Workshop Purpose: To understand new approaches to reduce residual confounding by unmeasured factors when comparing the effectiveness of pharmaceuticals using health care databases.

Workshop Description: Therapeutic substitution policies including multi-tiered co-payment systems and reference drug programs (RDP) are popular ways to contain drug spending. Such policies are based on the assumption of therapeutic equivalence of drugs within reimbursement groups. However, randomized clinical trials (RCTs) rarely compare active drugs head to head and almost always exclude populations that use the largest share of these drugs, i.e. elderly patients with multiple comorbidities. Epidemiologic studies using health care databases can compare multiple drugs head-to-head in elderly patients but are prone to confounding by unmeasured confounders. What are existing strategies to minimize such confounding in database studies? How can we do better and what are the most recent developments? The workshop will first define the need for comparative effectiveness and safety (CES) research using health care utilization databases. This is followed by an overview of design and analytic strategies to approach confounding by unmeasured factors in non-randomized CES research. The workshop will focus on methodological areas to control confounding in CES research that are generally under-appreciated: 1) New user designs and choosing the right comparison group, 2) external adjustment using validation study data, and 3) instrumental variable analysis. These three presentations will illustrate the underlying methodologic issues and use examples from pharmaceutical outcomes research for illustration.

Compliance/Adherence

W2: METHODS FOR MEDICATION COMPLIANCE STUDIES: PATIENT COMPLIANCE AS A PREDICTOR OF CLINICAL AND ECONOMIC OUTCOMES
Salon B
DISCUSSION LEADERS: Joyce Cramer, Associate Research Scientist, Yale University School of Medicine, West Haven, CT, USA; Femida Gwadry-Sridhar PhD, Assistant Professor, University of Western Ontario, and London Health Sciences Centre, London, ON, Canada; Joshua S. Benner PharmD, ScD, Principal, ValueMedics Research, LLC, Falls Church, VA, USA

Workshop Purpose: This workshop will 1) review the methodological issues that must be considered when using patient compliance measures as independent or predictor variables of clinical and economic outcomes; 2) discuss appropriate interpretation of such studies; and 3) discuss implications for future research in this field.

Workshop Description: Compliance with medications has become an increasingly important area of research as decision makers have recognized the extent of noncompliance and questioned the effect of this problem on important patient outcomes. In an increasing number of studies, researchers have used patient compliance data as an explanatory or independent variable. This workshop will identify research design, analysis, and interpretation issues associated with the use of various measures of compliance as independent variables. The faculty will illustrate common pitfalls, recommended methods and interpretations of prospective and retrospective study findings, and highlight several key areas for future research. Examples will be drawn from published and ongoing projects measuring patient compliance and outcomes in a variety of medications and diseases. Workshop participants will be encouraged to offer their perspectives and methodological recommendations regarding future studies of medication compliance as a predictor of clinical and economic outcomes.

Cost Study Methodology

W3: BEWARE OF LOGS: ISSUES TO CONSIDER WHEN ASKING “TO LOG OR NOT TO LOG?”
Salon C
DISCUSSION LEADERS: Jalpa A Doshi PhD, Research Assistant Professor of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Jieling Chen PhD, Health Economist, Merck Research Labs, Blue Bell, PA, USA;
Henry A Glick PhD, Assistant Professor of Medicine, University of Pennsylvania, Philadelphia, PA, USA

Workshop Purpose: The objectives of this workshop are to familiarize participants with complications that arise in the use of logarithmic transformation of costs in the economic analysis of skewed health care cost data.

Workshop Description: Despite recent methodological advances in the techniques to analyze cost data, the log transformation of costs continues to remain a popular choice for analysis among health economists and outcomes researchers. However, the naïve use of log transformations can raise questions concerning the validity of the results and conclusions from such analyses. In this workshop we will first provide an overview of the traditional rationale, theoretical concept, and interpretation of log transformation of costs including the need for and techniques in literature for retransformation of these data. Next, we will demonstrate the complications that arise in the use of log transformations for hypothesis testing in univariate analysis and for both inference and estimation in multivariate analyses. Issues that arise due to differences in variance (i.e. heteroskedasticity), skewness, and kurtosis between the study groups will be highlighted. Finally, we will outline analytic approaches that provide alternatives to log transformations. The workshop will be highly interactive and practical in orientation and will routinely provide examples from simulations and real-world data.

W4: INCORPORATING COMPLIANCE MEASURES IN RETROSPECTIVE COST STUDIES
Salon D
DISCUSSION LEADERS: Antoine C El Khoury PhD, Post-Doctoral Fellow, University of Maryland, Baltimore, MD, USA;
C. Daniel Mullins PhD, Professor and Chair, University of Maryland School of Pharmacy, Baltimore, MD, USA;
Fadia T Shaya PhD, MPH, Assistant Professor, Associate Director, University of Maryland, Baltimore, MD, USA

Workshop Purpose: The purpose of this workshop is to underscore the importance of accounting for compliance in retrospective cost studies.

Workshop Description: Cost analyses assess the magnitude of the economic burden of diseases. Many factors affect the cost of treatment; among them is how patients are complying with the therapy. Compliance with pharmacotherapy is an important factor in determining the effectiveness and side effects of treatment, and the associated costs that are attributed to that treatment. Incorporating compliance into cost studies is crucial for an accurate assessment of direct medical costs and downstream costs associated with improved or reduced effectiveness. Discussants will start by defining compliance, differentiating between adherence and persistence and exploring different measurement techniques of compliance. The second component of the workshop will focus on research methodologies used in building models of costs with and without compliance. We will show how small changes in the measurement of compliance can lead to significant changes in economic estimates. Special emphasis will be given to issues associated with retrospective cost of illness analyses, including the use of continuous versus dichotomous compliance measures, defining the gaps between refills, and problems related to cost data. Participants will be engaged through discussions, and encouraged to comment on the advantages and disadvantages of incorporating compliance measures into cost analyses.

Formulary Development

W5: USING ANONYMOUS PATIENT-LEVEL LONGITUDINAL DATA TO SUPPORT FORMULARY POLICY AND COVERAGE DECISIONS
Salon E & F
DISCUSSION LEADERS: Stephen J. Boccuzzi PhD, MBA, Vice President and Chief Scientific Officer, PharMetrics, a unit of IMS, Watertown, MA, USA; Dan Ollendorf MPH, Vice President, Applied Research, PharMetrics, a unit of IMS, Watertown, MA, USA; Michael E. Minshall MPH, Principal, CORE-USA, a unit of IMS, Fishers, IN, USA

Workshop Purpose: The purpose of this session is to help participants better understand:

• The value of anonymous patient level longitudinal data in supporting formulary policy and coverage decisions including the impact of formulary status and member contribution on overall healthcare costs and outcomes
• How various research approaches and tools can help develop and/or augment value proposition development and support for value-based purchasing decisions for managed markets
• How the changing healthcare climate (i.e. post-MMA) will demand more relevant and deeper insights into the delivery of quality, cost effective healthcare.

