Clinical expertise and decision making: An overview of bias in clinical practice.

2016 ◽  
pp. 23-60 ◽  
Author(s):  
Jeffrey J. Magnavita ◽  
Scott O. Lilienfeld
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Clinical Expertise

scholarly journals Judgment and decision-making in clinical dentistry

2020 ◽  
Vol 48 (11) ◽  
pp. 030006052097287
Author(s):  
Liviu Feller ◽  
Johan Lemmer ◽  
Mbulaheni Simon Nemutandani ◽  
Raoul Ballyram ◽  
Razia Abdool Gafaar Khammissa
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Knowledge Base ◽  
Clinical Judgment ◽  
Judgment And Decision Making ◽  
Data Driven ◽  
Evidence Based ◽  
Clinical Expertise ◽  
Statistical Approaches ◽  
Conferences And Congresses

The development of clinical judgment and decision-making skills is complex, requiring clinicians—whether students, novices, or experienced practitioners—to correlate information from their own experience; from discussions with colleagues; from attending professional meetings, conferences and congresses; and from studying the current literature. Feedback from treated cases will consolidate retention in memory of the complexities and management of past cases, and the conversion of this knowledge base into daily clinical practice. The purpose of this narrative review is to discuss factors related to clinical judgment and decision-making in clinical dentistry and how both narrative, intuitive, evidence-based data-driven information and statistical approaches contribute to the global process of gaining clinical expertise.

What Does Evidence-Based Practice Mean to You? A Follow-Up Study Examining School-Based Speech-Language Pathologists' Perspectives on Evidence-Based Practice

2020 ◽  
Vol 29 (2) ◽  
pp. 688-704
Author(s):  
Katrina Fulcher-Rood ◽  
Anny Castilla-Earls ◽  
Jeff Higginbotham
Keyword(s):  
Clinical Practice ◽  
Research Evidence ◽  
Evidence Based Practice ◽  
Evidence Based ◽  
Clinical Expertise ◽  
Speech Language Pathologists ◽  
School Based ◽  
Research Findings ◽  
Ebp Implementation

Purpose The current investigation is a follow-up from a previous study examining child language diagnostic decision making in school-based speech-language pathologists (SLPs). The purpose of this study was to examine the SLPs' perspectives regarding the use of evidence-based practice (EBP) in their clinical work. Method Semistructured phone interviews were conducted with 25 school-based SLPs who previously participated in an earlier study by Fulcher-Rood et al. 2018). SLPs were asked questions regarding their definition of EBP, the value of research evidence, contexts in which they implement scientific literature in clinical practice, and the barriers to implementing EBP. Results SLPs' definitions of EBP differed from current definitions, in that SLPs only included the use of research findings. SLPs seem to discuss EBP as it relates to treatment and not assessment. Reported barriers to EBP implementation were insufficient time, limited funding, and restrictions from their employment setting. SLPs found it difficult to translate research findings to clinical practice. SLPs implemented external research evidence when they did not have enough clinical expertise regarding a specific client or when they needed scientific evidence to support a strategy they used. Conclusions SLPs appear to use EBP for specific reasons and not for every clinical decision they make. In addition, SLPs rely on EBP for treatment decisions and not for assessment decisions. Educational systems potentially present other challenges that need to be considered for EBP implementation. Considerations for implementation science and the research-to-practice gap are discussed.

An introduction to advance care planning: practice at the frontline

2018 ◽  
Author(s):  
Anjali Mullick ◽  
Jonathan Martin
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Communication Skills ◽  
Advance Care Planning ◽  
Use Case ◽  
Care Planning ◽  
Practical Advice ◽  
Future Care ◽  
Case Vignettes ◽  
Advance Care

Advance care planning (ACP) is a process of formal decision-making that aims to help patients establish decisions about future care that take effect when they lose capacity. In our experience, guidance for clinicians rarely provides detailed practical advice on how it can be successfully carried out in a clinical setting. This may create a barrier to ACP discussions which might otherwise benefit patients, families and professionals. The focus of this paper is on sharing our experience of ACP as clinicians and offering practical tips on elements of ACP, such as triggers for conversations, communication skills, and highlighting the formal aspects that are potentially involved. We use case vignettes to better illustrate the application of ACP in clinical practice.

scholarly journals Text Classification in Clinical Practice Guidelines Using Machine-Learning Assisted Pattern-Based Approach

