A Knowledge-Modeling Approach to Integrate Multiple Clinical Practice Guidelines to Provide Evidence-Based Clinical Decision Support for Managing Comorbid Conditions

2017 ◽  
Vol 41 (12) ◽  
Author(s):  
Samina Abidi
Keyword(s):  
Clinical Practice ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Practice Guidelines ◽  
Practice Guidelines ◽  
Clinical Decision ◽  
Evidence Based ◽  
Comorbid Conditions ◽  
Knowledge Modeling ◽  
Modeling Approach

scholarly journals MP39: Characteristics of clinical decision support tools that impact physician behaviour: a systematic review and meta-analysis

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S55-S55
Author(s):  
K. A. Memedovich ◽  
D. Grigat ◽  
L. Dowsett ◽  
D. Lorenzetti ◽  
J. E. Andruchow ◽  
...  
Keyword(s):  
Systematic Review ◽  
Clinical Practice ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Practice Guidelines ◽  
Practice Guidelines ◽  
Meta Analysis ◽  
Clinical Decision ◽  
Meta Regression ◽  
Physician Adherence

Introduction: Clinical decision support (CDS) has been implemented in many clinical settings in order to improve decision-making. Their potential to improve diagnostic accuracy and reduce unnecessary testing is well documented; however, their effectiveness in impacting physician practice in real world implementations has been limited by poor physician adherence. The objective of this systematic review and meta-regression was to establish the effectiveness of CDS tools on adherence and identify which characteristics of CDS tools increase physician use of and adherence. Methods: A systematic review and meta-analysis was conducted. MEDLINE, EMBASE, PsychINFO, the Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews were searched from inception to June 2017. Included studies examined CDS in a hospital setting, reported on physician adherence to or use of CDS, utilized a comparative study design, and reported primary data. All tool type was classified based on the Cochrane Effective Practice and Organization of Care (EPOC) classifications. Studies were stratified based on study design (RCT vs. observational). Meta-regression was completed to assess the different effect of characteristics of the tool (e.g. whether the tool was mandatory or voluntary, EPOC classifications). Results: A total of 3,359 candidate articles were identified. Seventy-two met inclusion criteria, of which 46 reported outcomes appropriate for meta-regression (5 RCTs and 41 observational studies). Overall, a trend of increased CDS use was found (pooled RCT OR: 1.36 [95% CI: 0.97-1.89]; pooled observational OR: 2.12 [95% CI: 1.75-2.56]).When type of tool is considered, clinical practice guidelines were superior compared to other interventions (p=.150). Reminders (p=.473) and educational interventions (p=.489) were less successful than other interventions. Multi-modal tools were not more successful that single interventions (p=.810). Lastly, voluntary tools may be supperior to than mandatory tools (p=.148). None of these results are statistically significant. Conclusion: CDS tools accompanied by a planned intervention increases physician utilization and adherence to the tool. Meta-regression found that clinical practice guidelines had the biggest impact on physician adherence although not statistically significant. Further research is required to understand the most effective intervention to maximize physician utilization of CDS tools.

Formalizing clinical practice guideline for clinical decision support systems

2016 ◽  
Vol 23 (2) ◽  
pp. 146-156 ◽  
Author(s):  
Wessam Gad El-Rab ◽  
Osmar R Zaïane ◽  
Mohammad El-Hajj
Keyword(s):  
Clinical Practice ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Practice Guidelines ◽  
Practice Guidelines ◽  
Clinical Practice Guideline ◽  
Practice Guideline ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Clinical Knowledge

Clinical practice guidelines are valuable sources of clinical knowledge for healthcare professionals. However, the passive dissemination of clinical practice guidelines like publishing in medical journals is ineffective in changing clinical practice behaviour. In this work, we proposed a framework to help adopting an active clinical practice guideline dissemination approach by automatically extracting clinical knowledge from clinical practice guidelines into a clinical decision support system–friendly format. The proposed framework is intended to help human modellers by automating some of the manual formalization activities in order to minimize their manual effort. We evaluated our framework using all recommendations from two clinical practice guidelines produced by the Scottish Intercollegiate Guidelines Network: the ‘Management of lung cancer’ clinical practice guideline and the ‘Management of chronic pain’ clinical practice guideline. We conclude that the proposed framework can be effectively used to formalize drug and procedure recommendation in clinical contexts.

scholarly journals Comparing a Mobile Decision Support System Versus the Use of Printed Materials for the Implementation of an Evidence-Based Recommendation: Protocol for a Qualitative Evaluation (Preprint)

2018 ◽  
Author(s):  
Jhon Camacho ◽  
Ana María Medina Ch. ◽  
Zach Landis-Lewis ◽  
Gerald Douglas ◽  
Richard Boyce
Keyword(s):  
Clinical Practice ◽  
Decision Support ◽  
Clinical Practice Guidelines ◽  
Practice Guidelines ◽  
Mobile App ◽  
Second Phase ◽  
Evidence Based ◽  
Clinical Algorithm ◽  
Qualitative Evidence ◽  
Printed Materials

