scholarly journals Dreamtime: Version 5.0 of the Australian Guidelines for Preparing Submissions to the Pharmaceutical Benefits Advisory Committee (PBAC)

2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Paul C Langley
Keyword(s):  
Economic Evaluation ◽  
Advisory Committee ◽  
Research Program ◽  
Clinical Evidence ◽  
Decision Makers ◽  
Normal Science ◽  
Systematic Observation ◽  
Department Of Health ◽  
Rigorous Research ◽  
Australian Department

In September 2016 the Australian Department of Health published Version 5.0 of the Guidelines for Preparing Submissions to the Pharmaceutical Benefits Advisory Committee (PBAC). These guidelines, which were first published for comment in 1990, set out how to prepare a submission to list a new medicine or medicinal product on the Pharmaceutical Benefits Schedule (PBS). The guidelines give instructions on the information required by the PBAC and the Economic Sub-Committee (ESC), the most appropriate form for presenting clinical evidence and the standards for an economic evaluation. The purpose of this commentary is to consider whether or not the evidence standards proposed and the consequent modeled claims for economic effectiveness meet the standards of normal science: are the claims presented to support PBS listing credible, evaluable and replicable. The review concludes that the PBAC guidelines do not meet the standards expected in normal science. The absence of empirically evaluable claims means there is no way of judging whether they are right or even if they are wrong. If the Guidelines were never intended to support experimentation and systematic observation to generate feedback to health system decision makers, then this should be made clear by the PBAC. If not, then consideration should be given to redrafting the guidelines to ensure they conform to these standards. Hopefully, future versions of the guidelines will address this issue and focus on a rigorous research program of claims assessment and feedback.   Type: Commentary

scholarly journals True North: Building Imaginary Worlds with the Revised Canadian (CADTH) Guidelines for Health Technology Assessment

2017 ◽  
Vol 8 (2) ◽  
Author(s):  
Paul C Langley
Keyword(s):  
Best Practice ◽  
Health Technology ◽  
Decision Makers ◽  
Normal Science ◽  
Systematic Observation ◽  
Reference Case ◽  
Policy Makers ◽  
Health Technologies ◽  
Rigorous Research ◽  
The Uk

In March 2017 the Canadian Agency for Drugs and Technologies in Health (CADTH) released the 4th edition of their Guidelines for the Economic Evaluation of Health Technologies: Canada. These guidelines, which were first published and revised for a 3rd edition in 2006 are intended to help decision makers, health systems leaders and policy makers make well-informed decisions. They are designed, apparently, to support best practice in conducting health technology assessments in Canada. The purpose of this commentary is to consider whether or not the evidence standards proposed and the consequent modeled claims for economic effectiveness meet the standards of normal science: are the CADTH standards capable of generating claims for competing products that are credible, evaluable and replicable? The review argues that the standards proposed by CADTH do not meet the standards expected in normal science. Technical sophistication in building reference case imaginary worlds is not a substitute for claims that are experimentally evaluable or capable of assessment through systematic observation. There is no way of judging whether imaginary claims are right or even if they are wrong. CADTH is not alone in setting standards that fail to meet the standards of normal science. Recent commentaries on formulary submission guidelines in a number of other countries, to include Ireland, the Netherlands, France, Australia, the UK and New Zealand conclude that they are subject to the same criticism. If the CADTH guidelines were never intended to support feedback to health system decision makers, then this should be made clear. If not, then consideration should be given to withdrawing the guidelines to ensure they conform to these standards. Hopefully, future versions of the CADTH guidelines will address this issue and focus on a rigorous research program of claims assessment and feedback and not the building of imaginary worlds.   Type:  Commentary

Introducing Economic Evaluation as a Policy Tool in Korea: Will Decision Makers get Quality Information?

2005 ◽  
Vol 23 (7) ◽  
pp. 709-721 ◽  
Author(s):  
Kun-Sei Lee ◽  
Werner B F Brouwer ◽  
Sang-Il Lee ◽  
Hye-Won Koo
Keyword(s):  
Economic Evaluation ◽  
Decision Makers ◽  
Quality Information ◽  
Policy Tool

scholarly journals How Do Decision Makers in Europe Value Other Economic Evaluation Tools Than Cost-Effectiveness Analysis for Vaccines?