2021 ◽  
Vol 11 (8) ◽  
pp. 3296
Author(s):  
Musarrat Hussain ◽  
Jamil Hussain ◽  
Taqdir Ali ◽  
Syed Imran Ali ◽  
Hafiz Syed Muhammad Bilal ◽  
...  
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Clinical Practice ◽  
Clinical Practice Guidelines ◽  
Practice Guidelines ◽  
Machine Learning Algorithms ◽  
Nominal Group ◽  
Specific Information ◽  
Matching Techniques ◽  
Disease Specific

Clinical Practice Guidelines (CPGs) aim to optimize patient care by assisting physicians during the decision-making process. However, guideline adherence is highly affected by its unstructured format and aggregation of background information with disease-specific information. The objective of our study is to extract disease-specific information from CPG for enhancing its adherence ratio. In this research, we propose a semi-automatic mechanism for extracting disease-specific information from CPGs using pattern-matching techniques. We apply supervised and unsupervised machine-learning algorithms on CPG to extract a list of salient terms contributing to distinguishing recommendation sentences (RS) from non-recommendation sentences (NRS). Simultaneously, a group of experts also analyzes the same CPG and extract the initial patterns “Heuristic Patterns” using a group decision-making method, nominal group technique (NGT). We provide the list of salient terms to the experts and ask them to refine their extracted patterns. The experts refine patterns considering the provided salient terms. The extracted heuristic patterns depend on specific terms and suffer from the specialization problem due to synonymy and polysemy. Therefore, we generalize the heuristic patterns to part-of-speech (POS) patterns and unified medical language system (UMLS) patterns, which make the proposed method generalize for all types of CPGs. We evaluated the initial extracted patterns on asthma, rhinosinusitis, and hypertension guidelines with the accuracy of 76.92%, 84.63%, and 89.16%, respectively. The accuracy increased to 78.89%, 85.32%, and 92.07% with refined machine-learning assistive patterns, respectively. Our system assists physicians by locating disease-specific information in the CPGs, which enhances the physicians’ performance and reduces CPG processing time. Additionally, it is beneficial in CPGs content annotation.

scholarly journals The use of multiple-criteria decision-making theory to measure students’ perceptions of high-fidelity simulation

2017 ◽  
Vol 3 (3) ◽  
pp. 88-93 ◽  
Author(s):  
Maureen Anne Jersby ◽  
Paul Van-Schaik ◽  
Stephen Green ◽  
Lili Nacheva-Skopalik
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Repeated Measures ◽  
Clinical Decision Making ◽  
Learning Experience ◽  
Clinical Decision ◽  
High Fidelity ◽  
High Fidelity Simulation ◽  
Initial Exposure ◽  
Repeated Measures Design

BackgroundHigh-Fidelity Simulation (HFS) has great potential to improve decision-making in clinical practice. Previous studies have found HFS promotes self-confidence, but its effectiveness in clinical practice has not been established. The aim of this research is to establish if HFS facilitates learning that informs decision-making skills in clinical practice using MultipleCriteria DecisionMaking Theory (MCDMT).MethodsThe sample was 2nd year undergraduate pre-registration adult nursing students.MCDMT was used to measure the students’ experience of HFS and how it developed their clinical decision-making skills. MCDMT requires characteristic measurements which for the learning experience were based on five factors that underpin successful learning, and for clinical decision-making, an analytical framework was used. The study used a repeated-measures design to take two measurements: the first one after the first simulation experience and the second one after clinical placement. Baseline measurements were obtained from academics. Data were analysed using the MCDMT tool.ResultsAfter their initial exposure to simulation learning, students reported that HFS provides a high-quality learning experience (87%) and supports all aspects of clinical decision-making (85%). Following clinical practice, the level of support for clinical decision-making remained at 85%, suggesting that students believe HFS promotes transferability of knowledge to the practice setting.ConclusionOverall, students report a high level of support for learning and developing clinical decision-making skills from HFS. However, there are no comparative data available from classroom teaching of similar content so it cannot be established if these results are due to HFS alone.

scholarly journals Plain Language Summary: Opioid Prescribing for Analgesia After Common Otolaryngology Operations

2021 ◽  
Vol 164 (4) ◽  
pp. 704-711
Author(s):  
Samantha Anne ◽  
Sandra A. Finestone ◽  
Allison Paisley ◽  
Taskin M. Monjur
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Clinical Practice ◽  
Pain Management ◽  
Health Care Providers ◽  
Clinical Practice Guideline ◽  
Shared Decision ◽  
Care Providers ◽  
Plain Language ◽  
Opioid Prescribing

This plain language summary explains pain management and careful use of opioids after common otolaryngology operations. The summary applies to patients of any age who need treatment for pain within 30 days after having a common otolaryngologic operation (having to do with the ear, nose, or throat). It is based on the 2021 “Clinical Practice Guideline: Opioid Prescribing for Analgesia After Common Otolaryngology Operations.” This guideline uses available research to best advise health care providers, and it includes recommendations that are explained in this summary. Recommendations may not apply to every patient but can be used to facilitate shared decision making between patients and their health care providers.

