Abstract 267: Case-Based CME Improves on Clinical Decision-Making in Non-ST Elevation Myocardial Infarction

2015 ◽  
Vol 8 (suppl_2) ◽  
Author(s):  
Amy Larkin ◽  
Michael LaCouture ◽  
Caroline Padbury
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
P Values ◽  
St Elevation ◽  
The Mean ◽  
Post Assessment ◽  
Grand Rounds ◽  
Assessment Questions ◽  
Case Based

Introduction: Evolving therapies and guideline recommendations to treat non-ST elevation myocardial infarction (NSTEMI) create clinical confusion. The educational and practice impact of a case-based design of CME were measured on clinical decision-making related to NSTEMI treatment. Methods: The continuing medical education (CME) activity was developed as an online case-based text activity modeled after the interactive grand rounds approach where clinicians make clinical decisions about treatment for a given patient. The activity targeted primary care physicians (PCPs) and cardiologists who manage patients experiencing a NSTEMI and focused on application of guideline recommendations. The effects of education were assessed using a linked pre-assessment/post-assessment study design that separated learners into 3 categories: improved (incorrect pre, correct post), reinforced (correct pre and post), and unaffected (incorrect post). For all questions combined, the McNemar’s chi-squared test was used to assess whether the mean post[[Unable to Display Character: &#8208;]]assessment score differed from the mean pre[[Unable to Display Character: &#8208;]]assessment score. P values are shown as a measure of significance; P values <.05 are statistically significant. Cohen’s D was used to calculate the effect size. The activity launched online on April 16, 2014 and data were collected through July 24, 2014. Results: 533 PCPs and 531 cardiologist completed both the pre- and post-assessment survey with a large overall effect size of 1.836 ( P <0.05) and 1.799 ( P<0 .05), respectively. PCPs Correct responses on post-assessment questions ranged between 62% and 292% higher after CME completion. While only 8 (2%) participants answered all 4 questions correctly on the pre-assessment, 296 (56%) answered them all correctly on the post-assessment. Between 33% and 63% of participants showed improvement post-educational intervention. Cardiologists Correct responses on post-assessment questions ranged between 34% and 249% higher after CME completion. While only 28 (5%) participants answered all 4 questions correctly on the pre-assessment, 430 (81%) answered them all correctly on the post-assessment. Between 26% and 65% of participants showed improvement after the educational intervention. Conclusion: Online case-based CME activities modeled after the interactive grand rounds approach prompted changes in clinical knowledge, showing that when effectively constructed, this methodology is an effective tool to improve clinical application of guidelines and clinical decision-making in NSTEMI. This interactive educational format should be applied to CME for future activities.

scholarly journals Quantifying the Impact of Patient-Specific Factors and Disease Severity on Clinical Decision Making in Cuff Tear Arthropathy: A Case-Based Survey

2019 ◽  
Vol 15 (3) ◽  
pp. 276-285
Author(s):  
Adam P. Schumaier ◽  
Yehia H. Bedeir ◽  
Joshua S. Dines ◽  
Keith Kenter ◽  
Lawrence V. Gulotta ◽  
...  
Keyword(s):  
Decision Making ◽  
Disease Severity ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Patient Specific ◽  
Cuff Tear Arthropathy ◽  
Cuff Tear ◽  
Specific Factors ◽  
The Impact ◽  
Case Based

scholarly journals Teaching Cognitive Biases in Clinical Decision Making: A Case-Based Discussion

MedEdPORTAL ◽  
2015 ◽  
Vol 11 (1) ◽  
Author(s):  
Keng Sheng Chew ◽  
Jeroen van Merrienboer ◽  
Steven Durning
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Cognitive Biases ◽  
Clinical Decision ◽  
Case Based

A decision theory overview and case-based discussion

2021 ◽  
Vol 13 (8) ◽  
pp. 320-324
Author(s):  
David Thom
Keyword(s):  
Decision Making ◽  
Decision Theory ◽  
Reliability Analysis ◽  
Clinical Case ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
Use Of Technology ◽  
Case Based

Paramedics make decisions as part of their everyday role but often, the theory behind clinical decision-making is not discussed in depth. This article explores the theories of decision-making as they apply to a clinical case. With the increasing use of technology in healthcare, the introduction of human reliability analysis is becoming more pertinent.

Diagnostic conversations: Clinical Decision Making in surgery – Part 1

Diagnosis ◽  
2014 ◽  
Vol 1 (1) ◽  
pp. 99-102 ◽  
Author(s):  
David Allan Watters ◽  
Spencer Wynyard Beasley ◽  
Wendy Crebbin
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Learning Opportunities ◽  
Clinical Scenario ◽  
Decision Making Processes ◽  
Expert Surgeon ◽  
Thinking Processes ◽  
Royal Australasian College ◽  
Case Based

AbstractSound and efficient decision making are hallmarks of an expert surgeon. Unfortunately, those experts are often unable to explain their thinking processes, or to teach their trainees and colleagues how they do it. Surgeons and staff of the Royal Australasian College of Surgeons worked together to develop a model to explain the processes around clinical decision making and used this understanding and knowledge to devise a Clinical Decision Making (CDM) training course. The surgical faculty ensure the model is applicable to specific surgical cases, as well as presenting a framework of how clinical decisions are made. Wendy targets the specific decision making processes that are occurring with each clinical scenario, and highlights some of the learning opportunities that they provide. The conversation in this paper models the kinds of case-based interactions which occur in the development and teaching of the CDM course.

