Prescription Drug Monitoring Programs: An Assessment of the Evidence for Best Practices

  • Sep 19, 2012

Quick Summary

A PDMP is a statewide electronic database that gathers information from pharmacies on dispensed prescriptions for controlled substances. This white paper describes what is known about PDMP best practices and documents the extent to which these practices have been implemented.
Prescription Drug Monitoring Programs: An Assessment of the Evidence for Best Practices
Full Report PDF Download Chart Icon

Report Topic


II. Background

A brief history of PDMPs

Through 1989, nine PDMPs had been established. Two were located in state Attorneys General offices (California, 1939 and Pennsylvania, 1972); two in Departments of Public Safety (Hawaii, 1943 and Texas, 1981); two in Departments of Health, Bureau of Narcotics Enforcement (New York, 1970 and Rhode Island, 1978); one in a Department of Substance Abuse Services (Illinois, 1961); one in a Board of Pharmacy (Idaho, 1967); and one in a Department of Consumer Affairs, Bureau of Health Professions (Michigan, 1988). All of these programs collected information about Schedule II prescriptions¹ only, and all used state-­issued serialized prescription forms. The use of these multiple-­page forms allowed the original prescription records to be sent to the PDMP for key-­punch data entry, while the pharmacy, and in most cases the prescriber, kept a copy. 

Reflecting their locations primarily in state agencies concerned with public safety and drug enforcement, these early PDMPs all provided solicited reports, and most provided unsolicited reports to law enforcement personnel and regulatory agencies or professional licensing agencies. None provided reports to prescribers or pharmacists. The reports and, where relevant, PDMP investigations focused on prescribers selling prescriptions, pharmacies selling controlled
substances illegally, and organized doctor shopping rings. For example, narcotics enforcement in New York, using PDMP data, focused on Quaalude and barbiturate prescription abuse associated with sleep clinics in the late 1970s and
early 1980s, and subsequently on stimulant prescription abuse associated with weight clinics (Eadie, 2010).

With support from the U.S. Drug Enforcement Administration (DEA), the existing PDMP administrators created the Alliance of States with Prescription Monitoring Programs in November 1990. The Alliance was founded to provide a forum for support and information exchange among PDMPs, states where efforts were under way to establish a PDMP, and states where creation of a PDMP was being considered. At this time, PDMPs expanded data collection beyond Schedule II prescriptions. In the context of computer-based information technologies, a second generation of PDMPs came into existence that collected prescription information electronically, without the use of serialized prescription forms. Examples included the Oklahoma PDMP in 1990, located in the Department of Public Safety, and the Massachusetts PDMP in 1992, located in the Department of Public Health.

The Nevada PDMP, implemented in 1997 and located in the state Board of Pharmacy, ushered in a new era of PDMPs by providing data directly to prescribers and pharmacists. Initially, Nevada proactively sent unsolicited reports to the health care practitioners who had issued and dispensed prescriptions to possible doctor shoppers — that is, individuals receiving multiple simultaneous prescriptions of commonly abused drugs. This resulted in a rapid demand for reports upon request (Prescription Drug Monitoring Program Center of Excellence [PDMP COE], Notes from the Field [NFF] 2.5). While the reports initially were sent by fax, Nevada developed in 2001 an online system that began issuing reports based upon users’ direct inquiries. Kentucky soon followed Nevada’s lead, implementing a program in 1999 and developing online capabilities within a few years. In 1994, the Alliance initiated a process to help standardize electronic formats for data collection. This resulted in the publication of the American Society for Automation in Pharmacy’s (ASAP) first version of guidelines for pharmacies to submit controlled substances prescription data to PDMPs. The standards have been updated frequently to incorporate enhancements in electronic system capabilities, and all PDMPs are
now using a version of an ASAP standard.

Early studies in New York indicated that the state’s PDMP had greatly impacted stimulant, barbiturate, and later benzodiazepine prescribing and abuse (Fisher et al., 2011). Other studies suggested that serialized prescription forms required by PDMPs had a so-­called "chilling effect" on legitimate prescribing (Joranson & Dahl, 1989; Pearson et al., 2006; Fornili & Simoni-­‐Wastila, 2011). In 1996, OxyContin was introduced, and sales of prescription opioids began to increase markedly.  After a slow rise in 1984, the numbers of first-time illicit users of pain relievers doubled between 1994 and 1998. Unintentional drug overdose death rates, while increasing through the 1990s, began to increase more steeply in the early 2000s, largely attributed to increased prescription opioid prescribing and abuse (Hall et al., 2008; Bohnert et al., 2011).

