Publications

OBJECTIVES: To evaluate how changes in generic drug prices and the incidence of abrupt price increases varied with the number of manufacturers supplying each drug.

STUDY DESIGN: Analysis of 2005 to 2016 monthly wholesale acquisition costs (WACs) and University of Pittsburgh Medical Center Health Plan counts of pharmacy claims for National Drug Codes (NDCs) for generic drugs.

METHODS: Each year, NDCs were categorized according to the number of manufacturers offering each combination of active ingredient and dosage form: 1 to 3, 4 to 7, and more than 7. For every month from January 2006 to January 2017, we estimated the 12-month change in WAC (eg, 12-month change in January 2006 was calculated as the difference in WAC between January 2006 and January 2005, divided by the WAC in January 2005), before and after weighting each NDC by counts of pharmacy claims. We evaluated the proportion of NDCs that had large price increases, greater than 20%, 50%, 100%, and 500% within a year.

RESULTS: Before 2010, price changes were higher for drugs supplied by a lower number of manufacturers; however, after 2010, prices increased sharply, and drugs supplied by 4 to 7 manufacturers showed increases similar to or higher than those supplied by 1 to 3. In 2013, prices increased by an average of 29% for drugs supplied by 1 to 3 and 4 to 7 manufacturers, and 10% for more than 7. Price changes increased after weighting by counts of pharmacy claims, demonstrating that price increases disproportionately affected widely used drugs. The proportion of NDCs from drugs supplied by 1 to 3 manufacturers that doubled in price within a year was 3.6 times higher in 2012 to 2015 than in 2005 to 2009 (4.6% vs 1.3%, respectively).

CONCLUSIONS: Increases in generic drug prices are concerning because they affected widely used drugs and suggest that generic drug prices may be increasingly insensitive to competition.

BACKGROUND: Value-based contracts link medication payments to performance measures with the ultimate goal of lowering costs while improving patient outcomes. Previous multiple sclerosis (MS) value-based contracts have focused on indicators easily collected from claims or electronic health record data as their value-based outcomes, even though numerous other MS clinical indicators of interest exist. Uncertainty remains regarding which MS indicators are most meaningful to all stakeholders affected by a value-based contract.

OBJECTIVE: To identify meaningful MS indicators among key stakeholders for the purpose of informing a value-based contract for MS medications.

METHODS: Using a modified Delphi method, we surveyed 26 diverse stakeholders, including 8 patients and caregivers; 9 providers (neurologists, nurses, physician assistants, and specialty pharmacists); 2 pharmaceutical company representatives; 5 payers; and 2 pharmacy benefits managers. A list of 12 MS indicators was created from subject matter expert consultation and a literature review. All stakeholders reported on the meaningfulness and value of these 12 indicators through a 5-point Likert scale and forced selection of the 3 most meaningful indicators. All nonpatient stakeholders were additionally surveyed on collection feasibility of the same 12 indicators using a 5-point Likert scale. We defined consensus as ≥ 75% agreement on the meaningfulness and feasibility of an indicator (Likert scores 4 or 5). We performed a Fisher's exact test to assess differences between nonpatient and patient stakeholder rankings of indicators.

RESULTS: Consensus was reached for at least 1 indicator for all questions after 2 rounds. "Worsening physical disability" and "functional impairment" achieved 92% agreement on a Likert-scale question assessing indicator value, and 100% of participants selected "worsening physical disability" when asked to choose the 3 most meaningful indicators. "MS flares requiring an emergency department visit" and "MS flares requiring inpatient admission" were rated as the 2 most feasibly collected indicators (both received 89% agreement).

CONCLUSIONS: Using the Delphi method, we identified that disability and functional impairment are meaningful MS indicators to diverse stakeholders. These findings support the incorporation of important patient-reported outcomes into value-based contracts for MS medications.

DISCLOSURES: This study was supported by a grant from Express Scripts Holding Company, which provided research funding to the UPMC Center for Value-Based Pharmacy Initiatives for work on this study. Swart, Neilson, Good, and Parekh are employed by the UPMC Center for Value-Based Pharmacy Initiatives. Manolis is the Chief Pharmacy Officer of UPMC Health Plan, and Shrank was the Chief Medical Officer of UPMC Insurance Services Division at the time of this study. Henderson is employed by Express Scripts Holding Company.

BACKGROUND: The Opioid Safety Initiative decreased high-dose prescriptions across the Veterans Health Administration. This study sought to examine the impact of this intervention (i.e., the Opioid Safety Initiative) on pain scores and opioid prescriptions in patients undergoing total knee arthroplasty.

