Health Technology Assessment: Using Biostatistics to Break the Barriers of Adopting New Medicines, 1st Edition (Hardback) book cover

Health Technology Assessment

Using Biostatistics to Break the Barriers of Adopting New Medicines, 1st Edition

By Robert B. Hopkins, MA, MBA, PhD, Ron Goeree, MA

CRC Press

276 pages | 33 B/W Illus.

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pub: 2015-04-10
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Description

The term health technology refers to drugs, devices, and programs that can improve and extend quality of life. As decision-makers struggle to find ways to reduce costs while improving health care delivery, health technology assessments (HTA) provide the evidence required to make better-informed decisions.

This is the first book that focuses on the statistical options of HTAs, to fully capture the value of health improvements along with their associated economic consequences. After reading the book, readers will better understand why some health technologies receive regulatory or reimbursement approval while others do not, what can be done to improve the chances of approval, as well as common shortcomings of submissions for drug and device reimbursement.

The book begins by contrasting the differences between regulatory approval and reimbursement approval. Next, it reviews the principles and steps for conducting an HTA, including the reasons why different agencies will have a different focus for their scope in the HTA.

Supplying an accessible introduction to the various statistical options for different methods in an HTA, the book identifies the links to regulatory and reimbursement decisions for each option. It highlights many of the methodological advances that have occurred since HTA research began, to provide researchers and decision-makers with a cutting-edge framework. It also details the logical basis for the methods along with simple instructions on how to conduct the various techniques.

Both authors have considerable experience in generating evidence for submissions and reviewing submissions to decision-makers for funding. One of the authors has also received a nationally recognized lifetime achievement award in this area.

Table of Contents

Regulation, Reimbursement and Health Technology Assessment

Introduction

Regulatory Approval

Regulatory Approval for Prescription Drugs

Regulatory Approval for Devices

Regulatory Approval for Public Health and Other Non- Drug Non-Device Approvals

Reimbursement Approval for Drugs

Initiation of Drug Review for Reimbursement

Further Clinical Evidence for Drug Reimbursement

Consideration of Cost in Drug Reimbursement Decisions

Drug Price Negotiations

Reimbursement Approval for Devices

Health Technology Assessment

Step 1: Identify the Topic for Assessment

Step 2: Clear Specification of the Problem

Step 3: Gathering the Evidence

Step 4: Aggregation and Appraisal of the Evidence

Step 5: Synthesize and Consolidate Evidence

Step 6: Collection of Primary Data (Field Evaluation)

Step 7: Economic Evaluation, Budget and Health Systems Impact Analysis

Step 8: Assessment of Social, Ethical and Legal Considerations

Step 9: Formulation of Findings and Recommendations

Step 10: Dissemination of Findings and Recommendations

Step 11: Monitoring the Impact of Assessment Reports

Summary

References

Requirements and Sources of Data to Complete an HTA

Data Requirements to Complete an HTA

Cost-Effectiveness

Introduction to Health-Related Quality of Life

Introduction to Resource Utilization and Costs

Need for Modelling

Decision Analytic Model

Markov Model

Start with the Trials: Safety and Efficacy

Secondary Data Requirements

Rare Diseases

Effectiveness versus Efficacy

Long-Term Outcomes

Health-Related Quality of Life

Resource Utilization and Costs

Epidemiology

Summary

References

Meta-Analysis

Overview of Meta-Analysis

Initial Steps before a Meta-Analysis

A Comment on Frequentist and Bayesian Approaches

Steps in a Meta-Analysis

Step 1: Identify the Type of Data for Each Outcome

Step 2: Select an Appropriate Outcome Measure

Outcomes for Continuous Data

Step 3: Conduct the Preliminary Analysis with an Assessment of Heterogeneity

Weighting of Each Study

Random or Fixed Effects

Testing for Heterogeneity

Step 4: Adjustment for Heterogeneity

Step 5: Assess Publication Bias

Step 6: Assess the Overall Strength of Evidence

An Example of Meta-Analysis

Outliers

Risk-Adjusted or Unadjusted Analysis

Publication Bias

Meta-Analysis of Diagnostic Accuracy Studies

Example of Meta-Analysis for Diagnostic Accuracy

Hierarchical Summary Receiver Operator Curve

Summary

References

Appendix I: Diagnostic Accuracy Measures

Appendix II: Estimation of Cohen’s Kappa Score

Network Meta-Analysis

Introduction

Head-to-Head and Placebo-Controlled Trials

Step 1: Establish Potential Network Diagram of Linking Studies

Step 2: Check for Consistency in Outcomes for Common Linking Arms

Step 3: Conduct Meta-Analysis and Assess Heterogeneity within Common Comparators

Step 4: Conduct Indirect Meta-Analysis across the Comparators

Network Meta-Analysis Software

Step 5: Conduct Subgroup and Sensitivity Analyses

Step 6: Report Network Meta-Analysis Results

Bayesian Mixed Treatment Comparisons

Network Meta-Analysis Example

Assessing Robustness: Homogeneity and Consistency of Evidence

Adjustment for Difference in Baseline Characteristics

Network Meta-Analysis of Diagnostic Accuracy

References

Bayesian Methods

Introduction

Study Power for Trials of Rare Diseases

Interpretation of Bayesian Results

Bayesian Theorem

Step 1: Specify the Model

Step 2: Assign the Prior(s)