An element of the federal response to the increasing death rate was the creation of the Harold Rogers Prescription Drug Monitoring Program Grant Program in the Department of Justice, Bureau of Justice Assistance (BJA) in federal fiscal year 2002. BJA also designated the National Association for Model State Drug Laws (NAMSDL) to assist states in developing PDMP legislation. At about the same time, Purdue Pharma, manufacturer of OxyContin, began to support the creation of new PDMPs with technical as well as monetary assistance, specifying PDMP characteristics that it deemed
desirable. In 2005, Congress passed the National All Schedules Prescription Electronic Reporting (NASPER) Act, authorizing additional federal funding for PDMPs; the Substance Abuse and Mental Health Services Administration (SAMHSA) was designated as the lead agency for NASPER. In 2008, in collaboration with the Alliance of States with Prescription Monitoring Programs and the Heller School of Social Policy and Management at Brandeis University, BJA formed the PDMP Training and Technical Assistance Center, charged with assisting PDMPs in planning, implementing, and enhancing their programs. Two years later, BJA funded the PDMP COE at the Heller School in order to provide practice-­‐relevant information, evaluation, and expertise to PDMPs and their stakeholders, including the development of best practices. As the founder of these efforts and as the nation’s primary public funder of PDMPs via the Harold Rogers Grant Program, BJA has maintained a consistent focus on developing PDMP best practices and encouraging innovative applications of PDMP data. As will be noted in this paper, BJA gives priority funding consideration to states proposing to implement evidence-­based practices that contribute to PDMP effectiveness.

As a result of increased public and private support and the growing recognition of PDMPs’ potential to address the prescription drug abuse epidemic, PDMPs proliferated rapidly. In 2001, 16 states had passed legislation authorizing the creation of a PDMP; by June 2012, 49 states and one territory had passed such legislation, and 41 states had an operating PDMP.

The environment in which the newer PDMPs were implemented differs technologically and politically from that of PDMPs implemented through the early 2000s, generating an array of newer PDMP practices and a great diversity of practices across all PDMPs. For example, PDMPs implemented since 2001 have typically included a secure online portal for authorized providers to access PDMP data about their patients. All older PDMPs, except one, have evolved to permit provider access, often requiring new legislation authorizing such access, and then a costly retrofitting of PDMP
operations to accommodate online and other new technology and new user demands. In contrast to the oldest PDMPs, newer PDMPs are often prohibited by law from providing unsolicited reports on patient or health care provider activity to law enforcement agencies or providers (PDMP COE survey of PDMPs, 2010). Although the wide range of practices carried out by different PDMPs suggests the possibility of evaluating the effectiveness of individual practices, the diversity of practices itself constrains the extent to which individual practices can be isolated and assessed across PDMPs, since other practices most often cannot be held constant.

Although PDMPs currently differ in their relative emphasis on improving medical care versus reducing drug diversion and abuse, they are well positioned to serve both objectives. Indeed, these objectives substantially overlap since the appropriate prescribing of controlled substances can reduce their diversion and abuse, while law enforcement efforts can protect public health by limiting diversion. This is analogous to the collaboration of public health and law enforcement
agencies in reducing automobile accidents, injuries, and fatalities. For example, criminal investigations of doctor shoppers can bring people at risk of overdose and death into drug courts, where they can be placed into drug treatment and supervised, protecting health and saving lives. Likewise, law enforcement efforts to shut down pill mills and doctor shopping rings can have substantial public health benefits by reducing the supply of prescription drugs for street

The opportunity therefore exists in establishing PDMP best practices to bring together advocates of effective medicine, drug abuse prevention, drug control, and substance abuse treatment to address common objectives using a common tool: improving the legitimate use of controlled substances and mitigating the prescription drug abuse epidemic by utilizing PDMP data in all their diverse applications. Despite differences in operations and objectives among PDMPs, the history outlined above depicts an environment in which program modification is the norm, with the identification and adoption of new concepts, technologies, and standards as constants. This suggests that development of evidence-based best practices will be welcomed by PDMPs, and their adoption can be expected.

PDMP effectiveness

The established value of PDMPs

Before embarking on a consideration of PDMP best practices, it should be noted that evidence suggests PDMPs are effective in improving the prescribing of controlled substances and addressing the prescription drug abuse epidemic (PDMP COE, Briefing on PDMP Effectiveness, 2012). PDMP data are unique and irreplaceable in identifying questionable activity with respect to prescription drugs, such as doctor and pharmacy shopping, prescription fraud, and problematic prescribing. No other system exists that can compile all controlled substances prescriptions, regardless of who issued the prescription, which pharmacy dispensed it, or the source of payment. According to surveys of PDMP users and a study of emergency department doctors, PDMPs are an important tool in making sound clinical decisions when prescribing or dispensing controlled substances (ASPMP, 2007; Kentucky Cabinet for Health and Family Services, 2010; Baehren, 2010). Evaluations of PDMPs generally report good user satisfaction with the utility of PDMP reports (Virginia Department of Health Professions and Virginia State Police, 2004; Lambert, 2006; Rosenblatt, 2007).

