JNCI Monographs

JNCI Monographs 1998 1998(24):1-28;
© 1998 by Oxford University Press

This Article Extract FREE Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to My Personal Archive Download to citation manager Request Permissions Google Scholar Search for Related Content PubMed PubMed Citation Social Bookmarking          What's this?

Journal of the National Cancer Institute Monographs, No. 24, 1-28, 1998
© 1998 Oxford University Press

Integrating Economic Analysis Into Cancer Clinical Trials: the National Cancer Institute-American Society of Clinical Oncology Economics Workbook

	Introduction

Top Introduction Part I: Economic Analysis... Part II: Planning an... Part III: Implementing an... Part IV: Designing an... Part V: Statistical Issues Part VI: Economic Evaluation... Conclusion References

 
Clinical economics is a new and evolving discipline that addresses the economic implications of changes in medical practice. As applied to cancer care, clinical economics assesses the costs and effectiveness of new cancer interventions and can be a valuable endpoint in selected clinical trials. Through the integration of economics into clinical evaluations, information can be developed that contributes to the decisions of patients, clinicians, health care managers, and policymakers as to the most effective allocation of cancer care resources.

To begin a formal effort to promote the development of economic analyses in National Cancer Institute (NCI) clinical trials, NCI sponsored a conference in 1994 with cancer center and cooperative group representatives to initiate discussions on the importance, appropriateness, and complexity of such evaluations. In 1995, the American Society of Clinical Oncology (ASCO) established its Health Economics Working Group with a charge to develop specific guidelines for implementing economic evaluations in cancer clinical trials. As a follow-up to these initiatives, in 1996, NCI and ASCO convened a workshop to consider the practical implementation of economic evaluations in cancer clinical trials. The participants in this small workshop included experts from cooperative groups, NCI staff, and other experts who are actively involved in health economics.

This workbook is the product of the meeting and subsequent discussions by the participants. It is meant to identify and elucidate the important characteristics of economic studies in the context of clinical trials, to indicate the considerations that investigators should address in their planning and implementation of such studies, and to suggest possible approaches. The workbook is neither a definitive text defining how all aspects of such studies should be handled nor an official NCI document prescribing how studies must be done. Rather, it is a developing guide to be used as a practical reference that will be revised as the state of the art progresses. The writing committee hopes that the workbook will serve as a useful tool for NCI cooperative groups as they incorporate economics as a research endpoint into the evaluation of new cancer treatment, prevention, and diagnosis strategies.

	Part I: Economic Analysis and Cancer Clinical Trials

Top Introduction Part I: Economic Analysis... Part II: Planning an... Part III: Implementing an... Part IV: Designing an... Part V: Statistical Issues Part VI: Economic Evaluation... Conclusion References

 
This section briefly presents the framework of economic theory underlying cost-effectiveness analysis and its application to the field of oncology. It is not, however, an in-depth review of the theory of economic evaluation, because many comprehensive sources currently exist (1,2).

Why Economic Analysis?

The Rising Costs of Cancer Care The percentage of total deaths in the United States attributable to cancer has risen from 16.3% in 1965 to 23.3% in 1997 (3). From 1990 through 1996, the estimated costs of cancer treatment increased from $35 billion (4) to $50 billion due to higher inflation, increasing numbers of procedures and cases, and the aging of the population (5). Even conservative estimates, measuring only the direct costs of treatment, show cost increases from $18.1 billion in 1985 to $27.5 billion in 1990 to $41.4 billion in 1994 (6). Cancer will become the foremost cause of death in the United States by the end of the decade.

Statistics and predictions such as these underscore the likelihood that cancer will continue to absorb more of the increasingly limited resources of the U.S. health care system. Some researchers have suggested that increasing costs and demands from a sophisticated patient audience will require both implicit and explicit rationing (7,8). In any event, economic forces will contribute to a growing need to better evaluate treatment practices by all clinicians, thus insuring that we utilize the relatively scarce resources of the health care system in an appropriate manner.

Cancer therapies are increasingly resource intensive, as evidenced by stem cell transplantation for hematologic disorders and solid tumors, paclitaxel for palliative chemotherapy of breast and ovarian cancers as well as non-small-cell lung cancer (9), serotonin-antagonist antiemetics, and growth factors for supportive care during treatment. In an era of capitated physician and hospital payments, the resources available for cancer treatment will be increasingly constrained, and payers and purchasers will want to understand the value of cancer treatments, especially for resource-intensive therapies, before allowing widespread access to them. Furthermore, when health outcomes are identical for alternative therapies, the costs of these treatments may be the most important factor in determining whether to recommend or reimburse one of the treatments.

Encouraging examples of less intensive strategies have the potential to improve efficiency of cancer treatment, such as evidence-based, minimalist follow-up care for breast cancer patients (10), decreased use of tumor markers in breast and colorectal cancers (11), and conservative use of hematopoietic growth factors (12), as well as a shift to less expensive outpatient treatments for stem cell transplantation (13). However, these strategies remain a minority of cases of new treatments in oncology.

The Need to Improve Decision-Making Because few medical interventions that provide health benefits also result in reduced health care expenditures (Table 1), reliable economic analyses must be developed to improve our decision-making about the allocation of resources for cancer treatments (9,14,15). The rapid advancement of science and biotechnology, coupled with increasing fiscal pressures, may severely limit access to cancer treatments for which economic data are not available. It is worth remembering that medical ethicists have argued that the least ethical way to allocate resources is to continue to spend money on unexamined treatments (16,17).

View this table: [in this window] [in a new window]   Table 1. Efficacy and cost-effectiveness of selected cancer and other treatments*

 
As shown in Table 1, most treatments provide additional clinical benefits at an additional cost. Thus, economic efficiency does not imply a reduction in cost of care but provides a measure of the value provided for the cost of the treatment (18).

Economic information can strengthen arguments for adoption of new technologies that are economically attractive, provide additional input for decision-making in indifferent or gray areas, and provide clear-cut answers when costs are a major consideration (19). Most existing cancer treatments have not been evaluated with the stringency applied to newer treatments. For example, we have no "proof" that intensive treatment of metastatic breast cancer, compared with best supportive care, improves quality or quantity of life or saves money, because no randomized clinical trial has been performed in the past 20 years. This is not to say that intensive treatments are ineffective or exceed reasonable cost-effectiveness limits—only that they have not been studied with the same scrutiny as high-dose chemotherapy with stem cell transplantation (20).

Measurement of incremental benefit (additional lives saved by a strategy) and incremental cost (additional costs of a strategy) forms the backbone of comparative economic analysis. The four possible approaches of such analysis are listed in Table 2 and represent the combinations of costs and outcomes measurement. Estimates of absolute incremental differences in cost between trial arms are needed, just as they are for analyses of treatment benefits. For example, the primary outcome measure of a cost-effectiveness analysis is the additional cost incurred per year of life gained or quality-adjusted years of life gained. Such measurement requires explicit delineation of clinical benefit in terms of years of life saved or quality-adjusted years of life saved and of dollars spent on treatment, recurrence, survival, and death. The statistical implications of absolute and relative differences are discussed in Part V.

View this table: [in this window] [in a new window]   Table 2. Potential combinations of costs and outcomes

 
Perspectives on the Use of Resources Cost data are meaningful only when considered from a specific perspective, usually that of patient, caregiver, provider, payer, or society (i.e., the choice of perspective determines what events or expenditures are regarded as costs, as well as how those costs should be calculated). The societal perspective is often the most appropriate one for resource-allocation decisions (1), because its broad approach can minimize bias in comparisons; however, other perspectives may be important in attempts to understand the economic effects of a treatment.

