A year after launching a new oncology therapy, one manufacturer wanted to map the patient journey to identify access barriers. To build a longitudinal patient dataset, the company purchased both open and closed claims data from multiple vendors, along with transactional records. This patient data was then de-identified and linked via a third-party token engine. To gain a true end-to-end view of drug utilization, however, the company needed the ability to:
Challenge
In theory, the pharma company could now track a patient’s medical journey over time. But in practice, the tokenized data was insufficient, as it lacked plan-level details. While the team could see patients’ physicians, medications, and approved/denied claims, they had no visibility into their specific insurance plans.
Without that crucial information, there was no way to track how the patient’s formulary status and level of coverage impacted their care journey. The company realized that for more granularity, it needed to anchor its disparate data to MMIT’s trusted payer hierarchy.
Solution
The company used MMIT’s Data Enrichment service to augment its longitudinal records, adding verified plan-level context to all open, paid and pending claims. First, MMIT matched the company’s tokenized patient records against its data assets to identify patients that existed in both datasets. For overlapping patients, the service appended plan hierarchy attributes—including plan ID, payer, channel, formulary, tier and coverage status—to records that lacked this data.
Outcome
The Data Enrichment service also flagged discrepancies between the source data and MMIT’s plan data, enabling the manufacturer to determine which record should serve as its source of truth.
Now, the manufacturer has full visibility into its patients’ complex medical journeys. Its market access team is using this intelligence to identify specific cohorts subjected to restrictive formulary tiers. Armed with real-world evidence of how payer restrictions impact outcomes, they can now prioritize payers for engagement as they work to lift these restrictions. In the meantime, the company’s field teams are also using this intelligence to drive prescriber pullthrough campaigns.
Without plan-level information, organizations cannot accurately understand how formulary status, coverage restrictions and payer policies influence patient outcomes and treatment utilization.
MMIT matches tokenized patient records to its proprietary payer data and appends verified attributes such as payer, plan, channel, formulary tier and coverage status.
By connecting patient records to trusted payer intelligence, manufacturers can identify access barriers, prioritize payer engagement and better understand the relationship between coverage and utilization.
Get access to our newest use case by filling out the form below.