Workshop Description: Faced with rising healthare costs, managed markets are being forced to take a closer look at drug acquisition costs relative to expenditures in other cost centers. The utilization of anonymous patient-level longitudinal data can support outcomes research and decision support models that provide useful insights into the real world effectiveness of pharmaceutical agents, enhancing the “formulary value” dialog between biopharmaceutical companies and managed care companies.This educational session will assist attendees in obtaining a better perspective related to the impact of new acute and chronic pharmaceutical agents on formularies. A series of templates for the following categories will be completed within the session supported by presentations and discussions between the attendees and presenters. Categories include: 1.Identification of key issues facing pharmacy and medical directors 2.Translation of these issues into appropriate research questions 3.Identification of the metrics/outcomes that are relevant and desired by various managed market audiences 4.Development of analytic approaches and methods to address these research questions 5.Discussion regarding the use of various decision support tools and approaches to support value-based messaging for pricing and reimbursement 6.Discussion of various presentation formats including peer review publications, HECON dossiers, budget impact / cost effectiveness models.

Health Care Policy Development

W6: COLLECTING AND USING MEDICATION DATA FROM NATIONALLY REPRESENTATIVE PROVIDER-BASED SURVEYS
Liberty A
DISCUSSION LEADERS: Lisa L. Dwyer MPH, Health Scientist, National Center for Health Statistics, Hyattsville, MD, USA; Saeid Raofi MS, Pharmacoepidemiologist, National Center for Health Statistics, Hyattsville, MD, USA;
Karen A. Lees MPH, Epidemiologist, National Center for Health Statistics, Hyattsville, MD, USA

Workshop Purpose: This workshop will instruct participants in how the National Health Care Survey collects medication data from physician offices; hospital inpatient, outpatient, and emergency department settings; and nursing homes and the issues related to generating national estimates from these surveys.

Workshop Description: The role of medications in the U.S. health care system has gained considerable visibility over the past two decades. This visibility is due, in part, to the fact that drug expenditures have increased at a much higher rate than other contributors to health care costs. Recognizing this expanding role, the National Health Care Survey (NHCS), a family of national probability sample surveys of providers and health care encounters, is using a variety of approaches to capture data on medication prescribing and use. Conducted annually since 1992, the National Ambulatory Medical Care (NAMCS) and National Hospital Ambulatory Medical Care Surveys (NHAMCS) collect data from physicians and hospital outpatient and emergency departments on medications ordered, supplied, or administered during the visit. The 2004 National Nursing Home Survey (NNHS) for the first time collected data on medications taken by nursing home residents. In 2004, the National Hospital Discharge Survey (NHDS) completed a pilot study to assess the feasibility of collecting data on medications administered to inpatients during their hospital stay. This session provides participants with information about how medication data are collected across the three components of the NHCS--ambulatory care, long-term care, and hospital care--and how to generate national estimates from the NAMCS, NHAMCS, and NNHS. The lessons learned from the NHDS pilot study and future plans for data collection on medications will be discussed. Throughout the presentation, participants will be engaged in discussions about how to use these data to answer policy relevant questions.

W7: METHODS FOR QUANTIFYING THE GENEROSITY OF PHARMACY BENEFIT PLANS
Liberty C
DISCUSSION LEADERS: Nicole M. Nitz PhD, Researcher, i3 Innovus, an Ingenix Company, Eden Prairie, MN, USA; Rachel Halpern PhD, Researcher, Health Economics & Outcomes, Eden Prairie, MN, USA

Workshop Purpose: The advent of the Medicare Part D program underscores the increasingly complex landscape of available pharmacy benefits; the implementation of this program poses the challenge of incorporating this complexity into estimations of the impact of pharmacy benefit plans on medication adherence and other patient outcomes. This workshop will examine methods to describe and assess the generosity of pharmacy benefits, with a focus on the potential for concisely describing data that include plans with a wide variation in plan attributes such as deductibles and copayments.

Workshop Description: General economic theory suggests that all other things being equal (such as premiums), patients are more likely to select a ‘generous' pharmacy benefit plan, and show patterns of increased consumption under the plans with more ‘generous' benefits. In comparing a small set of plans, differences in the ‘generosity' of plans may be easily delineated (e.g. deductible vs. no deductible, high vs. low copay). However, in a landscape of hundreds of plans, quantifying and comparing ‘generosity' involves assessing a matrix of the combinations of factors including presence and level of a deductible, copayment, formulary tiering, generic requirements, etc. This workshop will examine the approaches described in the literature on the importance of each attribute of benefit structure, methods of categorization, and analytic approaches. Additionally, the workshop will explore the expected impact of each approach on estimates of the effect of benefit structure on patient outcomes. The benefits and limitations of existing methods for concisely and fully describing the generosity of a large and varied set of benefit plans will be debated. Participants will engage in a critical discussion of the use of health plan benefits data in applied health outcomes research and will be encouraged to identify creative solutions.

QoL/PRO Methodology Issues

W8: WHAT TYPE OF OUTCOME MEASURE IS THIS?
Room 401
DISCUSSION LEADERS: Judith T Barr ScD, Director, NERCOA, Northeastern University, Boston, MA, USA;
Pennifer Erikson PhD, President, OLGA, Pennsylvania State University, State College, PA, USA

Workshop Purpose: Following a presentation providing a conceptual foundation of characteristics and types of patient-reported outcomes (PROs), workshop participants will apply the principles of the Wilson/Cleary taxonomy of outcomes and the PRO Harmonization Task Force to determine the type and reporting source of outcome measures used in selected May 2005 ISPOR posters and other sources.

Workshop Description: The incorporation of health-related quality of life (HRQL) measures and patient-reported outcomes (PROs) into pharmacoeconomic research is an important step in the evolution of this field of study. However, there is a need to clarify that not all HRQL outcome studies are PROs, and conversely, not all PROs studies incorporate HRQL measures. In this workshop, we will present a conceptual overview of 1) health outcomes based on the 1995 Wilson/Cleary causal model linking clinical, symptom, functional status, health perceptions, and quality of life aspects of health and disease and 2) sources of health outcomes based on the Ad Hoc Task Force on PRO Harmonization. We will suggest examples of PRO and non-PRO outcome measures for each of Wilson/Cleary categories, and contrast and compare the information content and perspective of such measures. We will further develop concepts and definitions of Quality of Life and HRQL to include general and disease-specific HRQL measures as well as methods of utility assessment. Additional PRO measures such as patient satisfaction and adherence/compliance will be linked to our expansion of the Wilson/Cleary model. The place of clinician and proxy measures in our model also will be examined. In the last third of the workshop, participants will work in small groups to examine cases based on abstracts/posters from ISPOR and other sources, place each study's outcomes into our taxonomy, and determine whether or not the measures used are PRO and/or HRQL. We will conclude the workshop with a discussion of issues raised in these cases.

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Monday, May 22nd
3:15PM - 4:15PM - Workshops Session II

Clinical Study Methodology

W9: ANALYTICAL AND STATISTICAL CONSIDERATIONS IN THE DESIGN, CONDUCT AND ANALYSIS OF PROSPECTIVE PHASE IV STUDIES
Salon A
DISCUSSION LEADERS: Eric K Gemmen MA, Executive Director, Phase IIIb/IV Data Analysis & Health Economics, Quintiles Strategic Research Services, Falls Church, VA, USA; Hany Zayed PhD, Senior Statistical Scientist, Quintiles Strategic Research Services, San Francisco, CA, USA; Murtuza Bharmal BPharm, MS, PhD, Senior Health Outcomes Associate, Quintiles Strategic Research Services, Falls Church, VA, USA

Workshop Purpose: The purpose of this workshop is to help participants better understand the opportunities and challenges presented in the design, conduct and analysis of large, prospective Phase IV clinical studies.

