Finger on device

The vast majority of physicians and healthcare institutions now capture patient data in electronic health records (EHR), creating an immense storage of individual patients, and population health. And that resource is growing every day. Experts estimated, that as 2015, the average hospital was producing more than 665 terabytes of data, which is equivalent to 697,303,040 megabytes. This data give doctors instant access to more complete patient information which improves their ability to make the right treatment decisions quickly, eliminates errors, and adds efficiencies and costs savings that benefit the facility and the patients.

But what many biopharma leaders may not realize is how valuable EHR data can be to clinical research. These enormous data sets are being used to answer key research questions, inform trial design, and to improve patient recruiting. In 2010, for example, Penn Medicine used its Penn Research Trial Advisory app to recruit 200 patients from the ob-gyn department for infertility clinical trials in 2010. This represents an 87% increase in the number of physician-referred patients for clinical trials compared to the 4-month period before the new EHR recruitment procedure. More recently, in 2015 researchers at Johns Hopkins University used EHR data to develop a model of 27 variables that correctly predicts septic shock in 85% of cases.

Using EHR data in clinical research has also gained the attention of the US Food and Drug Administration (FDA). Last June the Center for Drug Evaluation and Research (CDER) announced interest in considering the use of electronic health records with electronic data capture (EDC) in order to improve clinical trials for new and investigational drugs. Test projects would "ideally test the use of a standards-based technology solution to enable the collection of related healthcare and clinical research information within a single system and workflow," according to the notice. Stakeholders could include EHR and EDC vendors, academic medical centers and others.

This should be capturing the attention of biopharma companies who are interested in finding new ways to improve recruiting, inform post market research, and to unearth real world evidence that can be used to improve the time, cost and efficiency of their projects.

For biopharma companies embarking on new studies, or continuing work on existing efforts, here are four ways that EHR databases may be able to support their efforts.

  1. Prove the conversion from efficacy to effectiveness in real-world settings. Biopharma teams can use EHR data to run research studies comparing outcomes of interest across various treatment groups without requiring any interaction between the patient and sponsor. By observing standard of care practices we are able to see if results in the real-world match clinical trial outcomes, where the patient population may less representative of the total population with the underlying disease.  

  2. Answer research questions around medical exposure among sub-populations of patients, such as pregnant women, or patients with diabetes. EHR databases have longitudinal data that can capture when exposure to particular medicine occurs, how it aligns with other healthcare events, and what are the patient outcomes. All of this provides insight into the impact of associated exposure before and after a medical event, as a way to track the long term safety of a drug.  

  3. Track market uptake. EHR databases are frequently updated, giving researchers near real-time evidence regarding how quickly a new drug is prescribed, who is prescribing it, whether it is being prescribed strictly for on-label use, and whether the prescription trends continue.  

  4. Get a broad picture of total healthcare utilization. When EHR data is linked to other data sources, like pharmacy refills, payer data, and hospitalization data, it can provide insight to support a variety of important healthcare considerations. These include insights into health economics, benefit/risk ratios for specific treatments, the true cost benefit of a treatment compared to existing therapies, and whether patients are adhering to prescribed medicines. All of these data can be used to demonstrate the real world value of a drug and to link clinical trial data to real world outcomes.

These are all complex question scenarios for EHR databases that require analytics skills to deliver, but the benefits of these inquiries are clear: EHR data is a valuable tool that can be used to deliver real-world evidence in support of clinical and market research. The companies that take advantage of these tools will gain speed and confidence in the validity of their results.