Assessing the costs of healthcare technologies in clinical trials

Johnston K, Buxton M J, Jones D R, Fitzpatrick R
Record ID 31999008428
Authors' objectives:

The overarching objective is to challenge investigators to think through their study design in order to collect appropriate resource-use information in the most efficient way. Specifically, the objectives are:

1. To identify methodological issues concerning the collection of resource-use data for costing purposes and its analysis

2. To classify methodological issues into: (1) those where there is general agreement about how they should be handled; (2) those remaining open because of legitimate differences in values or perspectives; and (3) those where further empirical testing could resolve how the issue should be handled

3. To demonstrate how existing data can be used to inform the design of costing studies in trials

4. To develop a framework or decision aid within which decisions about costing in specific trials can be made.

Authors' results and conclusions: Design issues address the types of cost to be included, such as health service, trial, future and productivity costs. The decision on which types of cost to include depends on seven key factors: 1. Possible links to economic welfare theory 2. The perspective to be adopted 3. The form of economic evaluation 4. The avoidance of double counting 5. The quantitative importance of the type of cost 6. Whether the cost can be attributed to the intervention 7. The time horizon of the study. The collection of detailed data on resource use for all patients may not be necessary; key cost-generating events can be measured. These can be defined as where there is variation in the frequency of events between arms of the trial or between patients within arms. Determining sample sizes for detecting differences in costs or cost-effectiveness involves identifying an economically important difference andhaving information on the variability of cost data from previous studies or from pilot studies. A further sampling issue to be addressed in multicentre trials is the selection of centres and whether resource-use and unit cost information should be collected from all centres. Data collection issues involve deciding on the appropriate resource-use data collection method. Resource-use data can be measured on a patient-specific basis by using, for example, interviews, questionnaires, case record forms or diary cards. In selecting a method, potential sources of bias have to be addressed, including recall bias, evasive answer bias, non-response bias, selection bias and question format. The validity and reliability of resource-use data collection methods have not been tested fully and are therefore not reported in the literature. Data analysis may also influence the design of the study. In summarising and synthesising cost data, issues such as how to pool data and how to handle missing and censored data have to be addressed. It is important to take into account the variability in cost data and its distribution. It is generally agreed that mean costs convey more useful information than medians because they relate to total cost. The methods used to address uncertainty in methods and results include both statistical and sensitivity analyses; these have complementary roles. Sensitivity analysis can also be used to generalise results. The presentation of results addresses reporting formats. Results should be presented in a disaggregated manner, for example, by separating resource use from unit costs and reporting the contribution of different types of cost to total costs. The development of a common reporting format for economic evaluations would increase the transparency of both methods and results. The design of future studies relies on transparent reporting in earlier studies so that issues such as the variability in cost data can be determined. There are two additional elements of the review. First, an existing data set on costing from a clinical trial was used to illustrate how evidence relating to costs from a completed study can be used to inform the design of data for costing. By examining the results of detailed data collection, the exercise illustrates that, in the example at least, it is possible for simpler data collection methods to be adopted to produce comparable results. The exercise demonstrates the usefulness of having access to, and analysing, existing data sets in order to address design issues. Secondly, a decision aid, or structured framework, has been developed within which decisions can be made about designing a costing study alongside a clinical trial. In effect, the decision aid requires answering a set of explicit questions. It is recommended that it should be tested in future studies.
Authors' recommendations: Methodological issues on which there is general agreement include identifying perspective, measuring units of resource use, and applying appropriate unit cost. Those issues remaining open because of legitimate differences in values or perspectives concern which perspective to adopt and whether to base decisions on economic welfare theory. Finally, methodological issues requiring further empirical study include: exploring optimal sampling approaches questions surrounding multicentre clinical trials testing the validity and reliability of resource-use data collection methods handling missing and censored data methods used to generalise results. By presenting issues in this way, the review recognises the inevitability of some issues remaining unresolved while at the same time allowing the specification of a future research agenda.
Authors' methods: Review
Project Status: Completed
URL for project:
Year Published: 1999
English language abstract: An English language summary is available
Publication Type: Not Assigned
Country: England, United Kingdom
MeSH Terms
  • Clinical Trials as Topic
  • Costs and Cost Analysis
Organisation Name: NIHR Health Technology Assessment programme
Contact Address: NIHR Journals Library, National Institute for Health and Care Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton Science Park, Southampton SO16 7NS, UK
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Copyright: 2009 Queen's Printer and Controller of HMSO
This is a bibliographic record of a published health technology assessment from a member of INAHTA or other HTA producer. No evaluation of the quality of this assessment has been made for the HTA database.