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

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.

Automated summary

In healthcare settings, compliance with clinical protocols and medical guidelines is important for high-quality treatment. This paper proposes new metrics for measuring compliance, using fuzzy aggregation techniques. These metrics consider the degree of compliance with activities, the compliance of patients, and the importance of activities. Applied to clinical protocols, these metrics help assess the effectiveness of implemented protocols in terms of compliance.