Creating a Data Commons – better decision making through integrated data
Synergia has been supporting diverse organisations to share data for their common good and to make better decisions for a decade.
In that time we have learned that the ‘soft’ issues (goals, relationships, principles, value, governance) are just as important as the ‘hard’ issues (data schemas, digital infrastructure, data analytics, data security) in creating an environment where organisations build synergies and value from shared data.
The problem is that for community-based organisations to work their way through these soft and hard issues is viewed as being too difficult, causing them to either not try, or in some cases start, fail and then give up.
Synergia has the solution, called the Data Commons. We start from a foundation of democratic principles – if you contribute data you have a say in how it is used. Starting with this basic principle seems to be the door opener for multiple diverse organisations to work together – as it creates a system of collective stewardship, which leads to transparency, trust and collective action.
- Simple and speedy: Having set up a number of integrated data systems, Synergia has now developed a process with clear steps to work through and useful processes and tools which simplify and speed up resolving the soft and hard issues and getting moving with common data infrastructure.
- Person/event level data is critical: To be clear, what we are talking about here is extracting, storing, linking and analysing information from multiple organisations patient management or case management systems relating to person-event level data. This is data that can be presented anonymously to identify trends, patterns, performance, quality aspects and equity for individual organisations or across a system.
Or, with the right permissions, identifiable information (e.g. NHI) can be used to link across a system – for example between community providers and hospitals to provide insight on patient journeys.
This data commons solution is the key to understanding and intelligently managing a system of connected care.
The technical solution is an easy-to-use web-based platform for organisations to collect and share their data with each other. The cloud-based solution has three components: an Upload portal, Data vault, and Insights platform. Our systems meet NZ privacy and security requirements.
There are four key steps to establishing a data commons solution:
- Relationship foundations – getting the foundational issues of relationships, goals, how a collective is to define value, data stewardship, Māori data sovereignty, resourcing and decision making worked through up front.
- Technical definitions – clarifying the technical challenge as it relates to the data (ensuring high quality data is being extracted into the Data Commons) and that the digital infrastructure and data science is designed in a way that meets the concerns and needs of all parties.
- Establishment and go live – development of the digital infrastructure with clear timeline and milestones. Develop algorithms for automating analysis. Provide training and support for organisations to simplify data extraction and get the most out of access to rich datasets.
- Delivering value – provide support and maintenance for the core digital infrastructure. Help organisations to understand how they can use data insight to drive service improvements and system-level quality.
We have developed a set of detailed templates, processes and tools to support the creation of a Data Commons. We know what works because we have done it for real with people and organisations who are solving real problems and wanting to make better decisions.
Recent use cases
- Hospice NZ: integrating data from 26 hospices around New Zealand, which are highly diverse and use multiple patient management systems. The platform integrates data on key process and outcome measures to support service improvement across the network
- Palliative Outcomes Initiative (POI): Those that have had a care plan through POI are linked to data from the urgent care clinics, hospitals, ambulance, primary care and MoH datasets, to understand their outcomes: requirements for subsequent care, and timing of death, to try and support the understanding of the impact of POI on end of life.
- POI geomapping: POI (Palliative Outcome Initiative) is provided a dynamic geomap of the hospices of Auckland, that identifies at-risk populations and the co-location of facilities and service usage. This draws on data in the IDI looking at determinants of health.
- Patient Access for Urgent & After Care: Integrating data from five EDs, 25 urgent care clinics, St John and PHO patient registers. The PAUA process and platform analyses non-identifiable patient-level information, including complaints, triage levels, diagnoses, length of stay and outcome, to get an unique understanding into urgent care being delivered in Auckland. By tracking individual patient outcomes for those that have high morbidity disease, and looking at what care was given in the week preceding diagnosis, an estimate can be made on whether their trajectory could have been changed.
Get in touch
Get in touch to learn more. To see a demonstration of our technical architecture and to discuss how creating your own Data Commons can help you move forward with shared, consistent and reliable data. Contact Paul Stephenson to discuss. (email@example.com)