Literature DB >> 28578757

Decision-making under pressure: medical errors in uncertain and dynamic environments.

Alicia M Zavala1, Gary E Day1, David Plummer2, Anita Bamford-Wade3.   

Abstract

Objective This paper provides a narrative overview of the literature concerning clinical decision-making processes when staff come under pressure, particularly in uncertain, dynamic and emergency situations. Methods Studies between 1980 and 2015 were analysed using a six-phase thematic analysis framework to achieve an in-depth understanding of the complex origins of medical errors that occur when people and systems are under pressure and how work pressure affects clinical performance and patient outcomes. Literature searches were conducted using a Summons Search Service platform; search criteria included a variety of methodologies, resulting in the identification of 95 papers relevant to the present review. Results Six themes emerged in the present narrative review using thematic analysis: organisational systems, workload, time pressure, teamwork, individual human factors and case complexity. This analysis highlights that clinical outcomes in emergency situations are the result of a variety of interconnecting factors. These factors may affect the ability of clinical staff in emergency situations to provide quality, safe care in a timely manner. Conclusions The challenge for researchers is to build the body of knowledge concerning the safe management of patients, particularly where clinicians are working under pressure. This understanding is important for developing pathways that optimise clinical decision making in uncertain and dynamic environments. What is known about the topic? Emergency departments (EDs) are characterised by high complexity, high throughput and greater uncertainty compared with routine hospital wards or out-patient situations, and the ED is therefore prone to unpredictable workflows and non-replicable conditions when presented with unique and complex cases. What does this paper add? Clinical decision making can be affected by pressures with complex origins, including organisational systems, workload, time constraints, teamwork, human factors and case complexity. Interactions between these factors at different levels of the decision-making process can increase the complexity of problems and the resulting decisions to be made. What are the implications for practitioners? The findings of the present study provide further evidence that consideration of medical errors should be seen primarily from a 'whole-of-system' perspective rather than as being primarily the responsibility of individuals. Although there are strategies in place in healthcare organisations to eliminate errors, they still occur. In order to achieve a better understanding of medical errors in clinical practice in times of uncertainty, it is necessary to identify how diverse pressures can affect clinical decisions, and how these interact to influence clinical outcomes.

Entities:  

Mesh:

Year:  2018        PMID: 28578757     DOI: 10.1071/AH16088

Source DB:  PubMed          Journal:  Aust Health Rev        ISSN: 0156-5788            Impact factor:   1.990


  11 in total

1.  Physicians under Pressure: Evidence from Antibiotics Prescribing in England.

Authors:  Thomas Allen; Dorte Gyrd-Hansen; Søren Rud Kristensen; Anne Sophie Oxholm; Line Bjørnskov Pedersen; Mario Pezzino
Journal:  Med Decis Making       Date:  2022-01-12       Impact factor: 2.583

2.  CADDIE2-evaluation of a clinical decision-support system for early detection of systemic inflammatory response syndrome in paediatric intensive care: study protocol for a diagnostic study.

Authors:  Antje Wulff; Sara Montag; Bianca Steiner; Michael Marschollek; Philipp Beerbaum; André Karch; Thomas Jack
Journal:  BMJ Open       Date:  2019-06-19       Impact factor: 2.692

3.  Collaboration and Satisfaction About Care Decisions in Team questionnaire-Psychometric testing of the Norwegian version, and hospital healthcare personnel perceptions across hospital units.

Authors:  Oddveig Reiersdal Aaberg; Marie Louise Hall-Lord; Sissel Iren Eikeland Husebø; Randi Ballangrud
Journal:  Nurs Open       Date:  2019-02-20

4.  Reducing medical error during a pandemic.

Authors:  A G C Hay-David; J B T Herron; P Gilling; A Miller; P A Brennan
Journal:  Br J Oral Maxillofac Surg       Date:  2020-04-11       Impact factor: 1.651

5.  A human factors intervention in a hospital - evaluating the outcome of a TeamSTEPPS program in a surgical ward.

Authors:  Oddveig Reiersdal Aaberg; Marie Louise Hall-Lord; Sissel Iren Eikeland Husebø; Randi Ballangrud
Journal:  BMC Health Serv Res       Date:  2021-02-03       Impact factor: 2.655

6.  Improving Emergency Department Patient-Physician Conversation Through an Artificial Intelligence Symptom-Taking Tool: Mixed Methods Pilot Observational Study.

Authors:  Justus Scheder-Bieschin; Bibiana Blümke; Erwin de Buijzer; Fabienne Cotte; Fabian Echterdiek; Júlia Nacsa; Marta Ondresik; Matthias Ott; Gregor Paul; Tobias Schilling; Anne Schmitt; Paul Wicks; Stephen Gilbert
Journal:  JMIR Form Res       Date:  2022-02-07

7.  Patients' Perceptions of Quality of Care: A Teamwork Intervention Study in a Surgical Ward.

Authors:  Marie Louise Hall-Lord; Randi Ballangrud
Journal:  SAGE Open Nurs       Date:  2022-02-08

8.  A Patient Outcomes-Driven Feedback Platform for Emergency Medicine Clinicians: Human-Centered Design and Usability Evaluation of Linking Outcomes Of Patients (LOOP).

Authors:  Alexandra T Strauss; Cameron Morgan; Christopher El Khuri; Becky Slogeris; Aria G Smith; Eili Klein; Matt Toerper; Anthony DeAngelo; Arnaud Debraine; Susan Peterson; Ayse P Gurses; Scott Levin; Jeremiah Hinson
Journal:  JMIR Hum Factors       Date:  2022-03-23

9.  Person- and job-specific factors of intuitive decision-making in clinical practice: results of a sample survey among Hungarian physicians and nurses.

Authors:  Gabor Ruzsa; Csenge Szeverenyi; Katalin Varga
Journal:  Health Psychol Behav Med       Date:  2020-03-23

10.  Monitoring Diagnostic Safety Risks in Emergency Departments: Protocol for a Machine Learning Study.

Authors:  Moein Enayati; Mustafa Sir; Xingyu Zhang; Sarah J Parker; Elizabeth Duffy; Hardeep Singh; Prashant Mahajan; Kalyan S Pasupathy
Journal:  JMIR Res Protoc       Date:  2021-06-14
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