As in clinical medicine, investigators must not make assumptions about how patients value treatment outcomes. For example, a recent clinical trial demonstrated substantial intellectual deficits in glioblastoma patients undergoing radiotherapy; but, because the treatment offered a few weeks of improved survival, most patients reported that they would choose the radiotherapy (21,22).

Multiple perspectives may be adopted within a single analysis to illustrate the views of patients, payers, policymakers, and health care providers. For example, the cost of providing a hospital service is usually different than the charge for the service and the amount paid by the insurance company. An episode of care may cost a hospital $7000, but the hospital charges $10 000 for the service. From the hospital's perspective, the charge is an overstatement of the resources consumed. If the patient must pay the full charge, however, that charge accurately represents cost from the patient's perspective. Alternatively, while a hospital can sometimes decrease its costs by discharging patients early, patients' costs may increase due to increased outpatient expenses that are not covered by health insurance.

When Are Economic Evaluations Justified?

Inclusion of economic evaluations in clinical trials can be justified in a variety of circumstances: when significant resources are at stake; when resource considerations are prominent; and when resource allocation decisions are imminent (23,24). Examples of each circumstance are provided below.

Significant Resources at Stake Antiemetics. Although individual doses of 5HT3-agonists, such as odansetron and granisetron, are not expensive, they carry a high potential volume of use and can account for 5% of a hospital's oncology pharmacy budget (data on file, Medical College of Virginia Hospitals).

Colony-stimulating factors (CSFs). The initial and additional costs of CSFs (granulocyte, granulocyte-macrophage, and erythropoietin) can consume up to 5% of a hospital's oncology pharmacy budget (data on file, Medical College of Virginia Hospitals).

Transplant procedures. High-dose chemotherapy with stem cell transplantation and similar experimental therapies carry a high dollar cost, regardless of volume. The cost of treatment and follow-up for leukemia and lymphoma patients receiving autologous bone marrow transplantations and granulocyte-macrophage CSF reached $79 892 (25).

Genetic predictors. BRCA1 and BRCA2 tests, genetic predictors for breast and ovarian cancer, can cost anywhere from $150 to $1500 per mutation, depending on whether a family's specific mutation has been identified. Lerman et al. (26) note that the high cost of such testing may deter some individuals from undergoing the test, and individuals may hesitate to request coverage from insurers for fear of future discrimination.

Resource Considerations Are Prominent Many therapies carry a high cost, regardless of their clinical outcome, such as high-dose chemotherapy with stem-cell transplantation for metastatic breast cancer and allogeneic bone marrow or stem cell transplantation from an unrelated matched donor (estimates allow $100 000-$250 000 for each uncomplicated case).

Other therapies vary widely in costs but produce similar clinical outcomes. For example, high-dose chemotherapy is commonly used as treatment for first-remission lymphoma, although less expensive standard-dose chemotherapy is known to produce similar or identical outcomes (27).

Resource Allocation Decisions Are Imminent Megakaryocyte growth factors have been proposed to eliminate the need for platelet transfusions and to allow for earlier hospital discharge after high-dose chemotherapy (25). Also, results of a trial of high-dose chemotherapy as adjuvant therapy for high-risk breast cancer (>10 positive lymph nodes) quickly changed the standard therapeutic approach to this disease (28).

When Not to Use Economic Analysis

Economic analysis is unnecessary when a primary therapy works well in a small number of patients—for example, testicular cancer treated with platinum (600 cases/year) (29). Furthermore, some therapies vary little in costs and produce similar clinical outcomes in very common diseases. For example, a number of chemotherapeutic combinations are used as adjuvant therapy for node-positive breast cancer, but they cost about the same and produce similar effects (30).

Also, economic analysis is unnecessary when its results are unlikely to alter clinical practice. For example, an economic analysis of breast self-examination might show that costs are higher in the screened population and fail to demonstrate clinical benefit. But the use of breast self-examination is so widespread that an economic analysis would not change the practice.

Generalizability of Observed Costs of Cancer Care

Cost reflects the resources needed to provide a service and it has two elements: "resource utilization" in some natural units (e.g., one hospital day or one dose of ceftazadime) and the "unit cost" or price (e.g., 1 hospital day in a semiprivate room for $460). Units and prices are multiplied to determine treatment costs. One might calculate physician costs by multiplying physician time by hourly physician earnings. The same principle applies to productivity costs: the cost of patient time can be calculated by multiplying time by a patient's daily wage rate.

Some administrative datasets provide reliable information only on resource utilization, whereas others provide reliable information only on total cost, and still others provide information on both. It is important to recognize that the resource utilization and price components of cost have different determinants. For example, resource utilization may be affected by treatment setting, organizational and technical innovation, and efficient use of fixed resources. Price may be affected by the degree of competition in health care markets, including geographic location, regulatory and legal restraints, and the bargaining power of health care payer organizations. The "learning curve" of better efficiency and lower cost that develops as procedures are performed more often may decrease some costs; alternatively, unforeseen consequences may increase expected costs. It is important to keep these issues in mind, because economic data obtained from one clinical trial may not always be generalizable to another time, setting, or pricing scheme.

Costs related to a disease entity have traditionally been classified into a number of categories, depending on whether the costs are directly related to the expenditure of medical or nonmedical resources related to treatment and care; whether the costs are a reflection of lost economicproductivity due to disease-related disability or premature mortality; or whether the costs are related to the pain and suffering caused by the disease (6). The four categories of costs are listed below:

Direct Medical Costs

• Resource use related to services and procedures delivered by the health care system in the course of treatment and care (hospital and physician costs); patient payment for medical supplies.
  

Direct Nonmedical Costs

• Resources expended by the patient and her family related to treatment and care (travel to treatment facility, parking, etc.).
  

Productivity Costs

• Not a financial transaction, but the monetary value of lost economic production due to morbidity or mortality, often utilized in cost-effectiveness or cost-utility analyses; may be important from a societal perspective or from the perspective of an employer—for example, in the analysis of treatments for substance abuse or treatments that effect the ability of cancer patients to return to work.
  

Intangible Costs

• Also not a financial transaction, but the monetary expression of pain and suffering associated with disease or treatment; various methods for measuring intangible costs, such as "willingness to pay," indicate that such "costs" can be quantified as a monetary value (i.e., the amount a patient would be willing to pay to avoid pain or suffering); for purposes of cost-benefit analysis, intangible costs are typically expressed in monetary terms, because the outcome of cost-benefit analysis is expressed in purely monetary terms; for cost-effectiveness analysis, intangible costs often are ignored, and for purposes of cost-utility analysis, intangible costs are expressed as part of the denominator in units of quality-adjusted life-years (QALYs)
  

While all of the categories of costs are included in cost-of-illness studies and cost-benefit analyses, only direct costs are usually included in cost-effectiveness (or cost-utility) analyses, which have become the most common approach in economic analysis of health care interventions (Table 3).

View this table: [in this window] [in a new window]   Table 3. Outcome and cost studies for presentation to decision makers

 
The Need to Make Decisions

The need for either implicit or explicit decision-making about resource allocation dictates that decision makers should know the total budget of a program, the efficiency or cost-effectiveness of the given modality, and the overall effect of each treatment. It is essential, therefore, that data be presented in such a way that decision makers can assess both the costs and potential clinical consequences of new cancer treatments (Table 3). Although the mechanics of such decision-making vary greatly from centralized planning to individual choice, only limited economic information is currently available to make these important treatment decisions.

