Sinead Quealy from VirtualVet and I have recently returned from a fantastic few days in Exeter where we ran our two days AHEAD workshop on the “roadmap to the digitisation of animal health data” with a focus on drug usage in food-producing animals. You can go here to read more about our joint vision for organising this workshop.
We were incredibly happy to be one of only eight international conferences sponsored by the Organisation for Economic Co-operation and Development (OECD)’s Co-operative Research Programme on Biological Resource Management for Sustainable Agricultural Systems in 2017. Despite spaces being limited to 25, we managed to have representatives from 10 OECD countries attending the workshop in person or via video link.
A good balance was achieved too in terms of the background of the participants.
Prof. Toby Mottram from eCow (UK) officially opened the workshop.
To try and create this picture, the structure of the 2 days was very much aligned with the magic triangle for business models: Why? What? and How?
The “why” of animal health data digitisation
The “why” of animal health data digitisation was made very obvious by Dr Barbara Han, a disease ecologist with the US Cary Institute of Ecosystem Studies. She argued that the hard limits of outbreak predictions are not set by technological innovations but that data is the frontier. Data-driven early warning systems for diseases are technologically possible & investment worthy. Still need convincing? Read her latest work on undiscovered bat hosts of filoviruses and implications for preventing future outbreaks of ebola virus.
Sinead Quealy from VirtualVet (Ireland) made the point that busy farmers and veterinarians need to harness the power of data digitisation to help them comply to existing legislation and demonstrate the responsible sourcing of medicines. Sinead’s arguments were echoed by Rebecca Veale from the National Farmers Union (UK) who presented the Animal Health Law, a new EU framework directive, which will ultimately replace more than 40 existing regulations and directives. With the new law clearly focusing on the control of endemic and exotic diseases to maintain the animal health and welfare of EU and trading partners’ stock, it is becoming increasingly important to reduce the regulatory burden for producers whilst maintaining these controls. This is where digital data can help!
Damien Barrett, from the Department of Agriculture, Food&Marine (Ireland), and Fin Twoney from the Department for Environment Food & Rural Affairs (UK) provided us with several examples on how both governments perform surveillance based on digital data.
Dr Ioannis Magouras from the Veterinary Public Health Institute (Switzerland) and Prof. Andrew Dowsey from Bristol University AMR Task Force (UK) filled us in on antimicrobial usage and resistance research data needs. Many questions remain currently unanswered: what quantity of antimicrobial drugs are used in veterinary medicine? what are the social factors contributing to antimicrobial usage and resistance in farming industry? What is the flow and fate of antimicrobial drugs and resistance into the environment and wildlife? Digital data could provide elements of answers to all three questions.
The “what” of animal health data digitisation
Harm-Jan van der Beek, MD of UNIFORM-Agri (Netherlands), took us through the reality of digital data capture and on-farm software adoption. Some challenges lie ahead but he also suggests areas of improvement: 1) barcode/QR code on medicines with proper information; 2) money back scheme for medicine packages & left-over (to know what is actually being used).
Sophie Throup, MD of RAFT Solutions (UK), emphasised the vast amounts of information in veterinary practices and the lack of standardised method for collating this knowledge. Their Data Vet project – a 3-year UK funded program and surveillance tool for veterinary practices – which has seen 369 diseases “digitally” mapped so far is a step in the right direction.
It became clear after hearing Frans van Diepen from the Netherlands Enterprise Agency and Jim Bracken from GS1 AISBL (Belgium) that many standard systems already exist to take us from identification, to capture and sharing. For example, EPCIS is a GS1 standard that enables trading partners to share information about the physical movement and status of products as they travel throughout the supply chain – from business to business and ultimately to consumers. We are moving forward in the right direction but are not quite there yet: “Traceability is not yet where it should be – it is not traceability if you can’t recall information quickly.”
The weak adoption of standards and control vocabularies (for data interoperability) was one of the challenges to the near real-time analysis and data interpretation which I highlighted in my talk. Other needs include: the need for data privacy and security, the need for methods capable of handling high dimensionality and large sample size, and the need for context. My last slide (see below) spurred a lot of exchanges in the room as it became increasingly clear that the issue of data & value ownership is central to our topic.
Christine Brett from GPrX Data explained what animal health can learn from digital approach to human health prescriptions. GPrX Data takes NHS big open data and makes it accessible and affordable for pharma and healthcare business intelligence and national sales teams. She introduced us to one of the many new terms coined during the workshop: “Datapretation” (go beyond providing data-provide solutions).
Dr Jorge Pinto Ferreira (Switzerland) gave a fascinating talk on Safoso‘s recent experience of the long process from digital data to real-world decisions in Vietnam. Safoso were called in to assess the Animal Health and Laboratory Information Systems in Vietnam. One of the main problems observed was the widespread use of non-standardised forms of reporting information which lead to considerable data duplication. This coupled to include a lack of strong, high-level leadership and insufficient personnel to deal with volume of paperwork resulted in a poor quality surveillance system. A new computerised and integrated reporting system was recommended and Jorge made a strong argument that the people at the source of our data are too often ignored and that they must be considered at the core of the digitisation process.
Dr John Al-Alawneh from the University of Queensland (Australia) gave us a great tour of some of the proactive farm decision support systems he and his colleagues have designed: “Once data is analysed, a farmer does not want academic reports, he wants to be advised on the best course of action for his farm”. Farmers need to be reassured that data digitisation is about moving towards quality assurance, not control.
The “how” of animal health data digitisation
Last, but certainly not least, it was important to start tackling the “how?” of digitisation.
Ene Karner, Copa Cogeca representative from Estonia, amazed us all with her presentation of her country’s digital society. Estonian political and technical leadership laid the foundation for e-Estonia on the principles of 1) decentralisation, 2) interconnectivity, 3) open platform and 4) open-ended process. I thoroughly recommend that you watch the videos introducing the system and how Estonia got there.
Dr Pat Lynch, RIKON director (Ireland), explained how the animal health value chain has traditionally been a closed business ecosystem built on transactional relationships. This has resulted in knowledge being siloed and inefficient resource utilisation. Today, this value chain is rapidly evolving with many new participants (feed companies, pharma…) redefining the industry. Furthermore, the increasing capabilities of smart, connected products not only reshape competition within the industry but expand the industry boundaries.
Exploring the “Open Collaboration” option in more details, we came across two new concepts. “Data Farm Communities”, such as Data Linker in Australia/New Zealand, are being formed by farmers with a desire to take control over their data by choosing how it is shared in a way that may create opportunities for financial gains. “Data Farm Aggregators” such as VirtualVet are actors that leverage the active participation of the data farm communities in order to aggregate their data for the provision of commercial services to other market stakeholders while ensuring maximum value of the farmers data.
Facilitated by Dr Pat Lynch , participants finally broke into groups to map out the “how?” of digital transformation.
We are currently in the process of organising all the different points for action which were raised during the afternoon of the second day. A report will be prepared and distributed…so watch this space!
Many of the contributions we heard over the two days will be published in a special research topic of the journal Frontiers in Veterinary Science. We expect the first papers to be online by early summer and we will keep you updated of the dissemination of AHEAD 2017 outcomes.