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.

Isolation of C. difficile Carriers Alone and as Part of a Bundle Approach for the Prevention of Clostridium difficile Infection (CDI): A Mathematical Model Based on Clinical Study Data.

Clostridium difficile infection is the most common hospital-acquired infection. Besides infected patients, carriers have emerged as a key player in C. difficile epidemiology. In this study, we evaluated the impact of identifying and isolating carriers upon hospital admission on the incidence of CDI incidence and hospital-acquired C. difficile colonization, as a single policy and as part of bundle approaches. We simulated C. difficile transmission using a stochastic mathematical approach, considering the contribution of carriers based on published literature. In the baseline scenario, CDI incidence was 6.18/1,000 admissions (95% CI, 5.72-6.65), simulating reported estimates from U.S. hospital discharges. The acquisition rate of C. difficile carriage was 9.72/1,000 admissions (95% CI, 9.15-10.31). Screening and isolation of colonized patients on admission to the hospital decreased CDI incidence to 4.99/1,000 admissions (95% CI, 4.59-5.42; relative reduction (RR) = 19.1%) and led to 36.2% reduction in the rate of hospital-acquired colonization. Simulating an antimicrobial stewardship program reduced CDI rate to 2.35/1,000 admissions (95% CI, 2.07-2.65). In sensitivity analysis, CDI incidence was less than 2.32/1,000 admissions (RR = 62.4%) in 95% of 1,000 simulations. The combined bundle, focusing on reducing C. difficile transmission from colonized patients and the individual risk of these patients to develop CDI, decreased significantly the incidence of both CDI and hospital-acquired colonization. Implementation of this bundle to current practice is expected to have an important impact in containing CDI.

ATG16L1 and IL23R variants and genetic susceptibility to crohn's disease: mode of inheritance based on meta-analysis of genetic association studies.

BACKGROUND: Autophagy and regulation of IL-23 signaling pathways have been implicated in the pathogenesis of Crohn's disease (CD). We studied the mode of inheritance and reviewed the association of 2 polymorphic variants of ATG16L1 and IL23R with CD. METHODS: We searched the PubMed and ISI Web of Science databases (up to May 2014) for pertinent articles. We included all studies that had a case-control design, with cases having CD and controls being healthy and reported full genotype frequencies for the ATG16L1 and/or IL23R variant of interest. We quantified the relative genetic risk using the model-free approach of the generalized odds ratio metric (ORG) and reported 95% precision estimates. Also, we explored the mode of inheritance using the degree of dominance h-index. RESULTS: Fifty-one studies fulfilled these requirements and were included in the analysis. These studies involved 12,762 patients and 16,735 controls evaluating the association of ATG16L1 (rs2241880 p.Thr300Ala) and 8110 patients and 11,900 controls evaluating the association of IL23R (rs11209026 p.Arg381Gln) with CD. The ATG16L1 variant rs2241880 was associated with increased susceptibility to CD (combined ORG = 1.38; 95% confidence interval, 1.29-1.48) and a nondominant mode of inheritance (suggesting that the effect of heterozygosity lies exactly in the middle of extreme homozygotes, h = 0). The IL23R variant rs11209026 was associated with significant protection (ORG = 0.46; 95% confidence interval, 0.41-0.53) and a recessive mode of inheritance, indicating that the effect of a heterozygous genotype would lie close to the wild-type homozygous genotype. In subgroup analysis, the significant effects persisted across Caucasian ancestry studies and pediatric populations but were lacking across studies in Asian populations. CONCLUSIONS: The ATG16L1 variant rs2241880 was associated with 38% increase in the risk for CD for higher mutational load, whereas IL23R variant rs11209026 decreased the risk by 54% for higher mutational load. The mode of inheritance for ATG16L1 variant demonstrated perfect additivity for genetic risk, whereas it showed recessiveness for the IL23R variant. This analysis permits risk stratification for CD based on the mutational status and highlight the need for additional studies in certain populations.

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.