METHODS: This was an ecological study of group-level data among 700 to 850 patients per month over 72 consecutive months (January 2010 to December 2015). The authors examined characteristics of cohorts treated before versus after rollout of the Opioid Safety Initiative (October 2013). Each month, the authors aggregated at the group-level the differences between mean postoperative and preoperative pain scores for each patient (averaged over 6-month periods), and measured proportions of patients (per 1,000) with opioid (and nonopioid) prescriptions for more than 3 months in 6-month periods, preoperatively and postoperatively. The authors compared postintervention trends versus trends forecasted based on preintervention measures.

RESULTS: After the Opioid Safety Initiative, patients were slightly older and sicker, but had lower mortality rates (postintervention n = 28,509 vs. preintervention n = 31,547). Postoperative pain scores were slightly higher and the decrease in opioid use was statistically significant, i.e., 871 (95% CI, 474 to 1,268) fewer patients with chronic postoperative prescriptions. In time series analyses, mean postoperative minus preoperative pain scores had increased from 0.65 to 0.81, by 0.16 points (95% CI, 0.05 to 0.27). Proportions of patients with chronic postoperative and chronic preoperative opioid prescriptions had declined by 20% (n = 3,355 vs. expected n = 4,226) and by 13% (n = 5,861 vs. expected n = 6,724), respectively. Nonopioid analgesia had increased. Sensitivity analyses confirmed all findings.

CONCLUSIONS: A system-wide initiative combining guideline dissemination with audit and feedback was effective in significantly decreasing opioid prescriptions in populations undergoing total knee arthroplasty, while minimally impacting pain scores.

BACKGROUND: Treatment by high-opioid prescribing physicians in the emergency department (ED) is associated with higher rates of long-term opioid use among Medicare beneficiaries. However, it is unclear if this result is true in other high-risk populations such as Veterans.

OBJECTIVE: To estimate the effect of exposure to high-opioid prescribing physicians on long-term opioid use for opioid-naïve Veterans.

DESIGN: Observational study using Veterans Health Administration (VA) encounter and prescription data.

SETTING AND PARTICIPANTS: Veterans with an index ED visit at any VA facility in 2012 and without opioid prescriptions in the prior 6 months in the VA system ("opioid naïve").

MEASUREMENTS: We assigned patients to emergency physicians and categorized physicians into within-hospital quartiles based on their opioid prescribing rates. Our primary outcome was long-term opioid use, defined as 6 months of days supplied in the 12 months subsequent to the ED visit. We compared rates of long-term opioid use among patients treated by high versus low quartile prescribers, adjusting for patient demographic, clinical characteristics, and ED diagnoses.

RESULTS: We identified 57,738 and 86,393 opioid-naïve Veterans managed by 362 and 440 low and high quartile prescribers, respectively. Patient characteristics were similar across groups. ED opioid prescribing rates varied more than threefold between the low and high quartile prescribers within hospitals (6.4% vs. 20.8%, p < 0.001). The frequency of long-term opioid use was higher among Veterans treated by high versus low quartile prescribers, though above the threshold for statistical significance (1.39% vs. 1.26%; adjusted OR 1.11, 95% CI 0.997-1.24, p = 0.056). In subgroup analyses, there were significant associations for patients with back pain (adjusted OR 1.25, 95% CI 1.01-1.55, p = 0.04) and for those with a history of depression (adjusted OR 1.28, 95% CI 1.08-1.51, p = 0.004).

CONCLUSIONS: ED physician opioid prescribing varied by over 300% within facility, with a statistically non-significant increased rate of long-term use among opioid-naïve Veterans exposed to the highest intensity prescribers.

BACKGROUND: The objective of this study is to describe the use of targeted therapies for the treatment of advanced renal cell carcinoma (RCC) and overall survival (OS) among patients in clinical practice in the Veterans Health Administration (VHA).

METHODS: A retrospective cohort of 286 patients from 24 VHA Medical Centers diagnosed with advanced clear cell RCC between Fiscal Year (FY) 2010 and FY2014 was followed through September 30, 2016. Among patients who received targeted therapy, we described the medications taken, duration of therapy, and overall survival. We also assessed the effect of the first therapy received on overall survival using Cox Proportional Hazards models.

RESULTS: There were 66 patients who did not receive therapy for their advanced RCC. Of the 220 treated patients, the mean (sd) number of medications received was 1.9 (1.1). The medications most commonly used first were sunitinib (61.8%), pazopanib (17.3%), and temsirolimus (10.9%). The median duration of first-line therapy was 86 days (interquartile range [IQR] 42, 210). Median total duration of therapy was 159 days (IQR 58, 397). 62.3% of patients had ≥ 1 dose of therapy held or reduced, mainly due to an adverse drug event (ADE). Median survival from the start of treatment to death was 1.08 years (IQR 0.80, 1.31). Finally, receipt of temsirolimus vs sunitinib (HR 1.95 [95%CI 1.09,3.47]) as the first targeted therapy was independently associated with an increased hazard of death.

