Impact of prescription coverage on hospital and physician costs: a case study of medicare beneficiaries with chronic obstructive pulmonary disease

2004 ◽  
Vol 26 (10) ◽  
pp. 1688-1699 ◽  
Author(s):  
B STUART ◽  
J DOSHI ◽  
B BRIESACHER ◽  
M WROBEL ◽  
F BAYSAC
2015 ◽  
Vol 31 (5) ◽  
pp. 441-449 ◽  
Author(s):  
Jennifer S. Albrecht ◽  
Ting-Ying Huang ◽  
Yujin Park ◽  
Patricia Langenberg ◽  
Ilene Harris ◽  
...  

2020 ◽  
Vol 7 (1) ◽  
pp. e000483 ◽  
Author(s):  
Tham Thi Le ◽  
Siyeon Park ◽  
Michelle Choi ◽  
Marniker Wijesinha ◽  
Bilal Khokhar ◽  
...  

BackgroundOpioids and sedatives are commonly prescribed in chronic obstructive pulmonary disease (COPD) patients for symptoms of dyspnoea, pain, insomnia, depression and anxiety. Older adults are advised to avoid these medications due to increased adverse events, including respiratory events. This study examines respiratory event risks associated with concomitant opioid and sedative use compared with opioid use alone in older adults with COPD.MethodsA 5% nationally representative sample of Medicare beneficiaries with COPD and opioid use between 2009 and 2013 was used for this retrospective cohort study. Current and past concomitant use were identified using drug dispensed within 7 days from the censored date: at respiratory event, at death, or at 12 months post index. Concomitant opioid and sedative use were categorised into no overlap (opioid only), 1 to 10, 11 to 30, 31 to 60 and >60 days of total overlap. The primary outcome was hospitalisation or emergency department (ED) visits for respiratory events (COPD exacerbations or respiratory depression). Propensity score matching was implemented and semi-competing risk models were used to address competing risk by death.ResultsAmong 48 120 eligible beneficiaries, 1810 (16.7%) concomitant users were matched with 9050 (83.3%) opioid only users. Current concomitant use of 1 to 10, 11 to 30 and 31 to 60 days was associated with increased respiratory events (HRs (95% CI): 2.8 (1.2 to 7.3), 9.3 (4.9 to 18.2) and 5.7 (2.5 to 12.5), respectively), compared with opioid only use. Current concomitant use of >60 days or past concomitant use of ≤60 days was not significantly associated with respiratory events. Consistent findings were found in sensitivity analyses, including in subgroup analysis of non-benzodiazepine sedatives. Additionally, current concomitant use significantly increased risk of death.ConclusionShort-term and medium-term current concomitant opioid and sedative use significantly increased risk of respiratory events and death in older COPD Medicare beneficiaries. Long-term past concomitant users, however, demonstrated lower risks of these outcomes, possibly reflecting a healthy user effect or developed tolerance to the effects of these agents.


2020 ◽  
Vol 40 (5) ◽  
pp. 619-632
Author(s):  
Isaac Corro Ramos ◽  
Martine Hoogendoorn ◽  
Maureen P. M. H. Rutten-van Mölken

Background. Evaluation of personalized treatment options requires health economic models that include multiple patient characteristics. Patient-level discrete-event simulation (DES) models are deemed appropriate because of their ability to simulate a variety of characteristics and treatment pathways. However, DES models are scarce in the literature, and details about their methods are often missing. Methods. We describe 4 challenges associated with modeling heterogeneity and structural, stochastic, and parameter uncertainty that can be encountered during the development of DES models. We explain why these are important and how to correctly implement them. To illustrate the impact of the modeling choices discussed, we use (results of) a model for chronic obstructive pulmonary disease (COPD) as a case study. Results. The results from the case study showed that, under a correct implementation of the uncertainty in the model, a hypothetical intervention can be deemed as cost-effective. The consequences of incorrect modeling uncertainty included an increase in the incremental cost-effectiveness ratio ranging from 50% to almost a factor of 14, an extended life expectancy of approximately 1.4 years, and an enormously increased uncertainty around the model outcomes. Thus, modeling uncertainty incorrectly can have substantial implications for decision making. Conclusions. This article provides guidance on the implementation of uncertainty in DES models and improves the transparency of reporting uncertainty methods. The COPD case study illustrates the issues described in the article and helps understanding them better. The model R code shows how the uncertainty was implemented. For readers not familiar with R, the model’s pseudo-code can be used to understand how the model works. By doing this, we can help other developers, who are likely to face similar challenges to those described here.


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