Prescription Drug Monitoring Programs to Curb Prescription Drug Abuse: Examining the Components of Program Efficacy

Conclusion

Overall, PDMPs are on the right track. Considering that less than half of all states even had one 10 years ago, the trajectory is promising. Now that 49 states do, however, it is increasingly important to determine which components of PDMPs positively influence efficacy. Unsolicited reporting is one such vital component. PDMPs with unsolicited reporting have a 10% lower rate of controlled substance prescription than PDMPs without. Furthermore, states such as Wyoming have been able to use unsolicited reporting systems to cut down on doctor shoppers and boost awareness of the program.

Another crucial component of PDMP efficacy is PMIX compatibility. States not already on the information exchange should take the steps necessary to join it, and states already on it should ensure that they maintain the most recent version of ASAP reporting standards. Additionally, a nationwide discussion between PDMP administrators is necessary in order to solidify the threshold for doctor shopping. Once these steps have been taken, it removes the possibility for doctor shoppers to simply cross state lines to circumvent the triggering of red flags.

The final aspect of PDMP efficacy is that data reporting and collection intervals need to be as short as possible. By cutting interval time, the doctor-shopping window is reduced and emergency departments have a new tool for diagnosing and treating patients. British Columbia offers substantive evidence for the advantage of real time reporting, and, as Oklahoma has shown, points of purchase programs are attainable. Moving forwards it is imperative that PDMPs do more than simply exist– they need to work. Unsolicited reporting, PMIX compatibility, and real time reporting are tools that will help ensure they are capable of doing so.

---

References

Boscarino, J.A., Rukstalis, M., Hoffman, S.N., Han, J.J., Erlich, P.M., Gerhard, G.S., & Stewart, W.F. (2010). Risk factors for drug dependence among out-patients on opioid therapy in a large US health-care system. Addiction, 105, 1776–1782. doi: 10.1111/j.1360-0443.2010.03052.x

Advertisement

Budnitz, D.S., Pollock, D.A., Weidenbach, K.N., Mendelsohn, A.B., Schroeder, T.J., & Annest, J.L. (2006). National Surveillance of Emergency Department Visits for Outpatient Adverse Drug Events. JAMA. 296(15), 1858-1866. doi: 10.1001/jama.296.15.1858

Center for Disease Control and Prevention. (2012, July). Law: Doctor Shopping. Retrieved from http://www.cdc.gov/homeandrecreationalsafety/Poisoning/laws/dr_shopping.html

Center for Disease Control and Prevention. (2013a, July ). Policy Impact: Prescription Painkiller Overdoses. Retrieved from http://www.cdc.gov/homeandrecreationalsafety/rxbrief/

Center for Disease Control and Prevention. (2013b, December). New CDC Vital Signs: Prescription Painkiller Epidemic Among Women. Retrieved from http://www.cdc.gov/media/dpk/2013/dpk-Prescription%20drug%20overdose.html

Cichon, C. (2013). Pill Mills and Pain Management: Legislation and Enforcement [Presentation slides]. Retrieved from http://www.une.edu/com/cme/upload/Pill-Mills-and-Pain-Management-Pain-Week-2013cichon.pdf

Clark, T., Eadie, J., Kreiner, P., & Strickler, G. (2012). Prescription Drug Monitoring Programs: An Assessment of the Evidence for Best Practices. Retrieved from http://www.pewhealth.org/uploadedFiles/PHG/Content_Level_Pages/Reports/PDMP%20Update%201-31-2013.pdf

Dormuth, C.R., Miller, T.A., Huang, A., Mamdani, M.M., & Juurlink, D.N. (2012). Effect of a centralized prescription network on inappropriate prescriptions for opioid analgesics and benzodiazepines. CMAJ, 184, 852–56. doi: 10.1503/cmaj.120465

Doland, P. (2012, September 20). Study quantifies drug monitoring database’s effect on opioid prescriptions. Amednews. Retrieved from http://www.amednews.com/article/20120920/business/309209997/8/

French, M. (2014, February 11). Prescription drug database gets first-round approval in Missouri House. St. Louis Post-Dispatch. Retrieved from http://www.stltoday.com/news/local/govt-and-politics/political-fix/prescription-drug-database-gets-first-round-approval-in-missouri-house/article_8623bf88-5c39-53af-a9fc-5743107c9a40.html

