Elaboration d'un score de vieillissement : propositions théoriques

Ageing is nowadays a major public health problem. Its description remains complex, both individual and collective conceptualization being interlaced with a strong subjective dimension. Health professionals are increasingly required to integrate ageing and prevention into their thought and to create adapted protocol and new tools. Ageing characterizes unavoidable changes in the body. It is usually measured by the age dependent on time and called “chronological age”. However, the criterion « chronological age » reflects imperfectly the actual ageing of the body depending on many individual factors. Also, this criterion has for a long time been replaced by another composite criterion called « biological age » supposed to better reflect the ageing process. In order to build a score of ageing adapted to general practice, a new methodology is proposed suitable for general practitioners. First of all, a first phase of this work consisted in a qualitative and quantitative survey conducted among general practitioners in France. This survey was done to obtain data on the use of predictive scores by general practitioners in their daily practice and their appropriateness, as well as to know the reasons of their non-utilization. Results showed that predictive scores are useful tools in daily practice to target a complex systemic approach insofar as they are simple to use (few items, items suitable for general practice) and their scientific validity is easily understood. In addition, patient’s age has been cited as a major criterion influencing general practitioners use of a predictive score. Results of this first phase have been used to propose a model of biological ageing, with reflexion on mathematical model as well as on component variables of this model. A selection of variables as markers of ageing was carried out from a review of the literature, taking into account their capacity of integration in general practitioners’ daily practice. This selection was completed by a mathematical approach based on an ascending process on a regression model. A control sample, assumed to be "normal ageing" on the basis of current knowledge in general medicine, was then used. This sample was first carried out from a review of the literature and then from a K-means method that classified this sample into several groups. The statistical dependence of measured variables was modeled by a Gaussian copula (taking into account only linear correlations of pairs). A standardized biological age was defined explicitly from these correlation coefficients. The tails of marginal distribution (method of excess) were estimated to enhance the discriminating power of the model. Results suggest interesting possibilities for a biological ageing calculation, and the predictive score they provide, suitable for general practitioners’ daily practice. Its validation by a morbidity and mortality survey will constitute the final phase of this workLe vieillissement fait actuellement l’objet de toutes les attentions, constituant en effet un problème de santé publique majeur. Sa description reste cependant complexe en raison des intrications à la fois individuelles et collectives de sa conceptualisation et d’une dimension subjective forte. Les professionnels de santé sont de plus en plus obligés d’intégrer cette donnée dans leur réflexion et de proposer des protocoles de prise en charge adaptés. Le vieillissement est une évolution inéluctable du corps dont la quantification est établie par l’âge dépendant du temps dit « chronologique ». Ce critère âge est cependant imparfait pour mesurer l’usure réelle du corps soumise à de nombreux facteurs modificateurs dépendant des individus. Aussi, partant de réflexions déjà engagées et consistant à substituer cet âge chronologique par un critère composite appelé « âge biologique », aboutissant à la création d’un indicateur ou score de vieillissement et sensé davantage refléter le vieillissement individuel, une nouvelle méthodologie est proposée adaptée à la pratique de médecine générale. Une première phase de ce travail a consisté à sonder les médecins généralistes sur leur perception et leur utilisation des scores cliniques en pratique courante par l’intermédiaire d’une enquête qualitative et quantitative effectuée en France métropolitaine. Cette étude a montré que l’adéquation entre l’utilisation déclarée et la conception intellectualisée des scores restait dissociée. Les scores constituent un outil d’aide à la prise en charge utile pour cibler une approche systémique souvent complexe dans la mesure où ils sont simples à utiliser (peu d’items et items adaptés à la pratique) et à la validité scientifiquement comprise par le médecin. Par ailleurs, l’âge du patient a été cité comme un élément prépondérant influençant le choix adéquat du score par le médecin généraliste. Cette base de travail a donc servi à proposer une modélisation de l’âge biologique dont la réflexion a porté tant sur le choix du modèle mathématique que des variables constitutives de ce modèle. Une sélection de variables marqueurs du vieillissement a été effectuée à partir d’une revue de la littérature et tenant compte de leur possible intégration dans le processus de soin en médecine générale. Cette sélection a été consolidée par une approche mathématique selon un processus de sélection ascendant à partir d’un modèle régressif. Une population dite « témoin » au vieillissement considéré comme normal a été ensuite constituée servant de base comparative au calcul de l’âge biologique. Son choix a été influencé dans un premier temps par les données de la littérature puis secondairement selon un tri par classification utilisant la méthode des nuées dynamiques. Un modèle de régression linéaire simple a ensuite été construit mais avec de données normalisées selon la méthode des copules gaussiennes suivi d’une étude des queues de distribution marginales. Les résultats ainsi obtenus laissent entrevoir des perspectives intéressantes de réflexion pour approfondir le calcul d’un âge biologique et du score en découlant en médecine générale, sa validation par une étude de morbidité constituant l’étape ultime de ce travai

