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

By Joshua J. Timmons
2014, Vol. 6 No. 05 | pg. 2/4 |

Prescription Drug Monitoring Programs of Today

PDMPs rely upon dispensers reporting a cluster of information upon drug pick-up. The list in Maryland, for example, includes patient name, gender, address, and date of birth. The dispenser must also electronically report the prescriber's DEA number, their own DEA number, and information about the drug being prescribed, such as national drug code (a drug identifier), dosage, and length of supply (Michael, 2013). All of this information is reported to Maryland’s PDMP database located within the Alcohol and Drug Abuse Administration (ADAA) headquarters.

After a prescription has been filled, and the information has been sent to the PDMP hub in their ADAA, clinicians soon have the ability to access the information. There is a delay, however, since Maryland only updates their PDMP every few business days (PDMP Training and Technical Assistance Center [PDMP TTAC], n.d.). Once data on a prescription enters the PDMP, a clinician in connection with the care of a patient is able to view the information (in much the same way they can view prior tests and notes from other doctors). PDMP use is not mandatory in Maryland, so use is not enforced and a doctor doesn’t need to access the information (Michael, 2013).

Regardless, once the information from a dispenser has entered Maryland’s PDMP, both pharmacists and doctors have the right to turn away patients that have been seeking out similar prescriptions from a variety of doctors. Law enforcement and medical licensing boards also have access to the PDMP data, with a judicial and administrative subpoena, respectively. Additionally, researchers can access the information once it has been de-identified. Maryland is not, however, currently on the PMIX framework, so it does not have access to other states’ PDMP data (Michael, 2013).

Maryland’s PDMP can be viewed as typical. Its data collection interval is a few days, which is slightly better than the average among PDMPs, and it lacks unsolicited reporting, as do most other states. In addition, the program lacks the technical capability of exchanging PDMP data with other states. Each of these represent a shortcoming in Maryland’s PDMP, and components that, if improved upon, would increase efficacy.

While there is a historical precedent for state run PDMPs– nine states had them in 1989– most began solely to monitor Schedule II substances, such as oxycodone (Clark, Eadie, Kreiner, & Strickler, 2012). These early systems were created with the intention of stifling sales of prescriptions, by physicians, and curbing the prevalence of doctor shopping rings. By 2001, 16 states had PDMPs and the programs began to take on more comprehensive roles: online portals became standard so that providers could request information about patients (Clark et al., 2012). Additionally, information became available to law enforcement so that drug related investigations could be completed more thoroughly and quickly. Today 49 states have a PDMP, with Missouri, the last state without one, currently making legislation to institute its own (Lear, 2011). Interestingly enough, Missouri is now known as the “doctor shopping capital of the country.” (French, 2014)

Preliminary research has yielded promising results. As Reifler et al. (2012) recently concluded, “despite the many inherent differences across all states, active P[D]MPs may be associated with a relative decrease over time in opioid misuse.” The same authors found that 61% of Ohio emergency departments prescribed less medicinal opioids than planned, when given access to the state’s PDMP. On the law enforcement side of the effort, the time required to investigate drug diversion cases has been reported to drop by 90% in Kentucky, 83% in Nevada, and 80% in Utah (USGAO, 2002).

Despite the encouraging findings– from the states that have publicly analyzed their PDMP’s effect– there remain many divides in the way that PDMPs operate. Some collect information on all scheduled substances, while others collect only Schedule II. The majority require that pharmacies request ID at pick-up, but 18 do not (meaning the pharmacist does not have to record the purchasers ID). In reality, there are more than 30 different metrics by which states PDMPs vary; this paper will investigate a few that stand out. In the midst of a prescription drug abuse epidemic, having the right tools available to prescription drug monitoring programs is imperative (Clark et al., 2012). This paper advocates for all PDMPs to adopt unsolicited reporting, PMIX compatibility, and a short data collection interval.

A Proactive Approach

One of the clearest divides among Prescription Drug Monitoring Programs is the reporting system used. Electronic PDMPs have the inherent capability of detecting behaviors and trends that fall in line with doctor shopping or pill mills, and this can be utilized to call attention to instances of abuse. PDMPs that automatically send these reports are known as “proactive” while those that do not are known as “reactive.” With a proactive system relevant officials– doctors, pharmacists, and law officials– are sent an automatically, computer-generated, report that outlines behavior in line with abuse; an advantage over the more use intensive reactive systems.

