Data-informed healthcare service design for multiple long-term conditions using online patient stories

2026-03-30

AI Summary

Traditional healthcare service designs struggle to meet the complex needs of patients with multiple long-term conditions (MLTC). This study addresses this gap by systematically integrating 2,320 online narratives from patients and caregivers, combining qualitative content analysis with large-scale text mining to construct a structured story database that precisely identifies service pain points. Innovatively bridging qualitative depth with quantitative breadth, the research distills three critical dimensions for service improvement: continuity of care, care coordination, and service accessibility. These findings provide empirical grounding and strategic priorities for redesigning healthcare systems to better support individuals living with MLTC.

Technology Category

• Machine Learning: Life-Long and Continual Learning
• Application Domains: Humanities & Computational Social Science
• Data Mining & Knowledge Management: Conversational Systems for Recommendation & Retrieval

Application Category

• User Modeling, Personalization and Recommendation: Studies of user behavior, including longitudinal effects of personalized systems
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Conventional service design methods are valuable for improving healthcare experience, but are limited in scale and information capture. Based on a constructed database of 2,320 stories from patients and carers with multiple long-term conditions (MLTC), this paper shows how real-life experiences can be used to inform healthcare service redesign. By combining the richness of qualitative insight with the breadth and representativeness of large-scale data, it identifies "Continuity of care", "Care coordination", and "Temporal - Access to services" as the priority redesign opportunities for MLTC.

Problem

• multiple long-term conditions
• healthcare service design
• patient stories
• continuity of care
• care coordination

Innovation

• data-informed design
• multiple long-term conditions
• patient stories
• care coordination
• continuity of care