Panel 2: methodological issues in conducting pharmacoeconomic evaluations--modeling studies.

نویسندگان

  • J Hay
  • J Jackson
چکیده

The primary purpose of modeling is to inform the decision-making process [1,2]. One considerable benefit of model formalization is that the uncertainties and assumptions in this process are made explicit and transparent. To estimate costs and outcomes, existing data are frequently insufficient to allow optimal healthcare decision-making. Each type of data (retrospective, prospective, meta-analysis, expert opinion) has inherent strengths and weaknesses. Good modeling practice incorporates the best available evidence from all possible sources into a set of explicit parameters. Although randomized clinical trials (RCTs) are the gold standard for clinical research, they are not always the best source of pharmacoeconomic and outcomes data. RCT-based data collection is often too costly, too time-consuming, or otherwise not feasible. Sometimes modeling is the only accessible means to inform the clinical and healthcare decision-making process [3]. Although useful for determining efficacy, data from RCTs have significant limitations that sharply reduce their usefulness for measuring the clinical outcomes and economic consequences of drug use in actual populations, including: • limited duration of follow-up, often only weeks or months; • exclusion or under-representation of many types of patients, especially the vulnerable; • sample sizes too small to detect infrequent events; • atypical treatment settings, providers, and subjects, which may influence compliance, event rates, and costs; • no assessment of healthcare utilization in routine care.

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عنوان ژورنال:
  • Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research

دوره 2 2  شماره 

صفحات  -

تاریخ انتشار 1999