Collection Of Resource Use Data Research Articles

Self-reported and routinely collected electronic healthcare resource-use data for trial-based economic evaluations: the current state of play in England and considerations for the future

BackgroundRandomised controlled trials (RCTs) are generally regarded as the “gold standard” for providing quantifiable evidence around the effectiveness and cost-effectiveness of new healthcare technologies. In order to perform the economic evaluations associated with RCTs, there is a need for accessible and good quality resource-use data; for the purpose of discussion here, data that best reflect the care received.Traditionally, researchers have developed questionnaires for resource-use data collection. However, the evolution of routinely collected electronic data within care services provides new opportunities for collecting data without burdening patients or caregivers (e.g. clinicians). This paper describes the potential strengths and limitations of each data collection method and then discusses aspects for consideration before choosing which method to use.Main textWe describe electronic data sources (large observational datasets, commissioning data, and raw data extraction) that may be suitable data sources for informing clinical trials and the current status of self-reported instruments for measuring resource-use. We assess the methodological risks and benefits, and compare the two methodologies. We focus on healthcare resource-use; however, many of the considerations have relevance to clinical questions.Patient self-report forms a pragmatic and cheap method that is largely under the control of the researcher. However, there are known issues with the validity of the data collected, loss to follow-up may be high, and questionnaires suffer from missing data. Routinely collected electronic data may be more accurate and more practical if large numbers of patients are involved. However, datasets often incur a cost and researchers are bound by the time for data approval and extraction by the data holders.ConclusionsOwing to the issues associated with electronic datasets, self-reported methods may currently be the preferred option. However, electronic hospital data are relatively more accessible, informative, standardised, and reliable. Therefore in trials where secondary care constitutes a major driver of patient care, detailed electronic data may be considered superior to self-reported methods; with the caveat of requiring data sharing agreements with third party providers and potentially time-consuming extraction periods. Self-reported methods will still be required when a ‘societal’ perspective (e.g. quantifying informal care) is desirable for the intended analysis.

Effectiveness and cost-effectiveness of a group-based pain self-management intervention for patients undergoing total hip replacement: feasibility study for a randomised controlled trial

Total hip replacement (THR) is a common elective surgical procedure and can be effective for reducing chronic pain. However, waiting times for THR can be considerable, and patients often experience significant pain during this time. A pain self-management intervention may provide patients with the skills to enable them to manage their pain and its impact more effectively before surgery. However, studies of arthritis self-management programmes have faced challenges because of low recruitment rates, poor intervention uptake, and high attrition rates. This study aimed to evaluate the feasibility of a randomised controlled trial (RCT) to assess the effectiveness and cost-effectiveness of a group-based pain self-management course for patients undergoing THR. Specific objectives were to assess trial design, ascertain recruitment and retention rates, identify barriers to participation, refine data collection methods, and evaluate uptake and patient satisfaction with the course. Patients listed for THR in an elective orthopaedic centre Bristol, UK were sent a postal invitation about the study. Participants were randomised to attend a pain self-management course plus standard care or standard care only using a computer-generated randomisation system. The pain self-management course was delivered by Arthritis Care and consisted of two half-day group sessions prior to surgery and one full-day group session 2–4 months after surgery. A structured course evaluation questionnaire was completed by participants. Outcomes assessment was by postal questionnaire prior to surgery and 1-month, 3-months and 6-months after surgery. Self-report resource use data were collected using a diary prior to surgery and inclusion of resource use questions in the 3-month and 6-month post-operative questionnaires. Brief telephone interviews were conducted with non-participants to explore barriers to participation. Postal invitations were sent to 385 eligible patients and 88 patients consented to participate (23% recruitment rate). Participants had a mean age of 66 years and 65% were female. Brief interviews with 57 non-participants revealed the most common reasons for non-participation were perceptions about the intervention and difficulties in getting to the hospital for the course. Of the 43 patients randomised to the intervention group, 28 attended the pre-operative pain self-management sessions and 11 attended the post-operative sessions. Participant satisfaction with the course was high, and patients enjoyed the group format. Retention of participants was acceptable, with 83% completing follow-up. Questionnaire return rates were high (76–93%), with the exception of the pre-operative resource use diary (35%). Completion rates for the resource use questions varied by category and allowed for an economic perspective from the health and social care payer to be taken. Undertaking feasibility work for a RCT is labour-intensive; however this study highlights the importance of conducting such work. Postal recruitment resulted in a low recruitment rate and brief interviews with non-participants provided valuable information on barriers to participation. Embedding collection of resource use data within questionnaires resulted in higher completion rates than using resource use diaries. While patients who attended the course gave positive feedback, attendance was low. Findings from this feasibility study enable us to design successful definitive group-based RCTs in the future.

PRM21 - Comparison of Alternative Methods of Resource-Use Data Collection for the Economic Evaluation of Health Care Interventions: A Case Study in Frail Older People

PRM21 - Comparison of Alternative Methods of Resource-Use Data Collection for the Economic Evaluation of Health Care Interventions: A Case Study in Frail Older People

Resource-Use Measurement Based on Patient Recall: Issues and Challenges for Economic Evaluation

Accurate resource-use measurement is challenging within an economic evaluation, but is a fundamental requirement for estimating efficiency. Considerable research effort has been concentrated on the appropriate measurement of outcomes and the policy implications of economic evaluation, while methods for resource-use measurement have been relatively neglected. Recently, the Database of Instruments for Resource Use Measurement (DIRUM) was set up at http://www.dirum.org to provide a repository where researchers can share resource-use measures and methods. A workshop to discuss the issues was held at the University of Birmingham in October 2011. Based on material presented at the workshop, this article highlights the state of the art of UK instruments for resource-use data collection based on patient recall. We consider methodological issues in the design and analysis of resource-use instruments, and the challenges associated with designing new questionnaires. We suggest a method of developing a good practice guideline, and identify some areas for future research. Consensus amongst health economists has yet to be reached on many aspects of resource-use measurement. We argue that researchers should now afford costing methodologies the same attention as outcome measurement, and we hope that this Current Opinion article will stimulate a debate on methods of resource-use data collection and establish a research agenda to improve the precision and accuracy of resource-use estimates.