PDMP data can be used to track emerging trends in legitimate prescribing; to evaluate efforts to improve prescribing practices, such as provider education initiatives (Fisher et al., 2011a); and to reduce drug abuse and diversion, such as drug abuse prevention programs and drug control policies (Carnevale & Associates and PDMP COE, 2010; PDMP COE, NFF 3.2). PDMPs currently assist in investigations of diversion of prescription drugs into illegal use (drug diversion) (PDMP COE, NFF 2.3), medical examiner practice (PDMP COE, NFF 2.6), drug courts (PDMP COE, NFF 2.4), and direct intervention with and supervision of doctor shoppers as an alternative to criminal investigation (PDMP COE, NFF
2.1), substance abuse treatment programs (PDMP COE, NFF 2.2), and epidemiological surveillance and early warning systems (Carnevale & Associates and PDMP COE, 2010). Although questions have been raised about the effectiveness of PDMPs (Fornili & Simoni-­‐Wastila, 2011), several studies suggest a connection between PDMP utilization or particular PDMP practices and positive outcomes related to improving, prescribing, and reducing prescription drug abuse (Pearson et al., 2006; Pradel et al., 2009; Reisman et al., 2009; Wang & Christo, 2009; Paulozzi & Stier, 2010; Fisher et al. 2011b;
LeMire et al., 2012; Reifler et al., 2012).

Given that PDMPs have already proven their worth in many applications, the question addressed in this white paper is what program characteristics and practices are likely to enable PDMPs to become more effective in collecting, analyzing, disseminating, and utilizing their data. See McDonald et al. (2004) for an earlier compilation of PDMP practices and recommendations for research on their effectiveness.

Conceptualizing effectiveness

The effectiveness of PDMPs can be conceptualized in terms of their impact in ensuring the appropriate use of prescription-­‐controlled substances, reducing their diversion and abuse, and improving health outcomes, both at the patient and community levels. This impact is maximized when prescription history data are, to the extent technologically feasible, complete and accurate; analyzed appropriately and expeditiously; made available in a proactive and timely manner; disseminated in ways and formats that best serve the purposes of end users; and applied in all relevant domains by all appropriate users. This suggests that PDMPs can be thought of as information systems with inputs, internal operations, outputs, and customers who make use of their products. An effective PDMP will optimize all system phases, expand its customer base to include all appropriate users, and make sure these customers are well trained in using the PDMP. Best practices need to be identified for each phase.

Considerable preliminary work has already been done in this regard, including in formulating the Alliance of States with Prescription Monitoring Programs’ Prescription Monitoring Program (PMP) Model Act (ASPMP, 2010), developing and continuously updating the standards for transmission of information from pharmacies to PDMPs (standards developed with ASAP), and identifying characteristics and practices of the "next generation" of PDMPs (Eadie, 2011, May and an “ideal” PDMP (Perrone & Nelson, 2012). Although the rationale for the practices mentioned in these documents in many cases seems both logical and plausible, the evidence base supporting them is often experiential and not well documented.

PDMP effectiveness can also be understood in the context of how PDMPs can best work together and in concert with other agencies, organizations, and health information technologies. Best practices will likely include data standardization and sharing among PDMPs and other agencies, as well as cooperative arrangements that maximize the value of PDMP data in their completeness, timeliness, analysis, and dissemination. To increase their effectiveness and impact, PDMPs must be integrated with other systems, including public health, health information exchanges, electronic health records,
electronic prescribing, public safety, drug abuse prevention, and drug control. This will ensure that their data are made seamlessly available to all those engaged in improving controlled substances prescribing and addressing the prescription drug abuse epidemic. An important intermediate measure of PDMP effectiveness is therefore the number and type of interorganizational linkages and information-­sharing agreements between PDMPs and other agencies. Section IV of this
paper covers practices that may increase such linkages.

Toward a checklist of PDMP best practices

This paper can be considered a step toward developing an evidence-­based checklist of PDMP best practices that could be used to evaluate a PDMP. Each practice would be defined operationally, and where possible and appropriate, quantitative metrics indicating success in carrying out the practice would be specified. Once parameters are established for each practice’s definition and metrics, annual or semiannual surveys of PDMPs could track their adoption. Some candidate practices considered below are sufficiently well-­‐defined and arguably have enough evidential support to already warrant their inclusion in a compendium of best practices, but many need more clarification, specificity, and evidence of effectiveness to support their inclusion. For example, practices in PDMP user recruitment, enrollment, and education need to be evaluated, such as the 2012 statutes in Kentucky, New York, Tennessee, and Massachusetts mandating PDMP enrollment and use. For demonstration purposes only, a checklist of the candidate practices considered below is presented in Appendix A.

¹ - The Controlled Substances Act, passed in 1970, established the five-­tiered schedule of controlled substances that
is now in effect. Drugs are assigned to one of these categories, or schedules, based on the substance’s medicinal value, harmfulness, and potential for abuse and diversion. Schedule II is the most restrictive of the schedules of legally available controlled substances. 

Date added:
Sep 19, 2012
Drug Safety
Collapse All


Alliance of States with Prescription Monitoring Programs (ASPMP). (2007). An assessment of state prescription monitoring program effectiveness and results. Retrieved Sep. 11, 2012, from

Alliance of States with Prescription Monitoring Programs (ASPMP). (2010). Prescription Monitoring Program Model Act 2010 revision.  Retrieved Feb. 26, 2012, from

Baehren, D.F., Marco, C.A., Droz, D.E., Sinha, S., Callan, E.M., & Akpunonu P. (2010). A statewide prescription monitoring program affects emergency department prescribing behaviors. Annals of Emergency Medicine, 56(1), 19-­‐23.

