONS: The study showed that the program enables prompt detection and investigation of outbreaks, respected the conditions of reliability of the information, evaluation of the acute diarrhea trends and careful inquiry. To intensify training to increase the ability of local professionals to recognize patterns of possible outbreaks and for suitable investigations is one of the major recommendations of this study.

La surveillance des maladies abortives chez les bovins actuellement absentes du territoire (dites maladies exotiques), parmi lesquelles figure la brucellose, constitue un cas emblématique de système de surveillance à faire évoluer. Cette surveillance n'est réellement organisée que pour la brucellose. Pour cette maladie, la surveillance évènementielle basée sur la déclaration obligatoire de tout avortement (DA) constitue la pierre angulaire de la surveillance, mais souffre de l'avis de l'ensemble des acteurs, d'une forte sous-déclaration, sans que cela ait été évalué. Dans le cadre de cette thèse, l'évaluation approfondie du dispositif de DA a permis de quantifier la faible sensibilité de ce dispositif et d'identifier l'influence de différents facteurs, structurels, humains et sanitaires, sur le processus de déclaration. En parallèle, des données démographiques et de reproduction, collectées respectivement à des fins de traçabilité des animaux et d'amélioration des performances génétiques, ont été utilisées pour élaborer des indicateurs indirects de survenue d'avortements. La modélisation des variations temporelles et spatio-temporelles de ces indicateurs a souligné la capacité d'outils de surveillance syndromique à identifier la survenue d'évènements abortifs à l'échelle individuelle et des élevages. Au vu de ces travaux, l'amélioration de la surveillance des maladies exotiques abortives passe par le renforcement du dispositif de DA et le développement d'outils de surveillance syndromique. Plus globalement, dans un contexte où les risques d'apparition de maladies exotiques ou émergentes et les formes épidémio-cliniques qu'elles revêtiraient sont très difficilement prévisibles, il apparaît nécessaire de revisiter la surveillance des maladies exotiques et émergentes en définissant des systèmes de surveillance intégrée, déclinés par filière de production, associant différentes modalités de surveillance. De tels systèmes, en couvrant des maladies connues ou non, présentes sous forme clinique ou asymptomatique, et sous forme sporadique, épizootique ou diffuse, optimiseraient les chances de détecter les maladies exotiques ou émergentes / The surveillance system for exotic abortive diseases in French cattle (i.e. abortive diseases that are not currently found in France), such as brucellosis, is a typical example of a surveillance system that is in need of improvement. This type of surveillance only actually exists for brucellosis. Clinical surveillance is the cornerstone of brucellosis surveillance and consists in the mandatory notification of each bovine abortion. However, while no quantitatively assessments have been made, it is common knowledge that this type of surveillance suffers from high levels of under-reporting. By providing an in-depth assessment of the bovine abortion notification surveillance system, we quantified its low sensitivity and identified the influence of structural, human and health factors on how decisions to report abortions are taken. In addition, demographic and reproductive data, collected for purposes of traceability and for genetic performance improvement, were used to devise indirect indicators of abortion occurrence. By modeling the temporal and spatio-temporal variations of these indicators, we highlighted the ability for syndromic surveillance systems to identify the occurrence of abortive events at individual and herd scale. Based on these studies, improving exotic abortive disease surveillance requires revising the mandatory notification surveillance system and developing syndromic surveillance systems. More generally, considering the difficulties in predicting the occurrence of exotic or emerging diseases and their clinical and epidemiological forms, it is necessary to reorganize the surveillance of exotic diseases by setting up integrated surveillance systems that would include different surveillance modalities. Such surveillance systems, implemented by production sector, would focus on known or unknown diseases, showing clinical or subclinical forms, and sporadic, epizootic or diffuse patterns, and would thus maximize the ability to detect exotic or emerging diseases

