The challenge is the need for a large patient pool because of the number of patients that end up being ineligible for trials due to pre-existing diseases or medications. The traditional process of accruing enough patients can take over a year. Big data saves time and money by providing the tools to more accurately match qualified patients to trials.
Moffitt is in discussions with other health centers to combine data and possibly set up a national research information exchange.
"This certainly isn't something one system can do effectively," Hulse said. "There aren't a sufficient number of patients in total. You need to combine data from many different institutions."
But combining data from multiple institutions presents its own set of challenges, mainly a lack of standard data formats and definitions across many data systems and sets, Griffin Vincent said. For example, when identifying a patient as male or female, one system might define this data field as "sex," while another might define it as "gender." The large amount of unstructured data also presents problems: discrete data fields can be mined much more easily than written notes.
Data that can advance clinical trials includes EHRs, practice management systems, payer databases, pharmacy databases and patient-reported data. The EHRs include all clinical data: diagnoses, procedures, labs, medications and adverse events. Practice management systems include scheduling and visit information, claims submissions and insurance information.
PatientPoint's partnership with Miami Children's has the potential to accelerate the recruitment, enrollment and retention of patients in clinical trials. Miami Children's has more than 200 ongoing clinical trials with multiple pharmaceutical companies as well as government-sponsored research. PatientPoint's technology can integrate diverse data sets to flag patients that have a high probability of qualifying for specific trials. It also uses e-signatures to obtain patient consent as approved by the Institutional Review Board, another time-saving measure.
But access to all of this data can get complicated.
"Getting the right approvals and consents to use the data from different sources for the research is complex but imperative to maintaining ethical and legal rights, and ensuring data privacy and security," Griffin Vincent said.
There is always room for improvement, but the use of big data in clinical trials is starting to transform the way trials are conducted.
"There's a lot of wasted time in clinical trials," Hulse said. "If we can mine the data in the right way, it's good on the patient side because it can get drugs to the market much faster, and it's good on the business side because it saves the pharmaceutical companies money."