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This paper overviews the EURONHEED (EUROpean Network of Health Economics Evaluation Databases) project. Launched in 2003, this project is funded by the EU. Its aim is to create a network of national and international databases dedicated to health economic evaluation of health services and innovations. Seven centres (France, Germany, Italy, The Netherlands, Spain, Sweden and the UK) are involved covering 17 countries. The network is based on two existing databases, the French CODECS (COnnaissance et Decision en EConomie de la Santé) database, created in 2000 by the French Health Economists Association (Collège des Economistes de la Santé), and the UK NHS-EED (NHS Economic Electronic Database), run by the Centre for Reviews and Dissemination, University of York, York, England.
The network will provide bibliographic records of published full health economic evaluation studies (cost-benefit, cost-utility and cost-effectiveness studies) as well as cost studies, methodological articles and review papers. Moreover, a structured abstract of full evaluation studies will be provided to users, allowing them access to a detailed description of each study and to a commentary stressing the implications and limits, for decision making, of the study. Access will be free of charge. The database features and its ease of access (via the internet: http://www.euronheed.org) should facilitate the diffusion of existing economic evidence on health services and the generalisation of common standards in the field at the European level, thereby improving the quality, generalisability and transferability of results across countries.
This paper describes recent reforms of quality assurance (QA) for the education of nurses, midwives and health visitors and reports qualitative findings from a study of how they are working out in practice. This study reported whether the stakeholders consider the system to be adequate for the principal aim of public protection. Using a postal survey and interviews, QA in nursing, midwifery and health visiting is compared and contrasted in the four countries of the United Kingdom. Issues of subjectivity versus objectivity in decision making over QA of nursing, midwifery and health visiting education and the extent to which these processes are rigorous arose. There is an inverse relationship between the number of higher education institutions in a country and the extent to which nursing, midwifery and health visiting QA personnel, responsible for conducting QA events, become involved with those institutions in offering advice and support. Generally speaking, where the changes have been greatest, satisfaction with the QA processes is lowest. Dissatisfaction was only expressed with processes and most likely arose from resistance to change but these are early days in the operation of the new QA procedures.
OBJECTIVES: To assess the extent and pattern of implementation of guidance issued by the National Institute for Clinical Excellence (NICE).
DESIGN: Interrupted time series analysis, review of case notes, survey, and interviews.
SETTING: Acute and primary care trusts in England and Wales.
PARTICIPANTS: All primary care prescribing, hospital pharmacies; a random sample of 20 acute trusts, 17 mental health trusts, and 21 primary care trusts; and senior clinicians and managers from five acute trusts.
MAIN OUTCOME MEASURES: Rates of prescribing and use of procedures and medical devices relative to evidence based guidance.
RESULTS: 6308 usable patient audit forms were returned. Implementation of NICE guidance varied by trust and by topic. Prescribing of some taxanes for cancer (P < 0.002) and orlistat for obesity (P < 0.001) significantly increased in line with guidance. Prescribing of drugs for Alzheimer's disease and prophylactic extraction of wisdom teeth showed trends consistent with, but not obviously a consequence of, the guidance. Prescribing practice often did not accord with the details of the guidance. No change was apparent in the use of hearing aids, hip prostheses, implantable cardioverter defibrillators, laparoscopic hernia repair, and laparoscopic colorectal cancer surgery after NICE guidance had been issued. CONCLUSIONS: Implementation of NICE guidance has been variable. Guidance seems more likely to be adopted when there is strong professional support, a stable and convincing evidence base, and no increased or unfunded costs, in organisations that have established good systems for tracking guidance implementation and where the professionals involved are not isolated. Guidance needs to be clear and reflect the clinical context.
OBJECTIVES: To identify existing guidelines and develop a synthesised guideline plus accompanying checklist. In addition to provide guidance on key theoretical, methodological and practical issues and consider the implications of this research for what might be expected of future decision-analytic models.
DATA SOURCES: Electronic databases.
REVIEW METHODS: A systematic review of existing good practice guidelines was undertaken to identify and summarise guidelines currently available for assessing the quality of decision-analytic models that have been undertaken for health technology assessment. A synthesised good practice guidance and accompanying checklist was developed. Two specific methods areas in decision modelling were considered. The first method's topic is the identification of parameter estimates from published literature. Parameter searches were developed and piloted using a case-study model. The second topic relates to bias in parameter estimates; that is, how to adjust estimates of treatment effect from observational studies where there are risks of selection bias. A systematic literature review was conducted to identify those studies looking at quantification of bias in parameter estimates and the implication of this bias.