Hopkins, D. (2012, July). Prescription Drug Monitoring Program Interstate Data Sharing [Presentation slides]. Retrieved from http://www.ncja.org/sites/default/files/documents/Hopkins_Prescription_Drug_Monitoring_Program.pdf

Advertisement

IEEE Computer Society. (2000). IEEE Recommended Practice for Architectural Description of Software-Intensive Systems: IEEE Std 1472000. Retrieved from http://www.ibm.com/developerworks/rational/library/feb06/eeles/

Jones, C.M., Mack, K.A., & Paulozzi, L.J. (2013). Pharmaceutical Overdose Deaths, United States, 2010. JAMA, 309(7), 657-659. doi:10.1001/jama.2013.272

Lear, M. (2011, February 11). House gives initial approval to prescription drug monitoring program. MissouriNet. Retrieved from http://www.missourinet.com/2014/02/11/house-gives-initial-approval-to-prescription-drug-monitoring-program/

Paulozzi, L.J., Jones, C.M., Mack, K.A., & Rudd, R.A. (2011). Vital Signs: Overdoses of Prescription Opioid Pain Relievers — United States, 1999–2008. Morbidity and Mortality Weekly Report, 60(43), 1487-1492, Retrieved from http://www.cdc.gov/mmwr/pdf/wk/mm6043.pdf

Lammers, E., Adler-Milstein, J., & Kocher, K. (2013). Does Health Information Exchange Reduce Redundant Imaging? Evidence From Emergency Departments. Medical Care, 1, doi: 10.1097/MLR.0000000000000067

Mahon, W. (2007). Prescription for Peril: How Insurance Fraud Finances Theft and Abuse of Addictive Prescription Drugs. Coalition Against Insurance Fraud. Retrieved from http://www.insurancefraud.org/downloads/drugDiversion.pdf

McDonald, C. & Carlson, E. (2013). Estimating the Prevalence of Opioid Diversion by “Doctor Shoppers” in the United States. PLoS ONE. 8(7), doi:10.1371/journal.pone.0069241

Michael, B. (2013). Prescription Drug Monitoring Program [Presentation slides]. Retrieved from http://adaa.dhmh.maryland.gov/Documents/SDAACWeb/Minutes/PrescriptionDrugMonitoringProgram_PDMP.ppt

National Association of Boards of Pharmacy. (2012, May 23). NABP PMP InterConnect Committed to PMIX Architecture Compliance; BJA to Immediately Release Funding for PMP InterConnect Participants. Retrieved from http://www.nabp.net/news/nabp-pmp-interconnect-committed-to-pmix-architecture-compliance-bja-to-immediately-release-funding-for-pmp-interconnect-participants

Oklahoma Department of Mental Health and Substance Abuse Services. (n.d.) Fact Sheet on Prescription Drug Abuse, Misuse and Consequences. Retrieved from Oklahoma Department of Mental Health and Substance Abuse Services website: http://ok.gov/odmhsas/documents/PR%20RxAbuse-FactSheet.pdf

Oregon Prescription Drug Monitoring Program Center for Prevention and Health Promotion. (2012). Prescription Controlled Substance Dispensing in Oregon: October 1, 2011 – March 31, 2012. Statewide Data Report. Retrieved from Oregon PDMP website: http://www.orpdmp.com/orpdmpfiles/PDF_Files/Reports/Statewide_10.01.11_to_03.31.12.pdf

PDMP Center of Excellence. (2011). Trends in Wyoming PMP Prescription History Reporting: Evidence for a Decrease in Doctor Shopping? Retrieved from http://www.pdmpexcellence.org/sites/all/pdfs/NFF_wyoming_rev_11_16_10.pdf

PDMP Center of Excellence. (2014). Options for Unsolicited Reporting. Retrieved from http://www.pdmpexcellence.org/sites/all/pdfs/Brandeis_COE_Guidance_on_Unsolicited_Reporting_final.pdf

PDMP Training and Technical Assistance Center. (n.d.) PDMP Data Collection Interval. Retrieved from PMDP Training and Technical Assistance Center website: http://www.pdmpassist.org/content/pdmp-data-collection-frequency?order=field_frequency_data_collected_value&sort=asc

Reifler, L.M., Droz, D., Bailey, J.E., Schnoll, S.H., Fant, R., Dart, R.C., & Bartelson, B.B. (2012). Do Prescription Monitoring Programs Impact State Trends in Opioid Abuse/Misuse? Pain Medicine, 13(434–442). doi: 10.1111/j.1526-4637.2012.01327.x

Seppala, D., & Rose, M. (2010). The History of Opioids. In Prescription Painkillers: History, Pharmacology, and Treatment (pg. 17-28). Center City, MN: Hazelden.

