Online Program
Wed, Jan 20 |
||
WK1 Bayesian Adaptive Methods for Clinical Trials |
8:30 AM - 5:15 PM
|
|
Overview: Thanks in large part to the rapid development of Markov chain Monte Carlo (MCMC) methods and software for their implementation; Bayesian methods have become ubiquitous in modern biostatistical analysis. In submissions to the U.S. FDA Center for Devices and Radiological Health, where data on new devices are often scanty but researchers typically have access to large historical databases, Bayesian methods have been in common use for over a decade and in fact were the subject of a recently-released FDA guidance document. Statisticians in earlier phases (especially Phase I oncology trials) have long appreciated Bayes' ability to get good answers quickly. Moreover, an increasing desire for adaptability in clinical trials (to react to trial knowledge as it accumulates) has also led to heightened interest in Bayesian methods. Objective: This full-day workshop (4 consecutive sessions) introduces Bayesian methods, computing, and software, and then goes on to elucidate their use in Phase I, II, and III trials. We include descriptions of how the methods can be implemented in WinBUGS, R, and BRugs, the version of the BUGS package callable from within R. In particular, we will illustrate the different ways a Bayesian might think about power when designing a trial, and how a Bayesian procedure may e calibrated to guarantee good long-run frequentist performance (i.e., low Type I and II error rates), a subject of keen interest to the FDA. Session 1 (8:30 am - 10:15 am): Introduction to Hierarchical Bayes Methods and Computing Bayesian inference: point and interval estimation, model choice Bayesian computing: MCMC methods; Gibbs sampler; Metropolis-Hastings algorithm Hierarchical modeling and metaanalysis Principles of Bayesian clinical trial design: predictive probability, indifference zone, Bayesian and frequentist operating characteristics (power, Type I error) Session 2 (10:30 am – 12:15 pm): Bayesian design and analysis for Phase I studies Rule-based designs for determining the MTD (e.g., 3+3) " Model-based designs for determining the MTD (CRM, EWOC, TITE monitoring, toxicity intervals) " Dose ranging and optimal biologic dosing Efficacy and toxicity Examples and software Session 3 (1:30 pm – 3:15 pm): Bayesian design and analysis for Phase II studies Standard designs: Phase IIA (single-arm) vs. Phase IIB (multi-arm) Predictive Probability-based methods Sequential stopping: for futility, efficacy Multi-arm designs with adaptive dose allocation Hierarchical Phase II models and examples Decision theoretic methods Session 4 (3:30 pm – 5:15 pm): Bayesian design and analysis for Phase III studies Confirmatory trials Adaptive confirmatory trials: adaptive sample size, futility analysis, arm dropping Modeling and prediction Examples from FDA-regulated trials Seamless Phase II-III trials Multiplicity and Subset Analysis Summary and Floor Discussion |
||
8:30 AM |
Bayesian Adaptive Methods for Clinical Trials
|
|
WK2 Estimating Treatment Effects Using Longitudinal Observational Data |
8:30 AM - 10:15 AM
|
|
Organizer(s): Douglas E. Faries, Eli Lilly & Co. |
||
Objectives: To educate participants and demonstrate the implementation of techniques for the assessment of causal treatment effects in longitudinal observational data. To educate and demonstrate implementation of newer local control and trajectory analysis techniques applied to assessing treatment effects in observational data. Summary: The availability and use of data from electronic medical records, claims databases, registries and other observational studies in medical research is increasing. However, assessing the causal effects of treatment in such naturalistic (observational) data requires strong assumptions and careful adjustment of potential biases. Assessing longitudinal observational data is even more complex, due to the potential for medication changes and time-varying confounding factors. In this workshop we will first discuss the value and demonstrate the implementation of newer techniques of assessing causal treatment effects in longitudinal observational data - such as marginal structural models (MSMs) and structural nested models. Advantages, assumptions, and disadvantages of the various approaches will be examined. For instance, MSMs utilize longitudinal inverse weighting to produce a confounder balanced pseudopopulation to allow for causal treatment comparisons. Secondly, we will introduce and demonstrate the use of local control techniques and trajectory analysis approaches for the assessment of treatment effects in longitudinal data. For instance, using high dimensional clustering one can obtain a counterfactual treatment difference estimate for each patient which can then be used within more common data mining methods to identify groups with differential treatment effects. In both presentations, the goal will be to provide a practical educational experience - where implementation issues are discussed and presented along with the theoretical basis for the approaches |