Step 3: Conduct the Simulation

Step 4: Assess Convergence

Step 5: Report the Findings

Advanced Bayesian Models

Advanced Example 1: Combining RCTs and Observational Data

Advanced Example 2: Covariate Adjustment

Advanced Example 3: Hierarchical Outcomes

Summary

References

Survival Analysis

Introduction

Kaplan–Meier Analysis

Exponential, Gompertz and Weibull Models

Establishing and Using Risk Equations

Diabetes Modelling

Acceptability of Surrogates

Survival Adjustment for Crossover Bias

Building a Life Table from Cross-Sectional Data

Summary

References

Costs and Cost of Illness Studies

From Clinical Events to Resource Utilization to Costs

Measurement of Resource Utilization

Attribution and Adjustment for Comorbidities

Strategies to Isolate the Cost of an Event

Regression Methods

Other Strategies to Estimate Costs

Unit Costs Valuation for Resources

Perspective and Types of Costs

Burden of Illness Study

Budget Impact Analysis

Statistical Issues with Cost Data

Summary

References

Health-Related Quality of Life

Why QOL?

Good Properties of Scales

Guidelines for Using QOL in HTA

From Utility to QALY

Assessing Change in QOL Scales

Change in Level of HRQOL and Domains over Time

Minimal Clinically Important Difference for HRQOL

Obtaining QOL Estimates from Trials and Literature

Independent QOL Study

Mapping between QOL Scales

Summary

References

Missing Data Methods

Common Trial Gaps

Missed Visits and Loss to Follow-Up

Explainable or Unexplainable Patterns of Missing Data

Intention-to-Treat or Per-Protocol Analysis

Multiple Imputation for Trial Data

Beautiful Bootstrap

Meta-Analysis Gaps

Missing Measures of Central Tendency

Missing Measures of Variance

Missing Data for Diagnostic Accuracy Studies

Unknown Lifetime Variances for Costs

Summary

References

Concluding Remarks

Academic Writing from a Biostatistician’s Point of View

Introduction

Discussion and Conclusion

Sentences and Paragraphs

Time Management for Writing

Future Research

Improving Reimbursement Submissions

Summary

References

Index

About the Authors

Robert Borden Hopkins, PhD, has been the biostatistician at the Programs for the Assessment of Technology in Health (PATH) Research Institute at McMaster University for the past 10 years and has more than 25 years of experience in health care. His role as the biostatistician continues to include educational support at the graduate level; designing and analyzing systematic reviews; designing, conducting and analyzing clinical studies (field evaluations); conducting economic evaluations, burden of illness studies and health technology assessments and providing peer review for more than 20 academic journals and government agencies.

Rob was the lead biostatistician for more than 75 funded research projects worth over $15 million, which generated over 100 peer-reviewed publications and abstracts and 40 technical reports for the government, as well over 200 conference, academic or government presentations. Recent methodological issues explored include handling of missing data in meta-analysis, trials and economic evaluations; network meta- analysis; trial-based economic analysis and cost/burden of illness studies.

Rob has presented his research at the following conferences: Society of Medical Decision Making, International Society for Pharmacoeconomics and Outcomes Research, Drug Information Association, Canadian Association for Population Therapeutics, Canadian Agency for Drugs and Technologies in Health (CADTH), Canadian Association for Health Services and Policy Research, Society for Clinical Trials, Health Technology Assessment International, Canadian Statistical Society, American Statistical Society, Canadian Health Economics Association and International Health Economics Association.

Ron Goeree, MA, is currently a professor in the Department of Clinical Epidemiology & Biostatistics, Faculty of Health Sciences, at McMaster University in Hamilton, Ontario, Canada, where he is the founding field leader for graduate studies of health technology assessment (HTA) at McMaster University.

Ron has established workshops on HTA all over the world, from Singapore to Oslo, and has published extensively (over 400 books, chapters, articles and abstracts). He has reviewed over 120 journal submissions and 80 national or provincial drug submissions or reports; Ron has served on nearly 50 industry advisory boards and more than 60 government/decision-maker committees and boards.

Ron’s research is conducted at the Programs for Assessment of Health Technology Research Institute at St. Joseph’s Healthcare Hamilton, where he has been the director since 2006. ‘As director of PATH, he has demonstrated the essential role health technology assessment can and should play in meeting the needs of health of health decision-makers. As an innovator, he helped pioneer the methodological framework for the field evaluation of non-drug technologies. As a dedicated professor and mentor, he has trained literally thousands of students, researchers, and decision-makers, making an immense contribution to the capacity in Canada to produce and use health technology assessment’, said O’Rourke, President and CEO of CADTH.

O’Rourke further said that ‘Professor Goeree is one of the pre-eminent HTA researchers and educators in the world’ (CADTH News Release 2012). Ron was the 2012 recipient of the CADTH HTA Excellence Award for lifetime and sustained achievement; he is co-editor of Value in Health and sits on the editorial boards of Medical Decision Making and the Journal of Medical Economics.

Subject Categories

BISAC Subject Codes/Headings:
BUS070080
BUSINESS & ECONOMICS / Industries / Service Industries
MED002000
MEDICAL / Administration
MED028000
MEDICAL / Epidemiology
MED090000
MEDICAL / Biostatistics