Barrett, K., & Watson, A. (2005). Physician perspectives on a pilot prescription monitoring program. Journal of Pain and Palliative Care Pharmacotherapy, 19(3), 5-­‐13. 

Blumenschein, K., Fink, J.L., Freeman, P.R., Kirsh, K.L., Steinke, D.T., & Talbert, J. (2010). Independent evaluation of the impact and effectiveness of the Kentucky All Schedule Prescription Electronic Reporting Program (KASPER). Lexington, Kentucky: Institute for Pharmaceutical Outcomes and Policy, University of Kentucky. Retrieved Sep. 11, 2012, from­B1A1-­4399-89AD-­25953BAD43/0/KASPEREvaluationFinalReport10152010.pdf

Boeuf, O., & Lapeyre-Mestre, M. (2007). Survey of forged prescriptions to investigate risk of psychoactive medications abuse in France: Results of OSIAP survey. Drug Safety, 30(3), 265-­‐276. 

Bohnert, A.S., Valenstein, M., Bair, M.J., Ganoczy, D., McCarthy, J.F., Ilgen, M.A., & Blow, F.C. (2011). Association between opioid prescribing patterns and opioid overdose-­related deaths. Journal of the American Medical Association, 305(13), 1315-­‐1321. 

Buurma, H., Bouvy, M.L., De Smet, P.A., Floor-­‐Schreudering, A., Leufkens, H.G., & Egberts, A.C. (2008). Prevalence and determinants of pharmacy shopping behaviour.  Journal of Clinical Pharmacy and Therapeutics, 33, 17–23.

Campbell, K.M., Deck, D., & Krupski, A. (2008). Record linkage software in the public domain: a comparison of Link Plus, The Link King, and a ‘basic’ deterministic algorithm. Health Informatics Journal, 14(1), 5-­‐15.

Carnevale & Associates and Prescription Drug Monitoring Program Center of Excellence. (2010). Prescription monitoring and prevention: recommendations for increased collaboration. Working paper produced for the Substance Abuse and Mental Health Services Administration. 

Centers for Disease Control and Prevention. (2010). Unintentional drug poisoning in the United States. Retrieved Feb. 26, 2012, from­issue-­brief.pdf

Coalition Against Insurance Fraud. (2007). Prescription for peril: how insurance fraud finances theft and abuse of addictive prescription drugs. Retrieved Sep. 11, 2012, from

Cochella, S., & Bateman, K. (2011). Provider detailing: an intervention to decrease prescription opioid deaths in Utah. Pain Medicine, 12(Suppl 2), S73-­‐S76. doi: 10.1111/j.1526-­‐4637.2011.01125.x.

Curtis, L.H., Stoddard, J., Radeva, J.I., Hutchison, S., Dans, P.E., Wright, A., Woosley, R.L., & Schulman, K.A. (2006). Geographic variation in the prescription of schedule II opioid analgesics among outpatients in the United States. Health Services Research, 41(3 Pt 1), 837-­‐855.

DuBose P., Bender A., & Markman, J.W. (2011, June). Rank-­‐ordering physicians by opioid abuse and diversion risk. Poster presented at the International Narcotics Research Conference, Hollywood, FL.

Dunn, K.M.,  Saunders, K.W., Rutter, C.M., Banta-­‐Green, C.J., Merrill, J.O., Sullivan, M.D., Weisner, C.M., Silverberg, M.J., Campbell, C.I., Psaty, B.M., & Von Korff, M. (2010). Opioid prescriptions for chronic pain and overdose. Annals of Internal Medicine, 152(2), 85-­‐93.

Eadie, J.L. (1990). Policy concerns: benzodiazepine abuse and misuse: New York State’s response. In B.B. Wilford (Ed.), Balancing the Response to Prescription Drug Abuse: Report of a National Symposium on Medicine and Public Policy (pp. 93-­‐102). Chicago IL: American Medical Association.

Eadie, J.L. (1993). New York State triplicate prescription program. In J.R. Cooper, D.J. Czechowicz, S.P. Molinari, & R.C. Petersen (Eds.), Impact of Prescription Drug Diversion Control Systems on Medical Practice and Patient Care: NIDA Research Monograph 131 (pp. 176-­‐193). Rockville, MD: U.S. Department of Health and Human Services, National Institute on Drug Abuse.

Eadie, J.L. (2010, May). Prescription monitoring programs and law enforcement: an overview. Presentation made at the PDMP/Law Enforcement meeting, Alliance of States with Prescription Monitoring Programs, San Antonio, TX.

Eadie, J.L. (2011, March). Prescription monitoring program roles. Presentation made at the Surgeon General’s Expert Panel on Prescription Drug Abuse in Youth, Washington, DC.

Eadie, J.L. (2011, May). Toward the next generation of PMPs: enhancing prescription monitoring programs’ ability to address the prescription drug abuse epidemic. Presentation made to the U.S. Senate Sub-­Committee on Crime and Terrorism, Washington, DC.

