Julia F. Slejko

Treatment Charges for Traumatic Brain Injury Among Older Adults at a Trauma Center

Objective: To provide charge estimates of treatment for traumatic brain injury (TBI), including both hospital and physician charges, among adults 65 years and older treated at a trauma center. Methods: We identified older adults treated for TBI during 2008–2012 (n = 1843) at Marylands Primary Adult Resource Center and obtained hospital and physician charges separately. Analyses were stratified by sex and all charges were inflated to 2012 dollars. Total TBI charges were modeled as a function of covariates using a generalized linear model. Results: Women comprised 48% of the sample. The mean unadjusted total TBI hospitalization charge for adults 65 years and older was

Prediction models for exacerbations in different COPD patient populations: Comparing results of five large data sources

36 075 (standard deviation,

Estimating Drug Costs: How do Manufacturer Net Prices Compare with Other Common US Price References?

63 073). Physician charges comprised 15% of total charges. Adjusted mean charges were lower in women than in men (adjusted difference, −

In-Hospital Mortality Following Traumatic Brain Injury Among Older Medicare Beneficiaries, Comparing Statin Users With Nonusers

894; 95% confidence interval, −

Patterns of Statin Use in Older Medicare Beneficiaries With Traumatic Brain Injury

277 to −

QUAD versus cfDNA in an urban population in the second trimester for detection of trisomy 21: a cost sensitivity analysis.

1512). Length of hospital and intensive care unit stay were associated with the highest charges. Conclusions: This study provides the first estimates of hospital and physician charges associated with hospitalization for TBI among older adults at a trauma center that will aid in resource allocation, triage decisions, and healthcare policy.

Hepatitis C Treatment Regimens Are Cost-Effective: But Compared With What?:

Background and objectives Exacerbations are important outcomes in COPD both from a clinical and an economic perspective. Most studies investigating predictors of exacerbations were performed in COPD patients participating in pharmacological clinical trials who usually have moderate to severe airflow obstruction. This study was aimed to investigate whether predictors of COPD exacerbations depend on the COPD population studied. Methods A network of COPD health economic modelers used data from five COPD data sources – two population-based studies (COPDGene® and The Obstructive Lung Disease in Norrbotten), one primary care study (RECODE), and two studies in secondary care (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoint and UPLIFT) – to estimate and validate several prediction models for total and severe exacerbations (= hospitalization). The models differed in terms of predictors (depending on availability) and type of model. Results FEV1% predicted and previous exacerbations were significant predictors of total exacerbations in all five data sources. Disease-specific quality of life and gender were predictors in four out of four and three out of five data sources, respectively. Age was significant only in the two studies including secondary care patients. Other significant predictors of total exacerbations available in one database were: presence of cough and wheeze, pack-years, 6-min walking distance, inhaled corticosteroid use, and oxygen saturation. Predictors of severe exacerbations were in general the same as for total exacerbations, but in addition low body mass index, cardiovascular disease, and emphysema were significant predictors of hospitalization for an exacerbation in secondary care patients. Conclusions FEV1% predicted, previous exacerbations, and disease-specific quality of life were predictors of exacerbations in patients regardless of their COPD severity, while age, low body mass index, cardiovascular disease, and emphysema seem to be predictors in secondary care patients only.