Workshop Description: The design of prospective Phase IV studies can range from randomized controlled studies to observational studies including product registries, disease registries, parallel cohort studies and cross-sectional studies. The choice of Phase IV study design requires multiple considerations including the study objectives, cost and time factors, regulatory requirements, and commercial sensitivities of the sponsor. Each of these prospective Phase IV study designs carries its own methodological challenges. This workshop will assess the analytical and statistical challenges that are commonly encountered in these studies, providing examples with solutions. Some of the specific methodological issues that will be discussed in the workshop include considerations in the choice of study design, common flaws in case report form (CRF) design, investigator site identification, choice of analysis populations, interim analysis of study endpoints, the treatment of missing data including imputation, adjusting for selection bias in non-randomized studies, post-hoc analysis and its statistical implications, etc. Discussion and questions will be solicited throughout the presentation. The workshop will conclude with audience participation via an interactive exercise that applies the contents discussed in the workshop to research problems.

Compliance/Adherence

W10: ADHERENCE: HOW DO WE MEASURE IT, AND WHOSE ADHERENCE ARE WE MEASURING?
Salon B
DISCUSSION LEADERS: Lisa Mucha PhD, Research Leader, Thomson Medstat, Cambridge, MA, USA; Tami Mark MBA, PhD, Associate Director, Thomson, Washington, DC, USA; Kathleen Foley PhD, Research Leader, Thomson Medstat, Philadelphia, PA, USA

Workshop Purpose: The purpose of this workshop is to review the various measures used to assess medication adherence. The applied work and discussion will help participants better understand the various ways to measure adherence and the pros and cons associated with each method. In addition, it will enable researchers to carefully consider whose adherence is being measured, particularly for cognitively impaired patients.

Workshop Description: There are numerous ways to assess patient adherence to a prescribed regimen. This workshop will present various measurement methods such as medication possession ratio (MPR), study possession ratio, discontinuation, switching, overlapping therapy, persistence over time, number and length of gaps in therapy, titration, and time to effective dose. We will show examples of how a single measure, such as MPR, can show different results over the same time frame depending on the number of treatment gaps. We will also show how different adherence measures within the same study can yield different conclusions. The use of multiple measures and the choice of deciding what the optimal measures are to report within a single study will be discussed. All the above examples will be shown in the context of a specific study of utilization of a medication for patients with cognitive impairment. Workshop participants will be engaged by calculating different adherence measures. Discussion and questions will be generated continuously during the workshop via the presentation of examples as well as the calculation of adherence measures. This workshop will also generate discussion of whose adherence is being measured (patient or caregiver) when the patient is not able to directly control his/her adherence.
 

Cost Study Methodology

W11: CREATIVE USES OF LINKED SEER-MEDICARE DATA IN MODEL-BASED PHARMACOECONOMIC EVALUATIONS
Salon C
DISCUSSION LEADERS: Kathy Lang PhD, Senior Consultant, i3 INNOVUS, Medford, MA, USA;
Michael E Stokes MPH, Research Analyst, i3 INNOVUS, Medford, MA, USA; Milton C Weinstein PhD, Principal Consultant, i3 INNOVUS, Harvard School of Public Health, Harvard Medical School, Boston, MA, USA

Workshop Purpose: The objectives of this workshop are to describe creative uses of the linked SEER-Medicare database in model-based pharmacoeconomic evaluations of oncology interventions.

Workshop Description: The Surveillance Epidemiology and End Results (SEER) Program represents a cancer surveillance system consisting of regionally-diverse tumor registries representing approximately 14% of the U.S. population. When linked with claims data from the Medicare 5% sample, the database offers a rich resource for outcomes research. Most published studies (and prior ISPOR workshops) have focused on the value of this data source in stand-alone retrospective database research. In this workshop, we provide several examples of creative uses of SEER-Medicare data in model-based pharmacoeconomic research, including cost-of-illness evaluations, cost-effectiveness analyses, and budgetary impact assessments. The SEER-Medicare database is an obvious source for estimation of model inputs related to patient demographics, treatment patterns, unit costs, and survival. There are several other creative applications in which these data can be used: (1) To construct matched samples that represent patients receiving conventional treatment for comparison to a new therapy evaluated solely in uncontrolled clinical trials; (2) To estimate medical-care costs and life expectancy following occurrence of selected events (e.g., recurrence, disease progression) that were endpoints in trials, but require continued follow-up in models; (3) To provide benchmark treatment pattern estimates that can be “tweaked” using expert opinion in other countries in which such data are unavailable; and (4) To construct clinical pathways models for subsequent use in pharmacoeconomic evaluations. Examples from prior work in breast cancer, colorectal cancer, lung cancer, skin cancer, kidney cancer, and other tumor types will be presented, and workshop participants will be invited to contribute additional examples. Limitations of SEER-Medicare data (e.g., lack of clinical detail, potential for coding inaccuracies, limited applicability, challenges in identifying cancer recurrence) also will be highlighted and solutions discussed.


W12: PRESENTING UNCERTAINTY IN COST EFFECTIVENESS RESEARCH
Salon D
DISCUSSION LEADERS: Katia Noyes PhD, MPH, Assistant Professor, University of Rochester School of Medicine, Rochester, NY, USA; Elisabeth Fenwick PhD, Lecture, University of Glasgow, Glasgow, United Kingdom

Workshop Purpose: Probabilistic sensitivity analysis (PSA) is becoming a key part of any cost-effectiveness (CE) study and is required by a growing number of organizations. Numerous publications describe the theory and methodology behind PSA, but few describe how to present the results of such analyses within papers and presentations. The participants of the workshop will learn how to 1. build confidence ellipses within the CE plane in Excel using patient-level data; 2. understand the relationship between the incremental cost-effectiveness ratio (ICER) point estimate, location of confidence ellipse in respect to the CE threshold and acceptability curves (CEAC); 3. build CEAC using Excel for Windows; 4. present and interpret results of CE analysis in a PowerPoint presentation.

Workshop Description: The instructors will describe the sources of uncertainty in cost-effectiveness studies using patient-level vs aggregated data, outline current recommendations for presenting uncertainty, and discuss several examples of studies that estimated and presented various types of uncertainty. Two approaches will be described in detail: confidence ellipses and acceptability curves. Using Excel spreadsheet and bootstrapped patient-level data, the instructors will demonstrate how to build confidence ellipses around ICER, step by step, and how to interpret such scatterplot. Similarly, the participants will learn how to generate CEACs for 2 and more competitive interventions and recognize the common problem with interpretation of CEACs. The instructors will show how confidence ellipses and CEACs compliment each other and help articulate results of CEA and consequences of making decisions based on those results to decision makers at various levels. Each participant will recieve a CD containing datasets and templates for generating CEAC and confidence ellipses in Excel and will be able to follow instructors during the workshop or generate these graphs on her/his own at their convenience. The participants will learn how to incorporate confidence ellipses and CEAC into PowerPoint presentation and use animation and color graphics to interpret the results and bring them closer to the audience.

