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Economic and Quality of Life Outcomes: The Four-Step Pharmacoeconomic Research Model

Economic and Quality of Life Outcomes: The Four-Step Pharmacoeconomic Research Model

Increasingly, economic data are being considered in formulary decisions. In oncology, pharmacoeconomic evaluations are essential to help decision makers weigh the associated costs and outcomes of competing chemotherapeutic interventions. In this article, we present a four-step pharmacoeconomic research model that can be customized for specific provider or payer systems. The model encompasses problem identification, clinical management analysis, three pharmacoeconomic analyses (cost consequence, expected cost, and cost effectiveness), and a sensitivity analysis-the rank order stability analysis (ROSA)-to validate the findings.


Health care professionals, policymakers, and formulary committee members are increasingly asked to augment formulary consideration of drug efficacy and safety with economic information. In this era of dwindling health care budgets, pharmacoeconomic analysis facilitates choices, in terms of overall outcomes between therapies competing for the same health care resources. This method of economic evaluation informs the programmatic medical decision maker of the appropriateness and value of health care procedures, including drugs [1]. In no other field has the necessity and relative value of such analyses proved to be more applicable than in oncology.

Comparisons of competing new chemotherapeutic interventions warrant a pharmacoeconomic evaluation to weigh associated costs and outcomes and compare these "offsets" with those of traditional therapy. Our four-step research approach described in this article is a flexible economic model for evaluating costs and consequences that
will accommodate provider-specific parameters.

One very useful analytic component of such a model, discussed below, is cost-effectiveness analysis, which compares the health effects of a treatment strategy with the resources that must be invested to adopt the strategy [2]. Comparison of effectiveness in cancer is particularly difficult, since the criteria for diagnosis vary with pathologists, and the criteria for prognosis vary with the extent of disease [3]. The ability to customize the economic model for specific provider or payer systems is essential in generating valid and generalizable pharmacoeconomic data.

Authoritative pharmacoeconomic research requires a coherent data set to ensure an effective valuation of costs and outcomes. Often, assumptions and biases are immersed within a data set, thereby compromising the integrity of an analysis. To compensate for this intrinsic uncertainty, the four-step model incorporates a comprehensive sensitivity analysis, described below, to identify "cost drivers" and specific points of model instability.

It should be emphasized that pharmacoeconomics is a prescriptive science, employed to facilitate choices in allocating scarce resources. When properly executed and validated, economic research studies provide essential information as input into the decision-making process [1]. Traditional considerations, such as safety, efficacy, equity, and access, should continue to serve as inputs into medical decisions.

Importance of Pharmacoeconomics to Oncology

Worldwide inflation of health care budgets has prompted many cost investigations, predominantly emphasizing drug therapy. New chemotherapeutic interventions have provided monumental improvements in patient care, but not without associated increases in drug therapy costs. Clinically significant outcomes (which may be curative, palliative, or preventive) require a pharmacoeconomic analysis to quantify cost-effectiveness of therapy. Desired outcomes attributed to new therapies may be appreciated by the provider, patient, and payer alike. An effective comparison of competing therapies warrants a valuation of desired and undesired outcomes of therapy, to ensure that a marginal outcome merits incremental cost.

Chemotherapy has resulted in improved palliation of symptoms, higher response rates, and extended time to treatment failures. These successful clinical results are allied with financial benefits that may be realized by the provider (eg, hospital), third-party payer (eg, Medicare), or patient. From the perspective of a provider or third-party payer, the cost savings generated by chemotherapy are partially derived from patients who have failed on primary therapy. The decreased follow-up care costs associated with treating failed therapy patients may be directly quantified as cost avoidance. Successful treatment, or successful period of care, may also be evaluated from the patient perspective as represented by quality of life. Cost effectiveness, possibly measured in terms of cost per event-free days, may provide a retrospective proxy for patient quality of life.

A longer-term research objective is to prospectively examine the economic implications of competing therapeutic interventions. Better efficacy and longer effective treatment periods translate into optimal resource utilization and improved patient quality of life. Validated survey instruments are employed to evaluate physical, social, and emotional aspects of a patient's well-being that are relevant and important to the patient [1]. This prospective technique will allow for a determination and financial quantification of patient disease-free periods, further demonstrating cost-effective or cost-utility benefits.


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