Welcome to the 31st annual congress of the Swiss Society for Medical Informatics!

A warm welcome to the annual congress of our national society and to Swiss eHealth Summit!

From the lab to the field: the challenges of the take-off process for a bedside mobility app

The implementation of mobile phone apps for patient care in hospital settings requires careful consideration of many challenges. The authors developed and pilot-tested a mobile app to support nursing workflow at the bedside in their institution,

Automatic annotation of French medical narratives with SNOMED CT concepts

The preliminary annotation results are encouraging and confirm that semantic enrichment of patient-related narratives can be accomplished by hybrid NLP systems, heavily based on syntax and lexicosemantic resources.

De-identification of French medical narratives

In this work, a rule-based method for the de-identification of French free-text medical data using natural language processing (NLP) tools is presented.

Going beyond the relapse peak on social network smoking cessation programmes: ChatBot opportunities

Gamification and mHealth: a model to bolster cardiovascular disease self-management

Swiss Variant Interpretation Platform for Oncology (SVIP-O)

SVIP is an ambitious project to establish a Swiss one-stop shop for the interpretation of somatic variants, enabling faster and more robust prioritisation.

Opioid dependence and the use of analgesics in a Swiss teaching hospital

A recent population study of Swiss insurance claims between 2006 and 2013 showed marked increases in the use of opioids and other analgesics.

E-general consent: development and implementation of a nationwide harmonised interactive electronic general consent

The goal of this project is to develop the general consent process further for a more flexible and admission-independent electronic request.

Inpatients suffering from alcoholism automatically identified by electronic phenotyping

The authors developed an algorithm that automatically detects stays of AUD patients in structured clinical data.