Dataset Information

A Laboratory Critical Incident and Error Reporting System for Experimental Biomedicine.

ABSTRACT: We here propose the implementation of a simple and effective method to enhance the quality of basic and preclinical academic research: critical incident reporting (CIR). CIR has become a standard in clinical medicine but to our knowledge has never been implemented in the context of academic basic research. We provide a simple, free, open-source software tool for implementing a CIR system in research groups, laboratories, or large institutions (LabCIRS). LabCIRS was developed, tested, and implemented in our multidisciplinary and multiprofessional neuroscience research department. It is accepted by all members of the department, has led to the emergence of a mature error culture, and has made the laboratory a safer and more communicative environment. Initial concerns that implementation of such a measure might lead to a "surveillance culture" that would stifle scientific creativity turned out to be unfounded.

SUBMITTER: Dirnagl U

PROVIDER: S-EPMC5131907 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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A Laboratory Critical Incident and Error Reporting System for Experimental Biomedicine.

Dirnagl Ulrich U Przesdzing Ingo I Kurreck Claudia C Major Sebastian S

PLoS biology 20161201 12

We here propose the implementation of a simple and effective method to enhance the quality of basic and preclinical academic research: critical incident reporting (CIR). CIR has become a standard in clinical medicine but to our knowledge has never been implemented in the context of academic basic research. We provide a simple, free, open-source software tool for implementing a CIR system in research groups, laboratories, or large institutions (LabCIRS). LabCIRS was developed, tested, and impleme ...[more]

PMID: 27906976

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Project description:IntroductionWhile there are guidelines for reporting on observational studies (eg, Strengthening the Reporting of Observational Studies in Epidemiology, Reporting of Studies Conducted Using Observational Routinely Collected Health Data Statement), estimation of causal effects from both observational data and randomised experiments (eg, A Guideline for Reporting Mediation Analyses of Randomised Trials and Observational Studies, Consolidated Standards of Reporting Trials, PATH) and on prediction modelling (eg, Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis), none is purposely made for deriving and validating models from observational data to predict counterfactuals for individuals on one or more possible interventions, on the basis of given (or inferred) causal structures. This paper describes methods and processes that will be used to develop a Reporting Guideline for Causal and Counterfactual Prediction Models (PRECOG).Methods and analysisPRECOG will be developed following published guidance from the Enhancing the Quality and Transparency of Health Research (EQUATOR) network and will comprise five stages. Stage 1 will be meetings of a working group every other week with rotating external advisors (active until stage 5). Stage 2 will comprise a systematic review of literature on counterfactual prediction modelling for biomedical sciences (registered in Prospective Register of Systematic Reviews). In stage 3, a computer-based, real-time Delphi survey will be performed to consolidate the PRECOG checklist, involving experts in causal inference, epidemiology, statistics, machine learning, informatics and protocols/standards. Stage 4 will involve the write-up of the PRECOG guideline based on the results from the prior stages. Stage 5 will seek the peer-reviewed publication of the guideline, the scoping/systematic review and dissemination.Ethics and disseminationThe study will follow the principles of the Declaration of Helsinki. The study has been registered in EQUATOR and approved by the University of Florida's Institutional Review Board (#202200495). Informed consent will be obtained from the working groups and the Delphi survey participants. The dissemination of PRECOG and its products will be done through journal publications, conferences, websites and social media.

Dataset Information

A Laboratory Critical Incident and Error Reporting System for Experimental Biomedicine.

Publications

A Laboratory Critical Incident and Error Reporting System for Experimental Biomedicine.

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