Deep penetration of personal computers, data communication networks, and the Internet has created a massive platform for data collection, dissemination, storage, and retrieval. Large amounts of textual data are now available at a very low cost. Valuable information, such as consumer preferences, new product developments, trends, and opportunities, can be found in this large collection of textual data. Growing worldwide competition, new technology development, and the Internet contribute to an increasingly turbulent business environment. Conducting surveillance on this growing collection of textual data could help a business avoid surprises, identify threats and opportunities, and gain competitive advantages.Current text mining approaches, nonetheless, provide limited support for conducting surveillance using textual data. In this dissertation, I develop novel text quantification approaches to identify useful information in textual data, effective anomaly detection approaches to monitor time series data aggregated based on the text quantification approaches, and empirical evaluation approaches that verify the effectiveness of text mining approaches using external numerical data sources.In Chapter 2, I present free-text chief complaint classification studies that aim to classify incoming emergency department free-text chief complaints into syndromic categories, a higher level of representation that facilitates syndromic surveillance. Chapter 3 presents a novel detection algorithm based on Markov switching with jumps models. This surveillance model aims at detecting different types of disease outbreaks based on the time series generated from the chief complaint classification system.In Chapters 4 and 5, I studied the surveillance issue under the context of business decision making. Chapter 4 presents a novel text-based risk recognition design framework that can be used to monitor the changing business environment. Chapter 5 presents an empirical evaluation study that looks at the interaction between news sentiment and numerical accounting earnings information. Chapter 6 concludes this dissertation by highlighting major research contributions and the relevance to MIS research.

Des études récentes ont montré que parmi les infections émergentes chez l'homme, env. 40% étaient des zoonoses liées à la faune sauvage. La surveillance sanitaire de ces animaux devrait contribuer à améliorer la protection de leur santé et aussi celle des animaux domestiques et des hommes. Notre objectif était de développer des outils de détection de problèmes sanitaires inhabituels dans la faune sauvage, en adoptant une approche syndromique, utilisée en santé humaine, avec des profils pathologiques comme indicateurs de santé non spécifiques. Un réseau national de surveillance des causes de mortalité dans la faune sauvage, appelé SAGIR, a fourni les données. Entre 1986 et 2007, plus de 50.000 cas ont été enregistrés, représentant 244 espèces de mammifères terrestres et d'oiseaux, et attribués à 220 différentes causes de mort. Le réseau a d'abord été évalué pour sa capacité à détecter précocement des événements inhabituels. Des classes syndromiques ont ensuite été définies par une typologie statistique des lésions observées sur les cadavres. Les séries temporelles des syndromes ont été analysées en utilisant deux méthodes complémentaires de détection : un algorithme robuste développé par Farrington et un modèle linéaire généralisé avec des termes périodiques. Les tendances séculaires de ces syndromes et des signaux correspondent a des excès de cas ont été identifiés. Les signalements de problèmes de mortalité inhabituelle dans le bulletin du réseau ont été utilisés pour interpréter ces signaux. L'étude analyse la pertinence de l'utilisation de la surveillance syndromique sur ce type de données et donne des éléments pour des améliorations futures. / Recent studies have shown that amongst emerging infectious disease events in humans, about 40% were zoonoses linked to wildlife. Disease surveillance of wildlife should help to improve health protection of these animals and also of domestic animals and humans that are exposed to these pathogenic agents. Our aim was to develop tools capable of detecting unusual disease events in free ranging wildlife, by adopting a syndromic approach, as it is used for human health surveillance, with pathological profiles as early unspecific health indicators. We used the information registered by a national network monitoring causes of death in wildlife in France since 1986, called SAGIR. More than 50.000 cases of mortality in wildlife were recorded up to 2007, representing 244 species of terrestrial mammals and birds, and were attributed to 220 different causes of death. The network was first evaluated for its capacity to detect early unusual events. Syndromic classes were then defined by a statistical typology of the lesions observed on the carcasses. Syndrome time series were analyzed, using two complimentary methods of detection, one robust detection algorithm developed by Farrington and another generalized linear model with periodic terms. Historical trends of occurrence of these syndromes and greater-than-expected counts (signals) were identified. Reporting of unusual mortality events in the network bulletin was used to interpret these signals. The study analyses the relevance of the use of syndromic surveillance on this type of data and gives elements for future improvements.

