Modelling of patient journey in chronic spontaneous urticaria: Increasing awareness and education by shorten patients' disease journey in Germany
Marcus Maurer, Matthias Augustin, Sabine Bauer, S. Ekanayake‐Bohlig, Philipp Kircher, Anja Knöll, Thomas Kramps, Hjalmar Kurzen, Sonja Laemmel, Natalija Novak, Eva Oppel, Lal Pirouzmandi, Michael Rebhan, Ulrich Reimnitz, Grit Richter‐Huhn, Beate Schwarz, Uwe Schwichtenberg, Petra Staubach, Christian Termeer, Antje Thielen, Katarina Varga, Dagmar von Bubnoff, Alexander Zink, Benjamin Gmeiner, Petra Nathan
Abstract
BACKGROUND: Chronic spontaneous urticaria (CSU) is both physically and emotionally stressful, and guideline recommendations are often not optimally implemented in clinical practice. The objective of this study was to provide an overview on the patient journey in CSU and to develop a mathematical model based on solid data. METHODS: The journey of CSU patients in Germany was traced through literature review and expert meetings that included medical experts, pharmacists and representatives of patient organizations. The current situation's main challenges in the patient journey (education, collaboration and disease management) were discussed in depth. Then, a probabilistic model was developed in a co-creation approach to simulate the impact of three potential improvement strategies: (1) patient education campaign, (2) medical professional education programme and (3) implementation of a disease management programme (DMP). RESULTS: Chronic spontaneous urticaria patients are severely burdened by delays in diagnosis and optimal medical care. Our simulation indicates that in Germany, it takes on average of 3.8 years for patients to achieve disease control in Germany. Modelling all three optimization strategies resulted in a reduction to 2.5 years until CSU symptom control. On a population level, the proportion of CSU patients with disease control increased from 44.2% to 58.1%. CONCLUSIONS: In principle, effective CSU medications and a disease-specific guideline are available. However, implementation of recommendations is lagging in practice. The approach of quantitative modelling of the patient journey validates obstacles and shows a clear effect of multiple interventions on the patient journey. The data generated by our simulation can be used to identify strategies for improving patient care. Our approach might helping in understanding and improving the management of patients beyond CSU.