JavaScript is Disabled
Your browser's JavaScript functionality is disabled. It has to be enabled to use this function of ConfTool.
Here you can find information on how to enable JavaScript
If you have any problems, please contact the organisers at design2026@fsb.unizg.hr.

Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 18th Apr 2026, 04:02:54pm CEST

Agenda Overview

Session

D335: DESIGNING HEALTHCARE SYSTEMS AND SERVICES

Time:

Wednesday, 20/May/2026:

11:30am - 12:30pm

Session Chair: Els Du Bois, University of Antwerp, Belgium

Location: Conference Hall Konavle

Presentations

Design practitioners’ perspectives on digital health implementation in complex systems

Fredrik Bodell, Dirk Snelders, Maaike Kleinsmann, Valeria Pannunzio

Delft University of Technology, The Netherlands

The implementation of services into complex systems is not well understood in design. We explore this issue by interviewing 24 design professionals with experience in implementing digital services in healthcare. We asked when they consider such services as implemented, and how they view the relation between design and implementation. Results reveal diverse perspectives on both topics. Given the wide dispersion in views, we propose two categories to describe implementation goals (impact on, and integration with systems), and to view design as a contributor to the implementation phase.

Exploring the role of a systems approach in improving long-COVID clinics

Garret Tan^1,2, Tom Bashford^1,3,4, P. John Clarkson^1,4

¹Health Systems Design Group, Department of Engineering, University of Cambridge, Cambridge, United Kingdom; ²Therapies Department, Whipps Cross Hospital, Barts Health NHS Trust, London, United Kingdom; ³Department of Anaesthesia, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom; ⁴Cambridge Public Health interdisciplinary research centre, University of Cambridge, Cambridge, United Kingdom

Long-COVID is a complex, multi-system condition with variable care across the UK. Using a systems and design engineering approach underpinned by Model-Based Systems Engineering (MBSE), this study examined Long-COVID clinic pathways through semi-structured interviews with 15 clinicians and patients. Thematic analysis identified five domains—attitudes, relationships, service integration, technology adoption, and safety netting. The final synthesised swimlane diagram revealed opportunities to improve coordination, operational efficiency, and patient safety within evolving care models.

Designing hope-oriented service touchpoints for adolescent oral health in public dental care

Marikken Høiseth^1,2, Arefe Jasbi¹, Silje Bøthun²

¹Department of Design, Norwegian University of Science and Technology, Norway; ²Department of Health Research, SINTEF, Norway

Adolescence is a critical period for establishing oral health habits, yet motivating young people remains challenging. This paper presents a pilot intervention in the Norwegian Public Dental Service, developed through co-design and guided by salutogenic and hope theory. The intervention consisted of three touchpoints: an SMS invitation, an in-clinic goal-setting dialogue, and a follow-up SMS embedded in routine care. Based on interviews with clinicians and adolescents, we explore how hope-oriented communication can be enacted within everyday clinical practice.

Collaborative mapping of bottlenecks and opportunities for AI-supported triage in Dutch mental healthcare

David Quijada-Fernandez¹, Hendrikus van Os^2,3, Maaike Kleinsmann^1,2, Jiwon Jung^1,4

¹Faculty of Industrial Design Engineering, Delft University of Technology, The Netherlands; ²Leiden University Medical Center, The Netherlands; ³University Medical Center Utrecht, The Netherlands; ⁴Surgery Department, Erasmus University Medical Center, The Netherlands

This paper explores the role of artificial intelligence to reduce resource burden and support service delivery processes in generalist secondary-care mental health services in the Netherlands. Through semi-structured interviews with domain experts and using service blueprinting as a stimulus, we identified challenges and bottlenecks in mental health care pathways and intervention opportunities. We propose four intervention directions for design researchers and developers to prototype and assess how AI technologies may alleviate capacity issues in mental healthcare.