Information Infrastructure for Health

It's not an Internet of Things: It's an Internet of People

ATI Scoping Workshop, Edinburgh

Neil D. Lawrence

18th November 2015

Global Health

What is an Information Infrastructure?

  • Talk at ControlPoint "Right First Time" Day.
    • Audience of Utility companies: Gas, Water, Electric.
  • What would a modern Water network look like?
    • Would we build such massive infrastructure?
    • It seems we can't even afford to properly maintain existing architecture.

Data Science in Africa

Data Science in Kenya

  • IBM Nairobi: Monitoring Small Farms
  • Makerere University:

    • Crop Monitoring (Ernest Mbweze)
    • Kudu: Distributed Bid Matching (Kenneth Bwire)
  • Collaboration with UN Global Pulse and Makerere

    • Disease Monitoring with Gaussian Processes (Ricardo Andrade Pacheco, Martin Mubangizi, John Quinn & NL)

Farr Institute at HeRC

  • Manchester and HeRC
    • Devolution of power in Social and Health to Manchester Region.
  • Manchester has long led in Health Informatics (Iain Buchan & Connected Health Cities)
    • Agenda extends acoss N8

UK - Where do we Lack Infrastructure

Case Study: Mental Health

  • NewMind Network (led by Chris Taylor)

    • Early Diagnosis of Dementia, Parkinsons.
    • Support for Bipolar disorder
    • What are the implications for Humans?
  • Clinicians, patients, device manufacturers.

Major Challenge

  • "Data Liquidity"
    • If we can't get to the data we can't learn.
  • Clinical Interests
    • Hard-won data is hard to obtain.
    • Working better in computational biology than health informatics?
    • Is it patient interests or practitioner interests?

Technical Challenges

  • Interconnecting data

    • Data of different types/modalities.
    • Weighting of text, images, clinical tests, genomics, transcriptomics, social media, music listening, loyalty card.
  • Scale: When Big Data is Small

  • Massively Missing Data

  • Steaming nature of data

    • Health vs Advertising

Time horizon: 10 years?

Social Challenges

Time horizon: ???


  • Closer integration of technical and social solutions.

  • It is not enough to provide centralised learning solutions working on large data.

    • inference integrated within information infrastructure
  • More focus on

    • information leakage,
    • frameworks of trust,
    • user-centric models for learning and data storage

Where does the ATI come in?

  • Open meeting September 2014:
  • Leadership + Critical Mass can do something
    • Enabling the social revolution requires a technical revolution.
  • A Coalition of the Competent
  • Corevolution of technology, law and society.
    • This needs multi-million pound institutes to achieve.