BackgroundOpioid dependence is a chronic condition with substantial health, economic and social costs. The study objective was to conduct a systematic review of published health-economic models of opioid agonist therapy for non-prescription opioid dependence, to review the different modelling approaches identified, and to inform future modelling studies. MethodsLiterature searches were conducted in March 2015 in eight electronic databases, supplemented by hand-searching reference lists and searches on six National Health Technology Assessment Agency websites. Studies were included if they: investigated populations that were dependent on non-prescription opioids and were receiving opioid agonist or maintenance therapy; compared any pharmacological maintenance intervention with any other maintenance regimen (including placebo or no treatment); and were health-economic models of any type.ResultsA total of 18 unique models were included. These used a range of modelling approaches, including Markov models (n = 4), decision tree with Monte Carlo simulations (n = 3), decision analysis (n = 3), dynamic transmission models (n = 3), decision tree (n = 1), cohort simulation (n = 1), Bayesian (n = 1), and Monte Carlo simulations (n = 2). Time horizons ranged from 6 months to lifetime. The most common evaluation was cost-utility analysis reporting cost per quality-adjusted life-year (n = 11), followed by cost-effectiveness analysis (n = 4), budget-impact analysis/cost comparison (n = 2) and cost-benefit analysis (n = 1). Most studies took the healthcare provider’s perspective. Only a few models included some wider societal costs, such as productivity loss or costs of drug-related crime, disorder and antisocial behaviour. Costs to individuals and impacts on family and social networks were not included in any model.ConclusionA relatively small number of studies of varying quality were found. Strengths and weaknesses relating to model structure, inputs and approach were identified across all the studies. There was no indication of a single standard emerging as a preferred approach. Most studies omitted societal costs, an important issue since the implications of drug abuse extend widely beyond healthcare services. Nevertheless, elements from previous models could together form a framework for future economic evaluations in opioid agonist therapy including all relevant costs and outcomes. This could more adequately support decision-making and policy development for treatment of non-prescription opioid dependence.Electronic supplementary materialThe online version of this article (doi:10.1186/s13722-017-0071-3) contains supplementary material, which is available to authorized users.
Background & Objectives: Acute Hyper tension is the most common condition seen in primary care and leads to myocardial infarction, stroke, renal failure, and death if not detected early and treated appropriately. The study was conducted with the objective to examine the incidence of different types of adverse drug reactions in drug treated hypertensive patients. Materials & Methods:Patients (n=382) who received antihypertensive agents were selected and interviewed using a standardized questionnaire. The Naranjo Algorithm, which categorizes the causality relationship into definite, probable, possible and doubtful, was used for the assessment of the exact nature of Adverse drug reaction (ADR). Results: Calcium channel blockers (CCBs) were the drug class with highest number (22 or 32.84%) of ADRs followed by Angiotensinconverting enzyme Inhibitors (ACEI) in 17 (25.38%), Angiotensin Receptor Blockers (ARB) in 12 (17.91%), diuretics in 10 (14.92%) and beta adrenergic antagonist in six (8.95%). Cardiovascular system (40 or 59.70%) was the most affected followed by central nervous system (16 or 23.88%) and respiratory and dermatological system each in 11 (16.42%) cases. On Naranjo's probability scale, nine (13.4%) of the ADRs were definite, 39 (58.2%) possible, 16 (23.9%) probable and three (4.5%) doubtful.Conclusion: Calcium channel blockers were mostly associated with ADRs while Cardiovascular system was the most frequently affected.Key words: Adver se dr ug r eactions; Antihyper tensive agents; Naranjo Algorithm Citation: Paudel S, Chetty MS, Laudar i S, Subedi ND. Adver se dr ug r eactions of antihyper tensive agents at tertiary care hospital in central Nepal. JCMS Nepal. 2017;13(2):284-9.
A411costs and productivity losses were calculated. Costs data were derived from Russian cost-of-illness study of depression and registered maximal drug prices list. The outcomes were modelled for 3 years period. Costs were converted to EUROs using the average weighted exchange rate in 2014 (1€ = 50.815RUR). Sensitivity analysis was performed. Results: Agomelatine appeared to be the dominant therapy in comparison with branded fluoxetine, sertraline and escitalopram, which allowed achieving maximum clinical outcome and utility (2.148 QALY vs 2.097, 2.133 and 2.119 QALY, respectively) at the lowest costs (€ 1,932 vs € 2,485, € 2,076 and € 2,454). Agomelatine remained dominant strategy even when only direct medical costs were included into analysis (€ 943 vs € 1,172, € 1,002 and € 1,290). ConClusions: Agomelatine was demonstrated to be the rational choice in comparison with other branded antidepressants routinely used in Russian health care settings.
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