Criteria for Evaluating the Soundness of an Economic Analysis

Economic analyses must be evaluated using defined criteria with clear goals in mind, just as clinical trials themselves are evaluated against a variety of accepted criteria. A full economic analysis of any cancer intervention should go beyond a simple identification of costs (Table 4). As the competition for scarce health care dollars intensifies, more therapies will be marketed as "cost-effective." Failure to explain these criteria should make the investigator wary about the quality of the economic analysis (31).

View this table: [in this window] [in a new window]   Table 4. Criteria for identifying a sound economic analysis*

 
Conclusion

In this section, we review the rationale for economic evaluation of new cancer treatments, including a discussion of why economic analysis is increasingly being implemented in cancer clinical trials, a discussion of when economic evaluations are justified, and an overview of the economic framework for evaluation of cancer clinical therapies.

Economic evaluation is an increasingly important component of clinical decision-making in the context of scarce or limited resources. Economic evaluation itself can contribute to decision-making in specific clinical settings as outlined in this section. Furthermore, economic evaluation goes beyond assessing the monetary cost of medical care to include such issues as productivity costs (loss to the economy from morbidity and mortality) and intangible costs (costs of pain and suffering related to illness or injury).

	Part II: Planning an Economic Analysis

Top Introduction Part I: Economic Analysis... Part II: Planning an... Part III: Implementing an... Part IV: Designing an... Part V: Statistical Issues Part VI: Economic Evaluation... Conclusion References

 
The previous section introduced some of the concepts of economic evaluation of new cancer therapies by reviewing the conceptual framework underlying economic evaluation of cancer clinical trials. Parts III through V will review these concepts in more detail and lay out a framework for the collection of economic data in clinical trials. The purpose of this section is to illuminate issues in the planning of economic analyses that may be important to clinical investigators designing protocols with an economic component.

Selection of Appropriate Trials

Economic evaluation can be an important secondary endpoint in clinical trials of new drugs and technologies, especially new cancer therapies. Implementing an economic evaluation, however, requires additional time and effort, including additional data collection, management, and analysis. In deciding whether to make this investment, investigators must consider whether economic analysis is likely to aid in decision-making regarding reimbursement for new therapies or technologies.

In general, investigators have suggested that economic evaluation is most appropriate in pivotal trials of new technologies or strategies when the investigational therapy is resource intensive or is likely to be utilized by a significant number of patients. Economic evaluation is less important in trials of "me-too" therapies, which may be similar in efficacy and cost to other clinical therapies. Here, however, the cost of therapy may be the important distinction between two treatment arms. Clinical investigators should develop economic hypotheses before approaching economic investigators to discuss the inclusion of economic analysis as an endpoint in the clinical trial.

Economic evaluations usually are proposed for inclusion in phase III clinical trials but can be included in phase II trials to allow for collection of pilot data that will be used in plans of pivotal phase III assessments. Phase IV studies are also appropriate for consideration for economic evaluation.

Some estimate of the potential difference in cost between treatment arms, and the resulting cost-effectiveness ratio if the targeted difference in survival is achieved, should be included in the concept sheet and protocol for any study with an economic component. Ideally, this estimate will be based on data collected in a pilot study, but a "back-of-the-envelope" calculation should be performed when pilot data are not available. Such estimates play a critical role in justifying the investment in an economic component and are needed for the planning of an efficient data collection strategy.

Timing of Data Collection

Data collection for economic studies can be based on prospective data that have been collected concurrently with the clinical trial or on retrospective data that have been collected after the trial's completion. The advantages and disadvantages of each approach are discussed in more detail in Part V.

Prospective economic evaluation assures that economic data will be available at the time of a trial's completion. It allows for collection of the four types of economic data (direct medical, direct nonmedical, productivity, and intangible), as well as quality-of-life data from study patients. But prospective collection of economic data requires substantial planning and is, in this sense, no different than prospective collection of clinical data. Because economic evaluation is usually a secondary endpoint of clinical trials, and because there is a risk that the null hypothesis will be adopted at the end of the trial, investigators should carefully consider the potential use of resources for an economic evaluation in a trial of an unknown or untested therapy.

Retrospective economic evaluation offers a more limited approach to assessment of resource use within clinical protocols, typically focusing on direct medical costs, because other types of data often are not available in the medical record. In addition, retrospective approaches can not assess patients' preferences or quality of life. However, in this approach, the expense of collecting economic data will only be required for therapies with proven efficacy.

The choice between prospective and retrospective data collection usually rests on the potential clinical effect of the new therapy and on the amount of resources available to investigators. If the trial is indeed an appropriate candidate for economic evaluation, and if resources are available for proper planning and design of an economic study, a prospective approach should be taken, because it will allow for a more thorough evaluation of the costs of a new therapy or technology.

Choice of Perspective

Economic evaluation of medical care is unique in that it assesses the costs and benefits of therapies from a variety of perspectives, including those of patients, caregivers, employers, payers, and society. However, clinical and economic investigators must determine which perspectives are most relevant to the clinical trial under consideration. For example, economic evaluation from a hospital's perspective requires consideration of inpatient costs but not outpatient or out-of-pocket costs. Data collection from a patient's perspective is more complex and may require primary data collection to yield more useful information on out-of-pocket costs and lost work days. Economic evaluation from a societal perspective is the most comprehensive of all and includes consideration of both patient and provider perspectives.

Unless a therapy is particularly burdensome to patients, the most common perspective for clinical trials is a "modified" societal perspective, which considers only direct medical costs. In this type of analysis, direct medical costs are quantified as social costs, but direct nonmedical and productivity costs are not routinely collected.

Time Horizon

Time horizon is defined as the time from randomization to follow-up for patients in clinical trials. Time horizon can affect the economic evaluation of new therapies by limiting the amount of information available to the assessment of the long-term effectiveness of treatment. Economic evaluation frequently requires a different time horizon than that proposed by clinical investigators.

Ideally, the time horizon of an economic evaluation should be such that all costs related to the therapies being compared are captured for analysis. This concept differs from the idea of time horizon in clinical trials, which can be based on time until a measurable clinical endpoint is achieved or until the end of some predetermined time period (e.g., 5 years). Under the ideal economic scenario, subjects would be randomized to a trial and followed until death or cure (32). Unfortunately, most clinical trials are conducted for a limited length of time.

In general, the time horizon for an economic evaluation of a clinical trial begins at the date of trial randomization. Alternative start dates for the time horizon include time of diagnosis or time of the onset of symptoms. Economic evaluations that begin before the time of randomization usually are attempting to assess important costs incurred during the prerandomization time period (e.g., a trial of bone marrow transplantation for patients with breast cancer may need to provide induction chemotherapy to 10 patients to find one responder for the transplant portion of the study; an investigator may be interested in the costs of screening as well as the costs of the prerandomization hospitalization) (33).

