Knowledge is power when it comes to healthcare data

Changes in who owns and uses healthcare data are transforming the way the pharmaceutical industry develops, prices and demonstrates the value of its products. Oxford PharmaGenesis COO Richard White talks to Inflexion about the evolution of data management and its implications for the sector.


Who owns data in the healthcare sector?

The ownership of data has changed. Until recently, it was the pharmaceutical industry that mostly controlled the creation and communication of data on its own assets. Healthcare systems would pay pharma upfront for these products (which were typically low unit-cost, and so had a manageable budget impact) and receive the value later.

Now, with these healthcare systems becoming more effective at collecting and analysing their data, the balance has shifted; within a few years of launch, they will have more data on a new asset than the originator pharmaceutical company. At the same time, pharmaceutical R&D has moved towards high unit-cost, low-volume treatments, such as orphan drugs, precision medicines and gene therapy. Faced with these potential ‘budget busters’, healthcare systems want to pay the pharmaceutical industry for the value at the time it is received. This means new value- and outcomes-based payment models, as well as revised approaches to pricing.

Examples of increasing healthcare system usage of real-world data can be seen around the world. In the UK NHS, the Salford Lung Study was a landmark example of a pragmatic clinical trial to demonstrate treatment effectiveness in a real-world setting. In the US healthcare system, Amgen’s Repatha secured preferred placement on the Harvard/Pilgrim Health Care formulary in exchange for rebates if defined real-world outcomes were not met. In Europe, CatSalut in Spain has developed health IT tools to link data sets for individual patients in order to implement outcomes-based contracts with pharmaceutical companies.

How is technology changing the health data landscape?

The potential for data science to transform healthcare is immense. Insights from real-world data – including electronic health records and real-time information from apps and wearables – could be used to identify people at risk of a condition, identify which interventions are most likely to yield a positive outcome, monitor signs and signals that the intervention is succeeding and thus demonstrate value to the healthcare system. As a result, the pharmaceutical industry, technology companies and healthcare systems are converging at the level of real-world data, artificial intelligence and predictive analytics.

Healthcare systems are embracing these potential benefits. In the US, the Artificial Intelligence Health Outcomes Challenge run by CMS (Centers for Medicare & Medicaid Services) aims to develop algorithms to predict health outcomes from Medicare fee-for-service data; similarly, the AHRQ (Agency for Healthcare Research and Quality) aims to use predictive analytics to forecast healthcare utilisation (e.g. hospital inpatient utilisation and average length of stay).

In order to be part of this evolution and to shape how the data and technology are used, many pharmaceutical companies have partnered with companies that collect or analyse data. Examples include Novo Nordisk and IBM Watson Health, who created a ‘virtual doctor’ for people with diabetes, and the collaboration of pharmaceutical giant Roche with Flatiron Health – with Roche ultimately acquiring the oncology-focused electronic healthcare record firm in February 2018 for US$1.9 billion.

From a reputational perspective, the pharmaceutical industry is arguably better placed than most technology companies to manage and analyse real-world patient data. Because healthcare has always been so highly regulated, pharma has an excellent track record of ensuring that patient data are kept private and used only for the original intended purpose. This contrasts markedly with some major technology companies whose misuse of consumer data was a major reason for the drafting of the GDPR in the EU.
How will data change the relationship between the pharmaceutical industry and healthcare systems?

Data science and technology companies are working with multiple stakeholders – pharmaceutical companies and healthcare systems alike – and so the pharmaceutical industry will no longer have control of the data, or how they are analysed. It’s a shift the industry needs to get accustomed to. 

And if it doesn’t? If pharma can’t ‘work nicely’ with healthcare systems, other models for interaction exist. Several US states are considering treating the pharmaceutical industry as a utility, creating upper limits for payments on a new drug. The principle that citizens have a basic right to, for example, electricity, and hence governments apply payment caps to assure its affordability, could also be applied to medicines developed by the pharmaceutical industry.

On the positive side, some of the changes that the industry needs to make are already afoot. Pharmaceutical Medical Affairs activities will increasingly engage with patients, physicians and pathways committees to demonstrate improved patient care and outcomes, and the more formal partnerships between Field Medical functions and payer decision-makers will aim to demonstrate value (e.g. reduced cost of care).

Richard White

Richard is Chief Operating Officer of Oxford PharmaGenesis, an independent HealthScience consultancy with more than 250 people worldwide that provides communications services to the global healthcare industry. Having joined the company in 2002, Richard led its expansion into multiple new sectors and offices, and was part of a management buy-out in 2013. Oxford PharmaGenesis won the Queen’s Award for Enterprise in 2015 and 2019, was named one of the 1000 Companies to Inspire Britain in 2017 and 2018, and has been included in the Pharma Fast 50 list of the fastest-growing privately owned companies in the UK for the past 2 years. 


Richard is a College Advisor to Green Templeton College, University of Oxford.