The failure to contain health-care costs and curtail growth is a growing national economic concern and public policy issue. The marketplace is rapidly changing how health care is paid for by moving from fee-for-service mechanisms to prospective payment, diagnosis-related groups, and increasing exclusion of some treatment(s).
As Eisenberg has stated, "To suggest that medical decision making can be divorced from consideration of cost denigrates the complexity of patient care" . The application of economic principles to medicine does not necessarily mean that less money should or will be spent, but that resources may be used more efficiently. A key question is: Can clinicians continue to maintain the current standards of care and provide the extent of services that Americans have come to expect?
It has been estimated that the oncology services provided by Medicare are increasing by approximately 17% annually . Four major reasons account for this growth:
1. Demographic changes
2. A common reluctance to stop "active" therapy
3. Increasing attention to quality of life concerns
4. Innovations in biotechnology (ie, potentially effective new therapies).
Cost-effectiveness analysis assumes a societal utilitarian perspective with the objective of maximizing net health benefit for all members of a population within a limited level of resources. This societal perspective is in stark contrast to the clinician's perspective, whose goal is to maximize his or her patient's health status (whatever the effect of those decisions on other patients or resources). This difference in perspective and objectives explains why many clinicians object to the use of cost-effectiveness analysis in setting policies.
Cost-effectiveness requires making comparisons between two or more alternative methods of approaching a health problem. The alternatives may include one or more different interventions or no treatment at all. Comparisons between approaches allow determining the incremental cost-effectiveness of a strategy: the additional cost and effectiveness obtained when one option is compared with the next most effective option or next most expensive alternative.
The use of cost-effectiveness analysis as a policy tool (either public or private) requires establishing cut-off points of either how much we are willing to spend to achieve a specific level of health benefits, or, for a finite amount of dollars, how we can maximize the level of health for all of us as a group. We have not yet reached a consensus about either form of the question. A comparative table of "dollars/life-year gained" is not an immutable listing, but a starting point for discussions on societal and individual expectations.
Costs can be controlled, and the cost-effectiveness of different strategies can occur at any stage in the natural history of cancer. Using the arbitrary categories of screening, staging, primary therapy, adjuvant therapy, monitoring, and palliative care, it is interesting to note that the majority of such studies have been conducted in either the screening or adjuvant therapy setting.
In our previously published review , it is striking to note how few studies have been conducted to evaluate the cost-effectiveness of any type of cancer therapy. Few comparisons have been made between treatments, eg, radiation therapy vs surgery. "Watchful waiting" (ie, no therapy) is rarely evaluated as an arm in studies of primary therapies. The majority of cost-effectiveness studies in oncology are comparisons of drug treatments. This may be due to the relative ease of estimating costs, or it may be a reflection of the nature of randomized trials. The cost estimates used in these studies vary widely, and make comparisons across settings difficult.
The optimal and least controversial method for performing a cost-effectiveness analysis is to use mature efficacy data. Efficacy data in cancer trials generally consist of changes in survival or in disease-free survival. Our group has assessed the cost-effectiveness of adjuvant chemotherapy, tamoxifen(Drug information on tamoxifen), or combination therapy in women with early breast cancer . These investigations were possible since the natural history of breast cancer is relatively well defined, the estimated efficacy of therapy is better known in breast cancer than in all other cancers, and the widespread use of chemotherapy was controversial at the time of publication, making the report publishable in a prominent journal. Our analyses translated clinical trial results into estimates of changes in survival, discounted survival (ie, current vs future years), and we estimated from a societal perspective the additional cost per quality-adjusted life-year. Our analyses and the work of others support the generalization that if meaningless differences in efficacy, primarily survival, occur with a specific therapy, then it will have a cost-effectiveness ratio that is generally acceptable.
There has been an increasing trend toward performing cost-effectiveness analyses without the benefit of efficacy data from randomized controlled trials. This is due to the unfortunate rapid dissemination into routine clinical care of technologies and therapies prior to optimal evaluation. This occurs most often in the settings of cancer and acquired immune deficiency syndrome (AIDS). Since it is impossible to "put the genie back into the lamp," cost-effectiveness assessments are needed to help guide health policy, but do not replace appropriate clinical trials. These models highlight the gaps in the current state of knowledge, identify the key variables to assess in trials, the need for community registries, and consequences of differences in short-term morbidity and mortality that are commonly found across settings.
To date, a strikingly small number of cost-effectiveness analyses of cancer treatment have focused primarily on the adjuvant setting. The lack of studies of metastatic and palliative care may be due to difficulties in measuring changes in quality of life. Cynics, however, could attribute this situation to a fear on the part of clinicians that systematic assessments would reveal the ineffectiveness of most oncologic care, with the result that the activities (and income) of most oncology practitioners would be cut. Given the movement to capitated payment systems, the paradigm is shifting in such a way that the government and private insurers will be expecting, and possibly demanding, systematic cost-effectiveness analyses of new therapies, and will be increasingly concerned with routinely performed treatments.