||
Estimating Treatment Effects Using Longitudinal Observational Data
|
||
WK3 Reducing the Impact of Selection Bias with Propensity Scores |
10:30 AM - 12:15 PM
|
|
This intermediate-level workshop describes and demonstrates effective strategies for using propensity score methods to address the potential for selection bias in observational studies comparing exposures. We will review main analytical techniques associated with propensity score methods (multivariable adjustment, matching and stratification using the propensity score, sensitivity analysis) and describe key strategic concerns related to effective estimation of the propensity score, assessment and display of covariate balance, choice of analytic technique, sensitivity analyses for matched samples, and communicating results effectively to nonstatisticians. We also will review the literature regarding recent methodological advances in propensity scores and application of propensity score methods to problems in health policy research. Attendees will receive detailed handouts. |
||
10:30 AM |
Reducing the Impact of Selection Bias with Propensity Scores
|
|
WK4 Microsimulation Modeling |
1:30 PM - 3:15 PM
|
|
Microsimulation models are characterized by simulation of individual event histories for an idealized population or cohort of interest. This workshop will present current uses of microsimulation models, including estimation of cost effectiveness and population effects of cancer screening intervention, though the focus will be on population-based microsimulation of cancer incidence and mortality. We will briefly review the key aspects of microsimulation modeling: model building, parameter calibration, model validation, and model application and interpretation |
||
1:30 PM |
Microsimulation Modeling
|
|
WK5 Cluster Randomized Trials in Health Policy Research |
3:30 PM - 5:15 PM
|
|
Electronic medical records (EMRs) with sophisticated clinical decision support (CDS) functions are increasingly common in health systems that have affiliated clinical practice sites. Cluster-randomized trials (CRTs) of different approaches to CDS are facilitated by EMRs in these systems by enabling identification of patients and problem areas that might benefit from CDS; providing rich clinical data for a priori balancing of practices on important characteristics before allocating practice clusters to intervention groups; and providing platforms for developing different types of CDSs, such as for patients or for providers. Course leaders will illustrate key points by highlighting an AHRQ-support CRT of CDS in diabetes across two organizations and 24 practice sites, and a small-group interactive task completed during the session will motivate the presentation |
||
3:30 PM |
Cluster Randomized Trials in Health Policy Research
|
|
PS-1 Poster Presentation: International Health Policy |
6:00 PM - 8:30 PM
|
|
|
||
Costing Study of Health Services Items for National Health Insurance Scheme Establishment in China.
|
||
Pro-Poor Health Policy in Nepal: Enlarging People's Choices
|
||
Addressing Malaria Morbidity and Mortality Through International Health Policy
|
||
Establishing a Reporting Framework for Health Information for the Council of Australian Governments
|
||
The Effects of Environmental Factors on Cancer Prevalence Rates and Specific Cancer Mortality Rates in a Sample of OECD Developed Countries
|
||
PS-2 Poster Presentation: US Health Policy and Community-Based Research |
6:00 PM - 8:30 PM
|
|
|
||
A New Linking Approach for Patient Medical Records in a Community Health Setting
|
||
Physical Therapy in Home Health Care: Modeling Eligibility and Estimating Effectiveness
|
||
An Approach to Obtain a More Complete Picture About Access to Medical Care by U.S. Patient Groups
|
||
A Community Based Intervention for Hypertension Implement by a Physician Hospital Organization
|
||
Do Current Surveillance Systems Provide Valid and Credible Statistical Information on 2009-H1N1?