BACKGROUND The distribution of printed materials is the most frequently used strategy to disseminate and implement clinical practice guidelines, although several studies have shown that the effectiveness of this approach is modest at best. Nevertheless, there is insufficient evidence to support the use of other strategies. Recent research has shown that the use of computerized decision support presents a promising approach to address some aspects of this problem. OBJECTIVE The aim of this study is to provide qualitative evidence on the potential effect of mobile decision support systems to facilitate the implementation of evidence-based recommendations included in clinical practice guidelines. METHODS We will conduct a qualitative study with two arms to compare the experience of primary care physicians while they try to implement an evidence-based recommendation in their clinical practice. In the first arm, we will provide participants with a printout of the guideline article containing the recommendation, while in the second arm, we will provide participants with a mobile app developed after formalizing the recommendation text into a clinical algorithm. Data will be collected using semistructured and open interviews to explore aspects of behavioral change and technology acceptance involved in the implementation process. The analysis will be comprised of two phases. During the first phase, we will conduct a template analysis to identify barriers and facilitators in each scenario. Then, during the second phase, we will contrast the findings from each arm to propose hypotheses about the potential impact of the system. RESULTS We have formalized the narrative in the recommendation into a clinical algorithm and have developed a mobile app. Data collection is expected to occur during 2018, with the first phase of analysis running in parallel. The second phase is scheduled to conclude in July 2019. CONCLUSIONS Our study will further the understanding of the role of mobile decision support systems in the implementation of clinical practice guidelines. Furthermore, we will provide qualitative evidence to aid decisions made by low- and middle-income countries’ ministries of health about investments in these technologies.

Clinical Practice Guidelines: What Are They? Where Are They? How Good Are They?

2009 ◽  
Vol 28 (5) ◽  
pp. 343-350 ◽  
Author(s):  
Joan Renaud Smith ◽  
Ann Donze
Keyword(s):  
Clinical Practice ◽  
Clinical Practice Guidelines ◽  
Practice Guidelines ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Health Care Team ◽  
Decision Making Process ◽  
Evidence Based ◽  
Practice Setting ◽  
Team Members

PREVIOUS COLUMNS HAVE FOCUSED on utilizing evidence-based practice to incorporate the best evidence into clinical practice. This column builds upon that knowledge and describes a specific type of presynthesized evidence meant to guide and inform practice: clinical practice guidelines (CPGs). Clinical practice guidelines have been in existence for years, and their development is based on the desire to move research into practice and promote consistency among practitioners.1 Clinical practice guidelines are tools for health care team members to use to enhance their knowledge and skill in integrating evidence into the clinical decision making process. This column defines CPGs and the significance they have in the practice setting and provides tools and resources necessary to locate, develop, and critically appraise them.

scholarly journals Clinical Decision Support Systems for Comorbidity: Architecture, Algorithms, and Applications

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Aihua Fan ◽  
Di Lin ◽  
Yu Tang
Keyword(s):  
Clinical Practice ◽  
Decision Support ◽  
Clinical Decision Support ◽  
System Performance ◽  
Clinical Decision Support System ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
The Other ◽  
Comorbid Conditions ◽  
High Level

In this paper, we present the design of a clinical decision support system (CDSS) for monitoring comorbid conditions. Specifically, we address the architecture of a CDSS by characterizing it from three layers and discuss the algorithms in each layer. Also we address the applications of CDSSs in a few real scenarios and analyze the accuracy of a CDSS in consideration of the potential conflicts when using multiple clinical practice guidelines concurrently. Finally, we compare the system performance in our design with that in the other design schemes. Our study shows that our proposed design can achieve a clinical decision in a shorter time than the other designs, while ensuring a high level of system accuracy.

scholarly journals Usefulness of Cochrane Reviews in Clinical Guideline Development—A Survey of 585 Recommendations

2022 ◽  
Vol 19 (2) ◽  
pp. 685
Author(s):  
Christoffer Bruun Korfitsen ◽  
Marie-Louise Kirkegaard Mikkelsen ◽  
Anja Ussing ◽  
Karen Christina Walker ◽  
Jeanett Friis Rohde ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Clinical Practice Guidelines ◽  
Practice Guidelines ◽  
Health Authority ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Evidence Based ◽  
Cochrane Reviews ◽  
Danish Health

The Danish Health Authority develops clinical practice guidelines to support clinical decision-making based on the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system and prioritizes using Cochrane reviews. The objective of this study was to explore the usefulness of Cochrane reviews as a source of evidence in the development of clinical recommendations. Evidence-based recommendations in guidelines published by the Danish Health Authority between 2014 and 2021 were reviewed. For each recommendation, it was noted if and how Cochrane reviews were utilized. In total, 374 evidence-based recommendations and 211 expert consensus recommendations were published between 2014 and 2021. Of the 374 evidence-based recommendations, 106 included evidence from Cochrane reviews. In 28 recommendations, all critical and important outcomes included evidence from Cochrane reviews. In 36 recommendations, a minimum of all critical outcomes included evidence from Cochrane reviews, but not all important outcomes. In 33 recommendations, some but not all critical outcomes included evidence from Cochrane reviews. Finally, in nine recommendations, some of the important outcomes included evidence from Cochrane reviews. In almost one-third of the evidence-based recommendations, Cochrane reviews were used to inform clinical recommendations. This evaluation should inform future evaluations of Cochrane review uptake in clinical practice guidelines concerning outcomes important for clinical decision-making.

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