Formulary Development

W13: FORMULARY DECISIONS FOR MEDICARE PART D
Salon E& F
DISCUSSION LEADERS: Fadia T Shaya PhD, MPH, Assistant Professor, Associate Director, University of Maryland, Baltimore, MD, USA; C. Daniel Mullins PhD, Professor and Chair, University of Maryland School of Pharmacy, Baltimore, MD, USA; Winston Wong PharmD, Director, Pharmacy Management, CareFirst BlueCross BlueShield, Baltimore, MD, USA 

Workshop Purpose: This workshop demonstrates the strengths of managed care claims databases used for formulary development in the context of Medicare Part D. The aim of the workshop is to provide practical tools to manage claims data and interpret results used for the cost-effectiveness, value and clinical claims considered by formulary committees.

Workshop Description: With the potential influx of 43 Million additional lives into managed care plans, as a result of the implementation of Medicare part D, there is an urgent need to streamline the approach to effectiveness and cost assessment of therapies. These analyses are at the basis of formulary decisions with huge implications to the health of vulnerable populations. We will discuss initiatives from the federal government, for a research network to derive effectiveness data in support of decision-making, such as the DEcIDE network from AHRQ and related activities from CMS. This hands-on workshop will examine practical issues and characteristics of managed care databases, and will outline their strengths and mention their limitations in answering research questions and supporting evidence and value claims. Specifically, we will discuss study design as relevant to elderly and disabled populations. With active participation from the audience, we will address methods to develop medical and prescription data queries, build patient cohorts, specify endpoints and choose analytical methods. Participants will be guided in methods to merge and match medical and prescription claims, and will identify validity issues related to properly specifying the data fields (e.g. primary, secondary and tertiary diagnoses, time of diagnosis, or billed charges versus paid charges etc ..). We will outline bias and confounding concerns, and demonstrate tools to handle them in retrospective claims data, as compared to prospective data. Participants will use and critique different methods, to show how they can lead to conflicting results. A case study will be used to interpret the answers to questions of value statement, cost-effectiveness, risk projection, compliance modeling and budget impact. By the end of the workshop, the participants will be able to apply the tools for research geared at formulary development as relevant to Medicare Part D.
 

Health Care Policy Development
W14: WHAT HEALTH OUTCOMES RESEARCHERS NEED TO KNOW ABOUT MEDICARE PART D
Liberty A
DISCUSSION LEADERS: Diane Simison PhD, Executive Director, Center for Pricing and Reimbursement, United BioSource Corporation, Arlington, VA, USA; Sandy Robinson MPA, Deputy Director, Center for Pricing and Reimbursement, United BioSource Corporation, Arlington, VA, USA; Beth Hahn PhD, Managing Director, Center for Pricing and Reimbursement, United BioSource Corporation, Arlington, VA, USA

Workshop Purpose: The purpose of this workshop is to provide an understanding of the Medicare Part D legislation and what it means for health outcomes research support for new and currently commercialized drugs.

Workshop Description: The implementation of Medicare Part D represents the largest change to the US health care system since the institution of Medicare and Medicaid. It will fundamentally change both the public and private health care markets in ways that will impact the work of pharmacoeconomic researchers. The workshop will consist of three modules: overview of Part D legislation; likely changes from the current marketplace and the impact on public and private reimbursement and market access; implications for pharmacoeconomics research. Participants will engage in a discussion of specific issues this legislation presents for modeling, prospective and retrospective research on elderly populations, and PRO research.


W15: EFFECTIVE HEALTH CARE: ASSESSING, DEVELOPING, AND COMMUNICATING EVIDENCE FOR HEALTH CARE DECISIONS
Liberty C
DISCUSSION LEADERS: Jean Slutsky PA, MSPH, Director, Center for Outcomes and Evidence, Agency for Healthcare Research and Quality, Rockville, MD, USA; Mark Helfand MD, MPH, Director, Oregon Evidence-based Practice Center, Professor of Medicine and Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA; Scott R. Smith MSPH, PhD, Pharmaceutical Outcomes Portfolio Lead, Agency for Healthcare Research and Quality, Rockville, MD, USA

Workshop Purpose: Participants will learn about the interacting roles of systematic reviews, outcomes research, and decision support in developing and communicating with the public about comparative effectiveness reviews. Participants will explore methodological challenges and current approaches to study comparative effectiveness and meaningfully communicate findings to decision makers.

Workshop Description: Patients, providers, and policymakers share an interest in making informed decisions about health care to promote good outcomes. One of the greatest challenges is finding reliable and practical data that can inform these decisions. Section 1013 of the Medicare Modernization Act (MMA) authorizes the Agency for Healthcare Research and Quality (AHRQ) to conduct and support research with a focus on outcomes, comparative clinical effectiveness, and appropriateness of pharmaceuticals, devices, and health care services. AHRQ has designed a program that systematically reviews existing evidence on effectiveness and comparative effectiveness of health care interventions relevant to the Medicaid, Medicare, and SCHIP programs, identifies critical research gaps, and, when appropriate, initiates data driven research studies using a network of accelerated research organizations with access to electronic health information data sources. The Effective Health Care Program also translates complex scientific findings into understandable language for health care decision makers through the John M. Eisenberg Clinical Decisions and Communications Science Center. The Effective Health Care Program sponsors methodological research on the best approaches for evaluating different data source and reducing the level of bias, how best to evaluate observational studies, best practices in risk communication, and when to update systematic reviews. Participants will discuss different approaches to analyzing, developing, and communicating comparative effectiveness research with the workshop presenters.


Risk Assessment

W16: REDEFINING RISK AND UNCERTAINTY IN OUTCOMES RESEARCH: COMING TO TERMS WITH THE UNKNOWN Room 401
DISCUSSION LEADERS: John F P Bridges PhD, Health Economist, University of Heidelberg, Heidelberg, Germany; Joshua Graff Zivin PhD, Assistant Professor, Columbia University, New York, NY, USA; Rachael Molnar MS, MD/PhD Fellow, Case Western Reserve University, Cleveland, OH, USA

Workshop Purpose: The purpose of this workshop is to help participants better understand the distinction between risk and uncertainty in outcomes research and to demonstrate where current methods in this area are lacking. Special emphasis is placed on methods to better understand true issues of uncertainty.

Workshop Description: While it has long been realized that medicine involves a great deal of uncertainty, traditional evaluation methods in outcomes research have either ignored this concept or arbitrarily dealt with it through sensitivity analysis. While a number of recent “stochastic” methods claim to deal with uncertainty, they fail to fully account for the “unknown” and focus on the observed random variation from limited samples. This session introduces participants to the “Knightian” definitions of risk and uncertainty that are often used in economics, and by doing so aims to demonstrate the limited capacity of outcomes research to deal with uncertainty. After identifying and dismissing a number of myths relating to (societal) decision making under risk and uncertainty, a number of new methods for dealing with risk and uncertainty are drawn from the economic and finance literatures. Participants will be engaged in discussion throughout the workshop (instead of limiting discussion to a question and answer period at the end of the session). Clinical oncology will be used as an extremely relevant example. We will also draw from a number of our empirical studies, both quantitative and qualitative, as the basis of case studies. At the conclusion of the seminar, participants will be better informed about the relative roles of risk and uncertainty in outcomes research, be more capable of identifying the flaws in our current methodology, and be empowered to explore possible alternatives to analyze risk and uncertainty. This session best suits clinicians or industry-based outcomes researchers who deal with the risks and uncertainties of new products.