|
||
Methods for Determing Viral Transmission in New York City (NYC) Schools During a Novel H1N1 Influenza Outbreak
|
||
PS-3 Poster Presentation: Health Services Research |
6:00 PM - 8:30 PM
|
|
|
||
Associations Between Health Insurance Status and Periodontal Disease Progression Among Gullah African Americans with Type 2 Diabetes After Adjustments for Glycemic Control and Other Covariates
|
||
Patterns of Consent: Linking Longitudinal Health Survey and Social Security Administration Records
|
||
Individual Insurance and Access to Care
|
||
The Impact of Occupational Injury on the Health of Family Members of Injured Workers
|
||
Detours on the Road to a Correct Diagnosis: The Role of Clinical Certainty
|
||
Comparing Expanded Criteria Donor (ECD) Transplant and Waitlist Survival Using Novel Two-Stage Estimation Methods
|
||
Trigger Events for High Spenders with Functional Limitations and Chronic Conditions
|
||
Economic and Atmospheric Conditions Related to Emergency Department Visits
|
||
Comparative Effectiveness of Communication Strategies for Medicare Beneficiaries
|
||
Dynamic Model of Human Mortality for Analyzes of Longitudinal Data on Aging, Health, and Longevity
|
||
Childhood Obesity, Physical Fitness and Educational Outcomes: The Use of a Large, Complex Administrative Data System to Inform Public Health and Education Policy.
|
||
PS-4 Poster Presentation: Methods |
6:00 PM - 8:30 PM
|
|
|
||
A Bayesian Approach to Variation Assessment of Clinical Outcomes Among Hospitals
|
||
High Dimension Multiple Imputation: Missing Blood Glucose Values in the Epidemiology of Diabetes Interventions and Complications Study
|
||
Transitioning to R with Health Policy Data
|
||
The Impact of Missing Data on Estimation of Health-Related Quality of Life Outcomes in a Longitudinal Clinical Trial
|
||
Evaluate the Medical Performance Using a New Semiparametric Regression Approach of Time-Dependent ROC Curve
|
||
An Extended Proportional Odds Model with Time-Varying Covariates
|
||
Funnel Plots as a Vehicle for Policy Relevant Analysis: Gaining Focus
|
||
Identification and Prediction of High Risk Complications of Asthmatic Conditions
|
||
Informing the Design of Host-Pathogen Interaction Studies When Infectious Disease Clinical Research Participants Consent to Use of Their Clinical Specimens and Electronic Health Records
|
||
Interval Estimation of Some Measures of Association for Epidemiological Data Sampled from Clusters: a Review and an Extension
|
||
Modeling Intraclass Correlation in Cluster-Randomized Trials with Binary Outcomes
|
||
Modeling Multiple Categorical Measurements Using Linear Latent Structure Analysis
|
||
Thu, Jan 21 |
||
Introduction/Welcome, HPSS Awards, Plenary Speech |
8:30 AM - 10:00 AM
|
|
|
||
C-1 Applications Using Matching Techniques |
10:30 AM - 12:15 PM
|
|
Chair(s): Somya Rao, Partners Healthcare |
||
|
||
10:35 AM |
Teen Sex and Propensity Score Matching: Will the Media Report Both? a Case Study
|
|
10:55 AM |
Entire Matching and Its Application in an Observational Study of Treatment for Melanoma
|
|
11:15 AM |
Calibrated Propensity Scores for Comparative Effectiveness Estimates with Disease Subject to Misclassification
|
|
11:35 AM |
Assessing the Robustness of Combining Propensity Theory and Methods to Assess the Impact of Unmeasured Confounders on the Estimation of Causal Effects
|
|
11:55 AM |
What to Do About Observational Studies
