Prevention Effectiveness Requires Transactional Consistency

By Doug Brockway

January 26, 2015

As discussed in this related post there is a minority of doctors and pharmacists that are consciously and intentionally involved in the diversion of prescription drugs will not turn themselves in based on what is shown in a PMP data base.  On the other side of the transactions are patients who intentionally take advantage of inconsistencies in our prevention systems and processes to gain access to drugs they should not have.  These are the doctor shoppers that PMPs are trying to stop.

Key goals of PMPs include the ability to review a patient’s prescription history, avoid duplication of drug therapy or possible drug interactions, and enable appropriately coordinated care across providers. But PMP data are subject to error in the interpretation by myriad physicians and pharmacists each applying their individual interpretations and doing it with different levels of diligence each time. This contributes to PMPs, as currently engineered, to being inadequate to the task of preventing opiate abuse.

One key issue with PMP data in this regard is that there are spelling, keying errors and missing information.  The PMP may have data for John Q. Public, John Public, J.Q. Public and more.  The underlying records for the patient are not likely the same.  In the terms of systems security, the physician must authenticate and verify the identity of the patient, decide which records to use, and then make a series of interpretations before deciding whether a patient is at risk for doctor shopping.

Another key issue is the delay or “float” in PMP data.  The most ambitious states require data to be submitted by pharmacists within a week of fulfillment, most are less strict.  When a patient who is not doctor shopping visits a doctor it will more likely not be within that one week window.  Their PMP record will be up-to-date.  A doctor shopper is more pressed by time, will see many providers within a week.  Their histories of opiate use will be out-of-date.

Combined, these weaknesses create a system that either is not repeatable in its application or, since it uses incomplete data, is repeatably evaluating incorrectly.  We need a system and process that is both repeatable and accurate.

Having a doctor or pharmacist interpret PMP data to evaluate if a patient is doctor shopping can be viewed as akin to a clothing salesperson or store manager interpreting your credit history to see if you should be able to buy that sweater you like.  The same salesperson will react differently to different customers, even to the same customer at different times and under different circumstances.  In the case of retail the basic analysis is done via computer separate from and agnostic to the sale, not by the person doing the selling.  Crucially, this is done in real-time with the swipe of a credit card or, more recently, with the presentation of an Apple Pay or similarly enabled mobile payment device.  Real time is important because if the checking is too time consuming and burdensome then the checker will often put in a less than stellar effort.

We’re all familiar with and depend on second opinions from doctors when we seek care.  We want to be sure that all possible diagnoses and proscriptions are considered and the best course of action is available to us.  A patient who is doctor shopping also relies on this variance but for dark purposes.  They want to use or sell pain killers. These doctor shoppers use the inconsistencies in doctors’ attention to, thoroughness regarding and interpretations of need for care to see multiple doctors until they get the outcome they want, additional opiates.  PMPs will be more effective when they are able to tighten the loopholes, make data (and thus interpretations) more consistent and up-to-date, and provide basic analysis of PMP data in real time at the point of care.