Predicting Fluctuating Rates of Hospitalizations in Relation to Influenza Epidemics and Meteorological Factors

International audienceIntroductionIn France, rates of hospital admissions increase at the peaks of influenza epidemics. Predicting influenza-associated hospitalizations could help to anticipate increased hospital activity. The purpose of this study is to identify predictors of influenza epidemics through the analysis of meteorological data, and medical data provided by general practitioners.MethodsHistorical data were collected from Meteo France, the Sentinelles network and hospitals’ information systems for a period of 8 years (2007–2015). First, connections between meteorological and medical data were estimated with the Pearson correlation coefficient, Principal component analysis and classification methods (Ward and k-means). Epidemic states of tested weeks were then predicted for each week during a one-year period using linear discriminant analysis. Finally, transition probabilities between epidemic states were calculated with the Markov Chain method.ResultsHigh correlations were found between influenza-associated hospitalizations and the variables: Sentinelles and emergency department admissions, and anti-correlations were found between hospitalizations and each of meteorological factors applying a time lag of: -13, -12 and -32 days respectively for temperature, absolute humidity and solar radiation. Epidemic weeks were predicted accurately with the linear discriminant analysis method; however there were many misclassifications about intermediate and non-epidemic weeks. Transition probability to an epidemic state was 100% when meteorological variables were below: 2°C, 4 g/m3 and 32 W/m2, respectively for temperature, absolute humidity and solar radiation. This probability was 0% when meteorological variables were above: 6°C, 5.8g/m3 and 74W/m2.ConclusionThese results confirm a good correlation between influenza-associated hospitalizations, meteorological factors and general practitioner’s activity, the latter being the strongest predictor of hospital activity

Elaboration d'un score de vieillissement (propositions théoriques)