scholarly journals Evaluation of a Novel Teleradiology Technology for Image-Based Distant Consultations: Applications in Neurosurgery

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1413
Author(s):  
Paulina Cewe ◽  
Gustav Burström ◽  
Ivan Drnasin ◽  
Marcus Ohlsson ◽  
Halldor Skulason ◽  
...  
Keyword(s):  
Decision Making ◽  
Data Storage ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Local Data ◽  
International Consultation ◽  
Telemedicine Technology ◽  
The Mean ◽  
Mean Time ◽  
Fast Access

In emergency settings, fast access to medical imaging for diagnostic is pivotal for clinical decision making. Hence, a need has emerged for solutions that allow rapid access to images on small mobile devices (SMD) without local data storage. Our objective was to evaluate access times to full quality anonymized DICOM datasets, comparing standard access through an authorized hospital computer (AHC) to a zero-footprint teleradiology technology (ZTT) used on a personal computer (PC) or SMD using national and international networks at a regional neurosurgical center. Image datasets were sent to a senior neurosurgeon, outside the hospital network using either an AHC and a VPN connection or a ZTT (Image Over Globe (IOG)), on a PC or an SMD. Time to access DICOM images was measured using both solutions. The mean time using AHC and VPN was 250 ± 10 s (median 249 s (233–274)) while the same procedure using IOG took 50 ± 8 s (median 49 s (42–60)) on a PC and 47 ± 20 s (median 39 (33–88)) on a SMD. Similarly, an international consultation was performed requiring 23 ± 5 s (median 21 (16–33)) and 27 ± 1 s (median 27 (25–29)) for PC and SMD respectively. IOG is a secure, rapid and easy to use telemedicine technology facilitating efficient clinical decision making and remote consultations.

scholarly journals Accuracy of a Point-of Care Hemoglobin A1c Assay - A Community Outreach Project

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A465-A466
Author(s):  
Noura Semreen ◽  
Gene Otuonye ◽  
Angelica Medina Pena ◽  
Natasha Rastogi
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Point Of Care ◽  
Clinical Decision ◽  
Mean Difference ◽  
Health Clinic ◽  
Sampling Point ◽  
The Mean ◽  
Hba1c Measurement ◽  
Hba1c Levels

Abstract Glycated hemoglobin (HbA1c) is an invaluable tool in diabetes mellitus (DM) management. Conventionally obtained via venous blood sampling, point-of-care (POCT) capillary HbA1c measurement offers an opportunity for immediate treatment modification, reduced cost & increased patient satisfaction. While previous studies using the POCT HbA1c test A1cNow+ have shown accuracy within a 0.5% range from the gold standard venous HbA1c, we noted discrepancy in our community health clinic & sought to evaluate the accuracy of POCT HbA1c levels compared to venous HbA1c levels to guide our clinical decision-making. In this 2-part study, we compared POCT HbA1c levels measured via a single use A1CNow+ HbA1c monitoring device & venous HbA1c samples measured by a standardized lab. Part1: after retrospective chart review, we identified 262 patients with prediabetes, Type1 or Type2 DM based on ADA guidelines who attended our clinic from January 2019-June 2019 & received POCT HbA1c with A1cNow+ testing during their visit. Of those cases, 47 patients also had a venous HbA1c at a standardized laboratory within 1 month of having their POCT HbA1c performed in our clinic. Part2: We noted variability in the temperature storage of A1CNow+ test strips. Storage was standardized to room temperature as per device instructions in June 2019. We subsequently reviewed charts from June 2019-December 2019 & identified 118 patients who had both POCT HbA1c & venous HbA1c measurement within a 1 month period. Patients was categorized into subgroups per ACP guidelines for DM control: prediabetic (HbA1c 5.7–6.4%), controlled DM (HbA1c 6.5 to 8.0%) & uncontrolled DM (HbA1c &gt;8.0%). The average difference between POCT & venous HbA1c tests was calculated & analyzed for statistical significance using paired t test analysis. Part1: For patients in prediabetic, controlled & uncontrolled DM subgroups, the mean difference between A1cNow+ & standardized venous HbA1c testing was 0.68% (p= 0.004), 1.15% (p= &lt;0.0001) and 1.36% (p= 0.0003) respectively. Part2: After standardization of test strip storage, the mean difference between A1cNow+ & venous HbA1c testing for prediabetic, controlled & uncontrolled DM patients was 0.33% (p= 0.002), 0.41% (p= 0.011) and 1.26% (p= &lt;0.0001) respectively. POCT HbA1c provides a unique opportunity to immediately address glycemic control. Its advantages are especially apparent in a patient population with limited resources & poor follow up, as in our clinic. Although standardizing test storage improved overall concordance between A1cNow+ HbA1c testing & venous HbA1c, there was still a statistically significant larger mean difference in uncontrolled DM patients. In prediabetic & controlled DM patients, however, POCT HbA1c was accurate within previously published reports of a 0.5% range when compared to venous HbA1c. An algorithm has since been developed to guide our clinical decision making with these findings.

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