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Tuesday, May 23rd
2:15PM-3:15PM -  Workshops Session III

Clinical Study Methodology

W17: ASSESSING THE CAUSAL EFFECTS OF TREATMENTS IN LONGITUDINAL NATURALISTIC DATA
Salon A
DISCUSSION LEADERS: Miguel A Hernan MD, DrPH, Assistant Professor of Epidemiology, Harvard School of Public Health, Boston, MA, USA; Marshall Joffe MD, PhD, Assistant Professor of Biostatistics, University of Pennsylvania, Philadelphia, PA, USA; Douglas Faries PhD, Research Advisor, Eli Lilly and Company, Indianapolis, IN, USA

Workshop Purpose: The goals of this workshop are to motivate participants to understand the issues with and the newer methods for addressing the challenges of identifying treatment effects in naturalistic data.

Workshop Description: In naturalistic data, patients may stop, switch or even augment the medications of interest. Detecting the causal effects of medications in such data is challenging due to the potential biases introduced by missing data and time-varying confounders. Even when groups are randomized at the start of the study, the naturalistic treatment patterns that follow involve medication changes that depend on time-varying factors and lead to imbalances between groups. Such time-varying imbalances must be accounted for in the statistical analyses. Standard methods that can incorporate time-varying covariates, such as Cox-proportional hazards models and repeated measures models, do not necessarily lead to unbiased estimates of causal treatment effects unless appropriate adjustments are made. In this workshop we will present a motivating example of assessing the outcomes of patients in a naturalistic schizophrenia study involving medication switching and patient dropout. Statistical methods to address the challenges of causal inference in such data will be presented and discussed. Discussion will include the use of marginal structural models and structural nested models – as contrasted with commonly used ad-hoc methods. Under a set of assumptions, these newer approaches can provide for unbiased estimates of causal effects of treatment even in the presence of medication switching, missing data, and time-varying confounders. Participation of the audience will be solicited at several key points in discussion to enhance the learning experience.


Compliance/Adherence

W18: AN ECONOMIC FRAMEWORK TO UNDERSTAND MEDICATION COMPLIANCE AND PERSISTENCE
Salon B
DISCUSSION LEADERS: Judith Shinogle PhD, Senior Economist, RTI, International, Washington, DC, USA;
Pamela Peele PhD, Associate Professor and Vice Chair, University of Pittsburgh, Pittsburgh, PA, USA;
Rachel Elliot PhD, Clinical Senior Lecturer, The University of Manchester, Manchester, United Kingdom

Workshop Purpose: This workshop will explore economic models of behavior to examine factors associated with medication compliance and persistence.

Workshop Description: Economic models will be presented that explore medication taking behaviors with the specific aim of applying these models to medication compliance and persistence. Sociological and psychological frameworks have suggested that intentional non-compliance is not a deviant behavior that stems from ignorance or particular socio-demographic characteristics. Economists have worked with psychologists to examine choice behavior more closely. This workshop will provide arguments for the use of economic models to further explain medication-taking behaviors. Models to be presented include (a) derivations of Neumann-Morgenstern utility theory to explain decisions under uncertainty about present and future health production and consumption; (b) the quantification by patients of those utilities using stated preference methods; (c) bilateral bargaining models to explore patient – provider interactions; (d) prospect theory models to examine how choices vary depending on the reference point (i.e., original health state) when faced with risk or uncertainty; and (e) issues related to time preferences and discount rates. Preliminary work linking these models to aspects of medication compliance and persistence will be presented. The audience will be solicited to assist in refining and discussing these approaches, as well as other economic models that may be relevant to understanding medication compliance and persistence. [This topic is a component of ongoing work by the Medication Compliance and Persistence Special Interest Group, Economics Working Group.]


Cost Study Methodology

W19: CENSORED COST DATA ANALYSIS: RECENT DEVELOPMENTS AND APPLICATION
Salon C
DISCUSSION LEADERS: Xin Ye PhD, Researcher, i3 Innovus, An Ingenix Company, Eden Prairie, MN, USA;
Henry Joe Henk PhD, Researcher, i3 Innovus, An Ingenix Company, Eden Prairie, MN, USA; Carolyn Harley PhD, Senior Director, i3 Innovus, An Ingenix Company, Eden Prairie, MN, USA; Lisa McGarry, M.P.H., Associate Director, i3 Innovus, Medford, MA, USA

Workshop Purpose: Health care cost data are often censored due to the loss of follow-up resulting from death, study drop-out, or health plan disenrollment. The objectives of this workshop are to: (1) help participants better understand the methodological issues related to analyzing right-censored cost data; (2) describe limitations of commonly-used methods to address variable length of follow-up; and (3) examine recent developments in right-censored cost data analysis, with an emphasis on weighted regression techniques.

Workshop Description: Health care cost data, in prospective research and in retrospective data analyses, are often right-censored. Commonly used method for dealing with this issue involve excluding subjects with incomplete cost data, last observation carried forward, and prorating results. These methods may substantially reduce the effective sample size and often results in estimation bias. Recently, several methods have been proposed to estimate the mean total costs inclusive of patients with censored data. The basic idea of these methods is to weight observations with complete follow-up by their inversed probabilities of inclusion. Some methods require detailed patient cost histories prior to censoring while others only make use of the total costs observed in follow-up. Using specific examples of health outcomes research and simulation studies, this workshop will review these techniques and provide practical guidance in the use of these methods. Participants will be engaged in a critical comparison of each technique, its impact on study results, and comparison to more commonly-used methods (e.g., per patient per month costs) through the use of applied examples and simulations. Discussion and questions will be solicited throughout the presentation.


W20: COLLECTING AND USING PRODUCTIVITY DATA FROM CLINICAL TRIALS
Salon D
DISCUSSION LEADERS: Joshua J. Gagne PharmD, Outcomes Research Fellow, Thomas Jefferson University, Philadelphia, PA, USA; Kenneth D. Smith PhD, Project Director, Thomas Jefferson University, Philadelphia, PA, USA; Laura T. Pizzi PharmD, MPH, Associate Director of Research, Thomas Jefferson University, Philadelphia, PA, USA

Workshop Purpose: The purpose of this workshop is to describe various issues in conducting productivity analyses using clinical trials data. Participants will learn some of the benefits and drawbacks of using clinical trials data for productivity analysis. They will learn about major conceptual and empirical issues researchers must consider for effective analysis.