Background: Respiratory illnesses can have a substantial impact on population health and burden hospitals in terms of patient load. Advance warnings of the spread of such illness could inform public health interventions and help hospitals manage patient services. Previous research showed that calls for respiratory complaints to Telehealth Ontario are correlated up to two weeks in advance with emergency department visits for respiratory illness at the provincial level. Objectives: This thesis examined whether Telehealth Ontario calls for respiratory complaints could be used to accurately forecast the daily and weekly number of emergency department visits for respiratory illness at the health unit level for each of the 36 health units in Ontario up to 14 days in advance in the context of a real-time syndromic surveillance system. The forecasting abilities of three different time series modeling techniques were compared. Methods: The thesis used hospital emergency department visit data from the National Ambulatory Care Reporting System database and Telehealth Ontario call data and from June 1, 2004 to March 31, 2006. Parallel Cascade Identification (PCI), Fast Orthogonal Search (FOS), and Numerical Methods for Subspace State Space System Identification (N4SID) algorithms were used to create prediction models for the daily number of emergency department visits using Telehealth call counts and holiday/weekends as predictors. Prediction models were constructed using the first year of the study data and their accuracy was measured over the second year of data. Factors associated with prediction accuracy were examined. Results: Forecast error varied widely across health units. Prediction error increased with lead time and lower call-to-visits ratio. Compared with N4SID, PCI and FOS had significantly lower forecast error. Forecasts of the weekly aggregate number of visits showed little evidence of ability to accurately flag corresponding actual increases. However, when visits were aggregated over a four day period, increases could be flagged more accurately than chance in six of the 36 health units accounting for approximately half of the Ontario population. Conclusions: This thesis suggests that Telehealth Ontario data collected by a real-time syndromic surveillance system could play a role in forecasting health services demand for respiratory illness. / Thesis (Master, Community Health & Epidemiology) -- Queen's University, 2009-08-11 16:20:44.553

La dématérialisation des données de santé a permis depuis plusieurs années de constituer un véritable gisement de données provenant de tous les domaines de la santé. Ces données ont pour caractéristiques d’être très hétérogènes et d’être produites à différentes échelles et dans différents domaines. Leur réutilisation dans le cadre de la recherche clinique, de la santé publique ou encore de la prise en charge des patients implique de développer des approches adaptées reposant sur les méthodes issues de la science des données. L’objectif de cette thèse est d’évaluer au travers de trois cas d’usage, quels sont les enjeux actuels ainsi que la place des data sciences pour l’exploitation des données massives en santé. La démarche utilisée pour répondre à cet objectif consiste dans une première partie à exposer les caractéristiques des données massives en santé et les aspects techniques liés à leur réutilisation. La seconde partie expose les aspects organisationnels permettant l’exploitation et le partage des données massives en santé. La troisième partie décrit les grandes approches méthodologiques en science des données appliquées actuellement au domaine de la santé. Enfin, la quatrième partie illustre au travers de trois exemples l’apport de ces méthodes dans les champs suivant : la surveillance syndromique, la pharmacovigilance et la recherche clinique. Nous discutons enfin les limites et enjeux de la science des données dans le cadre de la réutilisation des données massives en santé. / The dematerialization of health data, which started several years ago, now generates na huge amount of data produced by all actors of health. These data have the characteristics of being very heterogeneous and of being produced at different scales and in different domains. Their reuse in the context of clinical research, public health or patient care involves developing appropriate approaches based on methods from data science. The aim of this thesis is to evaluate, through three use cases, what are the current issues as well as the place of data sciences regarding the reuse of massive health data. To meet this objective, the first section exposes the characteristics of health big data and the technical aspects related to their reuse. The second section presents the organizational aspects for the exploitation and sharing of health big data. The third section describes the main methodological approaches in data sciences currently applied in the field of health. Finally, the fourth section illustrates, through three use cases, the contribution of these methods in the following fields: syndromic surveillance, pharmacovigilance and clinical research. Finally, we discuss the limits and challenges of data science in the context of health big data.