Le vieillissement fait actuellement l objet de toutes les attentions, constituant en effet un problème de santé publique majeur. Sa description reste cependant complexe en raison des intrications à la fois individuelles et collectives de sa conceptualisation et d une dimension subjective forte. Les professionnels de santé sont de plus en plus obligés d intégrer cette donnée dans leur réflexion et de proposer des protocoles de prise en charge adaptés. Le vieillissement est une évolution inéluctable du corps dont la quantification est établie par l âge dépendant du temps dit chronologique . Ce critère âge est cependant imparfait pour mesurer l usure réelle du corps soumise à de nombreux facteurs modificateurs dépendant des individus. Aussi, partant de réflexions déjà engagées et consistant à substituer cet âge chronologique par un critère composite appelé âge biologique , aboutissant à la création d un indicateur ou score de vieillissement et sensé davantage refléter le vieillissement individuel, une nouvelle méthodologie est proposée adaptée à la pratique de médecine générale. Une première phase de ce travail a consisté à sonder les médecins généralistes sur leur perception et leur utilisation des scores cliniques en pratique courante par l intermédiaire d une enquête qualitative et quantitative effectuée en France métropolitaine. Cette étude a montré que l adéquation entre l utilisation déclarée et la conception intellectualisée des scores restait dissociée. Les scores constituent un outil d aide à la prise en charge utile pour cibler une approche systémique souvent complexe dans la mesure où ils sont simples à utiliser (peu d items et items adaptés à la pratique) et à la validité scientifiquement comprise par le médecin. Par ailleurs, l âge du patient a été cité comme un élément prépondérant influençant le choix adéquat du score par le médecin généraliste. Cette base de travail a donc servi à proposer une modélisation de l âge biologique dont la réflexion a porté tant sur le choix du modèle mathématique que des variables constitutives de ce modèle. Une sélection de variables marqueurs du vieillissement a été effectuée à partir d une revue de la littérature et tenant compte de leur possible intégration dans le processus de soin en médecine générale. Cette sélection a été consolidée par une approche mathématique selon un processus de sélection ascendant à partir d un modèle régressif. Une population dite témoin au vieillissement considéré comme normal a été ensuite constituée servant de base comparative au calcul de l âge biologique. Son choix a été influencé dans un premier temps par les données de la littérature puis secondairement selon un tri par classification utilisant la méthode des nuées dynamiques. Un modèle de régression linéaire simple a ensuite été construit mais avec de données normalisées selon la méthode des copules gaussiennes suivi d une étude des queues de distribution marginales. Les résultats ainsi obtenus laissent entrevoir des perspectives intéressantes de réflexion pour approfondir le calcul d un âge biologique et du score en découlant en médecine générale, sa validation par une étude de morbidité constituant l étape ultime de ce travailAgeing is nowadays a major public health problem. Its description remains complex, both individual and collective conceptualization being interlaced with a strong subjective dimension. Health professionals are increasingly required to integrate ageing and prevention into their thought and to create adapted protocol and new tools. Ageing characterizes unavoidable changes in the body. It is usually measured by the age dependent on time and called chronological age . However, the criterion chronological age reflects imperfectly the actual ageing of the body depending on many individual factors. Also, this criterion has for a long time been replaced by another composite criterion called biological age supposed to better reflect the ageing process. In order to build a score of ageing adapted to general practice, a new methodology is proposed suitable for general practitioners. First of all, a first phase of this work consisted in a qualitative and quantitative survey conducted among general practitioners in France. This survey was done to obtain data on the use of predictive scores by general practitioners in their daily practice and their appropriateness, as well as to know the reasons of their non-utilization. Results showed that predictive scores are useful tools in daily practice to target a complex systemic approach insofar as they are simple to use (few items, items suitable for general practice) and their scientific validity is easily understood. In addition, patient s age has been cited as a major criterion influencing general practitioners use of a predictive score. Results of this first phase have been used to propose a model of biological ageing, with reflexion on mathematical model as well as on component variables of this model. A selection of variables as markers of ageing was carried out from a review of the literature, taking into account their capacity of integration in general practitioners daily practice. This selection was completed by a mathematical approach based on an ascending process on a regression model. A control sample, assumed to be "normal ageing" on the basis of current knowledge in general medicine, was then used. This sample was first carried out from a review of the literature and then from a K-means method that classified this sample into several groups. The statistical dependence of measured variables was modeled by a Gaussian copula (taking into account only linear correlations of pairs). A standardized biological age was defined explicitly from these correlation coefficients. The tails of marginal distribution (method of excess) were estimated to enhance the discriminating power of the model. Results suggest interesting possibilities for a biological ageing calculation, and the predictive score they provide, suitable for general practitioners daily practice. Its validation by a morbidity and mortality survey will constitute the final phase of this workST ETIENNE-Bib. électronique (422189901) / SudocSudocFranceF

Elaboration d'un score de vieillissement (propositions théoriques)

