Evidence map›Paper›PMID 38509500›Full record

ArticleBMC psychiatry2024

Developing a clinical decision support system software prototype that assists in the management of patients with self-harm in the emergency department: protocol of the PERMANENS project.

Philippe Mortier, Franco Amigo, Madhav Bhargav, Susana Conde, Montse Ferrer, Oskar Flygare, Busenur Kizilaslan, Laura Latorre Moreno, Angela Leis, Miguel Angel Mayer and 11 more

Abstract read
In one paragraph

Article in BMC psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Individual- and population-level associations of mental disorders with intentional self-harm.European psychiatry : the journal of the Association of European Psychiatrists · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Philippe MortierHospital del Mar Research Institute, Barcelona Biomedical Research Park (PRBB), Carrer Doctor Aiguader, 88, 08003, Barcelona, Spain. pmortier@researchmar.net.
Franco AmigoHospital del Mar Research Institute, Barcelona Biomedical Research Park (PRBB), Carrer Doctor Aiguader, 88, 08003, Barcelona, Spain.
Madhav BhargavSchool of Public Health & National Suicide Research Foundation, University College Cork, Cork, Ireland.
Susana CondeHospital del Mar Research Institute, Barcelona Biomedical Research Park (PRBB), Carrer Doctor Aiguader, 88, 08003, Barcelona, Spain.
Montse FerrerHospital del Mar Research Institute, Barcelona Biomedical Research Park (PRBB), Carrer Doctor Aiguader, 88, 08003, Barcelona, Spain.
Oskar FlygareCentre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Sweden.
Busenur KizilaslanNational Centre for Suicide Research and Prevention, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Laura Latorre MorenoHospital del Mar Research Institute, Barcelona Biomedical Research Park (PRBB), Carrer Doctor Aiguader, 88, 08003, Barcelona, Spain.
Angela LeisResearch Programme on Biomedical Informatics (GRIB), Hospital del Mar Research Institute, Barcelona, Spain.
Miguel Angel MayerResearch Programme on Biomedical Informatics (GRIB), Hospital del Mar Research Institute, Barcelona, Spain.
Víctor Pérez-SolaNeuropsychiatry and Drug Addiction Institute, Barcelona MAR Health Park Consortium PSMAR, Barcelona, Spain.
Ana Portillo-Van DiestHospital del Mar Research Institute, Barcelona Biomedical Research Park (PRBB), Carrer Doctor Aiguader, 88, 08003, Barcelona, Spain.
Juan Manuel Ramírez-AnguitaResearch Programme on Biomedical Informatics (GRIB), Hospital del Mar Research Institute, Barcelona, Spain.
Ferran SanzResearch Programme on Biomedical Informatics (GRIB), Hospital del Mar Research Institute, Barcelona, Spain.
Gemma VilagutHospital del Mar Research Institute, Barcelona Biomedical Research Park (PRBB), Carrer Doctor Aiguader, 88, 08003, Barcelona, Spain.
Jordi AlonsoHospital del Mar Research Institute, Barcelona Biomedical Research Park (PRBB), Carrer Doctor Aiguader, 88, 08003, Barcelona, Spain.
Lars MehlumNational Centre for Suicide Research and Prevention, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Ella ArensmanSchool of Public Health & National Suicide Research Foundation, University College Cork, Cork, Ireland.
Johan BjurebergCentre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Sweden.
Manuel PastorResearch Programme on Biomedical Informatics (GRIB), Hospital del Mar Research Institute, Barcelona, Spain.
Ping QinNational Centre for Suicide Research and Prevention, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

Funding

CIBER of Epidemiology & Public Health CIBERESP; CB06/02/0046Fundación la Marató de TV3 202220-30-31Instituto de Salud Carlos III (ISCIII) and by the European Union NextGenerationEU, Mecanismo para la Recuperación y la Resiliencia AC22/00006; AC22/00045ISCIII and co-funded by the European Union PI22/00107ISCIII-FSE Miguel Servet co-funded by the European Social Fund Plus ESF+; CP21/00078PFIS ISCIII FI23/00004the Health Research Board Ireland ERAPERMED2022the Research Council of Norway project no. 342386the Secretaria d'Universitats i Recerca del Departament d'Economia i Coneixement of the Generalitat de Catalunya AGAUR 2021 SGR 00624the Swedish Innovation Agency no. 2022-00549
6 · The paper itself

Abstract

backgroundSelf-harm presents a significant public health challenge. Emergency departments (EDs) are crucial healthcare settings in managing self-harm, but clinician uncertainty in risk assessment may contribute to ineffective care. Clinical Decision Support Systems (CDSSs) show promise in enhancing care processes, but their effective implementation in self-harm management remains unexplored.

methodsPERMANENS comprises a combination of methodologies and study designs aimed at developing a CDSS prototype that assists clinicians in the personalized assessment and management of ED patients presenting with self-harm. Ensemble prediction models will be constructed by applying machine learning techniques on electronic registry data from four sites, i.e., Catalonia (Spain), Ireland, Norway, and Sweden. These models will predict key adverse outcomes including self-harm repetition, suicide, premature death, and lack of post-discharge care. Available registry data include routinely collected electronic health record data, mortality data, and administrative data, and will be harmonized using the OMOP Common Data Model, ensuring consistency in terminologies, vocabularies and coding schemes. A clinical knowledge base of effective suicide prevention interventions will be developed rooted in a systematic review of clinical practice guidelines, including quality assessment of guidelines using the AGREE II tool. The CDSS software prototype will include a backend that integrates the prediction models and the clinical knowledge base to enable accurate patient risk stratification and subsequent intervention allocation. The CDSS frontend will enable personalized risk assessment and will provide tailored treatment plans, following a tiered evidence-based approach. Implementation research will ensure the CDSS' practical functionality and feasibility, and will include periodic meetings with user-advisory groups, mixed-methods research to identify currently unmet needs in self-harm risk assessment, and small-scale usability testing of the CDSS prototype software. DISCUSSION: Through the development of the proposed CDSS software prototype, PERMANENS aims to standardize care, enhance clinician confidence, improve patient satisfaction, and increase treatment compliance. The routine integration of CDSS for self-harm risk assessment within healthcare systems holds significant potential in effectively reducing suicide mortality rates by facilitating personalized and timely delivery of effective interventions on a large scale for individuals at risk of suicide.

Indexed as

Decision Support Systems, ClinicalSelf-Injurious BehaviorAftercareEmergency Service, HospitalHumansPatient DischargeSoftwareSystematic Reviews as TopicClinical decision support systemHospital Emergency ServiceIntentional self-harmKnowledge bases user-Centred Design.Machine learningRisk AssessmentRoutinely Collected Health dataSuicide

Identifiers

PMID38509500
PMCPMC10956300

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.