|
|
INV1 Incorporating Adaptive/Dynamic Treatment Strategies in Clinical Trial Designs |
10:30 AM - 12:15 PM
|
|
Organizer(s): Anirban Basu, University of Chicago |
||
Chair(s): Anirban Basu, University of Chicago |
||
|
||
10:35 AM |
An Introduction to Dynamic Treatment Regimes
|
|
11:05 AM |
Constructing Dynamic Treatment Regimes Using STAR*D and CATIE
|
|
11:35 AM |
Reinforcement Learning Strategies for Clinical Trials in Non-Small Cell Lung Cancer
|
|
12:05 PM |
||
INV2 Statistical Issues in Drug Safety |
10:30 AM - 12:15 PM
|
|
Organizer(s): Robert Gibbons, University of Illinois at Chicago |
||
Chair(s): Mary Beth Landrum, Harvard Medical School Department of Health Care Policy |
||
|
||
10:35 AM |
Meta-Analysis and Medical Technology Safety
|
|
11:05 AM |
Studying Drug Safety: From RCTs to OCER
|
|
11:35 AM |
Post-Approval Drug Safety Surveillance
|
|
12:05 PM |
||
TC1 Quantitative Models for Health Care Reform |
10:30 AM - 12:15 PM
|
|
Organizer(s): Arlene Ash, Umass Medical School |
||
Chair(s): Trena Ezzati-Rice, Agency for Healhcare Research and Quality |
||
Establishing a healthy “market” for health care services requires being able to recognize and pay for “value” in health care. The provision of many well-conducted, inexpensive care-giving episodes (a provider-centric measure of quality) is fully compatible with poor quality, expensive care for populations. These talks explore how researchers are working to develop alternative ways to identify and reward health care quality and value. |
||
10:35 AM |
The Role of Mathematical Modeling in Health Care Reform
|
|
10:55 AM |
Bundled Payments to Primary Care Physicians Using a Risk-Adjusted Primary Care Activity Level (PCAL) Model
|
|
11:15 AM |
Using Flexibility-Based Weights to Calculate a Composite Measure of Quality
|
|
11:35 AM |
Examining Post-Hospital Care Coordination by Its Outcomes: How Should We Measure Hospital Readmissions, ED Visits, and Timely EandM Service Use
|
|
C-2 Innovations in Statstical Modeling of Health Outcomes - Part I |
1:30 PM - 3:15 PM
|
|
Chair(s): Meena Khare, CDC/NCHS |
||
|
||
1:30 PM |
Bayesian and Frequentist Methods for Provider Profiling Using Risk-Adjusted Assessments of Medical Outcomes
|
|
1:50 PM |
Regression Tree Boosting to Adjust Health Care Cost Predictions for Diagnostic Mix
|
|
2:10 PM |
A Bayesian Two-Part Latent Class Model for Longitudinal Medical Expenditure Data
|
|
2:30 PM |
Using Latent Variable Modeling and Multiple Imputation to Calibrate Rater Bias: Application to a Diagnosis of Posttraumatic Stress Disorder
|
|
2:50 PM |
A Multi-Level Two-Part Random Effects Model, with Application to an Alcohol Dependence Study
|
|
C-3 Healthcare Quality |
1:30 PM - 3:15 PM
|
|
Chair(s): Alyce Sophia Adams, Kaiser Permanente Division of Research |
||
|
||
1:30 PM |
Is Higher Hospital System Spending Intensity Associated with better Acute Care Outcomes?
|
|
1:50 PM |
Random Coefficients Models for Subgroup Differences in Surveys of Health Care Quality
|
|
2:10 PM |
Novel Bayesian Multivariate Hierarchical Models of Random Coefficients of Casemix Adjustment Variables in a Survey Assessing Healthcare Experiences
|
|
2:30 PM |
Do Minimum Quality Standards Improve Quality? a Case Study of the Nursing Home Industry
|
|
2:50 PM |
Are Physicians Closing Their Doors to Medicare? Trends and Patterns in the Provision of Physician Services to Medicare Patients.