The benefit of a PDMP using unsolicited reports is that it cuts down on the work of the dispensers and suppliers having to request a report themselves and brings attention to red flags that may otherwise go unnoticed. For example, when Massachusetts switched to a proactive approach, only 8% of prescribers were aware of the number of other prescribers their patients had (Clark et al., 2012). So while reactive PDMPs only create reports in response to an inquiry, proactive systems can do the work automatically.

Unsolicited reports also have the capability to boost clinical awareness and overall utilization of PDMPs. Oftentimes, in states that don’t make PDMP use mandatory– as 33 do not– clinician use remains stagnant program creation. In Nevada, prescribers were sent unsolicited reports about potential doctor shoppers as soon as the system went online. Among the individuals flagged as potential doctor shoppers, dosage units and pharmacies visited dropped over subsequent years (COE, 2014). This drop has been widely attributed to a boost in PDMP awareness among prescribers and the calling of attention to cases of prescription abuse.

Wyoming offers a clear demonstration of unsolicited reporting raising PDMP use among clinicians. In October 2008, the PDMP of Wyoming sent out 66 unsolicited reports based upon evidence of doctor shopping. By September 2009, the PDMP sent out only 15. The drop in unsolicited reports can be linked to two things. The first is that the individuals who triggered the unsolicited reports, by falling above a certain threshold, were intercepted by relevant physicians and either sent to help or cut off from their prescription source. The other cause would be that doctors began to request solicited reports, reducing the need for unsolicited reports. This pans out when looking further at the data: within the same time frame as before, solicited reports jumped from 524 to 949 per month (COE, 2011). Whether the proactive system caught the heaviest abusers early in the year, or physicians simply became aware of the potential application of PDMP reporting and started requesting their own, the system accomplished exactly what it was intended to do: provide valuable information to prescribers.

Traditionally, law enforcement’s approach to identifying pill mills has relied upon the visual: unusual medical office location, security guards at front doors, long lines outside, a lack of medical equipment, or treatment options limited to pain medications. This kind of approach is cumbersome since it requires meticulous screening by law officials, and usually needs a slip-up on the part of the pill mill to begin an investigation. Automatically generated reports could expedite the identification process by sending law enforcement and medical licensing boards unsolicited reports based upon exorbitant prescription rates. Some indications that may be associated with a pill mill would be pain medication doses out of proportion with standard medical practice, consistent early renewing of medications associated with abuse, or having a large pool of patients that could meet the threshold for assumed doctor shopping.

Kentucky has taken a strong proactive approach against pill mills in recent years. Their PDMP automatically generates a list of prescribers with the highest number of prescriptions for substances linked to abuse. These prescribers– in the 98th percentile for prescription rate– are then reviewed to catch instances of false positives. If legal action is deemed necessary, the report is forwarded to licensure boards and a formal investigation is started. Thus far, over 80 investigations have been initiated by Kentucky’s automatically generated list of prescribers (COE, 2014). If more states took the proactive approach of Kentucky, it is unlikely that pill mills would manage to consistently avoid detection.

Unfortunately, as of November 2011, only 16 of the 38 active PDMPs were sending unsolicited reports; and of those, only 8 were sending reports to law enforcement. When it comes to law enforcement, politicians and constituents alike fear the implication of officers sifting through private health information. The reality is that only the most extreme cases need reported to law officials, and unsolicited reports can only augment the validity of prescribers’ decision-making. Additionally, an automatic reporting system takes the human element out of the initial investigation as the computer would only take note of the doctor shoppers or pill mills lying above a predetermined threshold. Licensure boards and law enforcement need only be involved when incidents of doctor shopping or pill mills are apparent.

Simeone and Holland (2006) used comparative analysis to show that states with unsolicited reporting have 10% lower sales of controlled substances compared to those without. Additionally, Wyoming has shown the potential for unsolicited reporting to draw awareness to a program and Kentucky has been able to catch many of its standout pill mills. If a screening tool has the potential to lessen prescription rates, the way unsolicited reports have been shown to do, it is worthy of further investigation and inclusion in each states’ monitoring program.

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