Le vieillissement fait actuellement l objet de toutes les attentions, constituant en effet un problème de santé publique majeur. Sa description reste cependant complexe en raison des intrications à la fois individuelles et collectives de sa conceptualisation et d une dimension subjective forte. Les professionnels de santé sont de plus en plus obligés d intégrer cette donnée dans leur réflexion et de proposer des protocoles de prise en charge adaptés. Le vieillissement est une évolution inéluctable du corps dont la quantification est établie par l âge dépendant du temps dit chronologique . Ce critère âge est cependant imparfait pour mesurer l usure réelle du corps soumise à de nombreux facteurs modificateurs dépendant des individus. Aussi, partant de réflexions déjà engagées et consistant à substituer cet âge chronologique par un critère composite appelé âge biologique , aboutissant à la création d un indicateur ou score de vieillissement et sensé davantage refléter le vieillissement individuel, une nouvelle méthodologie est proposée adaptée à la pratique de médecine générale. Une première phase de ce travail a consisté à sonder les médecins généralistes sur leur perception et leur utilisation des scores cliniques en pratique courante par l intermédiaire d une enquête qualitative et quantitative effectuée en France métropolitaine. Cette étude a montré que l adéquation entre l utilisation déclarée et la conception intellectualisée des scores restait dissociée. Les scores constituent un outil d aide à la prise en charge utile pour cibler une approche systémique souvent complexe dans la mesure où ils sont simples à utiliser (peu d items et items adaptés à la pratique) et à la validité scientifiquement comprise par le médecin. Par ailleurs, l âge du patient a été cité comme un élément prépondérant influençant le choix adéquat du score par le médecin généraliste. Cette base de travail a donc servi à proposer une modélisation de l âge biologique dont la réflexion a porté tant sur le choix du modèle mathématique que des variables constitutives de ce modèle. Une sélection de variables marqueurs du vieillissement a été effectuée à partir d une revue de la littérature et tenant compte de leur possible intégration dans le processus de soin en médecine générale. Cette sélection a été consolidée par une approche mathématique selon un processus de sélection ascendant à partir d un modèle régressif. Une population dite témoin au vieillissement considéré comme normal a été ensuite constituée servant de base comparative au calcul de l âge biologique. Son choix a été influencé dans un premier temps par les données de la littérature puis secondairement selon un tri par classification utilisant la méthode des nuées dynamiques. Un modèle de régression linéaire simple a ensuite été construit mais avec de données normalisées selon la méthode des copules gaussiennes suivi d une étude des queues de distribution marginales. Les résultats ainsi obtenus laissent entrevoir des perspectives intéressantes de réflexion pour approfondir le calcul d un âge biologique et du score en découlant en médecine générale, sa validation par une étude de morbidité constituant l étape ultime de ce travailAgeing is nowadays a major public health problem. Its description remains complex, both individual and collective conceptualization being interlaced with a strong subjective dimension. Health professionals are increasingly required to integrate ageing and prevention into their thought and to create adapted protocol and new tools. Ageing characterizes unavoidable changes in the body. It is usually measured by the age dependent on time and called chronological age . However, the criterion chronological age reflects imperfectly the actual ageing of the body depending on many individual factors. Also, this criterion has for a long time been replaced by another composite criterion called biological age supposed to better reflect the ageing process. In order to build a score of ageing adapted to general practice, a new methodology is proposed suitable for general practitioners. First of all, a first phase of this work consisted in a qualitative and quantitative survey conducted among general practitioners in France. This survey was done to obtain data on the use of predictive scores by general practitioners in their daily practice and their appropriateness, as well as to know the reasons of their non-utilization. Results showed that predictive scores are useful tools in daily practice to target a complex systemic approach insofar as they are simple to use (few items, items suitable for general practice) and their scientific validity is easily understood. In addition, patient s age has been cited as a major criterion influencing general practitioners use of a predictive score. Results of this first phase have been used to propose a model of biological ageing, with reflexion on mathematical model as well as on component variables of this model. A selection of variables as markers of ageing was carried out from a review of the literature, taking into account their capacity of integration in general practitioners daily practice. This selection was completed by a mathematical approach based on an ascending process on a regression model. A control sample, assumed to be "normal ageing" on the basis of current knowledge in general medicine, was then used. This sample was first carried out from a review of the literature and then from a K-means method that classified this sample into several groups. The statistical dependence of measured variables was modeled by a Gaussian copula (taking into account only linear correlations of pairs). A standardized biological age was defined explicitly from these correlation coefficients. The tails of marginal distribution (method of excess) were estimated to enhance the discriminating power of the model. Results suggest interesting possibilities for a biological ageing calculation, and the predictive score they provide, suitable for general practitioners daily practice. Its validation by a morbidity and mortality survey will constitute the final phase of this workST ETIENNE-Bib. électronique (422189901) / SudocSudocFranceF