In determining the appropriate length of the time horizon for economic evaluation, it is helpful to distinguish between two types of clinical trials—trials of therapies for metastatic cancer (mortality studies) and trials of adjuvant therapies. Clinical trials in these two settings pose different issues with respect to clinical and economic endpoints. Knowledge of the survival curves for the type of cancer being studied, along with projections of the expected benefit of the therapy, can be used to determine how long patients should be followed for an economic study. In mortality studies, the follow-up time is likely to be relatively short, so resource utilization can be assessed for all patients until time of death for a high proportion of study patients. In clinical trials of adjuvant therapies, some proportion of patients may be cured and thus live a normal life expectancy. Generally, patients can be followed for recurrence. In adjuvant therapy trials, one can consider three potential time frames—short-term (e.g., 6 months, 1 year), intermediate, and lifetime.

Outside the Time Horizon When the time horizon of a clinical study differs from that of the economic study, it may be necessary to track all resource use in both arms of the trial over a period that is longer than the relevant clinical endpoint, because important resource use may occur in the period beyond the time horizon of the clinical trial.

Sequelae Substantial long-term sequelae that may occur in the relatively distant future, whether related to the cancer itself or to treatment of the cancer, should be included in the analysis.

Relating Costs and Benefits The time horizon should be the same for the numerator and denominator of a cost-effectiveness ratio. For example, if an analysis includes 2 years of clinical follow-up data, it should also include 2 years of cost data. In a trial of adjuvant therapy, simply including the cost of treatment in the numerator and a longer follow-up in the denominator does not accurately reflect the relationship between the costs and benefits of the therapy being assessed.

Endpoints

Economic evaluation usually is based on a consideration of final outcomes, such as survival rather than response, disease-free survival, and time to progression. Thus, economic evaluation requires either consideration of a final outcome measure as an endpoint of the clinical trial or an understanding of how clinical trial endpoints will translate into final endpoints (for example, epidemiologic data may be available for estimations of cure rates for patients who demonstrate a complete response to treatment). Specification of outcomes measures must be determined prospectively by both clinical and economic investigators before the trial proceeds.

Baseline Characteristics

Clinical studies, except for some "large and simple" trials and a small number of special cases, are generally underpowered for evaluating secondary cost or quality-of-life measurements. Analytic techniques that assess nontreatment-related variance can be used to address this issue. Thus, the ability to detect differences in costs due to treatment assignment will increase if information on baseline characteristics of study patients is included as a set of covariates in analyses of secondary study endpoints. Baseline characteristics include resource use in the period prior to the trial, clinical status, diagnostic profile, disease stage and severity, level of social support, and health status. Variation in covariates among patients stem from the type of patient rather than from treatment assignment—for example, whether a patient is an inpatient or outpatient at the time of randomization can predict resource utilization after randomization.

Baseline covariates allow investigators to "disentangle" patient characteristics prospectively. Covariates may be used as predictors in regression analysis at the end of a study, or they can be used to stratify the randomization of any parameter that may be a factor in predicting costs to a high degree. Many of these data elements can be collected as part of eligibility determination and tagged as covariates in the economic evaluation. It is also important to consider any and all clinical information obtained prior to randomization as potential covariates. Ideally, covariates will be continuous variables.

External Validity

Where possible, the clinical protocol should be modified to reduce protocol-mandated tests or procedures to reduce protocol-induced charges in medical care (protocol-induced costs or benefits) and to ensure that the protocol mirrors "usual care" as much as possible. Economic investigators should also review the clinical protocol to ensure that there are no economic biases in the structure of the trial (e.g., there are no fixed discharge criteria included in the study and/or there are no differences in prescribed treatment across study areas). In addition, whether or not the clinical protocol procedures are modified to reduce mandated tests, efforts should be made to identify medical procedures that are mandated only for the research portion of the study. If these research resources are not related to treatment, their costs can be excluded from the analysis.

Economic evaluation raises a unique set of issues about the generalizability of clinical trials themselves. These studies are designed to influence clinicians, patients, and decision makers in their perceptions of the importance of a new therapy. Thus, economic evaluation aims to ensure that patients being studied in the clinical trial are as similar as possible to relevant patient populations in the "real world." For appropriate economic evaluation, therefore, clinical trials should be free of economic bias, should include patient entry criteria broad enough to provide support for the external validity of the analysis, and should, to the greatest extent possible, follow strict and objective standards in patient selection.

Trial investigators can reduce economic bias in the design of clinical studies by avoiding prespecified indications for discharge, supportive care interventions, or second-line therapies. Investigators can further reduce bias by identifying and minimizing protocol-induced costs or benefits, thus rendering the phase III clinical trial as realistic as possible in terms of actual practice in the community. Protocol-induced costs can include repeated diagnostic tests or other evaluations that do not directly contribute to clinical care or are not routine elements of clinical practice. Because these tests and evaluations can lead to diagnoses that otherwise might be missed in the usual care of patients, they can also yield clinical outcomes that would not be replicated in usual practice.

Finally, economic analysis is concerned with the generalizability of data developed from clinical trials. The external validity of studies is thus an important consideration in recruitment of subjects to the study. One such example of data that suggest clinical trial results can be replicated in the community are presented in a study of breast cancer mortality in British Columbia by Olivotto et al., showing that after adoption of routine adjuvant chemotherapy, mortality declined with an effect size identical to that of clinical trials (34).

An alternative view is that patient selection will probably continue to be a strong factor in most trials. The task for researchers is to determine how well bias to external validity can be modeled by obtaining good data on the relevant characteristics of patients enrolled in trials compared to patients who are likely to receive the treatment shown to be efficacious in the trial.

Salvage Protocols

In oncology, the potential for salvage or late use of interventions is important to consider in advance for economic evaluation. As mentioned above, the economic period of a treatment may be in discordance with clinical trial measures. Late use of interventions may provide crucial information for economic evaluation of a study, because treatment for disease progression can be very costly.

Economic evaluation can be implemented in this setting by including patients in the clinical trial for a fixed time period, allowing patients to remain in the economic protocol throughout this period even if they reach an endpoint of the clinical trial and withdraw from active treatment. Salvage protocols with economic arms also provide an opportunity for further economic data collection from patients who have failed treatment.

Finally, several unique statistical issues play a role in economic evaluation. Patients may incur fairly low costs until their disease has progressed, after which time they usually are withdrawn from the clinical trial. Yet, it is often at this point that patients become expensive and, thus, important to the economic evaluation. Economic studies often are designed to allow patients the option of continuing with the economic protocol, even after withdrawing from active treatment on the clinical protocol. In this limited way, many economic evaluations have been able to successfully follow large portions of a trial population beyond the time horizon of the clinical trial (25).

Importance of Early Collaboration Among Investigators

To be successful, economic investigators must understand the clinical aspects of the trial being considered as well as the potential clinical implications of the therapy or technology being evaluated. Likewise, clinical investigators must be able to develop economic hypotheses and to understand all elements of the economic study to ensure appropriate implementation of the economic study's design. Thus, clinical-economic evaluation is a truly collaborative undertaking between clinical and economic investigators.

Economic investigators should become familiar with the economic profile of the intervention under study: What resources are required to implement the therapy? For how long will these resources be required? What is the potential benefit of therapy? What are the potential resource offsets or savings from the new therapy compared with existing therapies? In addition, economic investigators should ask these questions in the context of the current standard of care. They should consider the potential risks of the new therapy as well as how the clinical trial's results might change the standard of care.

Clinical investigators should understand that there is no "standard" economic analysis to be simply appended to a clinical trial. Economic analysis is an important secondary endpoint of a study and, to be performed well, must be integrated throughout the clinical trial mechanism. Seamless integration of the economic component of the study with the quality-of-life data collection strategy is particularly important in any study that employs patient diaries as instruments of economic data collection. Most important, clinical investigators must "buy in" to the economic evaluation so that they have a stake in seeing that economic data are treated with as much care as clinical data. Recipes for failure of an economic evaluation include lack of commitment by clinical investigators to the collection of economic data and a lack of understanding by clinical investigators of the purpose of the economic evaluation.

