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The analysis of the relationship of pharmaceutical and device costs to health care systems has been termed pharmacoeconomics, and four types of analytical techniques are commonly used for this purpose, namely cost-minimization, cost-benefit, cost-effectiveness, and cost-utility analyses.1


With diminishing payments from private and government-based health insurance programs worldwide, physicians and administrators are forced to focus attention toward cost-containment in order to maintain a profitable (or at least “break-even”) enterprise. Cost analysis is an emerging tool in health care economics, which can help physicians and administrators meet these new challenges.


Cost analysis examines health care expenditures, and the subtypes of cost analysis also examine factors that are inserted into a denominator of a cost equation. Such factors include monetary benefits (eg, cost-benefit analysis, or CBA), incremental changes of health-status variables (eg, cost-effectiveness analysis, or CEA), and patient-reported quality of life (eg, cost-utility analysis, or CUA).2 If outcomes are determined to be equivalent regardless of the treatment program implemented, then a basic cost-minimization analysis is all that is required, since the denominators are equal and the only relevant comparison is between the cost numerators of the compared programs.3

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Clinical Pearls
The four types of analytical techniques used in pharmacoeconomics are
  • Cost-minimization
  • Cost-benefit analysis
  • Cost-effectiveness analysis
  • Cost-utility analysis

CEA is applicable when the effects of comparable health treatments or services share the same therapeutic goals, but have different degrees of effectiveness.4 With CEA, the analyst can compare alternative treatment strategies so that results can be expressed in identical effectiveness units. CEA accounts for the effect of a treatment plan on all clinical outcomes and its economic implications, rather than considering only the cost of devices, supplies, and pharmaceuticals.4 Effectiveness indicators, such as the number of adverse effects avoided or hospital stay reductions, are useful for comparing the different therapeutic alternatives considered. For this reason, CEA is one way of comparing treatment plans with the same desired effect but different outcome profiles, thus producing results expressed in terms of the number of adverse effects avoided. This approach implies weighting all adverse effects alike, or weighting the different adverse effects in the way deemed most suitable by the analyst.4


With respect to anesthesia selection, it is highly unlikely that comparing regional (RA) with general anesthesia/volatile agent (GAVA) techniques would show equal benefits or equal effectiveness (ie, life-years gained, days of disability avoided). RA significantly differs from GAVA, and the relevant side effect profiles and risks are quite different as well. In fact, in the past few years, it has become very clear in ambulatory procedures, for example, that the choices of the anesthetic and postoperative analgesic techniques have significant consequences on both the length of hospital stay and the frequency of unplanned hospitalization,5,6 and consequently, the overall cost of the surgery. As a result, comparisons between RA and GAVA would require ...

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