|
|
INV3 Multiple-Treatment Meta-Analysis for Promoting Comparative Effectiveness Research |
1:30 PM - 3:15 PM
|
|
Organizer(s): Christopher Schmid, Tufts Medical Center |
||
Chair(s): Joseph C Cappelleri, Pfizer Inc |
||
|
||
1:30 PM |
How Multiple-Treatments Meta-Analysis Can Challenge and Advance the Existing Clinical Evidence
|
|
1:55 PM |
Comparative Effectiveness Research: Finding the Best Evidence to Answer
|
|
2:20 PM |
Multi-Treatment Meta-Analysis for Categorical Outcomes
|
|
2:45 PM |
The Use of Multiple Treatment Comparisons in Health Technology Assessment
|
|
INV4 Beyond Simple Randomized Trials: Health Services Research Within the VA Healthcare System |
1:30 PM - 3:15 PM
|
|
Organizer(s): Roslyn A. Stone, University of Pittsburgh; Center for Health Equity Research and Promotion |
||
Chair(s): Roslyn A. Stone, University of Pittsburgh; Center for Health Equity Research and Promotion |
||
|
||
1:30 PM |
The Use of Antipsychotics in Veterans with Dementia: Did the Black Box Warnings Have Any Impact?
|
|
1:55 PM |
Causal Inference in Randomized Encouragement Design Studies with Non-Compliance and Non-Ignorable Missing Outcomes
|
|
2:20 PM |
Adaptive Designs in Substance Abuse Research, with Applications to VA and Non-VA Research
|
|
2:45 PM |
Multi-Level Modeling (And Thinking) in the Development and Validation of Health Care Quality Measures for Substance Abuse Disorder Treatment
|
|
3:10 PM |
Discussant: Challenges in the Design of Health Services Research Studies
|
|
C-4 Innovations in Statistical Modeling of Health Outcomes - Part II |
3:30 PM - 5:15 PM
|
|
Chair(s): Lisa M. Lix, School of Public Health, University of Saskatchewan |
||
|
||
3:30 PM |
Confidence Interval Estimates of Impact Numbers for a Cross-Sectional Sampling Scheme
|
|
3:45 PM |
On an Application of Structural Equation for Modeling of Health Index
|
|
4:00 PM |
Estimation of Osteoporosis Prevalence Over Time from Two Incomplete Data Sources Using Capture-Recapture Techniques
|
|
4:15 PM |
Functional Networks as a Novel Data Mining Scheme for Prediction of Healthcare Outcomes: a Comparative Study with Many Popular Statistical\Data Mining Procedures
|
|
4:30 PM |
Terminal Behavior of Recurrent Marker Processes
|
|
4:50 PM |
A Method to Assess Uncertainty in System-Level Performance Evaluation Measures and Statistical Benchmarks
|
|
5:00 PM |
||
INV5 Novel Methods for Using Decision Models in Economic Evaluation and Research Priority Setting in Health Care |
3:30 PM - 5:15 PM
|
|
Organizer(s): Anirban Basu, University of Chicago |
||
Chair(s): Anirban Basu, University of Chicago |
||
|
||
3:30 PM |
Integration of Meta-Analysis and Economic Decision Modeling for Evaluating Diagnostic Tests
|
|
4:00 PM |
The Value of Information in Benefit-Risk Analysis for Regulatory Approval
|
|
4:30 PM |
Applications of Decision Modeling to Assess the Value of Clinical Research
|
|
INV6 The Magic with Missing Data Methods: Is There More to the Prestige? |
3:30 PM - 5:15 PM
|
|
Organizer(s): Recai M. Yucel, University of Albany |
||
Chair(s): Recai M. Yucel, University of Albany |
||
|
||
3:30 PM |
What Happens When Imputation Model and Analysis Procedure Are Uncongenial?
