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Deaths Among Opioid Users: Impact of Potential Inappropriate Prescribing Practices
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Deaths Among Opioid Users: Impact of Potential Inappropriate Prescribing Practices

Jayani Jayawardhana, PhD; Amanda J. Abraham, PhD; and Matthew Perri, PhD
Inappropriate prescribing practices of opioids are a major risk factor for mortality among opioid users in the Georgia Medicaid population, although risk is lower in managed Medicaid.
In this study, FFS enrollees had a 27.00% rate of inappropriate incidences of opioid prescribing whereas managed care enrollees had a rate of 12.14%. The comparative effectiveness of FFS versus managed care strategies needs further evaluation to determine if safety measures, fiscal control, or clinical patient management are the source of differences between FFS and managed care. This question presents many opportunities for future research, including further policy analyses to determine if these trends also exist in private insurance plan populations. Using commercially available databases, such as IMS (now part of IQVIA) Health LifeLink, would be a reasonable approach. Better ways to link medical and pharmacy claims are also needed to be able to move from measuring all-cause death to measuring death from opioid causes. Although this variable is much harder to assess because of coding in the medical record, it is worth pursuing.

The finding that potential inappropriate prescribing increased the odds of death is significant in that it adds another risk factor to those previously identified. This means that policies aimed at controlling potential inappropriate medication use may be effective in reducing risk factors associated with opioid prescribing. This is certainly supported by the finding that patients in managed care Medicaid had a significantly lower chance of experiencing death in this population. These results provide impetus to more closely examine FFS versus managed care Medicaid, as we now have preliminary evidence that type of insurance plan is associated with health outcomes.

Although patient age and health status (comorbidities) are important determinants of their odds of death, we found violation of basic prescribing principles to be the most important predictor of death. Patients with 1 or more indicators of potential inappropriate prescribing of opioids died at a greater rate than those without these indicators when controlling for other factors. Further, participation in a managed care Medicaid insurance program also reduced the odds of death. This may also represent selection bias in type of insurance, as patients who do not make a plan selection at enrollment are assigned to FFS. It may represent a deeper problem with the provision of FFS Medicaid.

Limitations

There are several limitations in this study that should be considered when interpreting the results. First, it uses pharmacy claims data in the analysis, which show only filled prescriptions, not actual consumption. In addition, the data do not include information on nonprescription opioids, such as heroin and illicit fentanyl. Second, this study focuses only on the adult population (aged 18-64 years) in Georgia Medicaid during 2009 to 2014; thus, results may not be generalizable to other states, other populations, or other time periods. This time period was chosen for this study because it had the most recent data that were available to us. Third, similar to other studies, this study uses ICD-9-CM codes to identify diagnoses, which have their own limitations given that certain diagnoses, such as type of pain, may not be classified or reported accurately. Fourth, this study examines the association between potential inappropriate prescribing practices of opioids and deaths among opioid users. Therefore, additional analyses are needed to draw any causal effects of potential inappropriate prescribing of opioids on health outcomes, including death.

Like all cross-sectional studies, there is a serious risk of confounding from unobserved factors. We found major differences in observable traits between individuals with and without inappropriate prescriptions, which suggests that unobserved factors may also be important; interpretation of these results must be made with caution. That said, when we compare a more parsimonious model with the one reported (eAppendix Table 1), we find that the fuller model yields an even stronger association. Moreover, a longitudinal model with cluster-robust standard errors at the individual level reveals similar results to the fuller model in Table 2 (eAppendix Table 2).

CONCLUSIONS

The findings of this study indicate that incidences of potential inappropriate prescribing practices of opioids are significantly and positively associated with deaths among opioid users in the Georgia Medicaid population when controlling for other factors. In addition, results show that managed care Medicaid enrollees were less likely to experience death than FFS enrollees, indicating possible selection bias in the type of insurance among Medicaid enrollees, variations in prescribing and management practices within FFS and managed care plans, or a combination of both. The findings of this study are also consistent with previous findings in identifying usual risk factors, such as being male, white, and older, that are positively and significantly associated with mortality among opioid users. Although our results do not represent a causal effect, they are consistent with the notion that appropriate interventions targeted at reducing inappropriate prescribing practices of opioids could help lessen risk factors for mortality among opioid users in this population. Moreover, policies aiming to curb potential inappropriate prescribing practices of opioids within FFS insurance plans may be vital to decrease mortality rates in this population.

Author Affiliations: Department of Clinical and Administrative Pharmacy, College of Pharmacy (JJ, MP), and Department of Public Administration and Policy, School of Public and International Affairs (AJA), University of Georgia, Athens, GA.

Source of Funding: This research was supported by the National Institute on Drug Abuse of the National Institutes of Health under award number R01DA039930 and the Georgia Department of Community Health, contract number 2015012. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the Georgia Department of Community Health.

Prior Presentation: A previous version of this paper was presented at the 2017 International Health Economics Association Congress (Boston, MA; July 8-11, 2017) and the 2017 Addiction Health Services Research Conference (Madison, WI; October 18-20, 2017).

Author Disclosures: The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (JJ, AJA, MP); acquisition of data (MP); analysis and interpretation of data (JJ); drafting of the manuscript (JJ, AJA, MP); critical revision of the manuscript for important intellectual content (JJ, AJA, MP); statistical analysis (JJ); obtaining funding (JJ, MP); and administrative, technical, or logistic support (JJ, MP).

Address Correspondence to: Jayani Jayawardhana, PhD, University of Georgia, 250 W Green St, Athens, GA 30602. Email: jayaward@uga.edu.
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