Towards a Flexible Assessment of Compliance with Clinical Protocols Using Fuzzy Aggregation Techniques

3Citations
Citations of this article
10Readers
Mendeley users who have this article in their library.

Abstract

In healthcare settings, compliance with clinical protocols and medical guidelines is important to ensure high-quality, safe and effective treatment of patients. How to measure compliance and how to represent compliance information in an interpretable and actionable way is still an open challenge. In this paper, we propose new metrics for compliance assessments. For this purpose, we use two fuzzy aggregation techniques, namely the OWA operator and the Sugeno integral. The proposed measures take into consideration three factors: (i) the degree of compliance with a single activity, (ii) the degree of compliance of a patient, and (iii) the importance of the activities. The proposed measures are applied to two clinical protocols used in practice. We demonstrate that the proposed measures for compliance can further aid clinicians in assessing the aspect of protocol compliance when evaluating the effectiveness of implemented clinical protocols.

Cite

CITATION STYLE

APA

Wilbik, A., Vanderfeesten, I., Bergmans, D., Heines, S., Turetken, O., & van Mook, W. (2023). Towards a Flexible Assessment of Compliance with Clinical Protocols Using Fuzzy Aggregation Techniques. Algorithms, 16(2). https://doi.org/10.3390/a16020109

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free