ESTADÍSTICAS

In Aim 3, we evaluated the predictive performance of high-risk opioid use criteria. We mimicked how these types of measures are currently applied in the NC MLIP to get a sense for how effective this MLIP eligibility assessment approach is at enrolling individuals at the greatest risk for relevant public health outcomes from prescription drug abuse.

Ultimately, our claims-based opioid exposure measures performed poorly at predicting overdose and substance use disorder outcomes. The number of unique opioid-dispensing pharmacies, despite being

included in multiple MLIP programs’ eligibility criteria147, failed to discriminate between subjects

experiencing the outcomes and those that did not among opioid users in NC Medicaid. Even though the measures of number of opioid prescription fills and mean MME/day over a 60-day period were evaluated in the validation phase of Aim 3, neither of them proved to be very sensitive both alone or in

combination. For example, the ≥5 opioid fill criterion flagged 5,525 subjects as high-risk for accidental

opioid overdose, but it still only captured 26% of the 174 overdose events observed during the study period.

This poor performance by our selected high-risk opioid use criteria could be attributable to a few underlying causes. First, it is possible there simply exists a low performance ceiling for any claims-based measure of high-risk opioid use in predicting prescription drug overdose outcomes. The causes of overdose events may be too multifactorial to be captured in the limited scope of administrative claims data. Notably, Medicaid claims cannot capture the contributions of illicit drug use to overdose events,

which has experienced growing prevalence among nonmedical prescription drug users in recent years.262

As demonstrated in Aim 1, Medicaid claims also fail to capture highly prevalent controlled substance circumvention behavior that would contribute to adverse prescription drug abuse outcomes. Also, the 60- day opioid exposure window we used to simulate NC Medicaid eligibility assessment may have been too short for thorough assessment of opioid use risk. Much of the existing literature regarding claims-based

prescription abuse risk factors employed assessment periods of 90-365 days.140,141,151,155,161,169 _{This might}

explain why the measures of unique opioid dispensing pharmacies failed to discriminate subjects with overdose events in Aim 3. Pharmacy count measures shown to be predictive of relevant public health

outcomes typically used an assessment period of 6-12 months in prior studies.151,152,157,158,162 Lastly, the

application of NC MLIP eligibility criteria and the opioid use criteria in Aim 3 analyses did not adjust for patient-level characteristics known to be associated with nonmedical opioid use and related outcomes. Most of the existing literature examining optimal claims-based measures of high-risk opioid use

controlled for factors like age, sex, and clinical characteristics, despite this not being standard practice in

real-world MLIP operations.140,141,144,161 _{For example, optimal MLIP eligibility criteria may need to}

account for differences between the sexes, age categorizations, and the presence of certain baseline clinical diagnoses, particularly mental health conditions.

The fact that even the best claims-based measures of high-risk opioid use in Aim 3 performed poorly precluded our ability to confidently and definitively recommend specific binary opioid use

measures in assessing MLIP eligibility. New and actionable evidence for concrete claims-based measures of high-risk opioid use is needed before this can take place. Our Aim 3 findings illuminate the large role that subjectivity will play when MLIP administrators craft MLIP eligibility criteria. In this situation, two

key trade-offs must be considered: 1) Program capacity vs. desired sensitivity, and 2) Rapid vs. thorough risk assessment.

Aim 3 analyses clearly indicated that the sensitivity of high-risk opioid use criteria in capturing subjects who experienced an overdose had a strong positive relationship with the number of subjects flagged by that measure. Therefore, MLIP administrators must assess the extent to which they intend the MLIP to act as a tool for preventing adverse public health outcomes (favor increased program enrollment capacity and high sensitivity) or as a tool primarily for preventing waste and fraudulent use of Medicaid

resources (favor low program enrollment and high specificity).130 _{Additionally, MLIP administrators face}

a difficult decision regarding length of the eligibility assessment period. Shorter assessment periods, such as North Carolina’s two-month assessment, allows for more rapid identification of high-risk opioid use, and therefore timelier enrollment of high-risk beneficiaries in the MLIP. However, the poor performance of our 60-day measures, as well as the body of literature using assessment periods of 90 days and greater, suggest that claims-based measures of high-risk opioid use may perform better at predicting overdose events when assessed over periods of three months or more.

Moving forward, existing MLIPs should carefully reevaluate their approaches to assessing MLIP eligibility. The high prevalence of this policy strategy across the country means MLIPs are poised to play a useful role in the fight against prescription drug abuse in Medicaid. For this to come to fruition, though, a concerted effort is needed on behalf of administrators and policymakers to optimize MLIPs for

achieving public health outcomes. A primary mechanism for optimizing MLIPs is through enrolling beneficiaries that stand to benefit the most from the MLIP intervention, and enrolling enough of them to have the opportunity to cause meaningful reductions in overdose and substance use disorder outcomes. In this spirit, MLIP administrators should prioritize use of MLIP eligibility criteria that maximize sensitivity for capturing preventable prescription drug abuse outcomes.

MLIP administrators should also explore alternative approaches to assessing eligibility outside of the current practice of multiple dichotomous claims-based measures that improve the sensitivity for capturing relevant, preventable prescription drug abuse outcomes. More intricate algorithmic approaches

may be appropriate, which can assess multiple conditional criteria simultaneously and account for

relevant patient-level predictors.150 _{Opioid risk scoring methods may also have added benefit through its}

assessment and weighting of multiple claims-based measures of controlled substance use.168 If claims-

based approaches to assessing MLIP eligibility continue to perform poorly at identifying patients at high risk for preventable overdose events, then it may be necessary to rely more heavily on provider referrals. Providers’ professional judgment can account for more nuanced risk factors exhibited by patients that would not be measurable in claims data, such as illicit substance use or significant history of nonmedical controlled substance use in the patient’s household. However, the human element of provider referrals could introduce inappropriate biases in identifying MLIP enrollees, so additional processes for

independent vetting of provider referrals would be necessary to mitigate discriminatory MLIP enrollment practices.