Workshop Description: Healthcare costs burden employers via both direct medical costs and indirect costs resulting from time lost from work, which includes absence as well as reduced performance while on the job. Health-related lost productivity results in billions of dollars in indirect costs per year for U.S. employers alone. Productivity measurement tools included in clinical trials, such as patient diaries, represent an opportunity to collect productivity data.
This workshop will provide researchers with an overview of conceptual and empirical issues in measuring productivity in clinical trials, and offer recommendations for maximizing the opportunity to collect and analyze data from clinical trials. Examples of some of the issues will be illustrated with data, and include:
• Examples of productivity measurement tools
• Standard models of labor supply and factors that should be taken into account when attempting to measure effect of drug treatment on productivity measures
• Clinical studies powered to detect differences in clinical outcomes may not be sufficiently powered to detect differences in labor supply outcomes
• Productivity measurements via some tools captured at regimented intervals according to the clinical protocols which may not be adequate for productivity assessment
• A comparison/contrast of clinical trial data versus observational/naturalistic data and benefits and challenges associated with each of these study types
• The effects of recall period and recall bias on the collection of productivity data
• Tips to maximize the utility of productivity data in clinical trials

Formulary Development

W21: THE USE OF SOJA AND STEPS TO DETERMINE RATIONAL DRUG CHOICES
Salon E & F
DISCUSSION LEADERS: Robert Janknegt PhD, Hospital Pharmacist/Clinical Pharmacologist, Maasland Hospital, Sittard, Sittard, Netherlands; Michael Scott BSc, PhD, Chief Pharmacist, United Hospitals Trust, ANTRIM, United Kingdom

Workshop Purpose: The purpose of the workshop is to enable participants to understand the use of the objective techniques of SOJA and STEPS, including practical application, to the rational and transparent selection of drugs.

Workshop Description: The system of objectified judgement analysis (SOJA) will be described explaining the process of how the matrix is derived based on the key characteristics relevant to each therapeutic class. It will also cover how relative weights are applied to all criteria to enable a total score to be calculated.
The opportunity will be given to participants to carry out such an exercise on a particular therapeutic class.
Finally, how this process fits into the overall management of medicines will be covered via the safe, therapeutic, economic pharmaceutical selection (STEPS) model. This will include the practical implementation and will highlight the potential financial benefits that can be derived whilst still maintaining optimal patient care.


Health Care Policy Development

W22: PRESENTING UNCERTAINTY AROUND COST-EFFECTIVENESS ESTIMATES TO DECISION MAKERS: HOW SURE ARE WE?
Liberty A
DISCUSSION LEADERS: Mohan Bala PhD, Director, Centocor Clinical Research and Development, Inc, Malvern, PA, USA; Josephine Mauskopf PhD, Vice President, Health Economics, RTI Health Solutions, Research Triangle Park, NC, USA; Gary Zarkin PhD, Director, Behavioral Health Research Division, RTI International, Research Triangle Park, NC, USA

Workshop Purpose: The objective of this workshop is to review current approaches to presenting uncertainty around cost-effectiveness estimates to decision makers, and to propose a few modifications.

Workshop Description: Uncertainty around the input parameters to an economic model gives rise to uncertainty around the cost-effectiveness results generated by the model. We will review the different means of presenting this uncertainty to decision makers that have been used so far. These include sensitivity analysis, confidence intervals, scatter plots, stochastic league tables, and acceptability curves. In reviewing these approaches we will focus on two questions that the decision maker may have: (1) if I choose product X, what is the likelihood that I have made the wrong (non-optimal) choice, (2) in cases where I am wrong, what is the magnitude of loss of benefit or welfare. The acceptability curves, as currently used, focus solely on question 1. We will present a modification to acceptability curves that addresses both of the questions above. We will conclude the workshop with an interactive discussion on the relative merits of the different approaches of presenting uncertainty, and how decision makers should utilize this information.


W23: THE VALUE AND ACCEPTABILITY OF A BAYESIAN FRAMEWORK FOR DRUG REIMBURSEMENT AND MARKET ACCESS DECISION-MAKING
Liberty C
DISCUSSION LEADERS: Jeroen P Jansen PhD, Project Manager, Mapi Values, Houten, Netherlands; Keith Tolley MS, Director, Mapi Values, Bollington, Cheshire, United Kingdom

Workshop Purpose: Participants will be introduced to the construction of a Bayesian analytical framework for cost-effectiveness evaluations of competing interventions. Focus is on introduction of methods, acceptance by reimbursement authorities and market access agencies, and communication to decision-makers.

Workshop Description: The process of reimbursement and formulary decision-making is inherently Bayesian: in the presence of uncertainty, available information has to be used to decide which therapy is most likely to provide greatest value for money. Hence, a Bayesian approach is appropriate for performing analyses that support such decision-making. In this workshop participants are introduced to the use of one coherent Bayesian framework for conducting meta-analyses and for developing decision analytic models for competing interventions. With this approach all analyses are programmed within one computer program and performed in a Bayesian way (e.g. WinBUGS). This has several advantages: 1) Uncertainty in parameter estimates obtained with meta-analyses directly feed into the decision-model. No assumptions regarding uncertainty distributions are necessary in the ‘transition' of results from the meta-analysis performed in one software package to the model in another package; 2) It is possible to calculate the probability as to which of the competing interventions provides greatest outcomes; and 3) Improved transparency. As part of technology appraisals, NICE encourages Bayesian methods in economic evaluations. However, Bayesian methods are not necessarily utilized by other market access agencies around the world. In the workshop we will interactively discuss the level of acceptance by decision makers of such a Bayesian approach, and how perceived disadvantages can be overcome through communication and education. Furthermore, the advantages of the coherent framework for sponsors will be discussed, i.e. transparency and credibility of submitted cost-effectiveness evaluations. It will be shown that user interfaces for WinBUGS models can be developed to allow end-users without specific technical experience to update analysis within a Bayesian framework themselves.


Risk Assessment

W24: THE USE OF GENERAL PRACTICE RESEARCH DATABASES IN THE RISK MANAGEMENT OF NEWLY LICENSED MEDICATIONS
Room 401
DISCUSSION LEADERS: Tjeerd P Van Staa MD, PhD, Head of Research, General Practice Research Database, London, United Kingdom; Susan Eaton MSPH, MT, Head of GPRD Customer Services USA, General Practice Research database, Raleigh, NC, USA

Workshop Purpose: New European legislation now requires compliance to the Safety Specification, Risk Management and Risk Minimisation Plans. This workshop will address how general practice research databases can enable compliance to this new legislation.

Workshop Description: General practice databases have been used in the description of the epidemiology of outcomes with the indication of interest and for the monitoring of outcomes in patients using newly licensed medication. An example will be given how a newly developed tool can facilitate the conduct of these Risk Management studies, allowing the direct evaluation of comorbidity and medication profiles and of results of specific laboratory analyses. Routine signal detection of potential safety concerns is now also required for marketed medicines. It will be discussed whether large general practice research databases should be used for routine signal detection. Research database can also help to quantify the absolute excess risks of a medicine (rather than relative risks). An example will be given of a novel pharmacoeconomic model that estimates the excess risks in various groups of women using Hormone Replacement Therapy.