Pilot Testing

Economic evaluation can benefit from pilot testing in much the same way as clinical trials. Pilot testing offers investigators an opportunity to assess the use of case report forms (CRFs) and patient diaries in clinical trials so that they might become more familiar with the process of implementing a protocol and more knowledgeable about the economic profile of the disease under study. In addition, pilot tests can pinpoint a trial's "cost drivers" and help economic investigators characterize the distributions of cost data and predict the differences in cost between treatment arms or the total cost of care for study patients. Identifying cost drivers in a pilot study can reduce the data collection burden in the final study. Furthermore, pilot data can be helpful in identifying the toxicity profiles of a therapy and, in particular, the nature and frequency of high-cost events, such as hospitalizations for febrile neutropenia or cardiac toxicity. Similarly, pilot testing can provide information for estimations of sample size and expected cost differences between study arms (35).

Conclusion

This section reviews issues important for clinical investigators to consider in contemplating whether to implement an economic evaluation within a specific clinical trial. Issues for clinical investigators to consider include the selection of appropriate clinical trials for economic evaluation, timing of data collection, choice of perspective, time horizon, study endpoints, and external validity or generalizability of the study. Investigators must also consider that to design robust economic comparisons of clinical trials, economic evaluation requires input from economic investigators as early collaborators within the clinical team. To implement a successful protocol, clinical investigators must assist in the design of the economic evaluation and in the implementation of the economic component of the protocol.

	Part III: Implementing an Economic Analysis

Top Introduction Part I: Economic Analysis... Part II: Planning an... Part III: Implementing an... Part IV: Designing an... Part V: Statistical Issues Part VI: Economic Evaluation... Conclusion References

 
In the previous section, we reviewed some of the important concepts for a clinical investigator to consider when deciding whether to incorporate an economic evaluation into a clinical trial. In this chapter, we review in more detail many of the same issues from the perspective of someone who is designing an economic evaluation of a clinical trial. In the next chapter, we focus on the collection of data items themselves.

Study Outline

Economic evaluation measures the use of resources and often takes note of the same events of interest to clinical investigators, such as whether a patient receives a magnetic resonance imaging scan (MRI). Yet, while clinical investigators are most interested in the results of the MRI, economic investigators take greater interest in the number of MRIs consumed during the study period. In addition, economic investigators attempt to interpret changes in resource quantities. For example, a specific therapy may reduce length of stay for patients receiving autologous bone marrow transplant (ABMT) yet increase the need for outpatient follow-up visits. Costs are applied to these resource-utilization measures to demonstrate overall economic benefit or harm. For example, if inpatient days cost $700 each and physician visits cost $100 each, the ABMT scenario described above will save money if it reduces length of stay by 1 day and increases outpatient resource use by no more than the equivalent of six physician visits.

Thus, economic evaluation requires both resource utilization and unit cost information to provide an overall estimate of the resources consumed in the course of caring for an individual patient. The following sections focus specifically on the development of resource-use data and unit costs.

Resource-Use Categories

Oncology patients consume a variety of resources in the course of medical treatment, including hospital services, physician and nursing services, diagnostic tests, pharmaceutical products, radiation therapy, and ancillary services. Given the tremendous complexity of oncology care, economic investigators must make explicit decisions about the types and amounts of information they wish to incorporate into their protocols. In general, these data elements should include resources that carry significant costs (e.g., inpatient stays) and services that are likely to differ across treatment groups. The most important of these—known as "cost drivers"—represent resources that are both costly and differ across treatment groups (36) and they should be validated through pilot data collection efforts. Cost drivers are not simply drivers of a study's total cost but of the increments in costs between the study's treatment arms. Investigators should, therefore, assess the impact of a particular resource on the mean costs, the variance in costs, and the difference in costs between treatment arms before eliminating it from the list of data elements to be collected.

Computerized cost-accounting systems, which are increasingly being adopted by health care provider organizations, make it possible to retrieve information on resource use and costs for a variety of resource-use categories. For example, the Decision Support System used by Group Health Cooperative of Puget Sound contains information on resource use and costs for such categories as inpatient days, surgeries, outpatient/short-stay hospitalizations, primary care visits, specialty care visits, mental health visits, emergency room visits, community health services, diagnostic radiology, laboratory services, occupational/physical therapy, respiratory therapy, and pharmacy (37).

Direct Medical Costs: Inpatient and Outpatient Resource Utilization

Hospitalizations Hospitalizations typically represent the most intense period of resource utilization by clinical trial patients. Resources received during a hospitalization include hospital "hotel services" themselves, physician services, nursing services, laboratory and pathology services, blood work, operating rooms, and pharmaceutical products.

Hospital services are provided based on the type of unit to which the patient is assigned, e.g., intensive care, high care, telemetry, general, and rehabilitation. Thus, descriptions of resource utilization for hospital "hotel services" could be a description of length of stay or a description of length of stay by unit type (e.g., a 10-day admission of which 4 days were spent in the oncology unit and 6 were spent on the general medical floor). One distinguishing feature of the different unit types within a hospital is the level of nursing support services available to patients. Thus, location within the hospital is often also used as a description of the intensity of nursing care.

Physician Services Physician services in the hospital setting include those provided by the attending physician (either medical or surgical) and by consulting physicians. In the outpatient setting, they can include oncology services as well as services provided by primary care and consulting physicians. In an economic investigation, measures of physician effort can be characterized in terms of time (a 30-minute consultation) or workload units (resource-based relative value units [RVUs]) (38,39). These data can be collected for all physicians treating patients in the protocol or by the type of physician providing the service.

Surgical Procedures Surgical procedures are an important component of physician services. Performed for diagnostic and therapeutic purposes, surgical procedures can occur in and out of the hospital setting. The most global measure of surgical services is a description of the procedure itself (e.g., laparoscopy, colectomy). This description can be text based, or it can be coded using a standardized system such as the International Classification of Diseases (ICD) or the Common Procedural Terminology (CPT). Surgical procedures can be further described using a second level of detail—for example, the time in the operating room or the use of specific supplies, including blood products or isotopes. A third measure, which is especially important for outpatient surgical services, is a description of the location where the service is performed (e.g., hospital, outpatient surgical center, free-standing surgical center, physician's office). These levels of detail can be used to describe resource utilization by different treatment modalities.

Diagnostic Tests Some of the most important services provided to patients both in and out of the hospital are diagnostic tests. As mentioned above, economic investigators are interested in recording the number and types of services provided to patients. These resources can be captured in a variety of ways, including listing the number of radiologic or laboratory tests as either an aggregate measure or an itemized listing of the occurrence of specific types of tests and procedures.

Pharmaceutical Services Pharmaceutical utilization during hospitalization periods may already be captured within clinical CRFs' concomitant medication sections. If not, investigators may wish to detail the amount of medication received by patients during a hospital stay. Medication use can be characterized by medication type and dose (total daily dose) or by total dose received during a specific time period (i.e., daily dose, total dose during a course of chemotherapy, total dose during a hospitalization). In addition, economic investigators should record the route of administration, because intravenous administration may be more costly than oral administration. Data collection can include all concomitant medications or a subset of specific medications of interest to the investigators.

