Geographic variation in medication adherence in commercial and Medicare part D populations.

BACKGROUND: Previous literature has emphasized the importance of cost sharing, health literacy, socioeconomic status, cognitive function, disease burden, and polypharmacy as some of the determinants of medication adherence. Little research has been published examining disparities in adherence rates when comparing different regions of the United States. OBJECTIVE: To examine the impact of geography, socioeconomic status, and other demographic variables on medication adherence rates in a large national sample of Medicare Part D and commercially insured beneficiaries. METHODS: This study focused on users of oral antidiabetic, antihypertensive, and/or antilipidemic medications. Beneficiaries who had at least 2 antidiabetic, antihypertensive, or antilipidemic prescription fills in 2010, 2011, or 2012 and who were enrolled in a large commercial or Medicare Part D prescription drug plan for at least 80% of one of these years (9.6 months) were included in this study. Results were stratified by year and by benefit type. Logistic regression was used to test for the adherence differences among the 9 U.S. regions as defined by the U.S. Census Bureau. Additional variables included in the model to control for population differences were age, gender, socioeconomic status, and yearly out-of-pocket medication expenses. RESULTS: After meeting all inclusion and exclusion criteria, 379,533 beneficiaries were in the 2012 Medicare cohort, and 659,553 beneficiaries were in the 2012 commercial cohort. New England was statistically the most adherent geographic region in both cohorts (Medicare odds ratio [OR] = 1.512, CI = 1.399-1.635); commercial OR = 1.193, CI = 1.109-1.284). Younger age beneficiaries, lower income beneficiaries, and females were less adherent in both groups. CONCLUSIONS: In the commercial and Medicare populations, geography, socioeconomic status, age, and gender all impact the likelihood of a beneficiary being adherent to chronic medications for hypertension, diabetes, and hyperlipidemia. While this study does not elucidate the specific factors (i.e., health literacy, disease severity) driving geographic and other differences in medication adherence observed between groups, it does highlight the limitations of quality metrics and wellness initiatives that assume relative homogeneity in beneficiary characteristics across the United States.

Recommendations for urine drug monitoring as a component of opioid therapy in the treatment of chronic pain.

OBJECTIVE: Several prominent guidelines recommend that patients on long-term opioid therapy have periodic urine drug monitoring (UDM) for appropriate use; however, none address the specific questions of which patients to test, which substances to test for, how often to test, and how to act on the results. DESIGN: In the absence of adequate scientific evidence in the literature, a panel of experts in the field of pain and addiction medicine was convened to develop consensus UDM recommendations. The panel met three times between March 2010 and April 2011, and reviewed several drafts of the recommendations document between meetings. RESULTS: The group was able to achieve consensus on a set of UDM recommendations addressing test selection, test frequency, interpretation of results, and how to handle discrepancies based on specific results. CONCLUSION: While the participating panel members recognize that there currently is a limited evidence base to support the expert panel's recommendations, primary care providers and pain specialists are largely acting today based on anecdote, intuition, and individual experience. The recommendations are meant to begin to provide a framework for standardizing practices for UDM in the treatment of chronic pain, and to serve as a catalyst to advance research that quantifies the effects of UDM on opioid therapy management and patient outcomes.

High rates of inappropriate drug use in the chronic pain population.

Chronic opioid treatment is a highly effective method to treat chronic pain; however, the prevalence of abuse of opioids can make treating patients with these agents difficult for clinicians. The objective of this study was to describe rates of inappropriate utilization, abuse, and diversion in a population of patients who were prescribed chronic opioids, as measured by urine drug testing in the clinical setting. A retrospective analysis was conducted of results from all urine drug tests conducted by Ameritox, Ltd. between January 2006 and January 2009, for patients whose physicians ordered the test in order to screen for noncompliance. Data from 938,586 patient test samples showed that 75% of patients were unlikely to be taking their medications in a manner consistent with their prescribed pain regimen. Thirty-eight percent of patients were found to have no detectable level of their prescribed medication, 29% had a nonprescribed medication present, 27% had a drug level higher than expected, 15% had a drug level lower than expected, and 11% had illicit drugs detected in their urine. Note that all categories add to a total greater than 100% as each category is not mutually exclusive, and a single patient could fall into multiple categories. The high observed rate of noncompliance demonstrates a significant clinical concern and confirms the importance of periodic urine drug screening for the population prescribed long-term opioid therapy.

58th annual meeting american society of human genetics, 2008.

The 2008 ASHG meeting, which took place from November 11 to 15, brought almost 6,500 attendees to Philadelphia to learn about the latest advances in human genetics and genomics research. This conference is considered the world's largest gathering of human genetics researchers, academicians, clinicians, genetic counselors, and nurses. This article reviews the 1,000 Genomes Project, Gaucher's disease, warfarin dosing, and Huntington's disease.

Use of an algorithm applied to urine drug screening to assess adherence to an oxycontin regimen.

OBJECTIVE: This study examined the ability of an algorithm applied to urine drug levels of oxycodone in healthy adult volunteers to differentiate among low, medium, and high doses of OxyContin. PARTICIPANTS AND INTERVENTIONS: Thirty-six healthy volunteers were randomized to receive 80, 160, or 240 mg of daily OxyContin to steady state while under a naltrexone blockade. During days 3 and 4 of the study, urine samples of all participants were collected, and oxycodone levels detected in the urine were obtained using a liquid chromatography-mass spectrometry (LC-MS-MS) assay. OUTCOME MEASURES: The concordance was calculated for raw and adjusted LC-MS-MS urine oxycodone values within each study participant between their third and fourth day values. Also, an analysis of medians was calculated for each of the dosage groupings using Bonett-Price confidence intervals for both raw and adjusted LC-MS-MS values. RESULTS: The concordance correlation coefficient for the raw LC-MS-MS values between days 3 and 4 was 0.689 (95% confidence intervals = 0.515, 0.864), whereas the concordance correlation coefficient for the LC-MS-MS values using the algorithm (ie, normalized values) was 0.882 (95% confidence intervals = 0.808, 0.956). Because of greater variability in the raw values, some overlap was observed in the confidence intervals of the various OxyContin doses, whereas no overlap was observed in the normalized confidence intervals regardless of the application of a Bonferroni adjustment. CONCLUSIONS: In contrast to raw LC-MS-MS values, an algorithm that normalizes oxycodone urine drug levels for pH, specific gravity, and lean body mass discriminates well among all three of the daily doses of OxyContin tested (80, 160, and 240 mg), even with correcting for multiple analyses.