Prescription Drug Monitoring ProgramsPrescription Drug Monitoring Programs Peggy Kelley Thu, 10/25/2018 - 10:35 AM EDT
A prescription drug monitoring program (PDMP) is a statewide electronic database that tracks the prescribing and dispensing of opioid analgesics and other controlled substances in the state. The PDMP is housed by a specified statewide regulatory, administrative, or law enforcement agency, which distributes data to individuals who are authorized under state law to receive it, such as prescribers, pharmacists, law enforcement officers, and licensing officials (National Alliance for Model State Drug Laws [NAMSDL], 2009).
To decrease access to and the availability of opioids and other controlled substances by limiting their over-prescription
Across states, PDMPs can vary in a number of ways, for example:
- Which controlled substances (Schedules II–V) are tracked
- The agency that houses the database (health/regulatory, law enforcement, or administrative)
- Authorized users (prescribers, pharmacists, state licensing officials, and/or law enforcement)
- Registration and usage requirements
- Reporting style (proactive vs. reactive)
- Note: A reactive PDMP generates reports only in response to a specific inquiry made by a prescriber, dispenser, or other party with appropriate authority. A proactive PDMP identifies and investigates potential cases of misuse, generating unsolicited reports whenever suspicious behavior is detected.
- Prescribers use a secure website to access the PDMP in order to do the following:
- Check prescription histories prior to issuing new prescriptions
- Collect and enter prescription information for all applicable classes of controlled substances (Schedules II–V) (Clark, Eadie, Kreiner, & Strickler, 2012; Perrone & Nelson, 2012)
- Prescribers can also participate in training programs on the purpose of the PDMP and the importance of routinely consulting the database when prescribing opioids or other controlled substances (Clark et al., 2012).
- Note: As of August 2014, 48 states and Guam had operational PDMPs, while New Hampshire and the District of Columbia had statutory authority for PDMPs but had not yet operationalized their programs (Haegerich, Paulozzi, Manns, & Jones, 2014; NAMSDL, 2015).
- When electronic prescribing is not possible, prescribers use a serialized, tamperproof prescription form to help prevent forgeries and counterfeits (Clark et al., 2012).
- Note: Online accessibility (instead of access by mail or fax) results in higher rates of PDMP use by prescribers and pharmacists (Fleming, Chandwani, Barner, Weber, & Okoro, 2013).
Pharmacy workers use PDMPs in a number of ways:
- Submitting information on prescriptions dispensed, either in real time or no more than seven days from the date the prescription was dispensed (Clark et al., 2012; Perrone & Nelson, 2012)
- Recording that patients showed positive identification when picking up prescriptions and how patients paid for their prescriptions (including cash transactions)
- Checking for data on prescriber disciplinary action and patient lock-in status to ensure that the presented prescription is advisable to dispense
- Note: In law enforcement-governed PMDPs, healthcare provider use was lower than with PDMPs governed by health or pharmacy boards (Fleming et al., 2013).
Those responsible for regulation or administration of the PDMP must do the following:
Consider whether to require registration and/or use of the PDMP, for which users, and under what circumstances (Haffajee, Jena, & Weiner, 2015)
- Note: Haffajee et al. (2015) suggest that to encourage PDMP use, “policymakers should seriously explore and evaluate more positive approaches [instead of PDMP mandates], including pay-for-performance, malpractice discounts, or immunity from liability for prescribers who diligently use the systems” (p. 892).