CONCLUSION: Our analysis of targeted therapies for advanced RCC in VHA suggests duration of treatment is shorter in a real-world setting than in clinical trials, and dose reductions and ADEs are more common.

IMPORTANCE: Drug safety communications released by the US Food and Drug Administration (FDA) are often based on limited evidence on safety signals after approval. Varenicline may serve as a relevant case study because it was the target of several FDA communications in 2008 and 2009; ultimately, the Evaluating Adverse Events in a Global Smoking Cessation Study (EAGLES) dismissed safety concerns on increased suicidal thoughts and aggressive and erratic behavior on December 16, 2016.

OBJECTIVE: To examine the association between FDA drug safety communications and the use of varenicline.

DESIGN, SETTING, AND PARTICIPANTS: Retrospective, longitudinal, cross-sectional study of Veterans Health Administration (VHA) outpatient data from October 1, 2001, through December 31, 2018, and Medicaid drug state use data from July 1, 2006, through September 30, 2018, on varenicline prescribing.

MAIN OUTCOMES AND MEASURES: Prescribing records for varenicline and nicotine replacement therapy (NRT) in the VHA were extracted, and the number of unique varenicline and NRT users in the VHA per quarter was measured. An interrupted time series analysis was performed to describe the association between FDA safety warnings and the use of varenicline and NRT. To test the generalizability of the findings, similar analyses were conducted using the number of prescriptions reimbursed for varenicline by Medicaid every quarter in 2006-2018.

RESULTS: After its addition to the VHA national drug formulary in January 2007, varenicline use presented a steady increase, reaching a peak of 32 581 quarterly unique users in the first quarter of 2008. Within 12 months of the February 1, 2008, public health advisory, quarterly varenicline use in VHA patients decreased by 68.7% (from 32 581 to 10 182 patients; P < .001 for slope change), and NRT use increased by 32.1% (from 55 728 to 73 629 patients; P < .001 for slope change). In Medicaid prescriptions, varenicline use decreased by 38.0% (from 109 308 to 67 761 prescriptions; P < .001 for slope change) within 12 months of the 2008 public health advisory. Twelve months after the publication of the EAGLES trial, which showed no significant increase in psychiatric/behavioral effects with varenicline relative to NRT, use of varenicline increased by 42.7% in VHA patients (from 9251 to 13 199 patients; P = .01 for slope change) and by 26.0% in Medicaid prescriptions (112 063 to 141 122; P = .26 for slope change ).

CONCLUSIONS AND RELEVANCE: With use of varenicline as a case study, early communications from the FDA and VHA followed by a labeling change appeared to be associated with a considerable decrease in drug use, which may have been associated with negative public health consequences.

BACKGROUND: The 2014 Veterans Access, Choice and Accountability Act (i.e., "Choice") allows eligible Veterans to receive covered health care outside the Veterans Affairs (VA) Healthcare System. The initial implementation of Choice was challenging, and use was limited in the first year.

OBJECTIVE: To assess satisfaction with Choice, and identify reasons for satisfaction and dissatisfaction during its early implementation.

DESIGN AND PARTICIPANTS: Semi-structured telephone interviews from July to September 2015 with Choice-eligible Veterans from 25 VA facilities across the USA.

MAIN MEASURES: Satisfaction was assessed with 5-point Likert scales and open-ended questions. We compared ratings of satisfaction with Choice and VA health care, and identified reasons for satisfaction/dissatisfaction with Choice in a thematic analysis of open-ended qualitative data.

RESULTS: Of 195 participants, 35 had not attempted to use Choice; 43 attempted but had not received Choice care (i.e., attempted only); and 117 attempted and received Choice care. Among those who attempted only, a smaller percentage were somewhat/very satisfied with Choice than with VA health care (17.9% and 71.8%, p < 0.001); among participants who received Choice, similar percentages were somewhat/very satisfied with Choice and VA health care (66.6% and 71.1%, p = 0.45). When asked what contributed to Choice ratings, participants who attempted but did not receive Choice care reported poor access (50%), scheduling problems (20%), and care coordination issues (10%); participants who received Choice care reported improved access (27%), good quality of care (19%), and good distance to Choice provider (16%). Regardless of receipt of Choice care, most participants expressed interest in using Choice in the future (70-82%).

CONCLUSIONS: Access and scheduling barriers contributed to dissatisfaction for Veterans unsuccessfully attempting to use Choice during its initial implementation, whereas improved access and good care contributed to satisfaction for those receiving Choice care. With Veterans' continued interest in using services outside VA facilities, subsequent policy changes should address Veterans' barriers to care.