Production of Evidence-Based Informed Consent (EBIC) With Meaning Equivalence Reusable Learning Objects (MERLO): An Application on the Clinical Setting

Production of Evidence-Based Informed Consent (EBIC) With Meaning Equivalence Reusable Learning Objects (MERLO): An Application on the Clinical Setting

Myrtha Elvia Reyna Vargas (University of Toronto, Canada), Wendy Lou (University of Toronto, Canada) and Ron S. Kenett (Technion Israel, Israel)
DOI: 10.4018/978-1-7998-1985-1.ch005

Abstract

Apparently, during an informed consent, patients remember little of the information given and their comprehension level is often overestimated by physicians. This study measures level of understanding of informed consent for elective cesarean surgery using an evidence-based informed consent (EBIC) model based on six MERLO assessments. MERLO recognition and production scores and follow-up interviews of 50 patients and their partners were recorded. Statistical comparison of scores within couples was performed by weighted kappa agreement, t-tests, and Ward's hierarchical clustering. Recognition score means were high for patients and partners with low standard deviation (SD), while production scores means were lower with higher SD. Clustering analysis showed that only 70% (35/50) of couples were assigned to the same cluster and t-test yields significant difference of scores within couple. Kappa yields moderate agreement levels on all items except for items D and C, which are lower. Follow-up interviews show that participants consider MERLO assessments to be helpful in improving comprehension.
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Background

Even though physicians may try their best to guarantee that patients have understood all necessary aspects of a medical intervention, the ability to discern the patient’s actual understanding remains a complicated task. This is due to not obvious aspects involved in the process such as patient autonomy, level of stress, level of education, prior medical knowledge, etc. Previous studies have measured patient’s ability to recall information provided during an informed consent process, concluding that in most cases understanding levels are lower than desired (Crepeau et al., 2011; Kiss, 2004).

The motivation of this study is the necessity to have quantitative evidence (other than a checkmark on an informed consent sheet) ensuring the physician that a patient and/or his family have understood the implications, potential risks, and alternative treatments to a medical intervention.

The procurance of discrete measures of comprehension levels could be highly beneficial to hospital administration and legal services, as it could minimize controversies and legal implications resulting from ambiguous legislation that leads to different standards and criteria for what constitutes “adequate” informed consent and that fails to clarify how far the physician should go to ensure the patient has understood every aspect of the informed consent process (Hall, Prochazka, & Fink, 2012, p. 539).

In the following sections, the definition and process of evidence-based medicine and informed consent are explained. The term “Evidence Based Informed Consent” (EBIC) is introduced as well as its purpose and importance in the gynecology and obstetrics area.

Key Terms in this Chapter

Meaning Equivalence Reusable Learning Objects (MERLO): Multi-dimensional database that allows the sorting and mapping of important concepts through exemplary target statements of conceptual situations, and relevant statements of shared meaning.

Evidence-Based Informed Consent (EBIC): Process-based model for obtaining a signed informed consent form. It assumes that, in addition to an informative conversation, it is also necessary to verify the depth of the patient’s comprehension of the health issue and proposed medical intervention to follow.

Kappa Statistic: Statistical method frequently used to test interrater reliability between two categorical variables. It accounts for the possibility that raters or survey respondents actually guess on at least some variables due to uncertainty.

Hierarchical Clustering: Data driven statistical method used to place observations into groups (clusters) with a predetermined ordering from top to bottom. Each cluster contains “n” number of observations that are more similar between them than the ones contained in the other clusters.

Correlation: Statistical measure of how strongly two pairs of continuous variables are related. Within a clinical context, correlation is useful when the two variables being tested represent different clinical or physiologic parameters usually measured in different units.

Concordance: Level of agreement between two variables. It measures whether scores are consistent between them (as one increases the other increases in the same amount, or vice versa).

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