Between a logic of disruption and a logic of continuation: Negotiating the legitimacy of algorithms used in automated clinical decision-making

2021 ◽  
pp. 136345932199674
Author(s):  
Rikke Torenholt ◽  
Henriette Langstrup
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Patient Reported Outcomes ◽  
Patient Involvement ◽  
Clinical Decision Making ◽  
Diagnostic Procedures ◽  
Clinical Decision ◽  
Patient Reported ◽  
Pro Tools

In both popular and academic discussions of the use of algorithms in clinical practice, narratives often draw on the decisive potentialities of algorithms and come with the belief that algorithms will substantially transform healthcare. We suggest that this approach is associated with a logic of disruption. However, we argue that in clinical practice alongside this logic, another and less recognised logic exists, namely that of continuation: here the use of algorithms constitutes part of an established practice. Applying these logics as our analytical framing, we set out to explore how algorithms for clinical decision-making are enacted by political stakeholders, healthcare professionals, and patients, and in doing so, study how the legitimacy of delegating to an algorithm is negotiated and obtained. Empirically we draw on ethnographic fieldwork carried out in relation to attempts in Denmark to develop and implement Patient Reported Outcomes (PRO) tools – involving algorithmic sorting – in clinical practice. We follow the work within two disease areas: heart rehabilitation and breast cancer follow-up care. We show how at the political level, algorithms constitute tools for disrupting inefficient work and unsystematic patient involvement, whereas closer to the clinical practice, algorithms constitute a continuation of standardised and evidence-based diagnostic procedures and a continuation of the physicians’ expertise and authority. We argue that the co-existence of the two logics have implications as both provide a push towards the use of algorithms and how a logic of continuation may divert attention away from new issues introduced with automated digital decision-support systems.

scholarly journals Applying evidence-based medicine in general practice: a video-stimulated interview study on workplace-based observation

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Lisanne S. Welink ◽  
Kaatje Van Roy ◽  
Roger A. M. J. Damoiseaux ◽  
Hilde A. Suijker ◽  
Peter Pype ◽  
...  
Keyword(s):  
Decision Making ◽  
General Practice ◽  
Evidence Based Medicine ◽  
Evidence Based ◽  
Clinical Expertise ◽  
Stimulated Recall ◽  
Previous Discussion ◽  
Based Medicine ◽  
Stimulated Recall Interviews ◽  
Gp Training

Abstract Background Evidence-based medicine (EBM) in general practice involves applying a complex combination of best-available evidence, the patient’s preferences and the general practitioner’s (GP) clinical expertise in decision-making. GPs and GP trainees learn how to apply EBM informally by observing each other’s consultations, as well as through more deliberative forms of workplace-based learning. This study aims to gain insight into workplace-based EBM learning by investigating the extent to which GP supervisors and trainees recognise each other’s EBM behaviour through observation, and by identifying aspects that influence their recognition. Methods We conducted a qualitative multicentre study based on video-stimulated recall interviews (VSI) of paired GP supervisors and GP trainees affiliated with GP training institutes in Belgium and the Netherlands. The GP pairs (n = 22) were shown fragments of their own and their partner’s consultations and were asked to elucidate their own EBM considerations and the ones they recognised in their partner’s actions. The interview recordings were transcribed verbatim and analysed with NVivo. By comparing pairs who recognised each other’s considerations well with those who did not, we developed a model describing the aspects that influence the observer’s recognition of an actor’s EBM behaviour. Results Overall, there was moderate similarity between an actor’s EBM behaviour and the observer’s recognition of it. Aspects that negatively influence recognition are often observer-related. Observers tend to be judgemental, give unsolicited comments on how they would act themselves and are more concerned with the trainee-supervisor relationship than objective observation. There was less recognition when actors used implicit reasoning, such as mindlines (internalised, collectively reinforced tacit guidelines). Pair-related aspects also played a role: previous discussion of a specific topic or EBM decision-making generally enhanced recognition. Consultation-specific aspects played only a marginal role. Conclusions GP trainees and supervisors do not fully recognise EBM behaviour through observing each other’s consultations. To improve recognition of EBM behaviour and thus benefit from informal observational learning, observers need to be aware of automatic judgements that they make. Creating explicit learning moments in which EBM decision-making is discussed, can improve shared knowledge and can also be useful to unveil tacit knowledge derived from mindlines.

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