New legislation and regulations that aim to improve data privacy and increase data portability present biopharma companies with new challenges but also commercial opportunities. The 21st Century Cures Act, which went into effect last summer, will enable and improve the portability of data. The federal government has created industry standards that allow patients to pull their health data in and out of systems. From physicians’ offices to tech companies, every organization that houses personal health information must comply with these industry standards.
As a result, healthcare systems will have a standard way of communicating and patients will have the ability to compile data from all their doctors, pharmacies, and health apps into a personal health portal. Additionally, if they can gain access to anonymized versions of this clean, organized data, biopharma companies will be able to improve their insights into patient treatment journeys and, ideally, boost access to life-saving therapies.
Alongside these measures designed to improve portability of health data, new privacy laws are popping up across the United States. In the wake of the implementation of the European Union’s General Data Protection Regulation, California, Colorado, and Virginia passed data privacy regulations. Several other states are currently considering privacy legislation. Biopharma companies need to prioritize data governance to stay compliant in these rapidly changing times.
For the patient, these regulations offer an opportunity to take more ownership over their personal health data. As a result, the data will become much more accurate and likely more expensive for biopharma companies to access. Therefore, biopharma companies will be under increased pressure to maintain compliance and make the most of their data investments.
Three Keys to Success in the New Data Landscape
As biopharma companies look at their data management strategies, three main areas of focus will allow companies to better adapt to this changing data landscape.
1. Data governance: Companies need to be able to track patient-level information, manage it, and then link it across sources and platforms. To properly do this, they must document the flow of data, including where each data set is coming from, where it lives within technology platforms, and what reports and tables it is being pulled into. This integrated strategy allows companies to get the most value out of various data sets in an organized, trackable, and compliant manner.
2. Master data management (MDM): A robust MDM strategy is key to handling identified and deidentified data. As privacy laws proliferate, it is critical that the commercial operations team creates business processes that allow it to quickly manage and isolate an individual’s data. For example, if a company deidentifies patient data and a patient requests a list of all the data the company has on them, the company must be able to quickly find each relevant data asset. And it is likely that biopharma companies will be audited on this capability in the future.
3. Data access control: Commercial teams need to place increased scrutiny on how data is accessed and used within their companies. A robust data access control strategy will help biopharma companies maintain compliance. The analytics team should work with stakeholders in IT and other departments to put in place controls that ensure each user only has access to the data sets needed to do his or her job.
A comprehensive data strategy and governance plan is the key to data management success in this new environment. Before launching any analytics initiative, the commercial team must first think through governance of data management processes and assets in collaboration with the company’s legal department. The companies that put in place this governance foundation will equip themselves to comply with privacy laws and capitalize on the commercial opportunities associated with improved data quality and portability.
Improved Data Quality Boosts Engagement with Physicians and Patients
With the increased quality and availability of patient-level data, biopharma companies can revolutionize pricing models by better showcasing real-world evidence to prove the value of their therapies. For example, if a company can track a patient from diagnosis through treatment and post-treatment, it can use the data to illustrate the impact its product had on a patient’s outcome—such as a shorter hospital stay or minimizing recurrence of symptoms.
Especially for rare disease and orphan drugs, which, due to their limited addressable patient markets tend to be high priced, the improvement in patient-level data could facilitate a shift to more outcomes-based pricing. Biopharma companies will be able to use the outcome of the therapy to determine the cost that is ultimately born by the patient and the payer. To do this, companies need to be able to closely track patients—which is possible thanks to the increased data portability driven by the Cures Act. By reducing the risk payers face, outcomes-based pricing will allow manufacturers to more easily bring novel, life-saving therapies to market.
With more robust, accurate patient-level data, companies can also execute more sophisticated patient-journey tracking. For example, instead of just looking for a specific diagnosis code, the commercial team could monitor several pieces of information—such as specific symptoms and subsequent tests ordered—to identify potential patients. This information can then be used to improve digital promotion efforts. With a more accurate view of patient journeys, commercial teams can optimize how and when they engage with prescribing physicians through a mix of promotional channels.
Another commercial impact of improved patient-level data quality is the opportunity for biopharma companies to conduct more accurate, sophisticated forecasting. With more detailed data in hand, companies can use realistic values (instead of educated guesses) as levers in a forecast model or leverage machine learning-enabled models that can better utilize this detailed data. They can also better identify cause-and-effect relationships and improve modeling confidence.
Get More Out of Your Data Investment
As patients take more ownership of their health data, the name of the game for biopharma companies is value. Companies must have thorough data management and governance strategies to get the most value out of increasingly expensive patient-level data. And commercial teams need to use this data to drive more value for patients—from showcasing real-world evidence to more quickly and easily reaching patients with life-saving therapies.
New privacy regulations and the Cures Act will have a major impact on companies’ commercialization efforts. But the commercial teams that prepare today will position themselves to generate more long-term value from their data investments.