Development of a Database of Instruments for Resource-Use Measurement: Purpose, Feasibility, and Design

BackgroundHealth economists frequently rely on methods based on patient recall to estimate resource utilization. Access to questionnaires and diaries, however, is often limited. This study examined the feasibility of establishing an open-access Database of Instruments for Resource-Use Measurement, identified relevant fields for data extraction, and outlined its design. MethodsAn electronic survey was sent to authors of full UK economic evaluations listed in the National Health Service Economic Evaluation Database (2008–2010), authors of monographs of Health Technology Assessments (1998–2010), and subscribers to the JISCMail health economics e-mailing list. The survey included questions on piloting, validation, recall period, and data capture method. Responses were analyzed and data extracted to generate relevant fields for the database. ResultsA total of 143 responses to the survey provided data on 54 resource-use instruments for inclusion in the database. All were reliant on patient or carer recall, and a majority (47) were questionnaires. Thirty-seven were designed for self-completion by the patient, carer, or guardian, and the remainder were designed for completion by researchers or health care professionals while interviewing patients. Methods of development were diverse, particularly in areas such as the planning of resource itemization (evident in 25 instruments), piloting (25), and validation (29). ConclusionOn the basis of the present analysis, we developed a Web-enabled Database of Instruments for Resource-Use Measurement, accessible via www.DIRUM.org. This database may serve as a practical resource for health economists, as well as a means to facilitate further research in the area of resource-use data collection.

Methods for the Collection of Resource Use Data within Clinical Trials: A Systematic Review of Studies Funded by the UK Health Technology Assessment Program

Background The UK Health Technology Assessment (HTA) program funds trials that address issues of clinical and cost-effectiveness to meet the needs of the National Health Service (NHS). The objective of this review was to systematically assess the methods of resource use data collection and costing; and to produce a best practice guide for data capture within economic analyses alongside clinical trials. Methods All 100 HTA-funded primary research papers published to June 2009 were reviewed for the health economic methods employed. Data were extracted and summarized by: health technology assessed, costing perspective adopted, evidence of planning and piloting, data collection method, frequency of data collection, and sources of unit cost data. Results Ninety-five studies were identified as having conducted an economic analysis, of which 85 recorded patient-level resource use. The review identified important differences in how data are collected. These included: a priori evidence of analysts having identified important cost drivers; the piloting and validation of patient-completed resource use questionnaires; choice of costing perspective; and frequency of data collection. Areas of commonality included: the extensive use of routine medical records and reliance on patient recall; and the use of standard sources of unit costs. Conclusion Economic data collection is variable, even among a homogeneous selection of trials designed to meet the needs of a common organization (NHS). Areas for improvement have been identified, and based on our findings and related reviews and guidelines, a checklist is proposed for good practice relating to economic data collection within clinical trials.

Cost-effectiveness in clinical trials: using multiple imputation to deal with incomplete cost data

Cost-effectiveness has become an important outcome in many clinical trials and has resulted in the collection of resource use data and the calculation of costs for individual patients. A specific example is a Cancer Research UK phase III trial comparing chemotherapy (CT) against standard palliative care in patients with advanced non-small cell lung cancer. Resource usage from trial entry until death were collected and costs obtained on a subset of 115 trial patients. For some patients, however, the unavailability of medical notes resulted in some cost components, and hence total cost, being missing. The 82 patients with complete data were not representative of all trial patients in terms of effectiveness and thus it was necessary to address the missing data problem. Multiple imputation (MI) was used to impute values for the unobserved individual cost components, allowing total cost to be calculated and cost-effectiveness carried out for all patients in the cost sub-study. The results are compared with those from a complete case analysis. After MI, the results indicated that CT had a high probability of being cost-effective for a societal willingness to pay over 20,000 Pounds per life-year gained. This was in stark contrast with the complete case analysis, which suggested that CT was not a cost-effective use of resources at any reasonable level of willingness to pay for a life-year. Our findings are based on a relatively small retrospective study with all events observed. In conclusion, cost-effectiveness analysis of the complete cases only may give biased results, and therefore, in situations where there are missing costs, MI is recommended.

Assessing the costs of healthcare technologies in clinical trials.

Assessing the costs of healthcare technologies in clinical trials.

Economic Analysis Alongside Clinical Trials: Revisiting the Methodological Issues

Controlled clinical trials are recognized as the best source of data on the efficacy of health care interventions and technologies. Because economic evaluation is dependent on the quality of the underlying medical evidence, clinical trials have increasingly been viewed as a natural vehicle for economic analysis. However, the closer integration of economic and clinical research raises many methodological issues. This paper discusses these issues in trial design, collection of resource use data, collection of outcome data, and interpretation and extrapolation of results. Some guidelines are suggested for economic analysts wishing to undertake evaluations alongside clinical trials.