Executive Summary
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Background
Overview
Chapter 1: Global Formulary Submission Requirements
Chapter outline
1.1 Introduction
1.1.1 Key documents
1.1.2 The second level
1.1.3 Health technology assessments (HTAs)
1.1.4 The emergence of formulary submission guidelines
1.2 Current formulary submission standards
1.2.1 PBAC: standards for clinical assessment
Case study 1.1: The PBAC guidelines
1.2.2 England and Wales, NICE: standards for modeled cost-effectiveness claims
Case study 1.2: The NICE guidelines
1.2.3 WellPoint: standards for monitoring and validating claims
Case study 1.3: The WellPoint guidelines
1.2.4 The Scottish Medicines Consortium
Case study 1.4: The SMC guidelines
1.2.5 US: AMCP - an interim standard
Case study 1.5: The AMCP guidelines
1.2.6 Process and dossier submissions
Case study 1.6: Identifying reimburser requirements
1.2.7 Transparency and process
1.3 Hierarchy of clinical evidence
1.4 Formulary recommendations and assignments
1.5 The role of guidelines
Case study 1.7: The future of NICE - what could be NICER?
1.6 Linking cost-effectiveness and budget-impact claims
Case study 1.8: Viagra versus the PBAC
1.7 Overview: managing patient populations
Notes
Chapter 2: Guidelines from a Global Perspective
Chapter outline
2.1 A global guideline overview
Case study 2.1: The ISPOR guidelines summary
2.2 Formulary submission guidelines: documentation and process
2.3 Health technology assessments (HTAs) and the life cycle of a drug
2.4 Disease area and therapeutic class reviews
2.5 Bias and compliance
2.6 Technology scoping
2.7 The global dossier: meeting evidentiary and analytical standards
2.2: Proposed outline for a global dossier
Notes
Chapter 3: Uncertainty - Net Benefits, Product Ranking and the Reference Case
Chapter outline
3.1 Uncertainty in cost-effectiveness claims
3.2 Ranking therapy interventions
3.3 ICERs and net benefit measures
3.4 Defining net benefits
3.5 Interpreting ICERs
3.6 Net monetary benefit
3.7 Probabilistic sensitivity analysis
3.8 Estimating cost-effectiveness acceptability curves
Case study 3.1: Modelling a probabilistic sensitivity analysis
3.9 Interpreting, monitoring and validating claims
3.10 The NICE reference case
Case study 3.2: NICE reference case requirements
Case study 3.3: The EQ-5D and the SF-6D in liver transplant patients
3.11 Implications of the reference case requirements
3.12 Overview: thresholds and evidentiary standards
Notes
Chapter 4: The Clinical Outcomes Case
Chapter overview
4.1 Literature searches
4.1.1 Key databases
4.1.2 Reference inclusion/exclusion criteria
Case study 4.1: PBAC requirements for literature searches
4.2 Bias and systematic reviews
4.2.1 Randomisation
4.2.2 Follow-up
4.2.3 Blinding
Case study 4.2: Bias assessment in clinical trials
4.2.4 Filtering studies
4.3 Hierarchies of clinical evidence
Case study 4.3: The PBAC and WellPoint hierarchies of clinical evidence
4.4 Summarising clinical studies
Case study 4.4: Meeting PBAC trial summary requirements
4.5 Quality-scoring clinical studies
Case study 4.5: The Jadad quality-scoring algorithm
4.6 Pooled clinical data and meta-analyses
Case study 4.6: The PBAC requirements for meta-analysis
4.6.1 Identifying relevant studies
4.6.2 Eligibility criteria
4.6.3 Abstracting data
4.6.4 Statistical models
4.7 Adverse events and side-effect profiles
Case study 4.7: Pharmacoepidemiology
4.8 Defining comparator products 4
Case study 4.8: Comparator therapies in the PBAC guidelines
4.9 Epidemiology
Case study 4.9: WellPoint epidemiology profiling requirements
4.10 Place of product in therapy
Case study 4.10: The PBAC and expert opinion
4.11 Product profile
Case study 4.11: WellPoint product profile requirements
4.12 Therapy intervention strategies
Case study 4.12: NICE recommendations for Relenza in the treatment of influenza
4.13 Linking meta-analyses to modelled claims
Case study 4.13: Defining clinical parameters for cost-effectiveness modelling
4.14 Monitoring and validating clinical claims