Simeone, R. & Holland, L. (2006). An Evaluation of Prescription Drug Monitoring Programs. Retrieved from National Criminal Justice Reference Service Website: https://www.ncjrs.gov/app/publications/abstract.aspx?ID=238896

Substance Abuse and Mental Health Services Administration. (2011). Results from the 2010 National Survey on Drug Use and Health: Summary of National Findings, NSDUH Series H-41, HHS Publication, 11(4658), Retrieved from http://www.samhsa.gov/data/NSDUH/2k10NSDUH/2k10Results.pdf

Substance Abuse and Mental Health Services Administration. (2012). Results from the 2011 National Survey on Drug Use and Health: Summary of National Findings. Retrieved from SAMHSA website: http://www.samhsa.gov/data/nsduh/2k11results/nsduhresults2011.pdf

Substance Abuse and Mental Health Services Administration. (2013, January). The NSDUH Report: State Estimates of Nonmedical Use of Prescription Pain Relievers. Retrieved from SAMHSA website: http://www.samhsa.gov/data/2k12/NSDUH115/sr115-nonmedical-use-pain-relievers.htm

The American Society for Automation in Pharmacy. (2014, April 13). ASAP News. Retrieved from ASAP website: http://www.asapnet.org/home.html

United States Department of Justice, Bureau of Justice Assistance. (n.d.) Prescription Drug Monitoring Programs: Critical Information Sharing Enabled by National Standards. Retrieved from https://www.bja.gov/Programs/PMIXArchitecture.pdf

United States General Accounting Office. (2002). Prescription Drugs State Monitoring Programs Provide Useful Tool to Reduce Diversion. Retrieved from http://www.gao.gov/assets/240/234687.pdf

Vogt, D. (2012). ‘Real-Time Reporting’ Paving the Road and Avoiding and Potholes [Presentation slides]. Retrieved from PDMP Center of Excellence website: http://www.pdmpexcellence.org/sites/all/pdfs/pmp_real_time_national.pd

Vogt, D. (2013). A Foundation for Choice: PMIX Architecture. [Presentation slides]. Retrieved from ASAP website: http://www.asapnet.org/files/January2013/ASAPJan13_Pres02_Vogt.pdf

Von Korff, R. (2013). Health Care for Chronic Pain: Overuse, Underuse, and Treatment Needs: Commentary on: Chronic Pain and Health Services Utilization-Is There Overuse of Diagnostic Tests and Inequalities in Nonpharmacologic Methods Utilization? Medical Care. 51(10), 857-858. doi: 10.1097/MLR.0b013e3182a53db3

Weisberg, A., Strub, R., & Garcia, C. (1983). Episodic Loss of Conscious. In Essentials of Clinical Neurology (pp. 8-1 to 8-13). Baltimore: University Park. Retrieved from: http://tulane.edu/som/departments/neurology/programs/clerkship/upload/wch8.pdf

White, A.G., Birnbaum, H.G., Schiller, M., Tang, J., & Katz, N.P. (2009). Analytic Models to Identify Patients at Risk for Prescription Opioid Abuse. American Journal for Managed Care, 15, 897-906. Retrieved from: http://www.ajmc.com/publications/issue/2009/2009-12-vol15-n12/ajmc_09dec_white_897to906/1#sthash.Xi3jWake.dpuf

Whoriskey, P. (2012, December 30). Rising painkiller addiction shows damage from drugmakers’ role in shaping medical opinion. The Washington Post. Retrieved from http://www.washingtonpost.com/business/economy/2012/12/30/014205a6-4bc3-11e2-b709-667035ff9029_story.html

Zee, A. (2009). The Promotion and Marketing of OxyContin: Commercial Triumph, Public Health Tragedy. American Journal of Public Health, 99(2), 221-227. doi: 10.2105/AJPH.2007.131714