This study presents a systems approach to optimize patient journey mapping for improving treatment persistence in healthcare. Using a mixed-methods approach, it integrates health informatics, behavioral health, and systems engineering to map patient experiences and identify intervention points. Data from 2,847 patients with chronic conditions (diabetes, cardiovascular, mental health) over 24 months were analyzed using advanced analytics.
Key findings show a 34% improvement in treatment persistence through systematic mapping, highlighting critical phases: diagnosis/treatment planning, early treatment, adjustment periods, long-term maintenance, and care transitions. Influential factors include care coordination, communication quality, service accessibility, and behavioral health integration.
Technology-enabled mapping with predictive analytics and real-time monitoring offers actionable insights. Challenges include data integration, staff training, technology limitations, and cultural shifts toward patient-centered care. Best practices involve phased implementation, stakeholder engagement, and cross-functional teams.
The study informs healthcare policy, quality improvement, and patient-centered care models. Future research will explore AI applications, cultural/demographic influences, and standardized metrics for mapping effectiveness.