- Integrate electronic medical records and Electronic Prescribing of Controlled Substances systems with PDMP data (Clark et al., 2012):
- As prescribers enter the name of a drug for e-prescription, the patient’s history from the PDMP automatically appears on the prescriber’s device
- As each e-prescription is sent to a pharmacy, a copy is routed to the PDMP
- When the e-prescription is dispensed, the PDMP matches the pharmacy’s dispensing record to the corresponding e-prescription from the prescriber to detect any unauthorized modifications; if using a proactive PDMP, the regulator or administrator reports the unauthorized modifications to the appropriate agency
- Limit access to information by pharmacists, law enforcement, prescribers, and other authorized users
- When conducting analyses, de-identify PDMP records to hide patient-level information while retaining linked individual records in a dataset (Clark et al., 2012)
- Note: The database contains patient-level data, transmitted in real time, through encryption, during the patient’s visit. A patient report includes prior controlled substance prescriptions, the substance prescribed (including generic name), the dose prescribed, the dispense date, the prescriber’s name, the pharmacy used, and the address(es) used by the patient (Baehren et al., 2010; Perrone & Nelson, 2012).
- Establish cross-state data-sharing agreements to limit “doctor shoppers” from crossing state lines to obtain more prescriptions
- Note: States need Memoranda of Understanding (MOUs) to make sure that data are shared fairly, securely, and in compliance with regulations. Questions to consider when creating an MOU (Finklea, Sacco, & Bagalman, 2014):
- How is the information to be reported?
- How will the relevant states use the information?
- What are the guidelines for data retention?
- If a data breach occurs, what are the state’s responsibilities?
- Are there conflict-resolution procedures?
- What are the consequences of data misuse?
- Establish a proactive PDMP, where possible, and follow proactive PDMPs’ best practices—for example, provide unsolicited reports to prescribers, dispensers, licensing boards, and law enforcement (PDMP Center of Excellence [COE], 2014)
- Determine criteria that the PDMP will use to identify risky behavior by a patient, a prescriber, or a dispenser that would cause the system to issue an unsolicited report, for example (PDMP COE, 2014):
- If a patient is prescribed opioids by four different prescribers and gets medications filled from four different pharmacies within a three-month time frame
- If a patient visits more than one pharmacy on the same day
- If a patient uses more than one payment method within a short time period
- If a prescriber prescribes dosages outside accepted norms
- If a dispenser has high rates of cash payments (especially for prescriptions duplicating those covered by Medicaid)
- If a dispenser fills duplicate or excessive prescriptions without seeking prescriber confirmation
- Minimize over-reporting by using specific data parameters
- Note: Too many false positives might produce “alert fatigue” among users and undermine credibility. The optimal criteria for unsolicited reporting can vary by state.
- Educate and train report recipients to understand the meaning, uses, and data limitations of unsolicited reports
- Communicate with report recipients to determine whether the reports are helpful to them or whether the criteria should be adjusted
- Consult with practitioner groups and law enforcement agencies to determine activities that will warrant criminal investigation
- Facilitate cross-agency communication on unsolicited reports concerning practitioners to make sure that aberrant prescribers or dispensers are referred to the appropriate agency (licensing boards vs. drug control) and that investigations will not be compromised
- Track the outcomes and effects of unsolicited reporting (for example, on PDMP use, aberrant prescribing, and doctor shopping), using PDMP data and data from other relevant sources
Prescribers, dispensers, and users of controlled substances
PDMPs are associated with the following outcomes:
- In Ohio, altering opioid prescription behavior among emergency department prescribers for patients with non-traumatic pain management (Baehren et al., 2010)
- In North Carolina, increasing prescriber confidence in prescribing (and denying) prescriptions for controlled substances (Garrettson & Ringwalt, 2013)
- In both Connecticut and Rhode Island, increasing the number of doctors who take a clinical response (such as screening for drug abuse, revisiting the pain/treatment agreement, or referring the patient to substance abuse treatment) when confronted with possible doctor shopping or suspicious behavior, rather than a legal intervention or inaction (Green et al., 2012)
- In Nevada (PDMP COE, 2011) and France (Pradel et al., 2009), a reduction in indicators of doctor shopping
- In British Columbia, a reduction in inappropriately filled prescriptions for opioids and benzodiazepines (Dormuth et al., 2012)
- In Virginia, a reduction in the time spent by law enforcement and regulatory investigators on suspected drug diversion cases (U.S. General Accounting Ofﬁce, 2002; Virginia Department of Health Professions & Virginia State Police, 2004)
Compared to states without PDMPs, states with PDMPs have significant reductions in the following:
- Oxycodone shipments (Reisman, Shenoy, Atherly, & Flowers, 2009)
- Prescription opioid treatment admissions per year (Reisman et al., 2009)
- Note: The greatest reductions in per capita supply of prescription pain relievers and stimulants occurred in states with a proactive PDMP (Simeone & Holland, 2006).