2014 ◽  
Vol 17 (7) ◽  
pp. A675-A676 ◽  
Author(s):  
J.M. Höhne ◽  
N. Demarteau ◽  
Ö. Saka ◽  
B. Standaert ◽  
J. Kleintjens
Keyword(s):  
Economic Evaluation ◽  
Cost Effectiveness ◽  
Cost Effectiveness Analysis ◽  
Decision Makers ◽  
Evaluation Tools ◽  
Effectiveness Analysis

Resource allocation and economic evaluation in Australia's healthcare system

2011 ◽  
Vol 35 (3) ◽  
pp. 278 ◽  
Author(s):  
Abdolvahab Baghbanian ◽  
Ian Hughes ◽  
Freidoon A. Khavarpour
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Economic Evaluation ◽  
Cost Effectiveness ◽  
Decision Makers ◽  
Economic Evaluations ◽  
Healthcare Decision ◽  
Effectiveness Analysis ◽  
Allocation Decisions ◽  
Resource Allocation Decisions

Objective. To explore dimensions and varieties of economic evaluations that healthcare decision-makers do or do not use. Design. Web-based survey. Setting and participants. A purposive sample of Australian healthcare decision-makers was recruited by direct invitation through email. All were invited to complete an online questionnaire derived from the EUROMET 2004 survey. Results. A total of 91 questionnaires were analysed. Almost all participants were involved in financial resource allocations. Most commonly, participants based their decisions on patient needs, effectiveness of interventions, cost of interventions or overall budgetary effect, and policy directives. Evidence from cost-effectiveness analysis was used by half of the participants. Timing, ethical issues and lack of knowledge about economic evaluation were the most significant barriers to the use of economic evaluations in resource allocation decisions. Most participants reported being moderately to very familiar with the cost-effectiveness analysis. There was a general impression that evidence from economic evaluations should play a larger role in the future. Conclusions. Evidence from health economic evaluations may provide valuable information in some decisions; however, at present, it is not central to many decisions. The study suggests that, for economic evaluation to be helpful in real-life policy decisions, it has to be placed into context – a context which is complex, political and often resistant to voluntary change. What is known about the topic? There are increasing calls for the use of evidence from formal economic evaluations to improve the quality of healthcare decision making; however, it is widely acknowledged that such evidence, as presently constituted, is underused in its influence on allocation decisions. What does this paper add? This study highlights that resource allocation decisions cannot be purely based on the use of technical, economic data or systematic evidence-based reviews. In order to exploit the full potential value of economic evaluations, researchers need to make better sense of decision contexts at specific times and places. What are the implications for practitioners? The study has the potential to expand researchers and policy-makers’ understanding of the limited use of economic evaluation in decision-making. It produces evidence that decision-making in Australia’s healthcare system is not or cannot be a fully rational bounded process. Economic evaluation is used in some contexts, where information is accurate, complete and available.

When the decision is what to decide: Using evidence inventory reports to focus health technology assessments

2011 ◽  
Vol 27 (2) ◽  
pp. 127-132 ◽  
Author(s):  
Matthew D. Mitchell ◽  
Kendal Williams ◽  
Gretchen Kuntz ◽  
Craig A. Umscheid
Keyword(s):  
Systematic Reviews ◽  
Randomized Trials ◽  
Clinical Evidence ◽  
New Technologies ◽  
Health Technology ◽  
Decision Makers ◽  
Healthcare Decision ◽  
Healthcare Decision Making ◽  
Literature Searches ◽  
Primary Literature

Objectives: Health systems frequently make decisions regarding acquisition and use of new technologies. It is desirable to base these decisions on clinical evidence, but often these technologies are used for multiple indications and evidence of effectiveness for one indication does not prove effectiveness for all. Here, we describe two examples of evidence inventory reports that were performed for the purposes of identifying how much and what type of published clinical evidence was available for a given technology, and the contexts in which those technologies were studied.Methods: The evidence inventory reports included literature searches for systematic reviews and health technology assessment (HTA) reports, and systematic searches of the primary literature intended to count and categorize published clinical studies. The reports did not include analysis of the primary literature.Results: The inventory reports were completed in 3 to 4 days each and were approximately ten pages in length, including references. Reports included tables listing the number of reported studies by specific indication for use, and whether or not there were randomized trials. Reports also summarized findings of existing systematic reviews and HTA reports, when available. Committees used the inventory reports to decide for which indications they wanted a full HTA report.Conclusions: Evidence inventory reports are a form of rapid HTA that can give decision makers a timely understanding of the available evidence upon which they can base a decision. They can help HTA providers focus subsequent reports on topics that will have the most influence on healthcare decision making.

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