Feldman, L., Williams, K.S., Coates, J., & Knox. M. (2011). Awareness and utilization of a prescription monitoring program among physicians. Journal of Pain and Palliative Care Pharmacotherapy, 25(4), 313-­‐317.

Fischer, B., Jones, W., Krahn, M., & Rehm, J. (2011). Differences and over-­‐time changes in levels of prescription opioid analgesic dispensing from retail pharmacies in Canada, 2005-­2010. Pharmacoepidemiology and Drug Safety, 20(12), 1269-1277. doi: 10.1002/pds.2190.

Fisher, J.E., Zhang, Y., Sketris, I., Johnston, G., & Burge, F. (2011). The effect of an educational intervention on meperidine use in Nova Scotia, Canada: a time series analysis. Pharmacoepidemiology and Drug Safety, 21(2), 177-­‐183. doi: 10.1002/pds.2259.

Fisher, J.E., Sanyal, C., Frail, D., & Sketris, I. (2011). The intended and unintended consequences of benzodiazepine monitoring programmes: a review of the literature. Journal of Clinical Pharmacy and Therapeutics, 37(1), 7-­21. doi: 10.1111/j.1365-­‐2710.2011.01245.x.

Fornili, K., & Simoni-­‐Wastila, L. (2011). Prescription monitoring programs: striking the balance between medical use and diversion. Journal of Addictions Nursing, 22(1-­2), 77-82.

Gilson, A.M., Fishman, S.M., Wilsey, B.L., Casamalhuapa, C., & Baxi, H. (2012). Time series analysis of California's prescription monitoring program: impact on prescribing and multiple provider episodes. Journal of Pain, 13(2), 103-111.

Gomes, T., Mamdani, M., Dhalla, I., Paterson, M., & Juurlink, D. (2011). Opioid dose and drug-related mortality in patients with nonmalignant pain. Archives of Internal Medicine, 171(7), 686-­‐691.

Government Accountability Office (GAO). (2011). Medicare Part D: instances of questionable access to prescription drugs. (GAO-­12-104T). Washington, DC. Retrieved Sep. 11, 2012, from

Government Accountability Office (GAO). (2009). Medicaid: fraud and abuse related to controlled substances identified in selected states (GAO-­‐09-­‐957). Washington, DC. Retrieved Sep. 11, 2012, from

Hall, A.J., Logan, J.E., Toblin, R.L., Kaplan, J.A., Kraner, J.C., Bixler, D., Crosby, A.E., & Paulozzi, L.J.
(2008). Patterns of abuse among unintentional pharmaceutical overdose fatalities. The Journal of American Medical Association, 300(22), 2613-­‐20.

Johnson, E.M., Porucznik, C.A., Anderson, J.W., & Rolfs, R.T. (2011). State-­level strategies for reducing prescription drug overdose deaths: Utah's prescription safety program. Pain Medicine, Suppl 2:S66-­‐72. doi: 10.1111/j.1526-­1637.2011.01126.x.

Joranson, D.E. & Dahl, J.L. (1989). Achieving balance in drug policy: the Wisconsin model. In C.S. Hill, Jr. & W.S. Fields, Advances in Pain Research and Therapy (pp. 197-­‐204). New York, NY: Raven Press.

Joranson, D.E., Carrow, G.M., Ryan, K.M., Schaefer, L., Gilson, A.M., Good, P., Eadie, J., Peine, S., & Dahl, J.L. (2002). Pain management and prescription monitoring. The Journal of Pain Symptom Management, 23(3), 231-8.

Katz, N., Houle, B., Fernandez, K.C., Kreiner, P., Thomas, C.P., Kim, M., Carrow, G.M., Audet, A, & Brushwood, D. (2008). Update on prescription monitoring in clinical practice: a survey study of prescription monitoring program administrators. Pain Medicine, 9(5):587-­‐94. Epub 2008 Jun 28.

Katz, N., Panas, L., Kim, M., Audet, A.D., Bilansky, A., Eadie, J., Kreiner, P., Paillard, F.C.,  Thomas, C., & Carrow, G. (2010). Usefulness of prescription monitoring programs for surveillance: analysis of Schedule II opioid prescription data in Massachusetts, 1996-­‐2006. Pharmacoepidemiology and Drug Safety, 19(2), 115-­‐23.

Kentucky Cabinet for Health and Family Services and Kentucky Injury Prevention and Research Center. (2010). 2010 KASPER satisfaction survey: executive summary. Retrieved Sep. 11, 2012, from­‐924B-­4F11-­A10A-­5EB17933FDDB/0/2010KASPERSatisfactionSurveyExecutiveSummary.pdf

Kreiner, P. (2011, June). Non-­‐medical prescription drug use and market intervention: prescription drug monitoring program data and law enforcement. Presentation made at the National Institutes of Justice Annual Conference, Washington, DC.

Kreiner, P. (2012, April). Geospatial analyses of opioid overdose rates and rates of questionable activity in Massachusetts. Presentation made at the National Prescription Drug Abuse Summit, Orlando, FL.

