A Computational Perspective of Knowledge Empowerment for Healthcare Decision Making

Abstract

People in a variety of settings can be heard uttering the phrase that “knowledge is power” or the relatively equivalent concept that “information is power.” However, the research literature in particular lacks a simple and standardized way to examine the relationship between knowledge and power. There is a lack operational quantitative definitions of this relationship to adequately support the building of complex computational models used in addressing some longstanding public health and healthcare delivery issues like differential access to care, inequitable care and treatment, institutional bias, disparities in health outcomes, and eliminating barriers to patient-centered care. The objective of this discussion is to present a relational algorithm that can be used in both conceptual discussions on knowledge empowerment modeling, as well as in the building of computational models that want to explore the variable of knowledge empowerment within computer simulation experiments.