Radiation Oncology Physician services for radiation oncology treatment can be captured as described in the Physician Services section above. Use of radiation treatment facilities can be tracked by recording the types of services received by patients, the personnel effort required to provide such services, the duration of treatment, the dose of isotope delivered, and the setting where the treatment occurred. In radiation oncology protocols, more detailed treatment or service data may be collected.

Ancillary Services Many other services are available to patients in and out of the hospital. These services can be especially important to the care of oncology patients, although they are not delivered by physicians. Social work, speech therapy, pain management, occupational therapy, physical therapy, and clinical pharmacology services, to name a few, are usually measured by tracking the occurrence of specific consultations or by measuring the amount of time the provider spent in consultation with study patients.

Subacute-Care Facilities Cancer patients may utilize a variety of subacute-care facilities, including nursing homes, rehospitalization centers, and inpatient hospices. These resources may be quantified by the type of institution and the length of stay in the institution. For more specific studies, data can be collected on specific services received during the stay.

Direct Nonmedical Costs

Direct nonmedical costs include the costs of transportation to and from physician visits or hospitalizations and other costs related to receiving medical care. For extended stays at a treatment center, these costs can include the cost of hotel services or of moving families to a treatment center. Investigators should determine the specific resource quantities of interest to be captured as a direct nonmedical cost. These can include the number of hours of parking at specific treatment centers or the number of days spent at a hotel adjacent to a treatment center.

Measuring Resource Utilization

Data on resource measures can be collected from medical records and medical bills and through patient self-report. In this section we review the data sources available to economic investigators.

Medical Records Medical records include source documents, such as medical charts and abstracted flow sheets. These documents may contain data on all elements of resource utilization during a specific time period, such as the detailed information found on a hospital chart, which can be abstracted by data collectors to provide information for each of the resource categories reported in the previous section. Interpretation may be required for some data elements, such as unit type by day of hospitalization. Medical records are limited in that they often are not linked between inpatient and outpatient treatment facilities. Patients typically have multiple providers and, thus, multiple records, making it difficult to follow patients from one site to another.

Administrative Data Sources Many types of administrative data are available to economic investigators, including hospital and physician billing records and datasets from large managed care organizations (MCOs) or the Medicare program. Administrative datasets include information on resource quantities and can be used as a direct measure of resource utilization or abstracted to track utilization of specific services. As with medical records, certain administrative datasets may be available only for individual episodes of care (hospital datasets) and may not be available as linked records of inpatient and outpatient services. Also, Medicare and managed care administrative data may be available only for defined populations of patients and usually do not include information on noncovered services and specific service elements (for example, they may include little information on resources utilized during a hospitalization).

Patient Self-Report Patient self-report enables data to be collected for all medical care received by patients, whether or not it is provided at the study site. Patient self-report data can be used in several ways in an economic study. First, it may be the only means of collecting certain data items (direct nonmedical costs, productivity costs, intangible costs). Second, patients are often the only people with complete knowledge of all of the services they have received. Thus, patient self-report can be used to assess direct medical costs received by patients. However, patient self-report data may not be reliable for several types of information, including data on resource utilization during acute-care hospitalizations or for detailed information on treatments received. In these cases, patient self-report information should not be used as the sole data collection strategy for economic studies. Often, patient self-report is combined with source-document validation. In this strategy, patients report the occurrence of a specific service at a facility, which then leads to follow-up data collection with that facility.

In addition to direct medical resource-use data, patient self-report may include assessment of the amount of caregiver time required for care at home and the number of days lost from work or other activities. Alternatively, work loss could also be abstracted directly from patients' work records, though it is unlikely that this would be feasible in a typical clinical trial unless the trial were restricted to patients with a single employer (for example, in a workplace cancer screening trial).

Several methods exist for collecting patient self-report data for resource use items. Patients may be interviewed, either during a protocol visit or over the telephone. Alternatively, specially designed questionnaires may be mailed to patients at regular intervals. Problems occur with patient self-report data for a number of reasons. Patient recall of events becomes problematic when the recall period is extended, if the patient is a heavy user of medical care services, and/or illness interferes with the patient's mental status. Thus, scheduled visits or telephone or mail contact must be sufficiently frequent to avoid recall problems. An alternative way to avoid recall problems is to ask the patient to complete a diary at home as care is received. The diary should then be brought to the study site at each visit, used by the patient as a reference during telephone follow-up, or used as a reference when completing a mail questionnaire. Diary problems can be minimized through reminder telephone calls to the patient at regular intervals between visits and by means of a letter sent before each study visit reminding the patient to complete the diary. For patients who are illiterate or mentally incompetent, resource data can be obtained from a proxy, such as a family member or close friend.

For an example of the use of combined patient interviews and medical billing records for obtaining direct nonmedical costs, see Bennett et al. (40). Probably the most detailed and comprehensive survey instrumentation developed for the purpose of obtaining information on medical resource by way of patient interview is that developed for the National Medical Expenditure Survey (41).

Assigning Unit Costs: Direct Medical Costs

Data on the costs of resources used by patients may be available from standard costing data, from sources of care for individual patients, or from administrative data sets. Most U.S. hospitals maintain billing systems that can be used to record the costs of resources consumed by patients during a hospitalization. However, hospital billing information will only include a record of the specific services supplied by the hospital and may not include the cost of physician services during the hospital period. Except in specific settings, hospital billing information does not include information on the care received by patients on an outpatient basis. Thus, if a protocol follows patients over an extended period of time, data collection mechanisms should be available to collect both inpatient and outpatient resource use as well as the cost of these resources.

Administrative databases, such as the claims payment records of an MCO or large health plan, are becoming increasingly important sources of resource-use data in clinical protocols. However, given the fragmented nature of the U.S. health insurance system, the use of administrative datasets is not a feasible means of tracking resource use unless the study is designed around specific patient populations, such as patients more than 65 years of age (Medicare) or patients enrolled in a specific health plan.

Hospital Costs The most basic description of costs for hospital care is the cost of an entire hospital period. For example, a study in which the measure of resource utilization is hospital admission will assign an overall cost to each admission. The most common means of developing an estimate of aggregate cost is by first classifying the admission by diagnosis-related group (DRG), which combines the primary diagnosis and procedure with information about comorbidities. Medicare or other insurance payment information can then be used to assign a proxy for cost by the specific DRG. Another simple costing method tracks length of stay and assigns a cost per day, or a "per diem."

Generally, more specific information is collected on hospital resource utilization. Hospital financial information is available in the form of hospital charges. Because hospital charges are thought to overstate the actual costs of service, separate analysis of these data must be undertaken (42).

Hospitals in the United States must report their overall costs and charges to the Health Care Financing Administration (HCFA) on an annual basis. This Medicare "cost report" has been used by investigators to develop a "cost-to-charge ratio" that is used to convert hospital charges to hospital costs for the purpose of economic analysis. These cost-to-charge ratios can be developed either at an aggregate level for the institution or on a more specific level based on the hospital departments providing the relevant services. The relationship between costs and charges at hospitals actually varies considerably between hospital departments. When available, departmental cost-to-charge ratios may be a better proxy for costs of specific services than total cost-to-charge ratios. One severe limitation to this more detailed approach to assessment of hospital costs is that each hospital may have its own system of assigning costs to uniform billing (UB-92) categories. Thus, fresh frozen plasma may be included in one institution's blood bank cost center report but in the operating cost center in a different institution. These differences make aggregation of departmental cost-to-charge ratios a labor-intensive task. A study developed by the Cancer and Leukemia Group B (CALGB) is currently attempting to evaluate the capabilities of administrative datasets within CALGB member institutions. The group is expected to develop recommendations for strategies of requesting cost information from CALGB member institutions for economic evaluations within group studies.