Lambert, D. (2007). Impact evaluation of Maine’s prescription drug monitoring program.  Portland, ME: Muskie School of Public Service, University of Southern Maine.  Retrieved Sep. 11, 2012, from;jsessionid=FAED7067735280

LeMire, S. (2010). Evaluation of the efficacy of the North Dakota prescription drug monitoring program online training. Grand Forks, ND: Bureau of Educational Services and Applied Research (BESAR), University of North Dakota. Retrieved Sep. 11, 1012, from

LeMire, S., Martner, S., & Rising, C. (2012). Advanced practice nurses’ use of prescription drug monitoring program Information. The Journal for Nurse Practitioners, 383-­‐405. doi: 10.1016/j.nurpra.2012.02.016

Lipton, B., Laws, C., & Li, L. (2011). Workers compensation prescription drug study: 2011 update, NCCI Research Brief. Boca Raton, FL: National Council on Compensation Insurance Holdings Inc.
Retrieved Sep. 11, 2012, from

Lohr, K.N. (2004). Rating the strength of scientific evidence: relevance for quality improvement programs.  International Journal of Quality Health Care, 16(1), 9-­18.

Massachusetts Department of Public Health. (2010, August). Request to Public Health Council for final promulgation of amendments to regulations implementing the Controlled Substances Act, 105 CMR 700.000, concerning the Prescription Monitoring Program. Public Health Advisory Council Meeting, Boston, MA.

Massachusetts Department of Public Health. (2012, February). PDMP Advisory Council presentation. Public Health Advisory Council Meeting, Boston, MA.

Massachusetts Department of Public Health. (2012, April). Presentation made at National Rx Drug Abuse Summit, Washington, DC.

McDonald, D., Hurd, D., Lloyd-­‐Kolkin, S., Hamilton, C., Reddy, P., & Adedokun, L. (2004). Prescription monitoring programs: current practices and suggestions for further research on their effectiveness. Cambridge, MA: Abt Associates.

National Alliance for Model State Drug Laws. (2011a). Interstate sharing of prescription monitoring database information. Retrieved June 28, 2012, from

National Alliance for Model State Drug Laws. (2011b). States that allow practitioners to designate an authorized agent to access the PMP database. Retrieved June 28, 2012, from

National Alliance for Model State Drug Laws. (2012a). States that require practitioners to register for PMP database. Retrieved June 28, 2012, from

National Alliance for Model State Drug Laws. (2011b). States that require prescribers and/or dispensers to access PMP database in certain circumstances. Retrieved June 28, 2012, from

National Alliance for Model State Drug Laws. (2012c). States that require certain authorized users to undergo training and/or completion of educational courses before accessing PDMP data. Retrieved Sep. 11, 2012, from

Office of National Drug Control Policy. (2011). Epidemic: responding to America’s prescription drug abuse crisis. Washington, DC:  Executive Office of the President of the United States. Retrieved Feb. 26, 2012, from­‐content/prescription-­

Owens, D.K., Lohr, K.N., Atkins, D., Treadwell, J.R., Reston, J.T., Bass, E.B., Chang, S., & Helfand, M. (2010). AHRQ series paper 5: grading the strength of a body of evidence when comparing medical interventions—agency for healthcare research and quality and the effective health-­care program. The Journal of Clinical  Epidemiology, 63(5), 513-­‐23.

Paulozzi, L.J., & Stier, D.D. (2010). Prescription drug laws, drug overdoses, and drug sales in New York and Pennsylvania. The Journal of Public Health Policy, 31(4), 422-­‐32.

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-­‐54. doi: 10.1111/j.1526-­‐4637.2011.01062.x. Epub 2011 Feb 18.

Paulozzi, L.J. (2011, June). High-­‐decile prescribers: all gain, no pain? Presentation made at the 2011 Harold Rogers Prescription Drug Monitoring Program National Meeting, Washington, DC.

Paulozzi, L.J., Kilbourne, E.M., Shah, N.G., Nolte, K.B., Desai, H.A., Landen, M.G., Harvey, W., & Loring, L.D. (2012). A history of being prescribed controlled substances and risk of drug overdose death. Pain Medicine, 13, 87-­‐95.

Pauly, V., Frauger, E., Pradel, V., Rouby, F., Berbis, J., Natali, F., Reggio, P., Coudert, H., Micallef, J., & Thirion, X. (2011). Which indicators can public health authorities use to monitor prescription drug abuse and evaluate the impact of regulatory measures? Controlling High Dosage Buprenorphine abuse. Drug and Alcohol Dependence, 113(1), 29-­‐36. Epub 2010 Aug 8.

Payne, S., & Thayer, D. (2009). Epidemiological analysis of the Maine prescription monitoring program (PMP) data. Portland, ME: Muskie School of Public Service, University of Southern Maine. Retrieved Sep. 11, 2012, from­‐PMP.pdf

Pearson, S., Soumerai, S., Mah, C., Zhang, F., Simoni-­‐Wastilla, L., Salzman, C., Cosler, L., Fanning, T., Gallagher, P., & Ross-­‐Degnan, D. (2006). Racial disparities in access after regulatory surveillance of benzodiazepines. Archives of Internal Medicine, 166, 572-­‐579.

