BIOMEDICAL INFORMATICS
DESIGN AND IMPLEMENTATION OF A COMPUTERIZED INFORMATICS TOOL TO FACILITATE CLINICIAN ACCESS TO A STATES 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 enterprises electronic health record (EHR) system, using an application-programming interface (API) supplied by the states 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 Centers 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 users 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, Pearsons 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.
| Identifer | oai:union.ndltd.org:VANDERBILT/oai:VANDERBILTETD:etd-03152013-210331 |
| Date | 08 April 2013 |
| Creators | White, Steven John |
| Contributors | Dario Giuse, Dominik Aronsky, Ian Jones |
| Publisher | VANDERBILT |
| Source Sets | Vanderbilt University Theses |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.library.vanderbilt.edu/available/etd-03152013-210331/ |
| Rights | restrictone, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Vanderbilt University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
Page generated in 0.0018 seconds