Case study 4.14: The NICE appraisal of beta interferon and glatiramer for multiple sclerosis
Notes
Chapter 5: The Health Economics Case I - Generating Modelled Cost-effectiveness Claims
Chapter outline
5.1 Types of modelled claim
Case study 5.1: Modeling criteria in the PBAC guidelines
5.2 Decision-model frameworks
5.3 Resource units and direct costs
Case study 5.2: Current procedure terminology (CPT) codes
5.4 Valuing resource units
5.5 Indirect costs
Case study 5.3: Demonstrating workplace productivity benefits
5.6 Measuring outcomes
5.6.1 Construct
5.7 Modelling, sensitivity and simulation analyses
5.8 Spreadsheet models
5.9 Monitoring and validating cost-outcome claims
Case study 5.4: The impact of inhaler type on monthly treatment costs of asthma - a retrospective study
5.10 Meta-models
Case Study 5.5: The CORE diabetes meta-model
Notes
Chapter 6: The Health Economics Case II - Estimating System Impacts
Chapter outline
6.1 Defining terms
6.2 Forecasting product uptake
Case study 6.1: SMC requirements for product uptake projections
6.3 Patient switching and target populations
6.3.1 Defining a target population
6.3.2 Market segmentation
6.4 Budget-impact claims
6.4.1 Resource units and unit pricing
6.5 Estimated pharmacy budget impact
6.6 Estimated medical budget impact
6.7 Estimated total budget impact
Case study 6.2: PBAC requirements for financial impact assessment
Note
Chapter 7: Responding to Disease Area and Therapeutic Class Reviews
Chapter outline
7.1 Life-cycle product assessment
7.1.1 Clinical assessments
7.1.2 Anticipating requests for monitoring and validation
7.2 Assessing claims
7.3 Contractual requirements
7.4 Experimental approaches: naturalistic trial designs
Case study 7.1: The role of naturalistic trials
7.5 Non-experimental designs
7.5.1 Case-control studies
7.5.2 Cohort studies
7.6 Practice pattern variations
Case study 7.2: The WellPoint agenda
Notes
Chapter 8: Summary and Conclusions
Chapter outline
8.1 The future of technology appraisals
8.2 Technology appraisals in the short term
8.3 Technology appraisals in the longer term
Glossary
LIST OF FIGURES
Figure 3.1 Benefit and willingness to pay
Figure 3.2 Cost-effectiveness plane
Figure 3.3 Net monetary benefit
Figure 3.4 Ranking net monetary benefits
Figure 3.5 Cost-effectiveness acceptability curve
Figure 3.6 Decision model: Therapy A versus Therapy B
Figure 3.7 Simulated distribution of differences in costs
Figure 3.8 Simulated distribution of differences in outcomes
Figure 3.9 Distribution of cost and outcome difference coordinates in the cost-effectiveness plane
Figure 3.10 Simulated cost-effectiveness acceptability curve
LIST OF TABLES
Table 2.1 Key formulary submission guidelines: documentation and process
Table 3.1 Parameter values: Therapies A, B and C
Table 3.2 Simulation pairs of cost and outcome differences
Table 3.3 Simulated proportion of coordinate cost and outcome difference by willingness-to-pay threshold
Table 4.1 Grading of clinical studies
Dr Paul Langley is Director, Maimon Research LLC, a health technology consulting company based in Arizona. Dr Langley is also Adjunct Professor, College of Pharmacy, University of Minnesota.
Following graduation, he taught at universities in Canada, the UK, Australia and the US. He moved to the US in 1994 and taught at the University of Arizona and then the University of Colorado, where he was Professor in the School of Pharmacy, University of Colorado Health Sciences Center, Denver.
He joined 3M Pharmaceuticals in September 1999 as US and International Manager, Health Economics, leaving 3M in July 2005 to return to consulting and academic pursuits. Dr Langley?s major areas of research interest are in the modelling of drug impacts within healthcare systems, the development and application of guidelines for formulary submission evaluations and the application of health economics to the process of drug development.
Dr Langley received his undergraduate training in the UK and his postgraduate training in Canada, with a PhD in Economics from Queen?s University.