Given the increasing financial pressures resulting from changes in the health care system, many hospitals have developed their own cost-accounting systems to provide more detailed cost information for management decisions. However, not every institution has such an accounting system in place. Where these datasets exist, they can be used to assess the costs of services and may offer a more accurate reflection of the true costs of services than the cost-to-charge ratio (43).

It is difficult to develop costs for specific services from detailed hospital bills. Hospitals often keep track of every service received by an individual patient on a disaggregated basis. Thus, for a specific procedure or treatment—for example, an intensive care unit day or an hour of operating room time—the hospital may bill for each of the hundreds of components of that service separately. In fact, it may be impossible to develop an overall cost for specific services for an institution. One approach to resolving this issue is to develop a regression-based model that will use the resource counts in the economic protocol as predictor variables in decomposing the overall hospital bill. This technique could result in the development of bundled costs for the specific clinical services collected within a CRF.

More recently, hospitals have revised their billing procedures due to changes in market forces. For example, hospitals may agree to a contract price for procedures that are part of the research protocol, resulting in a gap between the actual bill and the contract price. Furthermore, some hospital accounting systems simply record the contract price. In these institutions, the process of tracking costs is predominantly being used for internal cost accounting but not for generating bills to external organizations. Some hospitals continue to generate bills but apply a contractual allowance to represent the difference between the charge and the contract price. Other hospitals have a separate accounting system for procedures priced through research contracts. If the data collection strategy for a proposed protocol is based solely on the use of administrative datasets, investigators must ensure that facilities are continuing to track resource utilization by specific patients in either the billing or cost-accounting systems at each center.

In a multi-institutional study, the costing strategy may be complicated by the inability to collect cost data at some study sites (most often because of lack of sufficient investigator resources to collect these data). In these cases, cost data may be obtained from a subset of study institutions. Statistical techniques to reflect this data collection strategy are discussed in Part V.

Physician Costs Physicians assign CPT codes when billing for their services. In a manner analogous to hospitals, charges for specific physician services may not be directly related to the costs of providing those services. However, there is no physician cost-to-charge ratio. In 1992, HCFA developed the Resource-Based Relative Value Scale (RBRVS) as a measure of the resource intensity of the specific physician services for each CPT code. The Medicare system currently implements this resource intensity measure in physician payment. RVUs may be used to calculate standard costs for physician services (44). It should be noted that there are facility charges associated with many outpatient medical procedures that are not included in the RBRVS fee schedule. These facility costs may need to be developed from other data sources. This is especially true for outpatient surgical services.

Nursing Services Costs for nursing services are usually developed on an hourly basis using an average wage rate for the type of nurse (registered nurse, nurse practitioner, etc.).

Diagnostic Tests Costs for diagnostic tests and procedures can include the costs of physician services as well as the costs of conducting the tests. The costs of physician services for diagnostic tests are reported as described above. The costs of conducting laboratory tests are available using a set of standard laboratory workload units (Lab RVUs). The costs of diagnostic tests include the facility fees for the service. The facility costs for radiology services may need to be developed from other data sources.

Pharmaceutical Services Pharmaceutical charges also vary depending on the pharmacy. One way of standardizing pharmaceutical costs is to use the average wholesale price available for specific pharmaceutical products (45), with the addition of a standard dispensing fee.

Subacute-Care Facilities Costs for subacute-care facilities may be developed based on published price lists using per diem rates. For studies that focus on the use of subacute-care facilities, a more detailed costing approach may need to be developed for the study. This would be the case in a study of alternative hospice treatment programs.

Capital Costs Investigators should also consider that some treatments require the purchase of capital equipment; for example, cancer centers may already own much of the equipment required for new treatments, but community hospitals may have to purchase equipment to implement certain services. Capital equipment purchases become fixed costs that are independent of the standard process of costing for an individual patient. In other words, there may be costs associated with a program of treatment that are shared by many patients, and this cost would not appear on patient billing data (this may especially be the case in phase III trials of experimental, unreimbursed technologies for which there is no market price for the service). Derivation of these costs requires specific costing efforts to be conducted in conjunction with the clinical trial.

Protocol Costs The costs of data collection in a research study should not be included in the economic assessment of the therapy. In addition, the costs of research-related archived materials not used for clinical care should be excluded from the assessment.

Assigning Unit Costs: Direct Nonmedical Costs

Often, these costs are measured from the patient's perspective and include the costs of direct nonmedical services purchased by patients. While these data may be captured as both resources and costs, direct nonmedical costs are more often captured solely as costs of resources. This is usually assessed by asking patients to record their out-of-pocket expenses for these services.

Aggregating Price and Quantity

There are four general approaches to data analysis that investigators may consider in developing the economic component of clinical trials. These include resource use collected for all trial patients and costs collected for all trial patients; resource use collected for all trial patients and costs collected in a subset of study patients; resource use collected for all trial patients and costs developed from administrative data sets; and prospective collection of cost data only (resource utilization would then be derived from the cost data). In economic evaluation of cancer clinical trials, the second and third strategies are the most common.

Some economic evaluation strategies actually omit measurement of resource consumption and concentrate instead on economic measures of resource use, such as hospital bills. These studies are undertaken when collecting resource consumption measures may not be feasible or may be prohibitively expensive, forcing the investigator to choose an alternative "billing" approach.

Generic Economic Evaluation Strategies Resource categories in clinical protocols must be specifically enumerated for both prospective and retrospective studies. The level of precision in the costing exercise is dependent upon the type of study being implemented.

Example. In a trial of low-molecular-weight heparin (outpatient) versus intravenous heparin (inpatient), no difference is expected in treatment outcome; however, a large difference is expected in the utilization of inpatient hospital resources. A list of resource categories to be collected in the clinical protocol might include hospital days by unit type, as well as physician visits.

Example. In a comparison of hospital settings in the administration of a 5HT3 odansetron bolus push versus intravenous administration, it is necessary to microcost the administration of the drugs. Such an approach represents a higher level of precision in the data than is required for the previous example. This study requires a microcosting exercise to track nursing time (and intensity) in providing antiemetic services to patients, with an effort to develop specific prices for these services.

Example. In a trial of adjuvant therapy for breast cancer assessing four versus eight cycles of chemotherapy, there is similar outpatient use of drug administration, pharmacy charges, diagnostic testing, and professional fees. The difference may lie in the hospitalization utilization rate for febrile neutropenia and in outpatient care for nausea, mucositis, dehydration, etc. Thus, investigators must evaluate outpatient resource utilization and occurrence of hospitalizations.

Inpatient Studies Inpatient studies are clinical trials that either occur within the hospital setting or enroll a high proportion of patients that are expected to receive hospital treatment during the course of the clinical trial. Examples include trials of new cytokine therapies as supportive care for bone-marrow transplantation, and studies of new surgical techniques for solid organ tumors, studies of intensive chemotherapy regimens administered on an inpatient basis but potentially having different effects on bone-marrow suppression. Data collection would focus on the intensity of treatment during the hospitalization, including tracking resource utilization by unit type within the hospital, physician visits, surgical procedures, diagnostic tests and procedures, and high-cost medications.