The Chikungunya Epidemic on La Réunion Island in 2005–2006: A Cost-of-Illness Study

For a long time, studies of chikungunya virus infection have been neglected, but since its resurgence in the south-western Indian Ocean and on La Réunion Island, this disease has been paid greater amounts of attention. The economic and social impacts of chikungunya epidemics are poorly documented, including in developed countries. This study estimated the cost-of-illness associated with the 2005–2006 chikungunya epidemics on La Réunion Island, a French overseas department with an economy and health care system of a developed country. “Cost-of-illness” studies measure the amount that would have been saved in the absence of a disease. We found that the epidemic incurred substantial medical expenses estimated at €43.9 million, of which 60% were attributable to direct medical costs related, in particular, to expenditure on medical consultations (47%), hospitalization (32%) and drugs (19%). The costs related to care in ambulatory and hospitalized cases were €90 and €2000 per case, respectively. This study provides the basic inputs for conducting cost-effectiveness and cost-benefit evaluations of chikungunya prevention strategies

Development of a score of ageing : proposal for a mathematical theory

Le vieillissement fait actuellement l’objet de toutes les attentions, constituant en effet un problème de santé publique majeur. Sa description reste cependant complexe en raison des intrications à la fois individuelles et collectives de sa conceptualisation et d’une dimension subjective forte. Les professionnels de santé sont de plus en plus obligés d’intégrer cette donnée dans leur réflexion et de proposer des protocoles de prise en charge adaptés. Le vieillissement est une évolution inéluctable du corps dont la quantification est établie par l’âge dépendant du temps dit « chronologique ». Ce critère âge est cependant imparfait pour mesurer l’usure réelle du corps soumise à de nombreux facteurs modificateurs dépendant des individus. Aussi, partant de réflexions déjà engagées et consistant à substituer cet âge chronologique par un critère composite appelé « âge biologique », aboutissant à la création d’un indicateur ou score de vieillissement et sensé davantage refléter le vieillissement individuel, une nouvelle méthodologie est proposée adaptée à la pratique de médecine générale. Une première phase de ce travail a consisté à sonder les médecins généralistes sur leur perception et leur utilisation des scores cliniques en pratique courante par l’intermédiaire d’une enquête qualitative et quantitative effectuée en France métropolitaine. Cette étude a montré que l’adéquation entre l’utilisation déclarée et la conception intellectualisée des scores restait dissociée. Les scores constituent un outil d’aide à la prise en charge utile pour cibler une approche systémique souvent complexe dans la mesure où ils sont simples à utiliser (peu d’items et items adaptés à la pratique) et à la validité scientifiquement comprise par le médecin. Par ailleurs, l’âge du patient a été cité comme un élément prépondérant influençant le choix adéquat du score par le médecin généraliste. Cette base de travail a donc servi à proposer une modélisation de l’âge biologique dont la réflexion a porté tant sur le choix du modèle mathématique que des variables constitutives de ce modèle. Une sélection de variables marqueurs du vieillissement a été effectuée à partir d’une revue de la littérature et tenant compte de leur possible intégration dans le processus de soin en médecine générale. Cette sélection a été consolidée par une approche mathématique selon un processus de sélection ascendant à partir d’un modèle régressif. Une