It’s the data, stupid! How Real World Data and health outcomes can revolutionise pharmaceutical development and healthcare systems
No other item of healthcare expenditure has been so thoroughly assessed when it comes to safety, effect and performance as pharmaceutical products. For decades, the clinical trial has been the gold standard of measuring these attributes, and indirectly the value, of pharmaceuticals.
Both the EU and US regulatory agencies demand ever increasing documentation on the performance of new drugs, from the relatively small scale phase 1 trials testing the safety profile of new molecules to the large phase 3, randomised controlled trials (RCTs).
With the results from the Clinical Trials, truckloads full of data, the pharmaceutical company could apply for marketing authorization, and then for a decision on pricing and reimbursement (the latter often requiring more studies proving cost-effectiveness, added therapeutic benefit or socio-economic value).
Clinical trials are, by nature and regulation, conducted in controlled circumstances. Patients are recruited according to certain procedures, the experimental drug is administered according to strict protocols etc. Yet real, everyday clinical practice is not so well structured.
Not every diagnosis is correct. Clinical protocols are not always followed – sometimes for good reason. Not all drugs are taken by patients according to the prescription. Multi-morbidity, or multiple medicine-taking may impact the final outcome. The reality of treating and curing patients is much more complex and “messy” than the orderly world of clinical trials _ and most healthcare professionals (HCPs) know this.
For most pharmaceuticals marketed according to the traditional model, the structured collection of data stops as soon as they are introduced in the healthcare system. While systems for detecting adverse events exist, none are in place to determine if a drug is less or more effective than previously known.
So what to do?
Clinical trials continue to play a vital role, but the solution lies in combining clinical trial data with real world data (RWD). RWD is all health data that is generated and collected in real clinical practice, in hospitals and clinics all across healthcare systems, and also in the administrative files of payers and insurance companies, and even patients’ homes.
RWD may be collected in a structured way, for example when a pharmaceutical enjoys a conditional marketing approval and the regulator requires additional studies, or when HCPs collect data to compare the effect of different surgical procedures or measure the spread of resistant bacteria.
Traditionally, most RWD has been scattered across healthcare systems, without any possibility to bring it together. Nevertheless, considerable efforts are now being made to unearth and utilise all this information for new purposes.
Scientific progress has rendered Real World Data increasingly important for pharmaceutical development. Advances in genomics, make it possible to tailor make drugs for patients, drive the development of pharmaceuticals for rare diseases, making medicine more personalised.
This complicates the recruitment if patients for traditional phase 3 trials, so new models are needed, that introduce innovative medicines for a limited number of patients in areas of unmet medical need, based on earlier phase trials, and then systematically followed up in clinical practice and successively introduced to new groups of patients.
This model – often called adaptive pathways – means more information is collected on the actual effect of a pharmaceutical during the entire life cycle of a drug than under the traditional model. As information on the drug’s effects is continuously collected and analysed, earlier decisions on clinical guidelines, cost-effectiveness, pricing and reimbursement, might have to be re-assessed and adjusted.
RWD in healthcare is also driven by the digital revolution. As Electronic Health Records replace paper versions, disease registries become digitised, hospitals introduce electronic decision support systems and patients start collecting their own health data, collating and using this data is becoming a reality.
Yet barriers must be overcome, and investments made, so healthcare systems and stakeholders can reap the benefits of the RWD revolution. Data are not always generated to the same standards, and are therefore not comparable. E-health systems are not always compatible between hospitals or countries, and patients don’t all have a single, electronic health record that stores data in one place. Data collected for different purposes can’t always be linked together and regulation sometimes stops data transfer between systems.
These investments must be made, though, and barriers overcome, because the potential gains for patients and healthcare systems goes far beyond the effectiveness and value of pharmaceuticals. It concerns the entire healthcare system, and every single euro spent on health and wellbeing.
Today we see what is easy to measure, numbers of: hospital beds; doctors; cancer screenings; hospital readmissions for diabetes; and so on. The ability to scrutinise RWD will allow us to assess actual patient health outcomes, not only crude measures such as mortality and healthy life years, but granular information about quality of care and the quality of life.
Comparing different interventions in terms of patient health outcomes will enable healthcare managers and policymakers to take much more informed decisions on implementing clinical practice and resource allocation. This will lead to improved health outcomes and better value in healthcare. In an era of ageing populations, when healthcare budgets and social security systems are put under increasing pressure, this is a reform that European healthcare systems cannot afford to do without.7