C-K Theory of Design andTransformation of Health Systems:Paper II

This paper focuses on C-K theory with its application to expand the scope of innovative solutions to transform health systems. The previous paper (Huttin,2024) provided a review of main design theories and a description of the research process and interactions between investigators for physicians’ choice models using random price generators. The selection of alternatives for that user case mainly related to medical policy problems (e.g. Huttin&Hausman,2021). However, such experimental studies require scaling up for bigger samples and therefore comprehensive user cases, to be useful for transformative tools in health system reforms. The use of C-K theory (Hatchuel&Weil,2002) may be a useful framework to generate data elements on economic and financial information, from conversation of care, and expand the dataspace, with innovative applications of the algorithms (as proposed in Prof.Huttin’s studies). The development of such economic models will impact the architecture of national or international accounting systems; therefore, they may require the design of ad hoc or satellite health accounts with such additional type of information. However, the architecture of health accounts is more driven by environmental communities who dominate methodological advances (e.g. agriculture, forestry management, etc.); modeling techniques in international health accounting generate specific tracers to integrate in aggregate indexes. Such development of the K space may be used for the health targets under the global agenda (e.g. SDGs).The statistical methods used to transform this K space, their selection process, and the identification of key parameters estimates will determine to a certain extent the transformation of health systems and will nurture the C concepts (e.g. more justice in reallocation of services and access to care).In global health, comparable national estimates are used (e.g. “Global Burden of Diseases” (GBD) and risk predictors for health risk evaluation). In relation to global pricing, the agenda refers to “Universal Health Coverage” (UHC), to accelerate access to affordable medical services in different regions of the world. Additional economic and financial information on populations with methodologies such as Hierarchical Bayesian Modeling (HBM) and its countervailing use (e.g., physicians reversed conjoint models, Huttin, 2017), with trained models on bigger samples and comprehensive user cases, contributes to structuring the pathway to transformative changes.