population dite « témoin » au vieillissement considéré comme normal a été ensuite constituée servant de base comparative au calcul de l’âge biologique. Son choix a été influencé dans un premier temps par les données de la littérature puis secondairement selon un tri par classification utilisant la méthode des nuées dynamiques. Un modèle de régression linéaire simple a ensuite été construit mais avec de données normalisées selon la méthode des copules gaussiennes suivi d’une étude des queues de distribution marginales. Les résultats ainsi obtenus laissent entrevoir des perspectives intéressantes de réflexion pour approfondir le calcul d’un âge biologique et du score en découlant en médecine générale, sa validation par une étude de morbidité constituant l’étape ultime de ce travailAgeing is nowadays a major public health problem. Its description remains complex, both individual and collective conceptualization being interlaced with a strong subjective dimension. Health professionals are increasingly required to integrate ageing and prevention into their thought and to create adapted protocol and new tools. Ageing characterizes unavoidable changes in the body. It is usually measured by the age dependent on time and called “chronological age”. However, the criterion « chronological age » reflects imperfectly the actual ageing of the body depending on many individual factors. Also, this criterion has for a long time been replaced by another composite criterion called « biological age » supposed to better reflect the ageing process. In order to build a score of ageing adapted to general practice, a new methodology is proposed suitable for general practitioners. First of all, a first phase of this work consisted in a qualitative and quantitative survey conducted among general practitioners in France. This survey was done to obtain data on the use of predictive scores by general practitioners in their daily practice and their appropriateness, as well as to know the reasons of their non-utilization. Results showed that predictive scores are useful tools in daily practice to target a complex systemic approach insofar as they are simple to use (few items, items suitable for general practice) and their scientific validity is easily understood. In addition, patient’s age has been cited as a major criterion influencing general practitioners use of a predictive score. Results of this first phase have been used to propose a model of biological ageing, with reflexion on mathematical model as well as on component variables of this model. A selection of variables as markers of ageing was carried out from a review of the literature, taking into account their capacity of integration in general practitioners’ daily practice. This selection was completed by a mathematical approach based on an ascending process on a regression model. A control sample, assumed to be "normal ageing" on the basis of current knowledge in general medicine, was then used. This sample was first carried out from a review of the literature and then from a K-means method that classified this sample into several groups. The statistical dependence of measured variables was modeled by a Gaussian copula (taking into account only linear correlations of pairs). A standardized biological age was defined explicitly from these correlation coefficients. The tails of marginal distribution (method of excess) were estimated to enhance the discriminating power of the model. Results suggest interesting possibilities for a biological ageing calculation, and the predictive score they provide, suitable for general practitioners’ daily practice. Its validation by a morbidity and mortality survey will constitute the final phase of this wor