TO TOP

Tuesday, May 23rd
3:30PM-4:30PM - Workshops Session IV

Clinical Study Methodology

W25: DEVELOPING ECONOMIC MODEL: PREDICTING CHANGE OVER TIME WITH FRACTIONAL POLYNOMIALS
Salon A
DISCUSSION LEADERS: K Jack Ishak MSc, Statistician, Caro Research Institute, Montreal, QC, Canada;
J. Jaime Caro MDCM, FRCPC, FAC, President & Scientific Director, Caro Research Institute, Concord, MA, USA

Workshop Purpose: The purpose of this workshop is to describe and illustrate a modeling strategy that uses fractional polynomials, a flexible technique, to develop prediction equations of change over time.

Workshop Description: Economic models often require predictions of measures of patients' condition over time (e.g., blood pressure). The data used to develop the prediction equations are collected in longitudinal studies that involve repeated measurements of the variables of interest. The challenge in deriving these equations lies in adequately capturing the pattern of the change in measures over time, which may not always be described by simple (e.g., linear or quadratic) functions. Furthermore, finding a single parameterization that works for all or most patients in the sample may not be possible. We present a two step approach in which patients are first classified into groups based on the general direction of the pattern of changes in the measure. Each group is then modeled separately using fractional polynomials to find the best-fitting parameterization of time from a set of pairs of powers of time. This is done in the context of linear hierarchical models which provide several advantages: 1) they take into account correlations between observations collected from the same patient; 2) they can incorporate covariates with time-varying values; 3) they can be extended to allow variability of parameters across individuals (e.g., each subject may have a different rate of change). We describe the model fitting process and illustrate the implementation of the method with actual data.


Compliance/Adherence

W26: CONTINUOUS ENROLLMENT AND THE INCOMPLETE INFORMATION TRADEOFF
Salon B
DISCUSSION LEADERS: Chi-Chang Chen PhD, Post-Doctoral Fellow, University of Maryland School of Pharmacy, Baltimore, MD, USA; C. Daniel Mullins PhD, Professor and Chair, University of Maryland School of Pharmacy, Baltimore, MD, USA; Fadia T Shaya PhD, MPH, Assistant Professor, Associate Director, University of Maryland, Baltimore, MD, USA

Workshop Purpose: To demonstrate the implications of requiring continuous enrollment in persistence studies and to discuss factors guiding the decision to incorporate continuous enrollment, recognize the impact of different approaches, and interpret study results properly.

Workshop Description: Researchers who use retrospective databases to conduct pharmacoeconomic studies often face the dilemma of requiring subjects to be continuously enrolled during the study period to be eligible for final analysis. Keeping only continuously enrolled subjects would sometimes substantially reduce the sample size, cause selection bias and result in external validity problems. Including all subjects recruited may lead to attrition bias and a threat to internal validity. This workshop will evaluate the benefits and drawbacks, specific to different types of studies, of requiring and not requiring continuous enrollment in research design and analysis. Participants will be engaged in comparing different approaches, through empirical examples, to better recognize their implications, to know when and how to address continuous enrollment issues and to interpret study results appropriately. Workshop participants will also be prompted to share their experiences in dealing with continuous enrollment issues.
 

Cost Study Methodology

W27: INTRODUCTION TO DECISION-THEORETIC NETWORKS FOR PHARMACOECONOMIC DECISION-MAKING
Salon C
DISCUSSION LEADERS: Gianluca Baio PhD, Research Fellow, University College London, London, United Kingdom; Jeroen P Jansen PhD, Project Manager, Mapi Values, Houten, Netherlands

Workshop Purpose: Participants will be introduced to Decision-Theoretic Networks, a methodology often used in several decision-making disciplines, but not yet in pharmacoeconomics. The workshop is intended to provide insight in the advantages of the use of such models in terms of understanding the problem, simplicity of representation, and power of analysis in cost-effectiveness evaluations.

Workshop Description: Cost-effectiveness evaluations or budget impact analysis represent a typical example of decision analysis problems, as they are performed for decision making regarding reimbursement of drugs or health care budget allocation under uncertainty. In contrast to traditional tools for decision making such as regression equations, decision trees and Markov models, Bayesian Belief Networks and Influence Diagrams have not been frequently used in pharmacoeconomics. In this workshop we aim to provide an introduction to these so called Decision-Theoretic Networks. A formal introductory background is followed by an example of a cost-effectiveness evaluation. Some advantages of decision-theoretic networks will be illustrated with the example: e.g. straightforward cost-effectiveness analysis for subgroups; and the possibility to combine expert prior opinion with empirical evidence in a very direct way. Furthermore, it will be shown how Influence Diagrams can be extended to incorporate parameter uncertainty and to perform probabilistic sensitivity analysis in a more efficient way. Participants will be encouraged to share their own assessment of its practical utility for decision-makers.
 

W28: DETERMINING EVENT PROBABILITIES FOR COST-EFFECTIVENESS ANALYSES FROM MODELING COUNT DATA
Salon D
DISCUSSION LEADERS: Quan V Doan, PharmD MSHS, Sr Associate Director, Cerner Health Insights, Beverly Hills, CA, USA; Zhimei Liu PhD, Sr Research Associate, Cerner Health Insights, Beverly Hills, CA, USA

Workshop Purpose: The purposes of this workshop are to discuss 1) the application of statistical models for analyzing count data and 2) the application of event rate information for determining probabilities in economic models.

Workshop Description: When performing a cost-effectiveness analysis, the probabilities of events are needed. In cases where count data over a certain period of follow-up time (or rates) are available, event probabilities can be converted from event rates. Modeling count data is important when events can occur more than once. Adjusted rates of events can be obtained through statistical modeling approaches such as the Poisson regression model. In SAS (Statistical Analysis Software), this is accomplished with the GENMOD procedure with an OFFSET option. This workshop presents a case study to illustrate the real-world application of the OFFSET option. The analytical process involves starting with a hypothesis, modifying the modeling strategy if results are counter-intuitive, and balancing between less and more advanced techniques with equal results. We demonstrate how misleading the results will be if the OFFSET option is not appropriately implemented. For example, treating the count or rate variable as the dependent variable without using the OFFSET option may lead to misleading conclusions. An analyst must keep in mind the conditions when the OFFSET option is appropriate. Audience participation will be solicited to discuss the advantages and disadvantages of this approach.


Health Care Policy Development

W29: VALUING HEALTH FOR REGULATORY CEA: RECOMMENDATIONS OF AN IOM COMMITTEE
Salon E&F
DISCUSSION LEADERS: Dennis G Fryback PhD, Professor, University of Wisconsin - Madison, Madison, WI, USA;
Milton C. Weinstein PhD, Principal Consultant, i3 Innovus; Professor, Harvard School of Public Health and Harvard Medical School, Boston, MA, USA

Workshop Purpose: The purpose is to introduce the findings and recommendations of the IOM committee on regulatory cost-effectiveness analysis to the medical outcomes and pharmacoeconomic research community, and to engage in a dialogue on how best to accomplish the research priorities outlined in the committee's report.

