scholarly journals Individual Reference Intervals for Personalized Interpretation of Clinical and Metabolomics Measurements

Author(s):  
Murih Pusparum ◽  
G&oumlkhan Ertaylan ◽  
Olivier Thas

The Population Reference Interval (PRI) refers to the range of outcomes that are expected in a healthy population for a clinical or a diagnostic measurement. This interval is widely used in daily clinical practice and is essential for assisting clinical decision making in diagnosis and treatment. In this study, we demonstrate that each individual indeed has a range for a given variable depending on personal biological traits. This Individual Reference Interval (IRI) can be calculated and be utilized in clinical practice, in combination with the PRI for improved decision making where multiple data points are present per variable. As calculating IRI requires several data points from the same individual to determine a personal range, here we introduce novel methodologies to obtain the correct estimates of IRI. We use Linear Quantile Mixed Models (LQMM) and Penalized Joint Quantile Models (PJQM) to estimate the IRI's upper and lower bounds. The estimates are obtained by considering both the within and between subjects' variations. We perform a simulation study designed to benchmark both methods' performance under different assumptions, resulted in PJQM giving a better empirical coverage than LQMM. Finally, both methods were evaluated on real-life data consisting of eleven clinical and metabolomics parameters from the VITO IAM Frontier study. The PJQM method also outperforms LQMM on its predictive accuracy in the real-life data setting. In conclusion, we introduce the concept of IRI and demonstrate two methodologies for calculating it to complement PRIs in clinical decision making.

2019 ◽  
Vol 43 (1 suppl 1) ◽  
pp. 513-524
Author(s):  
Álisson Oliveira dos Santos ◽  
Alexandre Sztajnberg ◽  
Tales Mota Machado ◽  
Daniel Magalhães Nobre ◽  
Adriano Neves de Paula e Souza ◽  
...  

ABSTRACT The medical education for clinical decision-making has undergone changes in recent years. Previously supported by printed material, problem solving in clinical practice has recently been aided by digital tools known as summaries platforms. Doctors and medical students have been using such tools from questions found in practice scenarios. These platforms have the advantage of high-quality, evidence-based and always up-to-date content. Its popularization was mainly due to the rise of the internet use and, more recently, of mobile devices such as tablets and smartphones, facilitating their use in clinical practice. Despite this platform is widely available, the most of them actually present several access barriers as costs, foreign language and not be able to Brazilian epidemiology. A free national platform of evidence-based medical summaries was proposed, using the crowdsourcing concept to resolve those barriers. Furthermore, concepts of gamification and content evaluation were implemented. Also, there is the possibility of evaluation by the users, who assigns note for each content created. The platform was built with modern technological tools and made available for web and mobile application. After development, an evaluation process was conducted by researchers to attest to the valid of content, usability, and user satisfying. Consolidated questionnaires and evaluation tools by the literature were applied. The process of developing the digital platform fostered interdisciplinarity, from the involvement of medical and information technology professionals. The work also allowed the reflection on the innovative educational processes, in which the learning from real life problems and the construction of knowledge in a collaborative way are integrated. The assessment results suggest that platform can be real alternative form the evidence-based medical decision-making.


2019 ◽  
Vol 43 (1 suppl 1) ◽  
pp. 513-524
Author(s):  
Álisson Oliveira dos Santos ◽  
Alexandre Sztajnberg ◽  
Tales Mota Machado ◽  
Daniel Magalhães Nobre ◽  
Adriano Neves de Paula e Souza ◽  
...  

ABSTRACT The medical education for clinical decision-making has undergone changes in recent years. Previously supported by printed material, problem solving in clinical practice has recently been aided by digital tools known as summaries platforms. Doctors and medical students have been using such tools from questions found in practice scenarios. These platforms have the advantage of high-quality, evidence-based and always up-to-date content. Its popularization was mainly due to the rise of the internet use and, more recently, of mobile devices such as tablets and smartphones, facilitating their use in clinical practice. Despite this platform is widely available, the most of them actually present several access barriers as costs, foreign language and not be able to Brazilian epidemiology. A free national platform of evidence-based medical summaries was proposed, using the crowdsourcing concept to resolve those barriers. Furthermore, concepts of gamification and content evaluation were implemented. Also, there is the possibility of evaluation by the users, who assigns note for each content created. The platform was built with modern technological tools and made available for web and mobile application. After development, an evaluation process was conducted by researchers to attest to the valid of content, usability, and user satisfying. Consolidated questionnaires and evaluation tools by the literature were applied. The process of developing the digital platform fostered interdisciplinarity, from the involvement of medical and information technology professionals. The work also allowed the reflection on the innovative educational processes, in which the learning from real life problems and the construction of knowledge in a collaborative way are integrated. The assessment results suggest that platform can be real alternative form the evidence-based medical decision-making.