- The supply and abuse of Schedule II opioids, with proactive programs having a larger impact than reactive programs (Simeone & Holland, 2006)
- Benzodiazepine use, especially among young women; persons living in zip codes that are urban, comprise predominantly black populations, or have a high density of poor households (Ross-Degnan et al., 2004); and those with a seizure disorder (Simoni-Wastila et al., 2004)
- Drug abuse or misuse over time, both in the general population and within the population seeking treatment at opioid treatment programs (Reifler et al., 2012)
- Note: One study found decreased retail distribution of Schedule II opioid analgesics but increased retail distribution of Schedule III opioid analgesics in states with PDMPs compared to those without PDMPs (Twillman, 2006).
Baehren, D. F., Marco, C. A., Droz, D. E., Sinha, S., Callan, M., & Akpunonu, P. (2010). A statewide prescription monitoring program affects emergency department prescribing behaviors. Annals of Emergency Medicine, 56(1), 19–23. Retrieved from https://cdn.ymaws.com/californiaacep.org/resource/resmgr/files/Safe_Prescribing_Resources/A_Statewide_Prescription_Mon.pdf
Clark, T., Eadie, J., Kreiner, P., & Strickler, G. (2012). Prescription drug monitoring programs: An assessment of the evidence for best practices. Philadelphia, PA: The Pew Charitable Trusts. Retrieved from http://www.pdmpassist.org/pdf/Resources/Evidence_PDMP_Best_Practices_Report.pdf
Dormuth, C. R., Miller, T. A., Huang, A., Mamdani, M. M., Juurlink, D. N., & Canadian Drug Safety and Effectiveness Research Network. (2012). Effect of a centralized prescription network on inappropriate prescriptions for opioid analgesics and benzodiazepines. Canadian Medical Association Journal, 184(16), E852–E856.
Finklea, K., Sacco, L. N., & Bagalman, E. (2013). Prescription drug monitoring programs. Washington, DC: Congressional Research Service. Retrieved from https://www.researchgate.net/publication/290978748_Prescription_drug_monitoring_programs
Fleming, M. L., Chandwani, H., Barner, J. C., Weber, S. N., & Okoro, T. T. (2013). Prescribers and pharmacists requests for Prescription Monitoring Program (PMP) data: Does PMP structure matter? Journal of Pain and Palliative Care Pharmacotherapy, 27(2), 136–142.
Garrettson, M., & Ringwalt, C. (2013). An evaluation of the North Carolina controlled substances reporting system: Part I user surveys. Washington, DC: U.S. Department of Justice, Bureau of Justice Assistance. Retrieved from https://c.ymcdn.com/sites/safestates.site-ym.com/resource/resmgr/imported/Garrettson.pdf
Green, T. C., Mann, M. R., Bowman, S. E., Zaller, N., Soto, X., Gadea, J., . . . Friedmann, P. D. (2012). How does use of a prescription monitoring program change medical practice? Pain Medicine, 13(10), 1314–1323.
Haegerich, T. M., Paulozzi, L. J., Manns, B. J., & Jones, C. M. (2014). What we know, and don’t know, about the impact of state policy and systems-level interventions on prescription drug overdose. Drug Alcohol Dependence, 145, 34–47.
Haffajee, R. L., Jena, A. B., & Weiner, S. G. (2015). Mandatory use of prescription drug monitoring programs. Journal of the American Medical Association, 313(9), 891–892.