INFLUENCE DES APPORTS EN GLUCIDES, LIPIDES, PROTEINES, VITAMINES ET OLIGOELEMENTS SUR LE METABOLISME OSSEUX

ST ETIENNE-BU Médecine (422182102) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Predicting hospital admissions with integer-valued time series

International audiencePrediction of seasonal epidemics have beenwidely treated in the medical literature, with various methods to forecast the future cases of a given disease, when it’s about infectious diseases: compartmental methods that forecast the number of persons at each state of the epidemic (susceptible, infected, resistant) are used(1), as well as methods based on time series (ARMA,ARCH,...)(2), this last method can be successful with large sample of data, assuming their normal distribution. Here, we propose to test time series for count data when the continuous time series are not adapted to predict health activity. The aim of this work is to predict the number of hospital admissions of future weeksat local scale, using methodsfor integer-valued time series:INAR(p) and INGARCH(p,q) methods(3–5), wehavealso test the autoregressive methods for continuous data

Forecasting emergency department admissions as a tool for improved health service

International audienceEmergency departments (ED) have difficulties coping with the rise of patients during seasonal epidemic crises. Particularly, during winter time, the influence of patients suffering from gastroenteritis, influenza and bronchiolitis lead to overcrowded emergency departments, and ultimately to patient rejection to other hospitals in the territory. The aim of the study is twofold, potential correlations between epidemic disease and environmental factors are sought and epidemics are then forecasted for classes of pathologies using the different correlation parameters that are found in the first part. The forecasting model serves as a mechanism to predict the incidence rate in ED and acts as the basis for a scheduling strategy to manage emergency departments. Historical data from various hospitals in the Rhone-Alpes region (France) as well as epidemic data collected from generalist physicians are used in the study. Environmental data of air pollutants and meteorological data are geographically matched with ED and used to extract potential correlation factors between them and the epidemics. These detailed historical meteorological data are obtained from the French national meteorological service. Thereafter, epidemic diseases of interest are modeled using a discretized compartmental epidemiological model. The epidemiological SEIR model allows us to track the evolution of the epidemics in four different categories of population (susceptible, exposed, infected and recovered). Additionally, a time series regression model is used to predict the time-varying infection rates of the epidemic model. Furthermore, a study on the number of individuals entering emergency departments following infections from the pathologies under analysis is performed. This last information allows us to study the effects of different epidemics on ED overcrowding and deploy a strategy to reduce waiting time of the patients in the ED. Waiting time reduction is done via the study of the interaction of the human resources of the ED. A scheduling strategy is then devised to organize the working hours of the different resources (physicians and nurses) according to the predictions made by the epidemic model under various constraints. Considering the multi-factor interaction of epidemics, we are able to devise an epidemic model that forecasts the infection peaks and use it to dynamically act changes in a health institution and thus reduce overcrowding during epidemic seasons. Under the hypotheses defined for the scheduling problem, the model gives us the optimal distribution of shifts for ED employees in front of stochastic demand patterns. The solution is obtained in only a few seconds for over 100 scenarios and the overall waiting time for the patients is significantly reduced compared to the solution obtained by fixing the shifts to what is currently practiced. Once the different factors affecting epidemics are determined, the epidemic model coupled with a statistical time series regression model allows us to get an accurate weekly forecast of the epidemics. As epidemics have a strong impact on overcrowding ED during the winter seasons, the forecast also forms the basis for an overcrowding reduction strategy that takes into account the key resources in the ED and reacts dynamically to changes in the estimated incidence

How We Can Reap the Full Benefit of Teleconsultations: Economic Evaluation Combined With a Performance Evaluation Through a Discrete-Event Simulation

Background In recent years, the rapid development of information and communications technology enabled by innovations in videoconferencing solutions and the emergence of connected medical devices has contributed to expanding the scope of application and expediting the development of telemedicine. Objective This study evaluates the use of teleconsultations (TCs) for specialist consultations at hospitals in terms of costs, resource consumption, and patient travel time. The key feature of our evaluation framework is the combination of an economic evaluation through a cost analysis and a performance evaluation through a discrete-event simulation (DES) approach. Methods Three data sets were used to obtain detailed information on the characteristics of patients, characteristics of patients' residential locations, and usage of telehealth stations. A total of 532 patients who received at least one TC and 18,559 patients who received solely physical consultations (CSs) were included in the initial sample. The TC patients were recruited during a 7-month period (ie, 2020 data) versus 19 months for the CS patients (ie, 2019 and 2020 data). A propensity score matching procedure was applied in the economic evaluation. To identify the best scenarios for reaping the full benefits of TCs, various scenarios depicting different population types and deployment strategies were explored in the DES model. Associated break-even levels were calculated. Results The results of the cost evaluation reveal a higher cost for the TC group, mainly induced by higher volumes of (tele)consultations per patient and the substantial initial investment required for TC equipment. On average, the total cost per patient over 298 days of follow-up was \texteuro 356.37 (US \392) per TC patient and \texteuro 305.18 (US \336) per CS patient. However, the incremental cost of TCs was not statistically significant: \texteuro 356.37 \textendash \texteuro 305.18 = \texteuro 51.19 or US \392 \textendash US \336 = US \56 (95% CI \textendash 35.99 to 114.25; P=.18). Sensitivity analysis suggested heterogeneous economic profitability levels within subpopulations and based on the intensity of use of TC solutions. In fact, the DES model results show that TCs could be a cost-saving strategy in some cases, depending on population characteristics, the amortization speed of telehealth equipment, and the locations of telehealth stations. Conclusions The use of TCs has the potential to lead to a major organizational change in the health care system in the near future. Nevertheless, TC performance is strongly related to the context and deployment strategy involved