Design and implementation of a computerized informatics tool to facilitate clinician access to a state’s prescription drug monitoring program database

Abstract

BIOMEDICAL INFORMATICS

DESIGN AND IMPLEMENTATION OF A COMPUTERIZED INFORMATICS TOOL TO FACILITATE CLINICIAN ACCESS TO A STATE’S PRESCRIPTION DRUG MONITORING PROGRAM DATABASE

STEVEN JOHN WHITE

Thesis under the direction of Professor Dario Giuse

Within the past decade, prescription drug abuse has emerged as a nationwide epidemic, with opioid-related poisoning deaths more than tripling since 1999. In an effort to bring this public health crisis under control, 43 states, including Tennessee, have enacted prescription drug monitoring programs (PDMPs), computerized databases of DEA-controlled substance prescriptions filled at pharmacies within the given state. Such programs have been found to be effective in curbing prescription opioid abuse by alerting prescribers to aberrant prescription-filling activity. However, they are commonly underutilized and have workflow barriers that impede clinical use. Ideally, PDMP queries could be generated seamlessly from within a medical enterprise’s electronic health record (EHR) system, using an application-programming interface (API) supplied by the state’s PDMP vendor. However, the enabling legislative language currently prohibits such access. Therefore, we developed and evaluated a Perl software program activated from within Vanderbilt University Medical Center’s EHR patient chart to send the properly coded/formatted user and patient-demographic information packets to the Tennessee PDMP website, without the use of an API. The program parses the returned data file for important prescription information and displays the filtered information to the user. By allowing the query to occur in the background, the user’s tether time to the computer is decreased from 3 minutes to 10 seconds per query.

During the evaluation phase, we used a quasi-experimental intervention design with two alternating 2-week control and intervention periods. Twenty-eight ED attending physicians participated in the study and queried the PDMP at their clinical discretion. During integrated PDMP query tool availability, 5.9 % (169/2844) of emergency department patients were screened compared with 2.2 % (62/2786) during periods when the tool was not available (p<0.001, Pearson’s Chi square). Data was not viewed in 20% of integrated tool assisted queries. The EHR-integrated PDMP query tool was well regarded by study physicians as an enhancement to workflow.