Establishing a Learning Healthcare System for Metastatic Prostate Cancer in the Dutch Healthcare System: Preconditions and Potential Benefits of Real-World Data Utilization
Author(s)
Belleman T1, van Deen W2, van Wijngaarden J3, de Groot S4, Kuppen MCP5, Uyl-De Groot C6
1Erasmus School of Health Policy & Management, Amsterdam, NH, Netherlands, 2Erasmus University Rotterdam, Rotterdam, Zuid Holland, Netherlands, 3Erasmus school of Health Policy & Maangement, Rotterdam, Zuid-Holland, Netherlands, 4Institute for Medical Technology Assessment, Erasmus University Rotterdam, Rotterdam, ZH, Netherlands, 5Maastro, Maastricht, Limburg, Netherlands, 6Erasmus University Rotterdam, Rotterdam, ZH, Netherlands
Presentation Documents
OBJECTIVES: This study aims to explore the establishment of continuous learning from real-world data (RWD) in metastatic prostate cancer (mPCa) care. The objective is to understand the utilization of RWD for learning and decision-making processes, with a focus on enhancing value-based healthcare.
METHODS: This study adopts a mixed-methods approach and utilizes the experiences of the Dutch Metastatic and Castration Resistant Prostate Cancer Registry (CAPRI). Stakeholder interviews were conducted with experts in the field of mPCa and learning health systems to understand how RWD can contribute to learning, change, and decision-making. The information gathered from these interviews was used to develop a comprehensive conceptual model that illustrates the role of RWD in facilitating a learning healthcare system.
RESULTS: Eleven interviews were conducted with twelve stakeholders consisting of physicians, insurers, pharmaceutical companies, and researchers of the Netherlands Comprehensive Cancer Organization. In the interview, twelve cases were identified in which RWD was used to change clinical practice. The underlying objectives of these cases were to assess the effectiveness of care, promote quality improvement, facilitate patient-centered care, and evaluate adherence to guidelines. The data supported practice change by generating insights about healthcare utilization, quality, and population trends. Crucial elements for fostering active learning include conversations about data among peers and credibility of data. Credibility of data depends not only on the quality of the data itself but also on other factors such as the goal of the evaluation (e.g., learning, auditing) and data ownership.
CONCLUSIONS: RWD was frequently used as an opener of discussions about the effectiveness and quality of care, which led to clinical improvements through diverse mechanisms. These findings underscore the potential of RWD to inform and enhance healthcare practices, thereby improving the efficiency and effectiveness of care delivery in the field of mPCa.
Conference/Value in Health Info
Value in Health, Volume 26, Issue 11, S2 (December 2023)
Code
HSD73
Topic
Clinical Outcomes, Real World Data & Information Systems
Topic Subcategory
Clinical Outcomes Assessment, Distributed Data & Research Networks, Performance-based Outcomes
Disease
No Additional Disease & Conditions/Specialized Treatment Areas, Urinary/Kidney Disorders