Peirce, G.L., Smith, M.J., Abate, M.A., & Halverson, J. (2012). Doctor and pharmacy shopping for controlled substances. Medical Care, 50(6), 494-­‐500.

Perrone, J., & Nelson, L. (2012). Medication reconciliation for controlled Substances: an “ideal” prescription drug monitoring program. The New England Journal of Medicine, 10.1056/NEJMp1204493.

Pradel, V., Frauger, E., Thirion, X., Ronfle, E., Lapierre, V., Masut, A., Coudert, C., Blin, O., & Micallef, J. (2009). Impact of a prescription monitoring program on doctor-­‐shopping for high dosage buprenorphine. Pharmacoepidemiology and Drug Safety, 18(1), 36-­‐43.

Prescription Drug Monitoring Program Center of Excellence. (2010). Positive customer identification. Unpublished analysis of state prescription monitoring data.

Prescription Drug Monitoring Program Center of Excellence. (2010). Unpublished analysis of PDMP performance measure data collected by the Bureau of Justice Assistance.

Prescription Drug Monitoring Program Center of Excellence. (2010). Trends in Wyoming PDMP prescription history reporting: evidence for a decrease in doctor shopping? NFF 1.1. Heller School, Brandeis University. Waltham, MA.

Prescription Drug Monitoring Program Center of Excellence. (2011). Unpublished analysis of the Second State PDMP Profiles Survey conducted for the Bureau of Justice Assistance.

Prescription Drug Monitoring Program Center of Excellence. (2011). Staying clear of the law and addiction: Nevada’s Pre-­‐Criminal Intervention Program. NFF 2.1. Heller School, Brandeis University. Waltham, MA.

Prescription Drug Monitoring Program Center of Excellence. (2011). Briefing on PDMP effectiveness: PDMPs—an effective tool in curbing the prescription drug abuse epidemic. Heller School, Brandeis University. Waltham, MA.

Prescription Drug Monitoring Program Center of Excellence. (2011). Keeping patients safe: a case study on using prescription monitoring program data in an outpatient addictions treatment setting. NFF 2.2. Heller School, Brandeis University, Waltham, MA.

Prescription Drug Monitoring Program Center of Excellence. (2001).Perspective from Kentucky: using PDMP data in drug diversion investigations. Notes from the Field 2.3. Heller School, Brandeis University. Waltham, MA.

Prescription Drug Monitoring Program Center of Excellence. (2011). Monitoring and changing behavior: the role of PDMP data in Kentucky drug courts. NFF 2.4. Heller School, Brandeis University. Waltham, MA.

Prescription Drug Monitoring Program Center of Excellence. (2011). Nevada’s proactive PDMP: the impact of unsolicited reports. NFF 2.5. Heller School, Brandeis University. Waltham, MA.

Prescription Drug Monitoring Program Center of Excellence. (2011). Drug-related deaths in Virginia: medical examiner use of PDMP data. NFF 2.6. Heller School, Brandeis University. Waltham, MA.

Prescription Drug Monitoring Program Center of Excellence. (2012). Real-­time reporting: Oklahoma’s pioneering PDMP. NFF 3.1. Heller School, Brandeis University. Waltham, MA.

Prescription Drug Monitoring Program Center of Excellence. (2012). Project Lazarus: using PDMP data to mobilize and measure community drug abuse prevention. NFF 3.2. Heller School, Brandeis University. Waltham, MA.

Reifler, L.M., Droz, D., Bartelson, B.B., Bailey, J.E., Schnoll, S., & Dart, R.C. (2012). Do prescription monitoring programs impact state trends in opioid abuse/misuse? Pain Medicine 2012:13, 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 efficacy. Substance Abuse: Research and Treatment. 2009:3, 41-­‐51.

Rigg, K.K., March, S.J., & Inciardi, J.A. (2010). Prescription drug abuse and diversion: role of the pain clinic. Journal of Drug Issues. 40(3), 681-­‐702.

Rosenblatt, N. (2007). Reducing the diversion of scheduled prescription medications in the Commonwealth of Kentucky: 2006 KASPER Satisfaction Survey: Executive summary. Kentucky Cabinet for Health and Family Services: Frankfort, KY.

Simeone, R. & Holland, L. (2006). An evaluation of prescription drug monitoring programs. Simeone Associates, Inc. Albany, NY. Retrieved on September 11, 2012 from

Sorg, M., Labrie, S., & Parker, W. (2009). Analysis and evaluation of participation by prescribers and dispensers in the Maine state prescription monitoring program. Margaret Chase Smith Policy Center, University of Maine. Retrieved on September 11, 2012 from

Substance Abuse and Mental Health Services Administration, National All Schedules Prescription Electronic Reporting Act Program Grants. (2005). Request for Applications (RFA) No. TI-­‐11-­‐F1, Catalogue of Federal Domestic Assistance (CFDA) No.: 93.975. p. 10.

