S23M Partner Jorn Bettin will be presenting on “Community Oriented and Patient Centred Health Service Co-Design” at the Australasian Digital Health Institute Summit (5 to 25 November 2020).
Mutual trust between patients and the network of care is a prerequisite for improvements in integrated and connected care. Patients, families, and local community service providers all have major roles to play in integrated health and care service delivery, and hence they should be key stakeholders in the co-design of such services.
The natural data architecture for supporting complete patient journeys is a network that includes patients and health and care professionals, where all participants in the network produce and share information with each other across organisational boundaries, in accordance with the varying needs of individual patient journeys.
We present a community oriented and patient centred health service design approach that uses the formal language of the “Human Lens” to model the complete network of care around patients. The core concepts of “Resources”, “Events”, and “Agents” (REA) allow collaboration patterns to be expressed in an intuitive visual notation that is easily understood by healthcare professionals and by local community representatives.
The critical role of trust
The potential for misunderstandings and mistrust can be minimised with a data governance framework and software tools that are explicitly designed to support trust building and communication between patients and the parties that are involved in the network of care.
An appropriate governance framework for federated data custodianship enables health and care professionals to access local and non-local patient data and clinical reports, and at the same time it can empower patients and their families to grant (and restrict) access to selected information artefacts to specific professionals, service providers, and roles within the healthcare sector.
Appropriate software and data architectures that include patients and their families as active participants in health data custodianship can enable innovative collaboration patterns between patients and the network of care. For example patients can be empowered to provide feedback and ask questions as needed regarding any entry in their medical history at any time, and can be equipped to monitor all health data access events.
In a federated REA health data architecture:
- The patient’s journey is described as a series of significant events.
- As part of their journey, patients interact with health and care professionals and with the help of adequate software tools.
- The patient journey is facilitated by the coordination of a multitude of resources within the network of care.
- The patient is the primary agent that has visibility of the patient history, with the ability to control access, but without the ability to tamper with the information recorded by health and care professionals.
Transparent and adaptive health and care delivery
A REA data architecture leads to a design where no service provider is emphasised over any other, and where each service provider can easily shift between the local perspective and the overall health and care delivery ecosystem perspective. The user interfaces exposed to patients, families, and healthcare professionals can continuously inform about the context of the displayed information artefacts, so that users are aware at all times:
- whether specific information artefacts pertain to the local context or to other service providers;
- whether the custodianship of specific information artefacts lies with the same entity that acts as the main data custodian in the local context or not;
- whether specific other service providers within the region or country are using the same national or regional standard data sets or not.
This level of transparency greatly facilitates collaboration between service providers and it catalyses the motivation for regional and national standardisation. It also simplifies and streamlines the process of rolling out the latest versions of national and regional standard data sets.
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