Incidence, criticality and typology of care-related adverse events in nursing homes based on initial epidemiological characteristics and possible prevention measures in France.

Knowledge of care-related adverse events in nursing homes in France is limited. An observational descriptive study was conducted in 25 nursing homes over a period of two weeks between 2016 and 2017. This study aimed to describe types of care-related adverse events and to assess their severity, the frequency with which they occurred, and their criticality. Eighty-six types of care-related adverse events, associated with 13 risk areas, were identified (31 of which were identified by an investigating physician). Of these types of events, 11 corresponded to an unacceptable level of criticality, and 13 were categorised as warranting surveillance. Efforts in nursing homes should focus on the different types of care-related adverse event: loss of or damage to a medical device, failure to administer medication, failure to coordinate between different establishments, shortfalls in planning and continuity of care, shortfalls in the information system, loss of or damage to laundry items, and unauthorised exit from the premises. Broad recommendations on preventing adverse events and improving nursing homes should be the subject of future study.

[Incidence, criticality and typology of care-related adverse event in nursing homes: first French epidemiological characteristics and prevention perspectives]. / Incidence, criticité et typologie des évènements indésirables en Ehpad : premières caractéristiques épidémiologiques françaises et perspectives de prévention.

Knowledge in France on the subject of care-related adverse events in the nursing home sector is sparse. An observational descriptive study was conducted in 25 nursing homes over a period of 2 weeks over periods of two weeks between 2016 and 2017. It aimed to describe the types of care-related adverse event, and to assess their seriousness, frequency of occurrence, and criticality. Eighty-six types of care-related adverse event belonging to 13 risk domains were identified (31 by the investigating physician). Among these types of event, 11 corresponded to an unacceptable level of criticality, and 13 were categorised as warranting surveillance. Efforts in nursing homes should focus on the various types of care-related adverse event: loss of or damage to a medical device; failure to administer a medication; failure to coordinate between structures; shortfalls in planning and care continuity; shortfalls in the information system; loss of or damage to laundry items; unplanned escapade. Recommendations on the main lines of prevention and improvement in nursing homes should be the subject of future study.

Associations between persistent organic pollutants and endometriosis: A multipollutant assessment using machine learning algorithms.

Endometriosis is a gynaecological disease characterised by the presence of endometriotic tissue outside of the uterus impacting a significant fraction of women of childbearing age. Evidence from epidemiological studies suggests a relationship between risk of endometriosis and exposure to some organochlorine persistent organic pollutants (POPs). However, these chemicals are numerous and occur in complex and highly correlated mixtures, and to date, most studies have not accounted for this simultaneous exposure. Linear and logistic regression models are constrained to adjusting for multiple exposures when variables are highly intercorrelated, resulting in unstable coefficients and arbitrary findings. Advanced machine learning models, of emerging use in epidemiology, today appear as a promising option to address these limitations. In this study, different machine learning techniques were compared on a dataset from a case-control study conducted in France to explore associations between mixtures of POPs and deep endometriosis. The battery of models encompassed regularised logistic regression, artificial neural network, support vector machine, adaptive boosting, and partial least-squares discriminant analysis with some additional sparsity constraints. These techniques were applied to identify the biomarkers of internal exposure in adipose tissue most associated with endometriosis and to compare model classification performance. The five tested models revealed a consistent selection of most associated POPs with deep endometriosis, including octachlorodibenzofuran, cis-heptachlor epoxide, polychlorinated biphenyl 77 or trans-nonachlor, among others. The high classification performance of all five models confirmed that machine learning may be a promising complementary approach in modelling highly correlated exposure biomarkers and their associations with health outcomes. Regularised logistic regression provided a good compromise between the interpretability of traditional statistical approaches and the classification capacity of machine learning approaches. Applying a battery of complementary algorithms may be a strategic approach to decipher complex exposome-health associations when the underlying structure is unknown.

[Incidence of adverse events associated with technical care and support in French nursing homes: the EHPAGE project]. / Incidence des événements indésirables associés aux actes de soins et d'accompagnement en Ehpad : projet EHPAGE.

A rise in the number of dependent elderly people has made nursing homes an important part of the French health system. Through the struggle against adverse events associated with treatments, the question of the residents' safety and wellbeing has been paramount. To get an estimation of the highest incidence rates of adverse events in nursing homes, we carried out a follow-up study on 536 residents over 15-day periods between November 2016 and May 2017 in 8 French nursing homes. Notifications by professionals coupled with explorations by an investigating physician helped evidence the different typologies and degrees of seriousness of treatment-related adverse events. The 149 treatment-related adverse events that were identified belonged to 13 risk domains. Four of these domains accounted for 60% of treatment-related adverse events: 'medication and medical provision', 'living environment', 'technical care and accompaniment', 'care organization and coordination'. Four treatment-related adverse events out of the 149 (2.7%) had a level of seriousness rated as 4; 16 (10.7%) had a seriousness level rated as 3. Finally, particular attention should be paid to suicide risk. These first results need to be corroborated, but they will help develop messages of prevention aimed at professionals.