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Published on: April 12, 2021
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Modeling Data Journeys to Inform the Digital Transformation of Kidney Transplant Services: Observational Study
Videha Sharma1,2, Iliada Eleftheriou1, Sabine N van der Veer1
1Centre for Health Informatics, Division of Informatics, Imaging and Data Science, The University of Manchester, Manchester, United Kingdom.
Journal of Medical Internet Research
|April 22, 2022
Summary
Data journey modeling revealed that manual data transfer and IT system limitations hinder kidney transplant referrals. Future solutions require regional interoperability and specialty-specific data views to improve care coordination.
Area of Science:
- Health Informatics
- Clinical Workflow Analysis
- Digital Health Transformation
Background:
- Data journey modeling offers insights into healthcare IT infrastructure and sociotechnical barriers.
- Kidney transplantation involves complex, multi-specialist coordination and data centralization across various IT systems.
- Current understanding of IT's role in managing patient data, communication, and workflows for kidney transplants is limited.
Purpose of the Study:
- To utilize data journey modeling to understand interoperability, data access, and workflow needs in a regional kidney transplant service.
- To identify IT-related challenges and opportunities within the kidney transplant referral pathway.
Main Methods:
- An incremental methodology was employed, including document review, expert interviews, and iterative modeling.
- The LOAD (landscape, organizations, actors, and data) framework was used for analysis.
- A data journey model diagram was developed to visualize the transplant referral pathway.
Main Results:
- The study visualized four organizations, over nine IT systems, and more than four actors involved in the transplant referral pathway.
- Data movement was heavily reliant on manual transcription into documents and actor interaction with IT systems, leading to time-consuming and error-prone processes.
- A significant lack of interoperability between and within organizations resulted in delays due to manual data transfer methods like post and email.
Conclusions:
- Data journey modeling highlighted that human actors, not IT systems, are central to data movement in kidney transplantation.
- The existing IT infrastructure creates a substantial administrative burden and does not support clinical workflows effectively.
- Future IT solutions must prioritize regional interoperability and specialty-specific data views to enhance multi-organizational clinical services like transplantation.
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