Data-informed healthcare service design for multiple long-term conditions using online patient stories
This work addresses service design for patients with multiple long-term conditions, offering a data-informed approach that is incremental over conventional methods.
The paper tackled the challenge of scaling healthcare service design for multiple long-term conditions by analyzing 2,320 online patient stories, identifying 'Continuity of care', 'Care coordination', and 'Temporal - Access to services' as key redesign opportunities.
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.