Publications

OBJECTIVE: Observational studies analyzing multiple exposures simultaneously have been limited by difficulty distinguishing relevant results from chance associations due to poor specificity. Set-based methods have been successfully used in genomics to improve signal-to-noise ratio. We present and demonstrate medication class enrichment analysis (MCEA), a signal-to-noise enhancement algorithm for observational data inspired by set-based methods.

MATERIALS AND METHODS: We used The Health Improvement Network database to study medications associated with Clostridium difficile infection (CDI). We performed case-control studies for each medication in The Health Improvement Network to obtain odds ratios (ORs) for association with CDI. We then calculated the association of each pharmacologic class with CDI using logistic regression and MCEA. We also performed simulation studies in which we assessed the sensitivity and specificity of logistic regression compared to MCEA for ORs 0.1-2.0.

RESULTS: When analyzing pharmacologic classes using logistic regression, 47 of 110 pharmacologic classes were identified as associated with CDI. When analyzing pharmacologic classes using MCEA, only fluoroquinolones, a class of antibiotics with biologically confirmed causation, and heparin products were associated with CDI. In simulation, MCEA had superior specificity compared to logistic regression across all tested effect sizes and equal or better sensitivity for all effect sizes besides those close to null.

DISCUSSION: Although these results demonstrate the promise of MCEA, additional studies that include inpatient administered medications are necessary for validation of the algorithm.

CONCLUSIONS: In clinical and simulation studies, MCEA demonstrated superior sensitivity and specificity for identifying pharmacologic classes associated with CDI compared to logistic regression.

BACKGROUND AND AIMS: Reactive testing has emerged as the new standard of care for managing loss of response to infliximab in inflammatory bowel disease [IBD]. Recent data suggest that proactive infliximab monitoring is associated with better therapeutic outcomes in IBD. Nevertheless, there are no data regarding the clinical utility of proactive infliximab monitoring after first reactive testing. We aimed to evaluate long-term outcomes of proactive infliximab monitoring following reactive testing compared with reactive testing alone in patients with IBD.

METHODS: This was a retrospective multicenter cohort study of consecutive IBD patients on infliximab maintenance therapy receiving a first reactive testing between September 2006 and January 2015. Patients were divided into two groups; Group A [proactive infliximab monitoring after reactive testing] and Group B [reactive testing alone]. Patients were followed through December 2015. Time-to-event analysis for treatment failure and IBD-related surgery and hospitalization was performed. Treatment failure was defined as drug discontinuation due to either loss of response or serious adverse event.

RESULTS: The study population consisted of 102 [n = 70, 69% with CD] patients [Group A, n = 33 and Group B, n = 69] who were followed for (median, interquartile range [IQR]) 2.7 [1.4-3.8] years. Multiple Cox regression analysis identified proactive following reactive TDM as independently associated with less treatment failure (hazard ratio [HR] 0.15; 95% confidence interval [CI] 0.05-0.51; p = 0.002) and fewer IBD-related hospitalizations [HR: 0.18; 95% CI 0.05-0.99; p = 0.007].

CONCLUSIONS: This study showed that proactive infliximab monitoring following reactive testing was associated with greater drug persistence and fewer IBD-related hospitalizations than reactive testing alone.

BACKGROUND: The Department of Veterans Affairs (VA) has implemented robust strategies to monitor prescription opioid dispensing, but these strategies have not accounted for opioids prescribed by non-VA providers. State-based prescription drug monitoring programs (PDMPs) are a potential tool to identify VA patients' receipt of opioids from non-VA prescribers, and recent legislation requires their use within VA.

OBJECTIVE: To evaluate VA physicians' perspectives and experiences regarding use of PDMPs to monitor Veterans' receipt of opioids from non-VA prescribers.

DESIGN: Qualitative study using semi-structured interviews.

PARTICIPANTS: Forty-two VA primary care physicians who prescribed opioids to 15 or more Veterans in 2015. We sampled physicians from two states with PDMPs (Massachusetts and Illinois) and one without prescriber access to a PDMP at the time of the interviews (Pennsylvania).

APPROACH: From February to August 2016, we conducted semi-structured telephone interviews that addressed the following topics regarding PDMPs: overall experiences, barriers to optimal use, and facilitators to improve use.

KEY RESULTS: VA physicians broadly supported use of PDMPs or desired access to one, while exhibiting varying patterns of PDMP use dictated by state laws and their clinical judgment. Physicians noted administrative burdens and incomplete or unavailable prescribing data as key barriers to PDMP use. To facilitate use, physicians endorsed (1) linking PDMPs with the VA electronic health record, (2) using templated notes to document PDMP use, and (3) delegating routine PDMP queries to ancillary staff.

CONCLUSIONS: Despite the time and administrative burdens associated with their use, VA physicians in our study broadly supported PDMPs. The application of our findings to ongoing PDMP implementation efforts may strengthen PDMP use both within and outside VA and improve the safe prescribing of opioids.

PURPOSE: Results of a study to estimate the prevalence of look-alike/sound-alike (LASA) medication errors through analysis of Veterans Affairs (VA) administrative data are reported.

