Established in nearly every state across America, prescription drug monitoring programs (PDMPs) are used to track the prescribing, dispensing and use of opioids and other controlled substances. At its core, PDMP databases help providers identify patients at-risk for prescription drug abuse and facilitate opportunities for intervention, medication reconciliation and reduction of controlled substance prescribing.
As an electronic database for tracking and surveying opioid and other controlled drugs, state PDMPs rely on electronically transmitted patient data such as prescription logs, billing records, patient profiles and counseling records. However, for PDMPs to thrive, the data collected, stored and analyzed must be exceedingly reliable and complete.
Now that opioid overdoses are the fifth leading cause of deaths in the U.S., providers and state health authorities are under increased pressure to rely on PDMPs for informed decision-making and effective care management. If we are to curb the nation's opioid crisis, the information must be consistently and correctly matched to the right patient.
PDMPs cite poor data quality as a leading challenge to patient record matching
Over the past decade, managing millions of patients’ digitized medication records has been a significant endeavor, according to pharmacy and PDMP administrators who gathered in September to discuss patient matching efforts at a symposium hosted by ONC. Much of the patient information pharmacy systems receive is erroneous and incomplete, containing a number of demographic inaccuracies for such elements as addresses, birth dates and phone numbers.
Additionally, records aren’t always updated when an individual moves or remarries, or when patients visit multiple providers in the same community, creating a number of duplicate records. Many patients also receive care in different states which increases the need to exchange patient data across state lines.
According to a 2019 state by state survey from the PDMP Training and Technical Assistance Center (TTAC) presented during the ONC symposium, most states are struggling to maintain the integrity of patient medication records.
When asked to identify the barriers to patient matching within their PDMP, the majority—53 percent—cited data quality issues and the lack of insight into matching methodology in use. Of the remaining responses, 30 percent cited lack of understanding of the matching process, 23 percent identified limited data elements and 19 percent pointed to a lack of available resources.
Patient matching and interoperability are critical aspects for PDMPs, and many continue to struggle with fragmented information and lack of substance use history in an individual’s health record. For physician practices located near a neighboring state boarder, the issue becomes even more difficult since the information available about an individual’s “in-state” activity may only represent a fraction of their prescription use. In identifying issues that hinder interstate patient matching, 55 percent cited both data quality issues and the lack of insight into matching methodology in use.
Technology considerations for improving PDMP patient matching
As healthcare systems focus more intently on promoting public health, the need to build a comprehensive PDMP database with integrated patient identification and matching solutions will become paramount. Automated patient ID matching tools like enterprise master patient indexes (EMPIs), for example, are rapidly shifting from a line of defense against duplicate records to the default approach for interoperability and enterprise-wide connectivity. Enterprise identity management solutions can also provide extensive data stewardship capabilities to maintain the integrity of the patient record and minimize manual remediation efforts.
A comprehensive, accurate and up-to-date PDMP that is integrated with electronic health records and is easily accessible can help providers make care interventions and identify fraud. PDMP administrators that seek to create an accurate control substance surveillance system and are hard pressed to manage large volumes of information, can turn to enterprise identity management platforms to unify and maintain the accuracy their data.
Using enterprise identity solutions in conjunction with prescriptive analytics and machine learning can help organizations leverage prescription data to anticipate risk and identify patterns with a high probability of abuse. Experts can then focus their time evaluating actionable insights rather than sifting through mines of data to intervene with personalized treatment plans.
Other technologies like identity verification tools to cross-check individuals against billions of public records, and blockchain to aggregate patient records into a single longitudinal entity can also support PDMP systems and safeguard against fraud.
As PDMPs design their databases for the future, the hope is they’ll utilize enterprise-grade identity management technology to instill trust in their data, enable a comprehensive prescription history and enhance controlled substance surveillance nationwide.