2017 ◽  
Vol 3 (3) ◽  
pp. 88-93 ◽  
Author(s):  
Maureen Anne Jersby ◽  
Paul Van-Schaik ◽  
Stephen Green ◽  
Lili Nacheva-Skopalik

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.


2021 ◽  
Author(s):  
Carsten Vogt

AbstractThe uptake of the QbTest in clinical practice is increasing and has recently been supported by research evidence proposing its effectiveness in relation to clinical decision-making. However, the exact underlying process leading to this clinical benefit is currently not well established and requires further clarification. For the clinician, certain challenges arise when adding the QbTest as a novel method to standard clinical practice, such as having the skills required to interpret neuropsychological test information and assess for diagnostically relevant neurocognitive domains that are related to attention-deficit hyperactivity disorder (ADHD), or how neurocognitive domains express themselves within the behavioral classifications of ADHD and how the quantitative measurement of activity in a laboratory setting compares with real-life (ecological validity) situations as well as the impact of comorbidity on test results. This article aims to address these clinical conundrums in aid of developing a consistent approach and future guidelines in clinical practice.


Author(s):  
Rikke Torenholt ◽  
Henriette Langstrup

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.


2020 ◽  
Vol 14 ◽  
pp. 117954682095341 ◽  
Author(s):  
Todd C Villines ◽  
Mark J Cziraky ◽  
Alpesh N Amin

Real-world evidence (RWE) provides a potential rich source of additional information to the body of data available from randomized clinical trials (RCTs), but there is a need to understand the strengths and limitations of RWE before it can be applied to clinical practice. To gain insight into current thinking in clinical decision making and utility of different data sources, a representative sampling of US cardiologists selected from the current, active Fellows of the American College of Cardiology (ACC) were surveyed to evaluate their perceptions of findings from RCTs and RWE studies and their application in clinical practice. The survey was conducted online via the ACC web portal between 12 July and 11 August 2017. Of the 548 active ACC Fellows invited as panel members, 173 completed the survey (32% response), most of whom were board certified in general cardiology (n = 119, 69%) or interventional cardiology (n = 40, 23%). The survey results indicated a wide range of familiarity with and utilization of RWE amongst cardiologists. Most cardiologists were familiar with RWE and considered RWE in clinical practice at least some of the time. However, a significant minority of survey respondents had rarely or never applied RWE learnings in their clinical practice, and many did not feel confident in the results of RWE other than registry data. These survey findings suggest that additional education on how to assess and interpret RWE could help physicians to integrate data and learnings from RCTs and RWE to best guide clinical decision making.


CJEM ◽  
2020 ◽  
Vol 22 (S1) ◽  
pp. S106-S106
Author(s):  
C. Dmitriew ◽  
R. Ohle

Introduction: Acute aortic syndrome (AAS) is an uncommon, life-threatening emergency that is frequently misdiagnosed. The Canadian clinical practice guidelines for the diagnosis of AAS were developed in order to reduce the frequency of misdiagnoses and number of diagnostic tests. As part of the guidelines, a clinical decision aid was developed in order to facilitate clinician decision-making based on practice recommendations. The objective of this study was to identify barriers and facilitators among physicians to implementation of the decision aid. Methods: We conducted semi-structured interviews with emergency room physicians working at 5 sites distributed between urban academic and rural settings. We used purposive sampling, contacting ED physicians until data saturation was reached. Interview questions were designed to understand potential barriers and facilitators affecting the probability of decision aid uptake and accurate application of the tool. Two independent raters coded interview transcripts using an integrative approach to theme identification, combining an inductive approach to identification of themes within an organizing framework (Theoretical Domains Framework), discrepancies in coding were resolved through discussion until consensus was reached. Results: A majority of interviewees anticipated that the decision aid would support clinical decision making and risk stratification while reducing resource use and missed diagnoses. Facilitators identified included validation and publication of the guidelines as well as adoption by peers. Barriers to implementation and application of the tool included the fact that the use of D-dimer and knowledge of the rationale for its use in the investigation of AAS were not widespread. Furthermore, scoring components were, at times, out of alignment with clinician practices and understanding of risk factors. The complexity of the decision aid was also identified as a potential barrier to accurate use. Conclusion: Physicians were amenable to using the AAS decision aid to support clinical decision-making and to reduce resource use, particularly within rural contexts. Key barriers identified included the complexity of scoring and inclusion criteria, and the variable acceptance of D-dimer among clinicians. These barriers should be addressed prior to implementation of the decision aid during validation studies of the clinical practice guidelines.


2001 ◽  
Vol 19 (2) ◽  
pp. 594-595 ◽  
Author(s):  
Mark Somerfield ◽  
Aminah Jatoi ◽  
Phuong L. Nguyen ◽  
Shaji Kumar ◽  
Jeff Sloan ◽  
...  

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