La France connaît un vieillissement de sa population sans précédent. La part des séniors s’accroît et notre société se doit de repenser son organisation pour tenir compte de ce changement et mieux connaître cette population.De nombreuses cohortes de personnes âgées existent déjà à travers le monde dont quatre en France et, bien que la part de cette population vivant dans des structures d’hébergement collectif (EHPAD, cliniques de soins de suite) augmente, la connaissance de ces seniors reste lacunaire.Aujourd’hui les groupes privés de maisons de retraite et d’établissements sanitaires comme Korian ou Orpéa s’équipent de grandes bases de données relationnelles permettant d’avoir de l’information en temps réel sur leurs patients/résidents. Depuis 2010 les dossiers de tous les résidents Korian sont dématérialisés et accessibles par requêtes. Ils comprennent à la fois des données médico-sociales structurées décrivant les résidents et leurs traitements et pathologies, mais aussi des données textuelles explicitant leur prise en charge au quotidien et saisies par le personnel soignant.Au fil du temps et alors que le dossier résident informatisé (DRI) avait surtout été conçu comme une application de gestion de base de données, il est apparu comme une nécessité d’exploiter cette mine d’informations et de construire un outil d’aide à la décision destiné à améliorer l’efficacité des soins. L’Institut du Bien Vieillir IBV devenu entretemps la Fondation Korian pour le Bien Vieillir a alors choisi, dans le cadre d’un partenariat Public/Privé de financer un travail de recherche destiné à mieux comprendre le potentiel informatif de ces données, d’évaluer leur fiabilité et leur capacité à apporter des réponses en santé publique. Ce travail de recherche et plus particulièrement cette thèse a alors été pensée en plusieurs étapes.- D’abord l’analyse de contenu du data warehouse DRI, l’objectif étant de construire une base de données recherche, avec un versant social et un autre de santé. Ce fut le sujet du premier article.- Ensuite, par extraction directe des informations socio-démographiques des résidents dès leur entrée, de leurs hospitalisations et décès puis, par un processus itératif d’extractions d’informations textuelles de la table des transmissions et l’utilisation de la méthode Delphi, nous avons généré vingt-quatre syndromes, ajouté les hospitalisations et les décès et construit une base de données syndromique, la Base du Bien Vieillir (BBV) . Ce système d’informations d’un nouveau type a permis la constitution d’une cohorte de santé publique à partir de la population des résidents de la BBV et l’organisation d’un suivi longitudinal syndromique de celle-ci. La BBV a également été évaluée scientifiquement dans un cadre de surveillance et de recherche en santé publique au travers d’une analyse de l’existant : contenu, périodicité, qualité des données. La cohorte construite a ainsi permis la constitution d’un outil de surveillance. Cet échantillon de population a été suivi en temps réel au moyen des fréquences quotidiennes d’apparitions des 26 syndromes des résidents. La méthodologie d’évaluation était celle des systèmes de surveillance sanitaire proposée par le CDC d’Atlanta et a été utilisée pour les syndromes grippaux et les gastro entérites aiguës. Ce fut l’objet du second article.- Enfin la construction d’un nouvel outil de santé publique : la distribution de chacun des syndromes dans le temps (dates de transmissions) et l’espace (les EHPAD de transmissions) a ouvert le champ de la recherche à de nouvelles méthodes d’exploration des données et permis d’étudier plusieurs problématiques liées à la personne âgée : chutes répétées, cancer, vaccinations et fin de vie. / French population is rapidly aging. Senior citizens ratio is increasing and our society needs to rethink its organization, taking into account this change, better knowing this fast growing population group.Even if numerous cohorts of elderly people already exist worldly with four in France and, even as they live in growing numbers in nursing homes and out-patient treatment clinics, knowledge of this population segment is still missing.Today several health and medico-social structures groups as Korian and Orpéa invest in big relational data bases enabling them to get real-time information about their patients/residents. Since 2010 all Korian residents’ files are dematerialized and accessible by requests. They contain at the same time, structured medico-social data describing the residents as well as their treatments and pathologies, but also free-textual data detailing their daily care by the medical staff.Through time and as the computerized resident file (DRI) was mainly conceived as a data base management application, it appeared essential to mine these data and build a decision-making tool intended to improve the care efficiency. The Ageing Well Institute becoming meanwhile the Korian Ageing Well Foundation chose then, working in a private/public partnership, to finance a research work intented to better understand these datas’ informative potential, to assess their reliability and response to public health threats. This research work and this thesis were then designed in several steps:- First, a content analysis of the data warehouse DRI, the objective being to build a research data base, with a social side and a health side. This was the first paper subject.