Markovian-based clustering of internet addiction trajectories

A hidden Markov clustering procedure is applied to a sample of n=185 longitudinal Internet Addiction Test trajectories collected in Switzerland. The best solution has 4 groups. This solution is related to the level of emotional wellbeing of the subjects, but no relation is observed with age, gender and BMI

Etude sur les trajectoires de prise en charge médicale des migrant-e-s issu-e-s du domaine de l’asile dans le Canton de Vaud : phase préparatoire

Ce rapport décrit la réalisation et les résultats de la phase préparatoire de l’étude sur les trajectoires de prise en charge médicale des requérants d'asile et des bénéficiaires de l'aide d'urgence dans le canton de Vaud qui sont enregistrés auprès de l’Etablissement vaudois d’accueil des migrants (EVAM) dans le Canton de Vauda. Cette étude aura pour objectifs de décrire les trajectoires et les coûts liés aux soins des migrant-e-s issu-e-s du domaine de l’asile (MDA) et de comparer les caractéristiques des MDA suivis par le Réseau de santé et migration (RESAMI) par rapport aux MDA suivis par le système de soins ordinaire. Il s'agit notamment de vérifier si le RESAMI suit les MDA les plus vulnérables, comme cela était prévu par le canton de Vaud. Cette étude servira également à identifier un nombre limité d'indicateurs facilitant le monitorage des activités du RESAMI à des fins de pilotage

Transforming a Patient Registry Into a Customized Data Set for the Advanced Statistical Analysis of Health Risk Factors and for Medication-Related Hospitalization Research: Retrospective Hospital Patient Registry Study.

Hospital patient registries provide substantial longitudinal data sets describing the clinical and medical health statuses of inpatients and their pharmacological prescriptions. Despite the multiple advantages of routinely collecting multidimensional longitudinal data, those data sets are rarely suitable for advanced statistical analysis and they require customization and synthesis. The aim of this study was to describe the methods used to transform and synthesize a raw, multidimensional, hospital patient registry data set into an exploitable database for the further investigation of risk profiles and predictive and survival health outcomes among polymorbid, polymedicated, older inpatients in relation to their medicine prescriptions at hospital discharge. A raw, multidimensional data set from a public hospital was extracted from the hospital registry in a CSV (.csv) file and imported into the R statistical package for cleaning, customization, and synthesis. Patients fulfilling the criteria for inclusion were home-dwelling, polymedicated, older adults with multiple chronic conditions aged ≥65 who became hospitalized. The patient data set covered 140 variables from 20,422 hospitalizations of polymedicated, home-dwelling older adults from 2015 to 2018. Each variable, according to type, was explored and computed to describe distributions, missing values, and associations. Different clustering methods, expert opinion, recoding, and missing-value techniques were used to customize and synthesize these multidimensional data sets. Sociodemographic data showed no missing values. Average age, hospital length of stay, and frequency of hospitalization were computed. Discharge details were recoded and summarized. Clinical data were cleaned up and best practices for managing missing values were applied. Seven clusters of medical diagnoses, surgical interventions, somatic, cognitive, and medicines data were extracted using empirical and statistical best practices, with each presenting the health status of the patients included in it as accurately as possible. Medical, comorbidity, and drug data were recoded and summarized. A cleaner, better-structured data set was obtained, combining empirical and best-practice statistical approaches. The overall strategy delivered an exploitable, population-based database suitable for an advanced analysis of the descriptive, predictive, and survival statistics relating to polymedicated, home-dwelling older adults admitted as inpatients. More research is needed to develop best practices for customizing and synthesizing large, multidimensional, population-based registries. RR2-10.1136/bmjopen-2019-030030