METHODS: Veterans with at least 2 filled prescriptions for 1 medication in 20 LASA drug pairs during the period April 2014-March 2015 and no history of use of both medications in the preceding 6 months were identified. First occurrences of potential LASA errors were identified by analyzing dispensing patterns and documented diagnoses. For 7 LASA drug pairs, potential errors were evaluated via chart review to determine if an actual error occurred.

RESULTS: Among LASA drug pairs with overlapping indications, the pairs associated with the highest potential-error rates, by percentage of treated patients, were tamsulosin and terazosin (3.05%), glipizide and glyburide (2.91%), extended- and sustained-release formulations of bupropion (1.53%), and metoprolol tartrate and metoprolol succinate (1.48%). Among pairs with distinct indications, the pairs associated with the highest potential-error rates were tramadol and trazodone (2.20%) and bupropion and buspirone (1.31%). For LASA drug pairs found to be associated with actual errors, the estimated error rates were as follows: lamivudine and lamotrigine, 0.003% (95% confidence interval [CI], 0-0.01%); carbamazepine and oxcarbazepine, 0.03% (95% CI, 0-0.09%); and morphine and hydromorphone, 0.02% (95% CI, 0-0.05%).

CONCLUSION: Through the use of administrative databases, potential LASA errors that could be reviewed for an actual error via chart review were identified. While a high rate of potential LASA errors was detected, the number of actual errors identified was low.

OBJECTIVE: We sought to estimate size and sources of differences in per capita expenditures on primary care medications in the US versus ten comparable countries combined: Australia, Canada, France, Germany, the Netherlands, New Zealand, Norway, Sweden, Switzerland, and the United Kingdom.

METHODS: Using market research data on year 2015 volumes and sales of medicines, we measure total per capita expenditures on six categories of primary care prescription drugs: hypertension treatments, pain medications, lipid lowing medicines, non-insulin diabetes treatments, gastrointestinal preparations, and antidepressants. We quantified the contributions of five drivers of the observed differences in per capita expenditures.

RESULTS: We estimated that the US spent 203% more per capita on primary care pharmaceuticals than did the ten comparable countries. Despite the difference in spending levels, on average, Americans actually purchased 12% fewer days of related therapies than residents of the comparator countries. Most of the observed difference in expenditures was due to higher transaction prices of medicines and the use of a more expensive mix of medicines in the US.

CONCLUSIONS: If utilization patterns and pharmaceutical prices in the US were similar to those in the 10 comparator countries combined, total spending on primary care pharmaceuticals would fall by 30% or more. Such evidence on the level and drivers of US pharmaceutical expenditures should inform policies in this sector.

BACKGROUND: Overlapping use of opioids and benzodiazepines is associated with increased risk for overdose. Veterans receiving medications concurrently from the U.S. Department of Veterans Affairs (VA) and Medicare may be at higher risk for such overlap.

OBJECTIVE: To assess the association between dual use of VA and Medicare drug benefits and receipt of overlapping opioid and benzodiazepine prescriptions.

DESIGN: Cross-sectional.

SETTING: VA and Medicare.

PARTICIPANTS: All veterans enrolled in VA and Medicare Part D who filled at least 2 opioid prescriptions in 2013 (n = 368 891).

MEASUREMENTS: Outcomes were the proportion of patients with a Pharmacy Quality Alliance (PQA) measure of opioid-benzodiazepine overlap (≥2 filled prescriptions for benzodiazepines with ≥30 days of overlap with opioids) and the proportion of patients with high-dose opioid-benzodiazepine overlap (≥30 days of overlap with a daily opioid dose >120 morphine milligram equivalents). Augmented inverse probability weighting regression was used to compare these measures by prescription drug source: VA only, Medicare only, or VA and Medicare (dual use).

RESULTS: Of 368 891 eligible veterans, 18.3% received prescriptions from the VA only, 30.3% from Medicare only, and 51.4% from both VA and Medicare. The proportion with PQA opioid-benzodiazepine overlap was larger for the dual-use group than the VA-only group (23.1% vs. 17.3%; adjusted risk ratio [aRR], 1.27 [95% CI, 1.24 to 1.30]) and Medicare-only group (23.1% vs. 16.5%; aRR, 1.12 [CI, 1.10 to 1.14]). The proportion with high-dose overlap was also larger for the dual-use group than the VA-only group (4.7% vs. 2.3%; aRR, 2.23 [CI, 2.10 to 2.36]) and Medicare-only group (4.7% vs. 2.9%; aRR, 1.06 [CI, 1.02 to 1.11]).

LIMITATION: Data are from 2013 and cannot capture medications purchased without insurance; unmeasured confounding may remain in this cross-sectional study.

CONCLUSION: Among a national cohort of veterans dually enrolled in VA and Medicare, receiving prescriptions from both sources was associated with greater risk for receiving potentially unsafe overlapping prescriptions for opioids and benzodiazepines.

PRIMARY FUNDING SOURCE: U.S. Department of Veterans Affairs.