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Related Concept Videos

Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
Quality Control01:05

Quality Control

Quality control is one of the three cyclical quality assurance activities that help keep a system under statistical control. Typical quality control activities include creating quality control charts, conducting proficiency testing, and documenting and archiving results.
Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
Quality Assurance01:19

Quality Assurance

Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
Bias01:22

Bias

Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
Controls in Experiments01:13

Controls in Experiments

When conducting an experiment, it is crucial to have control to reduce bias and accurately measure the dependent variables. It also marks the results more reliable. Controls are elements in an experiment that have the same characteristics as the treatment groups but are not affected by the independent variable. By sorting these data into control and experimental conditions, the relationship between the dependent and independent variables can be drawn. A randomized experiment always includes a...
Methods of Documentation V: CBE01:23

Methods of Documentation V: CBE

Charting by Exception, or CBE, is a method of documentation used in healthcare, particularly in nursing, that focuses on documenting only significant or abnormal findings rather than recording every detail. This approach aims to streamline the documentation process, improve efficiency, and ensure that healthcare providers can quickly identify deviations from normalcy in patient assessments.
In CBE, healthcare professionals establish predefined standards of practice that define what constitutes...

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X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells
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Controlling quality in CME/CPD by measuring and illuminating bias.

David Dixon1, Jatinder Takhar, Jennifer Macnab

  • 1Continuing Professional Development, Schulich School of Medicine & Dentistry, The University of Western Ontario, Canada.

The Journal of Continuing Education in the Health Professions
|June 15, 2011
PubMed
Summary

This study assessed a tool for measuring bias in continuing medical education (CME/CPD). While the tool shows potential for quality control, standardized training is crucial to improve reliability across different sites.

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Area of Science:

  • Medical Education Research
  • Quality Improvement in Healthcare
  • Bias Detection in Medical Education

Background:

  • Growing concern regarding bias in industry-supported continuing medical education/continuing professional development (CME/CPD).
  • Previous research in 2007 validated an assessment tool for measuring bias in CME.
  • Need to evaluate the tool's applicability across diverse settings.

Purpose of the Study:

  • To assess the application of a bias measurement tool in various Canadian CME/CPD environments.
  • To further understand the reliability and validity of the tool in multi-site settings.
  • To inform the development of quality control mechanisms in CME/CPD.

Main Methods:

  • Established a national steering committee with representatives from academic institutions and professional colleges.
  • Refined the bias assessment tool and updated training materials.
  • Conducted a multi-site study involving 5 academic CME/CPD centers across Canada.
  • Utilized a train-the-trainer model for consistent implementation via videoconferencing.

Main Results:

  • Content reviews demonstrated moderate inter-rater reliability (ICC = 0.54).
  • Live reviews exhibited poor overall inter-rater reliability.
  • One participating center achieved substantial inter-rater reliability (ICC = 0.68).

Conclusions:

  • The bias assessment tool can be integrated into a multistage process for CME/CPD quality control.
  • Standardized and cost-effective training protocols are essential to enhance tool reliability.
  • Further development is needed to ensure consistent application and maximize the tool's effectiveness.