Workshop Description: In 2003, the Office of Management and Budget (OMB) instituted a new requirement: Federal agencies must supplement benefit–cost analysis with cost-effectiveness analysis for economically significant health and safety regulations. OMB then commissioned a study from an Institute of Medicine consensus committee to recommend best practices for regulatory agencies conducting CEAs. Valuing Health for Regulatory Cost-Effectiveness Analysis, the report of the IOM committee released January 2006, makes recommendations in four areas: Selecting an integrated measure of effectiveness appropriate for regulatory health endpoints; Constructing and reporting cost-effectiveness ratios; Presenting information needed for making regulatory choices and decisions; and Data and research needs to improve health-related quality of life measurement and regulatory CEAs. While the report addresses the use of CEA in the context of regulatory analysis, the IOM committee's recommendations have implications for other applications of CEA. The report offers a current review and evaluation of alternative health-adjusted life year metrics, and of several generic indexes commonly used to estimate QALYs. It identifies sources for existing health state index values for regulatory analysis, and offers algorithms for choosing among sources for such values. The workshop leaders will present an overview of the report for medical outcomes and pharmacoeconomic researchers. The ethical implications of various effectiveness measures, and of QALYs in particular, are reviewed in the report and also will be discussed in the workshop. After briefly reviewing the data and research priorities outlined in the report, the discussion leaders will engage in a dialogue with the participants regarding challenges, opportunities and approaches to meeting requirements set forth in the report.
 

W30: UTILIZATION OF RETROSPECTIVE DATABASES TO INFORM EVIDENCE BASED DRUG POLICY MAKING
Liberty A
DISCUSSION LEADERS: Christian A Gericke MD, MPH, MSc, Senior Research Fellow in Health Care Management, Berlin University of Technology, Berlin, Germany; Elaine Morrato MPH, Outcomes Research Fellow, Johns Hopkins University, Baltimore, MD, USA; Marya Zilberberg MD, FCCP, Regional Associate Director Outcomes Research, Ortho Biotech Clinical Affairs, LLC, Bridgewater, NJ, USA

Workshop Purpose: The objectives of this workshop are to introduce the concept of using retrospective databases for drug licensing and reimbursement policy decision making and to present case studies from Europe and North America where the use of retrospective databases has had a substantial impact on health policy making.

Workshop Description: While efficacy refers to how a therapy performs in a well-defined clinical setting under highly controlled circumstances, policy is designed for broad real-world utilization, where the concept of effectiveness in routine care is much more applicable. Currently the licensing and reimbursement of drugs and other medical technologies relies primarily on efficacy data derived from randomized clinical trials (RCT). However, effectiveness data from retrospective databases take into consideration such factors as patient and practice variations, and present a much more generalizable picture. There are a plethora of data sources, prospectively collected, which may be better suited to answer the questions of policy than a typical phase III RCT. Questions such as what is the economic burden of a particular illness, how does one drug compare to another in a particular class, are there any emerging safety signals associated with a newly-approved therapy, and the like, can be answered promptly and inexpensively, and in real time, given the appropriate methodology, with a well targeted secondary, or retrospective, analysis of such an existing database. The robustness of such an approach lies in the application of valid epidemiologic analytic methodologies to what is usually a much larger sample size than that seen in an RCT. The workshop will firstly introduce participants to current uses of retrospective drug databases for real-world policy decisions and secondly provide an analysis of a number of influential policy decisions in selected European and North American countries for which analyses of retrospective databases have been of prime importance. In the participant discussion, the focus will be on how to develop retrospective database research further to better inform policy decision-making.

W31: POWERFUL DATA, MEANINGFUL ANSWERS: AN INTRODUCTION TO THE HEALTHCARE COST & UTILIZATION PROJECT AND APPLICATIONS FOR CEA, COI, AND HEALTH POLICY RESEARCH STUDIES
Liberty C
DISCUSSION LEADERS: Tom Brady PhD, Lead Health Services Researcher, Medstat, Washington, D.C, USA;
Allison Russo MPH, Lead Health Services Researcher, Medstat, Washington, D.C, USA

Workshop Purpose: Learning Objectives: This workshop will provide an introduction to the Healthcare Cost and Utilization Project (HCUP) databases and products, with an emphasis on how HCUP may help facilitate cost-effectiveness analyses, cost-of-illness studies, and health care policy research. During this interactive session, participants will: (1) learn about the family of HCUP data, tools, and products; (2) review CEA, COI, and health policy research examples/projects using HCUP databases to illustrate the diversity and breadth of research that these data can support; (3) discuss research ideas and how they could be investigated using HCUP data.

Workshop Description: This workshop will provide an introduction to the Healthcare Cost and Utilization Project (HCUP) databases and products, with an emphasis on how HCUP may help facilitate cost-effectiveness analyses, cost-of-illness studies, and health care policy research. HCUP is a family of health care databases and related software tools, support services, and products created through a Federal-State-Industry partnership and sponsored by the U.S. Department of Health and Human Services (DHHS), Agency for Healthcare Research and Quality (AHRQ). HCUP has the largest collection of longitudinal, all-payer, encounter-level data that is publicly available. Current databases include comprehensive statewide inpatient, ambulatory surgery, and emergency department data. Two additional databases foster national estimates of hospital care for all patients and for children. The workshop will begin with a brief introduction of HCUP databases, software tools, and products. Particular emphasize will be given to products of greatest interest to the ISPOR audience, such as the cost-to-charge ratio algorithm – a method that converts charges to costs—and HCUPnet – the free online query system that provides instant access to aggregated statistics from HCUP databases. After this introduction, the workshop will review CEA, COI, and health policy research examples that use HCUP databases to illustrate the diversity and breadth of research that these data can support. The workshop concludes with an open discussion about research ideas and how they could be investigated using HCUP data. In addition, session participants will also receive a CD containing valuable resources that expand on topics covered in the session—data file descriptions, research examples that use HCUP data, information on how to access documentation, and instructions on how to obtain HCUP products.

QoL/PRO Methodology Issues

W32: VALIDATING COMPUTERIZED QUALITY OF LIFE MEASURES FOR USE IN CLINICAL TRIALS
Room 401
DISCUSSION LEADERS: Chad J. Gwaltney PhD, Assistant Professor, Brown University, Providence, RI, USA;
Paul C. Beatty PhD, Research Scientist, National Center for Health Statistics, Hyattsville, MD, USA; Brian Tiplady PhD, Senior Clinical Scientist, Invivodata, Inc, Edinburgh, United Kingdom

Workshop Purpose: The purpose of this workshop is to help participants better understand issues and apply established methods involved in validating computerized versions of paper and pencil quality of life assessments.

Workshop Description: Using computers to collect quality of life (QOL) data in clinical trials can increase patient compliance and satisfaction, as well as decrease the amount of time spent on data management and entry. Accordingly, clinical drug trials are increasingly using computers to collect quality of life data. However, there is some concern that transferring a validated paper questionnaire to computer may involve changes that could influence the performance of the measure. Additionally, computer measures require the patient to navigate through the questionnaire in a different way (e.g., using push-buttons to move from screen to screen), which could influence the measure. In this workshop, we will (a) review the literature on the equivalence of computerized and pencil-and-paper QOL measures, (b) discuss user interface features that may cause computerized measures to perform differently from their paper counterparts, and (c) outline steps involved in cognitive interviewing, a method that can be used to ensure that patients comprehend the items and response options used in computerized measures in the intended manner. Participants will be encouraged to ask questions during the presentations, in order to stimulate discussion. Participants will also review an applied example of cognitive interviewing, in order to gain a better understanding of how this technique is applied in a cognitive laboratory.