Outpatient Studies Outpatient studies are clinical trials that either occur outside the hospital setting or enroll a high proportion of patients who are not expected to receive hospital treatment during the course of the clinical trial. Data collection would focus on the utilization of services on an outpatient basis, including physician services, nursing services, surgical procedures, diagnostic tests and procedures, and use of high-cost medications (including chemotherapy). Information about acute-care hospitalization would be recorded. However, unless there were an explicit hypothesis about the intensity of the hospital services by treatment arm, data collection on use of resources within the hospital setting could be minimized. For example, data could be collected on length of stay by unit type but not on diagnostic tests or procedures or medication use.

Subacute-Care Studies Studies of patients within subacute-care facilities (i.e., hospice care, nursing home care, or rehabilitation care) require information about the use of the subacute-care facility but often do not require information about other outpatient treatments. Information about acute-care hospitalization would be recorded. However, unless there were an explicit hypothesis about the intensity of the hospital services with treatment, data on use of resources within the hospital setting could be minimized.

Conclusion

In summary, this section addresses some of the major issues in designing and implementing an economic evaluation within a clinical trial. Issues highlighted in this section include the potential direct medical and direct nonmedical resources that can be captured in a clinical trial, the assessment of productivity and intangible costs, the sources of data for capturing resource utilization information, the methodology for assigning unit costs to the resources collected in the protocol, and methods of refining data collection instruments for different types of clinical trials. There is no "boiler-plate" economic evaluation. Clinical and economic investigators must review the requirements for the different data elements within their protocol. They must also assess alternative strategies for collecting cost information for the resources collected within the economic protocol.

	Part IV: Designing an Effective Data Collection Strategy

Top Introduction Part I: Economic Analysis... Part II: Planning an... Part III: Implementing an... Part IV: Designing an... Part V: Statistical Issues Part VI: Economic Evaluation... Conclusion References

 
Designing Data Collection Forms

When integrating economics into an existing clinical trial design, investigators should attempt to collect only those items that are necessary for the economic analysis. Existing forms, such as clinical trial report forms and flow sheets, often contain much of the required information (see Appendix I). It may be necessary to add only a few variables to collect sufficient information to conduct the study. Variables should include any subset of those listed below, depending on the type of trial and the study analysis plan.

View larger version (67K): [in this window] [in a new window]   Appendix I. Excerpt from Clinical Trial Case Report Form

 
When collecting data centered around actual resource use, the CRFs used to collect the data must be designed and pilot tested prior to data collection. They should allow the investigators to record core areas of resource use required for the study. Specific forms are developed to track major resource use by study patients. These forms often are divided into hospital resource use, outpatient resource use, other institutional resource use, caregiver support, and covariates.

Hospital Resource Data The following are important data elements to consider for collection when patients are hospitalized during the clinical trial:

• facility name and location;
  
• admission and discharge dates;
  
• reason for admission (e.g., protocol treatment, elective admission, and urgent admission);
  
• hospital room type (e.g., ward, step-down, intensive care unit);
  
• surgical procedure (type as well as duration of procedure);
  
• transfusions of blood or blood products (date, type, number);
  
• major laboratory tests (date, type, number);
  
• major radiologic tests (date, type, number);
  
• medications (date, type, route, dosage);
  
• chemotherapy (dates, types, routes, dosage);
  
• radiotherapy (dates, fractionation, site, dosage); and
  
• physician visits (date, type, duration in minutes).
  

Outpatient Resource Data The following are important data elements to consider for collection when patients are treated in an outpatient setting:

• date, type, and duration of visit;
  
• type of facility;
  
• reason for visit (routine, elective follow-up, emergent follow-up);
  
• surgical procedure (type and duration of procedure);
  
• major laboratory tests (date, type, number);
  
• major radiologic tests (date, type, number);
  
• medications (date, type, route, dosage);
  
• chemotherapy (date, type, route, dosage);
  
• radiotherapy (date, fractionation, site, dosage);
  
• physician visits (date, type, duration in minutes); and
  
• home care (dates/frequency of visits, skill requirements).
  

Subacute-Care Institutional Resource Use The following are important data elements to consider for collection when patients are treated in subacute-care institutions:

• nursing home (date of admission, date of discharge, level of care); and
  
• hospice care (date of admission, date of discharge, level of care).
  

Caregiver Support The following are important data elements to consider for collection when assessing caregiver burden:

• caregiver burden (number of hours of paid and unpaid caregiver support);
  
• days of usual activity missed (work, school, home activities);
  
• out-of-pocket costs;
  
• transportation costs; and
  
• caregiver quality of life.
  

Covariates The following are important covariates to be collected within the economic trial:

• comorbidities;
  
• patient's demographic characteristics;
  
• geographic proximity of patient to site of care;
  
• insurance coverage status;
  
• caregiver status;
  
• prior hospitalizations (within the past year);
  
• employment status;
  
• disease severity;
  
• prior physician visits (within the past year); and
  
• cancer history (prior chemotherapy, prior radiation therapy, prior surgery, date of diagnosis).
  

Collecting Data

Beginning Data Collection There are essentially three approaches to collecting trial data on a prospective basis—1) collection at a fixed time period; 2) collection at the beginning of a designated medical event; and 3) collection after a treatment cycle or hospitalization. The strategy for data collection should be planned well in advance and will depend on the needs of the specific trial (for example, whether outpatient treatment is being compared with inpatient treatment).

Collection at fixed time periods. Most economic studies query patients about resource utilization at fixed time periods—for example, on a monthly or quarterly basis. This method assures that economic data are not omitted in the study protocol and that follow-up is comparable across the study areas. This data collection strategy is also the best method to assess quality-of-life data for study patients.

Starting from an event. Clinical trials that measure resource utilization from the time of a predesignated event often use toxicity as a marker. For example, a data collection form might instruct, "In the case of toxicity, please indicate (on another form) what resources were used to treat the toxicity." The event-triggered method is limited in that a significant amount of resource utilization may not be linked to toxicity.

Starting after a treatment cycle or hospitalization. Data can also be collected at the end of a treatment cycle, such as a cycle of chemotherapy, or after a computed tomography (CT) scan or other procedure or test. This method provides reasonable certainty—if interviews are conducted at least quarterly—that all instances of resource utilization and the reasons for each will be captured. More frequent interviews may be required for sicker patients, though the data collection strategy should be standardized to keep costs low.

Why Collect Nonstudy-Site Data? Although nonstudy-site data are difficult to collect, the data do reflect resource utilization at sites outside the treatment center. The costs of these resources can be substantial when significant portions of care are provided in these settings. For example, bone-marrow transplant patients may receive much of their follow-up care at nonstudy sites.

Obtaining Informed Consent

Primary economic data collection that requires access to medical records or other confidential sources must have the clearance of the study subject. Trials that follow patients to nonstudy centers must develop more elaborate consent procedures to ensure that all patient records are included in the consent. In general, a consent form should be designed to encompass as many potential sources of information as possible, particularly if the investigators anticipate having to collect information from outside the study center. The consent form should allow the study investigators access to the patients' financial records at whatever sites the patients receive care.

Medical resource-use data collection may involve abstraction by trial personnel or data from the patient's medical records or medical bills. To obtain a patient's medical bill in the United States, the principal investigator must include a release-of-information statement in the patient consent form. This can be a requirement for enrollment in the study or optional depending on the design of the study. Pat