Hippo at AI PublicSector Week 2026
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Event insights from the Hippo team
Thank you for attending our sessions at AI Public Sector Week 2026!
We’ve compiled some insights from the week into this helpful destination so you can catch up on all the presentations and resources from the Hippo team.
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eBook: Designing better prompts
AI tools accelerate work, but consistent results require us to treat a prompt as a brief, not a command. The new eBook, Designing Better Prompts, introduces six habits rooted in design thinking, like clarity and context, to transform trial-and-error prompting into an intentional, repeatable process. This framework helps teams use AI responsibly and efficiently by focusing on designing for better output.
Presentation slides and recordings
Following AI Public Sector Week, we'll also send the session slides and recordings for all three of our talks.
- Predicting patient risk: How Mid Yorkshire NHS Trust built trust in generative AI - with Anna Lay at 3:00pm, 19 March
- Building AI Capability in Government at Scale - with Heather James, Matt Wilkes and Suze Hawkins at 4:30pm, 19 March
- Innovation without risk: Generating open-source synthetic data using LLMs for Virtual Wards - with Ed Hiley at 10:30am, 20 March
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Our talks at AI Public Sector Week 2026
Predicting patient risk: How Mid Yorkshire NHS Trust built trust in generative AI
In a healthcare environment where resources are stretched and patient safety is paramount, how can we ensure the right clinician reaches the right patient at the right time? At Mid Yorkshire NHS Teaching Trust, pharmacy teams traditionally spent hours manually identifying high-risk patients across 1,100 beds, a process that was time-intensive and ripe for digital transformation.
This session shares the journey of developing the Clinical Pharmacy Prioritisation Software Tool (CPPST), a proof-of-concept that leverages Machine Learning and Generative AI to autonomously flag high-priority patients with 93-97% accuracy. Attendees will learn how the project team moved from a digitised dataset to a predictive model that boosts staff morale and improves efficiency. We go behind-the-scenes of a responsible AI deployment, detailing how the team overcame clinician nervousness towards machine learning through innovative, play-based education and human-centred design. From the Discovery phase to iterative data modelling, we explore how to ensure AI outputs remain human-readable and explainable, supporting rather than replacing expert clinical judgement.
- A blueprint for Responsible AI: How to use ethical frameworks and human-centred design to move from a data hypothesis to a viable clinical decision-support tool.
- Building clinician trust: Practical techniques (including gamified workshops playing "Guess Who") to demystify machine learning concepts for frontline staff and overcome cultural barriers.
- Technical iteration and explainability: Insights into the transition from statistical modelling to using Generative AI to provide human-readable reasoning for why a patient is flagged as high-risk.
- Data governance and security: Navigating the complexities of NHS data profiling and pseudonymisation to ensure patient privacy while fostering innovation.
- Scaling impact: How identifying complex cases with high accuracy (<2.2% false positives) allows frontline staff to devote more time to direct patient treatment.
Building AI Capability in Government at Scale
If you’re tasked with improving how teams understand, adopt, and challenge new technology, this session offers a behind-the-scenes look at how a government department and supplier partnered to build long-term capability in AI.
We’ll share how Hippo partnered with a Department to design a tailored, multi-phase programme — starting with a week-long, hands-on AI learning experience for hundreds of public servants, and evolving into targeted policy engagement and future-focused design workshops.
Phase 1 – AI Week: Covering AI fundamentals, real-world use cases, and the ethical questions every team needs to address.
Phase 2 – Policy Impact Workshops: Working directly with policy groups to explore where AI could influence decision-making and service delivery.
Phase 3 – Design in a Day (coming next): Facilitating rapid prototyping of future service and policy scenarios.
You’ll leave with practical frameworks, examples, and lessons learned on how to scale capability building from awareness to action — creating a confident, questioning workforce that keeps innovation human-first, delivers value for money, and makes the most of your partnerships.
Innovation without risk: Generating open-source synthetic data using LLMs for Virtual Wards
Virtual wards and “Hospital at Home” models are transforming NHS care, but designing them often stalls due to the complexities of accessing real-world patient data. How do we build predictive risk models or test clinical thresholds when live or mature patient data often isn’t available?
In this session, we showcase a collaborative project with NortHFutures, Teesside University, Newcastle University, and Hull and East Riding Frailty Hospital at Home Virtual Ward that solved this data deadlock. We developed an open-source, OMOP-based synthetic data generator specifically for virtual hospital scenarios. This tool creates believable, realistic patient populations (complete with realistic vital signs, symptom surveys and social deprivation markers) without utilising a real patient record.
We will demonstrate how this approach allows multidisciplinary teams to test intervention thresholds and explore healthcare inequalities in a safe-to-fail environment. Attendees will learn how synthetic data, mapped to the international OMOP standard, can accelerate the development of AI-driven decision support and ensure that new care models are safe, inclusive and grounded in reality from day one.
- Accelerating innovation: How to use synthetic data to design and test clinical pipelines in parallel with information governance processes, reducing project lead times.
- The Power of OMOP: Why using the Common Data Model (CDM) ensures AI models and dashboards are "plug-and-play" for live NHS environments.
- Modelling inequality: Practical methods for integrating deprivation and geography data to see how care outcomes vary across different communities.
- Open-source collaboration: How to access and implement the virtual ward generator for your own Trust or integrated care system.
