Correlation of Opioid Mortality with Prescriptions and Social Determinants: A Cross-sectional Study of Medicare Enrollees.

BACKGROUND: The opioid epidemic is an escalating health crisis. We evaluated the impact of opioid prescription rates and socioeconomic determinants on opioid mortality rates, and identified potential differences in prescription patterns by categories of practitioners. METHODS: We combined the 2013 and 2014 Medicare Part D data and quantified the opioid prescription rate in a county level cross-sectional study with data from 2710 counties, 468,614 unique prescribers and 46,665,037 beneficiaries. We used the CDC WONDER database to obtain opioid-related mortality data. Socioeconomic characteristics for each county were acquired from the US Census Bureau. RESULTS: The average national opioid prescription rate was 3.86 claims per beneficiary that received a prescription for opioids (95% CI 3.86-3.86). At a county level, overall opioid prescription rates (p < 0.001, Coeff = 0.27) and especially those provided by emergency medicine (p < 0.001, Coeff = 0.21), family medicine physicians (p = 0.11, Coeff = 0.008), internal medicine (p = 0.018, Coeff = 0.1) and physician assistants (p = 0.021, Coeff = 0.08) were associated with opioid-related mortality. Demographic factors, such as proportion of white (p white < 0.001, Coeff = 0.22), black (p black < 0.001, Coeff = - 0.19) and male population (p male < 0.001, Coeff = 0.13) were associated with opioid prescription rates, while poverty (p < 0.001, Coeff = 0.41) and proportion of white population (p white < 0.001, Coeff = 0.27) were risk factors for opioid-related mortality (p model < 0.001, R 2 = 0.35). Notably, the impact of prescribers in the upper quartile was associated with opioid mortality (p < 0.001, Coeff = 0.14) and was twice that of the remaining 75% of prescribers together (p < 0.001, Coeff = 0.07) (p model = 0.03, R 2 = 0.03). CONCLUSIONS: The prescription opioid rate, and especially that by certain categories of prescribers, correlated with opioid-related mortality. Interventions should prioritize providers that have a disproportionate impact and those that care for populations with socioeconomic factors that place them at higher risk.

The Impact of Shortages on Medication Prices: Implications for Shortage Prevention.

BACKGROUND: Medication shortages are frequent and have clinical and financial ramifications; however, their effect on drug prices remains unknown. OBJECTIVE: To examine price progression of medications affected by a shortage. METHODS: We collected prices of medications covered under Medicare Part B, reflective of general market prices, and data on clinically relevant shortages for the period 2005-16. We used linear mixed-effects models to examine the price growth of affected medications. RESULTS: Shortage medications demonstrated a quarterly price growth of -0.5 % (95 % confidence interval [CI] -1.6, 0.6) in the period preceding a shortage, 4.3 % (95 % CI 3.6, 4.5) during a shortage, and 4.1 % (95 % CI 2.6, 5.5) in the post-shortage period. Medications not affected by a shortage had a quarterly price growth of 0.2 % (95 % CI -0.3, 0.6). CONCLUSIONS: Medication shortages are associated with price increases, and these increases are likely reactive to the low profitability of the affected medications and thus, proactive collaboration between the US Food and Drug Administration and industry can serve to identify low-profit drugs and evaluate measures to ensure continued production.

Adaptation of Cost Analysis Studies in Practice Guidelines.

Clinical guidelines play a central role in day-to-day practice. We assessed the degree of incorporation of cost analyses to guidelines and identified modifiable characteristics that could affect the level of incorporation.We selected the 100 most cited guidelines listed on the National Guideline Clearinghouse (http://www.guideline.gov) and determined the number of guidelines that used cost analyses in their reasoning and the overall percentage of incorporation of relevant cost analyses available in PubMed. Differences between medical specialties were also studied. Then, we performed a case-control study using incorporated and not incorporated cost analyses after 1:1 matching by study subject and compared them by the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement requirements and other criteria.We found that 57% of guidelines do not use any cost justification. Guidelines incorporate a weighted average of 6.0% (95% confidence interval [CI] 4.3-7.9) among 3396 available cost analyses, with cardiology and infectious diseases guidelines incorporating 10.8% (95% CI 5.3-18.1) and 9.9% (95% CI 3.9- 18.2), respectively, and hematology/oncology and urology guidelines incorporating 4.5% (95% CI 1.6-8.6) and 1.6% (95% CI 0.4-3.5), respectively. Based on the CHEERS requirements, the mean number of items reported by the 148 incorporated cost analyses was 18.6 (SD = 3.7), a small but significant difference over controls (17.8 items; P = 0.02). Included analyses were also more likely to directly relate cost reductions to healthcare outcomes (92.6% vs 81.1%, P = 0.004) and declare the funding source (72.3% vs 53.4%, P < 0.001), while similar number of cases and controls reported a noncommercial funding source (71% vs 72.7%; P = 0.8).Guidelines remain an underused mechanism for the cost-effective allocation of available resources and a minority of practice guidelines incorporates cost analyses utilizing only 6% of the available cost analyses. Fulfilling the CHEERS requirements, directly relating costs with healthcare outcomes and transparently declaring the funding source seem to be valued by guideline-writing committees.