Substance Abuse and Mental Health Services Administration, Drug Abuse Warning Network. (2010). Highlights of the 2009 Drug Abuse Warning Network (DAWN) findings on drug-­related emergency department visits. The DAWN Report. DAWN10-­‐1228. Retrieved on September 11, 2012, from­of-­the-2009-Drug-Abuse-Warning-­Network-­DAWN-­Findings-on-Drug-­Related-Emergency-­Department-­Visits/DAWN10-1228

Substance Abuse and Mental Health Services Administration, Treatment Episode Data Set. (2011) Substance abuse treatment admissions for abuse of benzodiazepines. The TEDS Report. TEDS11-­0602. Retrieved on September 11, 2012, from­Abuse-­Treatment-Admissions-for-­Abuse-­of-Benzodiazepines/TEDS11-­0602

Tufts Health Care Institute Program on Opioid Risk Management. (2011). Advancing safe opioid prescribing through prescriber training and behavior change. Retrieved on September 11, 2012, from

Twillman, R. (2006). Impact of prescription monitoring programs on prescription patterns and indicators of opioid abuse. Journal of Pain, Supplement. 7(4), S6.

Ulbrich, T.R., Dula, C.A., Green, C.G., Porter, K., & Bennett, M.S. (2010). Factors influencing community pharmacists' enrollment in a state prescription monitoring program. Journal of the American Pharmacists Association. 50(5), 588-­‐94.

United States Government Accountability Office (GAO). (2002). Prescription drugs: state monitoring programs provide useful tool to reduce diversion. Washington, D.C. GAO Report GAO-­‐02-­‐634.

Virginia Department of Health Professions and Virginia State Police. (2004). Prescription monitoring program. Richmond, VA. Retrieved September 11, 2012, from

Virginia Prescription Monitoring Program. (2010). 2010 Statistics. Retrieved September 11, 2012, from

Wang, J., & Christo, P.J. (2009). The influence of prescription monitoring programs on chronic pain management. Pain Physician. 12(3), 507-­‐515.

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 of Managed Care. 15(12), 897-906.

Whitely, M.  (2012, January) Opioids pose major concern for comp stakeholders. Workcompcentral available by subscription at­‐ K71GSo

Wilsey, B.L., Fishman, S.M., Gilson, A.M., Casamalhuapa, C., Baxi., H, Zhang, H., & Li, C.S. (2010). Profiling multiple provider prescribing of opioids, benzodiazepines, stimulants, and anorectics. Drug and Alcohol Dependence. 112(1-­‐2), 99-106. Prescription Drug  Monitoring Programs: An Assessement of the Evidence for  Best Practices

Wilsey, B.L., Fishman, S.M., Gilson, A.M., Casamalhuapa, C., Baxi., H, Lin, T.C., & Li, C.S. (2011). An analysis of the number of multiple prescribers for opioids utilizing data from the California Prescription Monitoring Program. Pharmacoepidemiology and Drug Safety. 20(12), 1262-8. doi: 10.1002/pds.2129.

Related Resources

Pew Testimony Before the U.S.-China Economic and Security Review Commission

Other Resource

Allan Coukell, senior director of drugs and medical devices, testified before the U.S.-China Economic and Security Review Commission on the global pharmaceutical supply chain security and the importance of the newly passed Drug Quality and Security Act.


Testimony of Elizabeth Jungman on Counterfeit Medicines

Issue Brief

The House Energy and Commerce Subcommittee on Oversight and Investigation held a hearing on Feb 16 entitled "Counterfeit Drugs: Fighting Illegal Supply Chains." Elizabeth Jungman, director of drug safety and innovation testified on counterfeit drugs the importance that newly passed Drug Quality and Security Act will have on the safety of the U.S. pharmaceutical supply chain.



Case Studies: How Unsafe Drugs Can Reach Patients

Issue Brief

The following case studies illustrate breaches to the pharmaceutical supply chain—the route a drug travels from its raw material origins to the delivery of a finished medicine. These examples, all of which are discussed in Pew Health Group’s report After Heparin: Protecting Consumers from the Risks of Substandard and Counterfeit Drugs, demonstrate the different ways in which contaminated, fake, or otherwise unsafe medicine can reach patients, and underscore the need for reform.


Pew Comments to FDA Draft Guidance on 503A

Issue Brief

On January 31, Pew submitted comments to the U.S. Food and Drug Administration in response to draft guidance on the implementation of Title I of the Drug Quality and Security Act and addressed five topics: anticipatory and office stock compounding; quality standards; FDA / state coordination; MOUs to address inordinate interstate shipment of compounded drugs; use of bulk drug substances.


Improving the Safety and Quality of Our Drug Supply

Other Resource
On Nov. 18, 2013, Congress passed the landmark Drug Quality and Security Act, bipartisan legislation to safeguard the U.S. pharmaceutical supply from counterfeit and contaminated drugs. The act creates a national system to track and authenticate prescription medications as they progress from the manufacturer to the patient. It also addresses the risks posed by drugs made by large-scale compounding pharmacies. More