Public Funding for Outcomes Based Healthcare Ltd

As a business whose main value lies in IP/discoveries from R&D rather than current sales/cashflow, it is vital to secure expert advice on both protection of IP, and how that needs to be handled within our ownership and employee structure. This is both to reflect relative contributions to IP creation within the business, but also to ensure an IP strategy which is internally consistent with business ownership and employee incentivisation (eg. through use of EMI option schemes).

**Background:** Outcomes Based Healthcare (OBH) is currently working on **COVID-19 'vulnerable' population analysis**, identifying cohorts 'at risk' of severe illness. This includes two key groups identified by the CMO/NHS Digital: those 'At High Risk' (c.1.5 million) on the 'Shielded Patient List', and those normally 'At Risk' of flu (c.19 million). This project builds on a programme of work undertaken for a different purpose (**'Bridges to Health' national population segmentation**), over the past 12 months, in conjunction with NHS England (NHSE), Public Health England (PHE) and Arden & GEM Commissioning Support Unit (AGEM). Using linked, longitudinal, nationally held data (less opt-outs), those 'At risk' of severe illness from COVID-19 can be identified and quantified, at local, regional and national levels, using relevant conditions in the existing segmentation model. **Project:** OBH will evaluate relative risk of different conditions/risk factors on a) admission to hospital b) admission to ITU and c) mortality relating to COVID-19\. Development of a COVID-19 Mortality Risk Score (CMRS) and COVID-19 Admission Risk Score (CARS) will enable the risk profile of local areas to be accurately assessed according to the latest emerging evidence. This analysis would also support understanding of the effect of age on COVID-19 complications independent of comorbidities, thus providing insight into genuine risk factors versus confounding variables. Given time needed to develop a vaccine, this work will also inform interim management of, and exit from, lockdown restrictions. It may also be used to track indirect health outcomes arising from the pandemic. **Innovation:** Rapidly repurposing the robust foundations of an existing national person-centred data model developed over a number of years, this work reflects an innovative approach to supporting the COVID-19 response, enabling rapid analysis within the bounds of OBH's existing data access arrangements and privacy safeguards. Development of COVID-19 Risk Scores would inform predictions of future patterns and trends of infection, whilst also providing insights to inform the exit strategy from the current lockdown restrictions in the UK. The flexibility of the model allows new risk factors and conditions to be incorporated in real-time as new evidence emerges. The outputs of the model can be rapidly circulated via several different methods, including the COVID-19 Health Data Research UK Slack Channel, as well as via the FutureNHS Platform. As this work is built on standard international coding terminology (ICD-10 and OPCS), this work could be translated internationally to support other digitised health systems. **Extension for Impact Funding**: the way health systems respond to the Covid-19 pandemic is rapidly evolving, requiring OBH to adapt their support at the same pace. For instance: a) the clinical criteria for the vulnerable populations have evolved and recently have been amended by the government requiring additions to derive these from the source datasets. b) utilisation of condition information from the vaccine clinical trials became a priority so that OBH can support NHS England, as requested, with national prioritisation of administering Covid vaccines when they become available in due course c) over the summer, a group from Oxford University has developed an individual Covid risk score, based on a subset of national primary care records. The data used for this risk score is different from the data being used for this project. However, both our work and the Oxford work can be used for cross validation to refine and improve our understanding of the conditions putting people most at risk of Covid-19

‘Real World Outcomes’ : Feasibility study exploring adaptation of OBH Outcomes Platform to enable new innovations, drugs, devices, technologies to measure their impact on people, through real-time, population-level outcome measurement. Understanding which interventions impact people’s outcomes, using retrospective and Real World Evidence, enables a more precise and stratified approach to treatment. This also enables new reimbursement models for new technologies that improve people’s outcomes. OBH are experts in defining and measuring health outcomes. We offer specialist advice, tools and technology to help commissioners and providers make a reality of value-based healthcare strategies and outcomes-based contracts, tailored to specific populations and pathways. Our key focus is to shift measurement and reimbursement away from solely treating illness, towards improving people’s health.

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Healthcare costs are rising faster than our ability to pay them. According to the ONS, the UK’s total healthcare expenditure nearly tripled over the past 15 years, rising from just over £50bn in 1997 to nearly £150bn in 2012, with the management of chronic conditions accounting for the highest proportion of these costs. Current healthcare systems manage individuals with chronic conditions based on the experience of what tends to work best for most of the people, most of the time. Measuring and paying providers on health outcomes is fundamentally new in global health systems. Many outcomes can only be measured from patients themselves. Outcomes Based Healthcare (OBH) is at the forefront of using data science to understand chronic disease progression at the individual level. Knowledge about specific behaviours, lifestyles and environments can reveal insights about how an individual’s condition is most likely to progress and impact on their health outcomes. OBH is creating a new technology to make acquiring this knowledge as easy as carrying your phone in your pocket. OBH aims to radically change how we collect patient-reported outcomes. By removing barriers to actively reporting outcomes data and by engineering novel machine learning techniques between reported and passively collected data related to how you go about your daily life and our behaviours, OBH is establishing a new, more precise way to track both outcomes and the behaviours that affect them. This tool has the potential to help healthcare move beyond the costly and not particularly effective status quo of measuring and paying based on activity and processes of care, to one where a healthcare economy can truly understand how the impacts of their services, interventions and treatments are affecting what really matters most to people around their health.

Can a better understanding of your personal characteristics help unlock new insights into disease? Could your credit score, your income and your shopping habits help predict whether you are about to have a heart attack? This project focuses on people with diabetes- specifically looking at whether linking big atypical, non-health data sets with health data can reliably predict who is likely to benefit from a health intervention or who is not. Outcomes Based Healthcare, Big Data Partnership, Camden Clinical Commissioning Group and the University of Surrey are working together to research exactly these questions over the next two years. These insights will enable clinicians to understand whether their preventative measures or interventions are likely to be effective, ineffective, wasteful, or even harmful. This moves from a disease-based to a personalised, data-driven health system. To paraphrase Aristotle, it is really important to understand what sort of person has a disease, in order to more precisely understand what sort of disease a person really has. Data science holds the answer to this ancient riddle.