Related Experiment Video

Updated: Jan 25, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

An Approach for Data Mining of Electronic Health Record Data for Suicide Risk Management: Database Analysis for

Sofian Berrouiguet^1,2,3,4, Romain Billot⁴, Mark Erik Larsen⁵

¹Adult Psychiatry, Brest Medical University Hospital at Bohars, Brest, France.

JMIR Mental Health

|May 9, 2019

Abstract

Background:

In an electronic health context, combining traditional structured clinical assessment methods and routine electronic health-based data capture may be a reliable method to build a dynamic clinical decision-support system (CDSS) for suicide prevention.

Objective:

The aim of this study was to describe the data mining module of a Web-based CDSS and to identify suicide repetition risk in a sample of suicide attempters.

Methods:

We analyzed a database of 2802 suicide attempters. Clustering methods were used to identify groups of similar patients, and regression trees were applied to estimate the number of suicide attempts among these patients.

Results:

We identified 3 groups of patients using clustering methods. In addition, relevant risk factors explaining the number of suicide attempts were highlighted by regression trees.

Conclusions:

Data mining techniques can help to identify different groups of patients at risk of suicide reattempt. The findings of this study can be combined with Web-based and smartphone-based data to improve dynamic decision making for clinicians.

Keywords:

clinical decision support system data mining electronic health mobile phone prevention suicide suicide attempts

More Related Videos

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

Published on: April 13, 2021

Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management

Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management

Published on: June 23, 2023

Related Concept Videos

Data Reporting and Recording

Data Reporting and Recording

Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...

Statistical Software for Data Analysis and Clinical Trials

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...

Analysis of Population Pharmacokinetic Data

Analysis of Population Pharmacokinetic Data

Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...

How Data are Classified: Numerical Data

How Data are Classified: Numerical Data

Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...

Articles linked to this work by shared authors, journal, and citation graph.

Interpretable Topic Modeling of Spontaneous Speech in Depression Using Large Language Models: Multilingual Four-Cohort Study.

JMIR mental health·2026

Prescription Trends for Bipolar Disorder With and Without Comorbid Substance Use and Anxiety Disorders: A Global Bipolar Cohort Collaborative Study.

Bipolar disorders·2026

Epigenetic Age Accelerations and the Clinical Presentation of Bipolar Disorders: A Latent Profile Analysis in the FACE-BD Sample.

Bipolar disorders·2026

Use of a Conversational Agent for Training Mental Health Professionals in Suicide Safety Planning: Pilot Feasibility and Acceptability Study.

JMIR mental health·2026

Intranasal Esketamine Versus Other Pharmacological Strategies in Treatment-Resistant Depression with High Suicide Risk: A Six-Month Naturalistic Study.

Clinics and practice·2026

Designing interventions guided by digital phenotype and pharmacogenetics in Spain for suicidal behaviour based on retrospective data: the multicentre SMARTomicS study protocol.

BMJ open·2026

See all related articles