Translating Pharmacometrics to a Pharmacoeconomic Model of COPD

BackgroundDrug costs are frequently estimated in economic analyses using wholesale acquisition cost (WAC), but what is the best approach to develop these estimates? Pharmaceutical manufacturers recently released transparency reports disclosing net price increases after accounting for rebates and other discounts.ObjectiveOur objective was to determine whether manufacturer net prices (MNPs) could approximate the discounted prices observed by the U.S. Department of Veterans Affairs (VA).MethodsWe compared the annual, average price discounts voluntarily reported by three pharmaceutical manufacturers with the VA price for specific products from each company. The top 10 drugs by total sales reported from company tax filings for 2016 were included. The discount observed by the VA was determined from each drug’s list price, reported as WAC, in 2016. Descriptive statistics were calculated for the VA discount observed and a weighted price index was calculated using the lowest price to the VA (Weighted VA Index), which was compared with the manufacturer index.ResultsThe discounted price as a percentage of the WAC ranged from 9 to 74%. All three indexes estimated by the average discount to the VA were at or below the manufacturer indexes (42 vs. 50% for Eli Lilly, 56 vs. 65% for Johnson & Johnson, and 59 vs. 59% for Merck).ConclusionsManufacturer-reported average net prices may provide a close approximation of the average discounted price granted to the VA, suggesting they may be a useful proxy for the true pharmacy benefits manager (PBM) or payer cost. However, individual discounts for products have wide variation, making a standard discount adjustment across multiple products less acceptable.

Comparing total and disease specific Healthcare costs for Glaucoma Patients before and after their index Diagnosis: a retrospective claims database analysis

Background: Traumatic brain injury (TBI) is a significant public health concern for older adults. Small-scale human studies have suggested pre-TBI statin use is associated with decreased in-hospital mortality following TBI, highlighting the need for large-scale translational research. Objective: To investigate the relationship between pre-TBI statin use and in-hospital mortality following TBI. Methods: A retrospective study of Medicare beneficiaries 65 and older hospitalized with a TBI during 2006 to 2010 was conducted to assess the impact of pre-TBI statin use on in-hospital mortality following TBI. Exposure of interest included atorvastatin, fluvastatin, lovastatin, pravastatin, rosuvastatin, and simvastatin. Beneficiaries were classified as current, recent, past, and nonusers of statins prior to TBI. The outcome of interest was in-hospital mortality. Logistic regression was used to obtain odds ratios (ORs) and 95% confidence intervals (CIs) comparing current, recent, and prior statin use to nonuse. Results: Most statin users were classified as current users (90%). Current atorvastatin (OR = 0.88; 95% = CI 0.82, 0.96), simvastatin (OR = 0.84; 95% CI = 0.79, 0.91), and rosuvastatin (OR = 0.79; 95% CI = 0.67, 0.94) use were associated with a significant decrease in the risk of in-hospital mortality following TBI. Conclusions: In addition to being the most used statins, current use of atorvastatin, rosuvastatin, and simvastatin was associated with a significant decrease in in-hospital mortality following TBI among older adults. Future research must include clinical trials to help exclude the possibility of a healthy user effect in order to better understand the impact of statin use on in-hospital mortality following TBI.

Mortality and Associated Morbidities Following Traumatic Brain Injury in Older Medicare Statin Users

Background: In addition to lowering lipids, statins also may be beneficial for older adults sustaining a traumatic brain injury (TBI), as statin use prior to and following trauma may decrease mortality following injury. However, despite statins’ potential to reduce mortality, there is limited research regarding statin use among older adults. Objective: To characterize and investigate factors associated with statin use among older adults with TBI. Methods: A retrospective drug utilization study was used to characterize statin use among Medicare beneficiaries 65 and older hospitalized with a TBI during 2006 to 2010 and with continuous Medicare Parts A, B, and D coverage 6 months prior and 12 months following TBI. Logistic regression was used to investigate the factors associated with statin use. The exposure of interest was statin use prior to and following TBI. Results: Of the 75 698 beneficiaries included in the study, 37 874 (~50%) of beneficiaries used a statin at least once during the study period. The most common statin used was simvastatin, while fluvastatin was the least used statin. Statin users were more likely to have cardiovascular diseases when compared to nonusers. Hyperlipidemia was a major factor associated with statin use and had the greatest impact on statin use compared to nonuse (odds ratio = 9.54; 95% confidence interval = 9.07, 10.03). Conclusions: This national sample of older adults with TBI suggests that statins are commonly used. Future studies must next examine the impact of statin use on mortality and secondary injury in order to shape pharmacological therapy guidelines following TBI.