Evidence map›Paper›PMID 29233155›Full record

ArticleBMC medical informatics and decision making2017

A meta-model for computer executable dynamic clinical safety checklists.

Shan Nan, Pieter Van Gorp, Xudong Lu, Uzay Kaymak, Hendrikus Korsten, Richard Vdovjak, Huilong Duan

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Digital Cognitive Aids to Support Adaptation of Surgical Processes to COVID-19 Protective Policies.IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA) · 2020
    Article
  6. Toward Improving Surgical Outcomes by Incorporating Cognitive Load Measurement into Process-Driven Guidance.Software Engineering in Healthcare Systems (SEHS), IEEE/ACM International Workshop on · 2018
    Article
  7. Process Driven Guidance for Complex Surgical Procedures.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018
    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

7 authors.

Shan NanSchool of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China.
Pieter Van GorpSchool of Industrial Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Xudong LuSchool of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China. lvxd@zju.edu.cn.ORCID http://orcid.org/0000-0001-7658-5250
Uzay KaymakSchool of Industrial Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Hendrikus KorstenSchool of Industrial Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Richard VdovjakPhilips Research Europe, Eindhoven, The Netherlands.
Huilong DuanSchool of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China.

Funding

Chinese National Science and Technology Major Project 2016YFC0901703
6 · The paper itself

Abstract

backgroundSafety checklist is a type of cognitive tool enforcing short term memory of medical workers with the purpose of reducing medical errors caused by overlook and ignorance. To facilitate the daily use of safety checklists, computerized systems embedded in the clinical workflow and adapted to patient-context are increasingly developed. However, the current hard-coded approach of implementing checklists in these systems increase the cognitive efforts of clinical experts and coding efforts for informaticists. This is due to the lack of a formal representation format that is both understandable by clinical experts and executable by computer programs.

methodsWe developed a dynamic checklist meta-model with a three-step approach. Dynamic checklist modeling requirements were extracted by performing a domain analysis. Then, existing modeling approaches and tools were investigated with the purpose of reusing these languages. Finally, the meta-model was developed by eliciting domain concepts and their hierarchies. The feasibility of using the meta-model was validated by two case studies. The meta-model was mapped to specific modeling languages according to the requirements of hospitals.

resultsUsing the proposed meta-model, a comprehensive coronary artery bypass graft peri-operative checklist set and a percutaneous coronary intervention peri-operative checklist set have been developed in a Dutch hospital and a Chinese hospital, respectively. The result shows that it is feasible to use the meta-model to facilitate the modeling and execution of dynamic checklists.

conclusionsWe proposed a novel meta-model for the dynamic checklist with the purpose of facilitating creating dynamic checklists. The meta-model is a framework of reusing existing modeling languages and tools to model dynamic checklists. The feasibility of using the meta-model is validated by implementing a use case in the system.

Indexed as

HospitalsModels, OrganizationalWorkflowChecklistCoronary Artery BypassHumansMedical ErrorsPatient SafetyPercutaneous Coronary InterventionBPMNChecklistDroolsGASTONGLIFMetamodel

Identifiers

PMID29233155
PMCPMC5727863

What OpenQuestion 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 OpenQuestion graph.