RESULTS: Fifteen studies met the inclusion criteria and were reviewed and consolidated into a single set of brief statements of good practice. From this, a checklist was developed and applied to three independent decision-analytic models. Although the checklist provided excellent guidance on some key issues for model evaluation, it was too general to pick up on the specific nuances of each model. The searches that were developed helped to identify important data for inclusion in the model. However, the quality of life searches proved to be problematic: the published search filters did not focus on those measures specific to cost-effectiveness analysis and although the strategies developed as part of this project were more successful few data were found. Of the 11 studies meeting the criteria on the effect of selection bias, five concluded that a non-randomised trial design is associated with bias and six studies found 'similar' estimates of treatment effects from observational studies or non-randomised clinical trials and randomised controlled trials (RCTs). One purpose of developing the synthesised guideline and checklist was to provide a framework for critical appraisal by the various parties involved in the health technology assessment process. First, the guideline and checklist can be used by groups that are reviewing other analysts' models and, secondly, the guideline and checklist could be used by the various analysts as they develop their models (to use it as a check on how they are developing and reporting their analyses). The Expert Advisory Group (EAG) that was convened to discuss the potential role of the guidance and checklist felt that, in general, the guidance and checklist would be a useful tool, although the checklist is not meant to be used exclusively to determine a model's quality, and so should not be used as a substitute for critical appraisal.
CONCLUSIONS: The review of current guidelines showed that although authors may provide a consistent message regarding some aspects of modelling, in other areas conflicting attributes are presented in different guidelines. In general, the checklist appears to perform well, in terms of identifying those aspects of the model that should be of particular concern to the reader. The checklist cannot, however, provide answers to the appropriateness of the model structure and structural assumptions, as these may be seen as a general problem with generic checklists and do not reflect any shortcoming with the synthesised guidance and checklist developed here. The assessment of the checklist, as well as feedback from the EAG, indicated the importance of its use in conjunction with a more general checklist or guidelines on economic evaluation. Further methods research into the following areas would be valuable: the quantification of selection bias in non-controlled studies and in controlled observational studies; the level of bias in the different non-RCT study designs; a comparison of results from RCTs with those from other non-randomised studies; assessment of the strengths and weaknesses of alternative ways to adjust for bias in a decision model; and how to prioritise searching for parameter estimates.
OBJECTIVES: Health-care technology reviews now increasingly include outcome costs as well as clinical effects. This study reports the findings and implications of a survey to explore the usefulness of the National Health Service Economic Evaluation Database (NHS EED) within this process.
METHODS: Postal survey of lead authors of Technology Assessment Reviews (TARs) commissioned by the United Kingdom's National Institute for Clinical Excellence (NICE). The questionnaire investigated the usefulness of NHS EED in terms of (a) search strategy, (b) data extraction, (c) quality assessment, and (d) determining requirements for new modeling studies. Qualitative data were requested, including opinions regarding NHS EED.
RESULTS: NHS EED was used in 90 percent of all identified reviews (n = 46). The questionnaire response rate was 63 percent. The percentage of scores 3 or above (most useful), 2 or below (least useful), or N/A were, respectively, (a) search strategy= 62 percent, 23 percent, 15 percent; (b) data extraction = 23 percent, 27 percent, 50 percent, (c) quality assessment= 38 percent, 19 percent, 42 percent; (d) determining requirements for new modeling studies = 27 percent, 23 percent, 50 percent. The results were expanded further in the qualitative data from the respondents.
CONCLUSIONS: NHS EED is a useful tool for a variety of tasks in the NICE/TAR process but not, unsurprisingly, as a replacement for understanding primary studies. There is, however, a need to reduce the impact of time lags between the publication of economic evaluations and the appearance of abstracts relating to them on NHS EED. The results will inform future developments of the NHS EED database, which should increase its usefulness to researchers
This paper provides a first outline of the European Network of Health Economic Evaluation Databases (EURO NHEED) project. The project is funded by the European Commission and will implement, in 7 European centres based in France, Germany, Italy, The Netherlands, Spain, Sweden and the United Kingdom, databases on the economic evaluation of healthcare interventions. The network will be based on two existing and well-established resources, namely the UK's NHS Economic Evaluation Database (NHS EED), and France's Connaissances et Décision en EConomie de la Santé (CODECS) database. EURO NHEED will initially cover 17 European countries and will provide its users with bibliographic records, detailing the main characteristics of all included studies. In addition, structured abstracts will be provided for articles identified as full economic evaluations (cost-benefit, cost-effectiveness or cost-utility), which will offer a detailed critique of the findings and the methodology used. These databases will be accessible free of charge on the Internet. The EURO NHEED project is the first attempt to develop such a resource on a multi-national basis. The project will bring together Health Economists and Information Scientists from the European Union and beyond and is anticipated to facilitate a number of benefits and advances in the field of Health Economics. These include harmonisation and increased understanding of the theory and methodology of economic evaluation in healthcare, the interpretation of the generalisability of studies to target settings, and the influence of healthcare system variations among the European countries. The project will therefore advance the state of the art in collecting, summarising, critiquing and disseminating economic evaluations of healthcare conducted within Europe.
