By Heather Von Allmen
Arthur Conan Doyle’s ubiquitous fictional detective Sherlock Holmes once said, “It is a capital mistake to theorize before one has data.” Indeed, good data can make or break many healthcare organizations — including pharmaceutical companies. In particular, anonymized lab data can prove useful to these companies for many reasons:
- It can help them evaluate testing behaviors. When a pharmaceutical product is approved for use, prescribing information includes details about how the medicine is to be prescribed. In some cases, physicians need to monitor certain health indicators — for example, liver and kidney function — routinely while the patient is taking the drug, and adjust dosing or therapy appropriately. By linking diagnostic lab results with other anonymized Real World Data, companies can understand if physicians are routinely testing patients and making proper adjustments to their therapy. This information can be used to determine if additional education is needed for physicians to ensure prescribing instructions are followed consistently, improving patient care.
- It provides additional insights into patient outcomes. The purpose of any given medication is to improve whatever condition precipitated the prescription in the first place. When pharmaceutical companies have access to longitudinal lab results linked with other Real World Data, they can see whether patients on their product have better outcomes, as evidenced by improved test levels and/or fewer complications, resulting in lower cost of care.
- It can show payers that the treatment is working. Ultimately, pharmaceutical companies want patients to be able to get access to their medications. The physician’s decision to prescribe and patient’s willingness to fill the prescription is driven by many different factors, including the willingness of insurance companies to cover the cost of a given medication. If a pharmaceutical company can provide evidence, via an outcomes study that includes diagnostic test results, that their medication works better than other options on the market, that can mean patients get access to a medication that can improve their health.
Prognos can work with companies to extract the lab results they need to monitor testing and measure patient outcomes and link it to a variety of prescription and claims data sources. Additionally, through its artificial intelligence (AI) capabilities, Prognos can identify correlations in the data that humans would not be able to see, and use those correlations to help pharmaceutical companies evaluate their product’s efficacy more easily. Not only does Prognos extract the data, but it can also organize that information so that it is usable and useful. Sherlock Holmes would be proud.