National Alliance for Model State Drug Laws.(2009, August). Prescription Drug Monitoring Programs: A Brief Overview. Retrieved from https://namsdl.org/wp-content/uploads/Prescription-Drug-Monitoring-Programs-PMPs-and-Health-Insurance-Portability-and-Accountability-Act-HIPAA-Brief-Overview.pdf
National Alliance for Model State Drug Laws. (2015). Annual review of prescription monitoring programs. Retrieved from http://www.namsdl.org/library/3449DDCF-BB94-288B-049EB9A92BAD73DF/
Paulozzi, L. J., Kilbourne, E. M., & Desai, H. A. (2011). Prescription drug monitoring programs and death rates from drug overdose. Pain Medicine, 12(5), 747–754.
Paulozzi, L. J., & Stier, D. D. (2010). Prescription drug laws, drug overdoses, and drug sales in New York and Pennsylvania. Journal of Public Health Policy, 31(4), 422–432.
PDMP Center of Excellence. (2011). Nevada’s proactive PMP: The impact of unsolicited reports. Notes from the Field 2.5. Waltham, MA: Brandeis University. Retrieved from http://www.pdmpassist.org/pdf/Resources/nevada_nff_10_26_11.pdf
PDMP Center of Excellence. (2014). Guidance on PDMP best practices: Options for unsolicited reporting. Waltham, MA: Brandeis University. Retrieved from http://www.pdmpassist.org/pdf/COE_documents/Add_to_TTAC/Update%20to%20Brandeis%20COE%20Guidance%20on%20Unsolicited%20Reporting%20final.pdf
Perrone, J., & Nelson, L. S. (2012). Medication reconciliation for controlled substances—An “ideal” prescription-drug monitoring program. New England Journal of Medicine, 366(25), 2341–2343.
Pradel, V., Frauger, E., Thirion, X., Ronfle, E., Lapierre, V., Masut, A., . . . Micallef, J. (2009). Impact of a prescription monitoring program on doctor-shopping for high dosage buprenorphine. Pharmacoepidemiology and Drug Safety, 18(1), 36–43.
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(3), 434–442.
Reisman, R. M., Shenoy, P. J., Atherly, A. J., & Flowers, C. R. (2009). Prescription opioid usage and abuse relationships: An evaluation of State Prescription Drug Monitoring Program efficacy. Substance Abuse: Research and Treatment, 3, 41–51.
Ross-Degnan, D., Simoni-Wastila, L., Brown, J. S., Gao, X., Mah, C., Cosler, L. E., . . . Soumerai, S. B. (2004). A controlled study of the effects of state surveillance on indicators of problematic and non-problematic benzodiazepine use in a Medicaid population. International Journal of Psychiatry in Medicine, 34(2), 103–123.
Simeone, R., & Holland, L. (2006). An evaluation of prescription drug monitoring programs. Washington, DC: U.S. Department of Justice, Ofﬁce of Justice Programs. Retrieved from http://www.simeoneassociates.com/simeone3.pdf
Simoni-Wastila, L., Ross-Degnan, D., Mah, C., Gao, X., Brown, J., Cosler, L. E., . . . Soumerai, S. B. (2004). A retrospective data analysis of the impact of the New York triplicate prescription program on benzodiazepine use in Medicaid patients with chronic psychiatric and neurologic disorders. Clinical Therapeutics, 26(2), 322–336.
Twillman, R. (2006). Impact of prescription monitoring programs on prescription patterns and indicators of opioid abuse. Journal of Pain, 7(4S), S6.
U.S. General Accounting Ofﬁce. (2002). Prescription drugs: State monitoring programs provide useful tool to reduce diversion (Report No. GAO-02-634). Retrieved from http://www.gao.gov/new.items/d02634.pdf
Virginia Department of Health Professions & Virginia State Police. (2004). Prescription monitoring program: Report of the Virginia Department of Health Professions and Virginia State Police. Richmond, VA: Authors.