Use Case: Health and Wellbeing Dashboard
Granular, AI-curated health and wellbeing records shareable under personal control.
Overview
As Humans, we each have one body. And yet data about it is scattered across a myriad of systems; and often in-accessible to the one person it matters most to; the one who often has to repeat, and share it many times over.
DataPal Health and Wellbeing Dashboard gives people that base level of health and wellbeing data in a simple, self-controlled accessible format. It can ingest data manually, on a semi-automated basis; or through connection to a range of apps and services. It then uses AI to curate and augment the base data to ensure it is a good representation, in useful formats and shareable with the active, auditable permission of the individual.
Context
People need, and should have great access to accurate data about their health and wellbeing. That allows for understanding, day to day management, improvement, decision-making and appropriate care and treatment.
Then, beyond personal use, people often need to share their health and wellbeing data - holistically, or in sub-sets with other parties. That might be a local gym, the life assurance company, a private medical insurer, a pharmacy, the GP, a hospital. They all have valid reasons for accessing and potentially updating those personal details; in the current mode that is not easy. So each one currently builds their ‘own’ copy of the data.
Challenge
We typically don’t need our health and wellbeing data in our faces, all the time. But it is critical to know that it is accessible when we really need it. And that those who want or need to make full use of their data should be able to do so without hindrance.
But…., that data is sensitive. It has no one master, authoritative source. It is, by definition, distributed. And it is hugely important for the individual that it be accurate, accessible and able to interact with external data sources such as condition, treatment and pharmaceutical databases.
Solution
DataPal Health and Wellbeing Intelligence addresses these challenges by shifting control to the individual. Critically, this is about the individual as a point of integration and control of their data on a distributed basis.
The view of their own body, health and wellbeing is curated by the individual; supported by API’s, apps, AI and agents permissioned to write to the individual’s own view.
DataPal then enables approved apps and services to “connect to the combined data” — securely, selectively, and on the individual’s terms. This addresses that architectural problem in which the individual currently has to go from one silo to the next to access sub-sets of their data.
How It Works (Flow)
Data entry and ingest: Individuals enter their own base data, and then connect up further available data sources.
Data cleaning and consolidation: DataPal automatically standardises formats, matches related data, and fills in missing context.
AI-Based Augmentation: External data sources and machine learning enrich the health and wellbeing records, adding metadata and preparing for analytics.
An array of charts and reports are generated, including forward projections, next best actions and emerging decisions.
Human-in-the Loop Review: People engage with their own data, its projections and draw in additional guidance as needs be. Decisions are made and models adjusted where needs be.
Granular Permissioning: Individuals may choose to share all, some, or even just one health and wellbeing record with relevant third parties — time-bound, purpose-specific, and revocable at any time.
Ongoing Learning: Once a record type has been augmented, DataPal auto-recognises and enriches future similar records.
Actors
Individual / Data Owner: Ingests, enriches, and manages their transaction data and permissions.
Data Provider/ Service/ App: Enabling the capture and ongoing flow of data into DataPal.
Organisation / Service Provider: Requests specific, purpose-limited access to verified transaction data (e.g., for lending, loyalty, or service fulfilment).
DataPal Platform: Provides ingestion, cleaning, AI augmentation, and permission management under the IEEE 7012 MyTerms model.
AI Agent / Developer: Builds value-added services — such as check-up reminders, prescription management, or decision-making assistants — using DataPal’s APIs.
Benefits
Individuals gain clear, usable health and wellbeing records; control exactly what’s shared; unlock new value from their own data. Longer term individuals build an automated, personalised data vault that continuously learns and enriches itself over time and enables good health and wellbeing related decision-making.
Health and wellbeing service providers access accurate, consented, and purpose-specific transaction data. Longer term lower compliance risk, improved customer trust, and better service personalisation.
Developers / ecosystem access a composable, consent-based data platform for building innovative financial and AI services. Longer term grow new business models based on privacy-first, customer-controlled data collaboration.
Society / regulators, demonstrates practical privacy innovation and human-centric data sharing. Longer term this encourages transparent, compliant data ecosystems aligned with public trust.
Outcomes
Much improved and more controlled data sharing experience for individuals who need to share their health and wellbeing data with other parties.
Significant improvement in health and wellbeing data quality and completeness through AI augmentation.
Increased user trust and engagement, measured by granular data sharing control.