- Then, by direct extraction of the residents’ socio-demographic information at nursing home (NH) entry, adding hospitalizations and deaths, and finally, by an iterative textual extraction process of the transmissions data and by using the Delphi method, we created twenty-four syndromes, added hospitalizations and deaths and built a syndromic data base, the Ageing Well data base. This information system of a new kind, allowed the constitution of a public health cohort for elderly people from the BBV residents’population and its syndromic longitudinal follow-up. The BBV was also scientifically assessed for surveillance and public health research through present situation analysis: content, periodicity and data quality. This cohort then gave us the opportunity to build a surveillance tool and follow the residents’ population in real-time by watching their 26 daily frequency syndromic distributions. The methodology for that assessment, Atlanta CDCs’ health surveillance systems method, was used for flu and acute gastro enteritis syndroms and was the second paper subject.- Finally, the building of a new public health tool: each syndrom’s distribution through time (transmissions dates) and space (transmissions NH ids) opened the research field to new data exploration methods. I used these to study different health problems afflicting senior citizens: frequent falls, cancer, vaccinations and the end of life.

Indiana University-Purdue University Indianapolis (IUPUI) / Public health agencies protect the health and safety of populations. A key function of public health agencies is surveillance or the ongoing, systematic collection, analysis, interpretation, and dissemination of data about health-related events. Recent public health events, such as the H1N1 outbreak, have triggered increased funding for and attention towards the improvement and sustainability of public health agencies’ capacity for surveillance activities. For example, provisions in the final U.S. Centers for Medicare and Medicaid Services (CMS) “meaningful use” criteria ask that physicians and hospitals report surveillance data to public health agencies using electronic laboratory reporting (ELR) and syndromic surveillance functionalities within electronic health record (EHR) systems. Health information exchange (HIE), organized exchange of clinical and financial health data among a network of trusted entities, may be a path towards achieving meaningful use and enhancing the nation’s public health surveillance infrastructure. Yet the evidence on the value of HIE, especially in the context of public health surveillance, is sparse. In this research, the value of HIE to the process of public health surveillance is explored. Specifically, the study describes the real and perceived completeness and usefulness of HIE in public health surveillance activities. To explore the real value of HIE, the study examined ELR data from two states, comparing raw, unedited data sent from hospitals and laboratories to data enhanced by an HIE. To explore the perceived value of HIE, the study examined public health, infection control, and HIE professionals’ perceptions of public health surveillance data and information flows, comparing traditional flows to HIE-enabled ones. Together these methods, along with the existing literature, triangulate the value that HIE does and can provide public health surveillance processes. The study further describes remaining gaps that future research and development projects should explore. The data collected in the study show that public health surveillance activities vary dramatically, encompassing a wide range of paper and electronic methods for receiving and analyzing population health trends. Few public health agencies currently utilize HIE-enabled processes for performing surveillance activities, relying instead on direct reporting of information from hospitals, physicians, and laboratories. Generally HIE is perceived well among public health and infection control professionals, and many of these professionals feel that HIE can improve surveillance methods and population health. Human and financial resource constraints prevent additional public health agencies from participating in burgeoning HIE initiatives. For those agencies that do participate, real value is being added by HIEs. Specifically, HIEs are improving the completeness and semantic interoperability of ELR messages sent from clinical information systems. New investments, policies, and approaches will be necessary to increase public health utilization of HIEs while improving HIEs’ capacity to deliver greater value to public health surveillance processes.