|
|
4:00 PM |
Posterior Predictive Checking of Imputation Models
|
|
4:30 PM |
Incomplete Data: Analysis and Sensitivity Analysis
|
|
5:00 PM |
Discussant: Joseph Schafer, the Pennsylvania State University
|
|
Discussant(s): Joseph L Schafer, The Pennsylvania State University |
||
TC2 Modern Methods in Health Disparities Research |
3:30 PM - 6:00 PM
|
|
Organizer(s): Amelia M Haviland, RAND Corporation |
||
Chair(s): Zhiwei Zhang, NORC at the University of Chicago |
||
This session describes a range of statistical tools applicable to health disparities research, particularly disparities by race/ethnicity and socioeconomic status. The first two speakers discuss methods relevant to coping with less than ideal data: one due to a lack of race/ethnicity information and the second due to small sample sizes for demographic groups of interest in repeated cross-sectional data. The next two speakers discuss techniques for investigating the reasons behind observed disparities – either through experimental design or hierarchical modeling and multiple data sources. The final speaker applies multiple techniques to assess the robustness of disparity estimates. The methods employed include Kalman filters, Bayesian methods, drawing on multiple data sources, vignette studies, and tests for sensitivity to unmeasured confounders. |
||
3:30 PM |
Using Administrative Data to Identify Spanish-Preferring Seniors
|
|
4:10 PM |
Improving Health Outcome Estimates in Small Populations: a Smoothing Across Time in Repeated Cross-Sectional Data
|
|
4:30 PM |
Using Standardized Encounters to Understand Disparities in Patient Experiences
|
|
4:50 PM |
Disparities in Immunization Rates for Seniors by Hispanic Ethnicity and Spanish-Language Preference
|
|
5:10 PM |
How Robust Is the Association Between Neighborhood Socioeconomic Status and Coronary Heart Disease Among Women?
|
|
Fri, Jan 22 |
||
C-5 Estimating Treatment Effects |
8:30 AM - 10:15 AM
|
|
Chair(s): James O'Malley, Harvard Medical School |
||
|
||
8:35 AM |
Estimating Treatment Effects in a Principal Stratification Framework When Treatment Received Depends on a Key Covariate
|
|
8:55 AM |
Estimating Treatment Effects in Longitudinal Surgical Clinical Trials with Partial Compliance Affecting Both Treatment Arms
|
|
9:15 AM |
A Strategy to Identify Differential Treatment Effects Based on Recursive Partitioning Methods
|
|
9:35 AM |
Near/Far Matching: a Nonparametric Instrumental Variable Technique for Binary Outcomes
|
|
9:55 AM |
What Can Experiments Tell Us About Clinical Decision Making?
|
|
C-6 Health Services Research |
8:30 AM - 10:15 AM
|
|
Chair(s): Ya-Shen Tina Shih, M.D. Anderson Cancer Center |
||
|
||
8:35 AM |
Risk Estimation for the Next Generation of Cervical Cancer Screening Programs
|
|
8:50 AM |
Statistics and Substance Abuse Policy
|
|
9:10 AM |
A Unifying Framework for Assessing Changes in Life Expectancy Associated with Changes in Mortality: The Case of Violent Deaths
|
|
9:25 AM |
Statistical Considerations for Patient-Reported Outcomes
|
|
9:40 AM |
Impact of Prior Authorization on Quality, Cost and Outcomes Among Adults with Mental Illness in Medicaid
|
|
9:55 AM |
Mental Disorders and Employment Status in VA Patients
|
|
INV7 Modeling Efforts to Inform Healthcare Initiatives and Policy |
8:30 AM - 10:15 AM
|
|
Organizer(s): Steven B. Cohen, Agency for Healthcare Research and Quality |
||
Chair(s): Marc N Elliott, RAND Corporation |
||
|
||
8:35 AM |
Issues of Data Capacity and Statistical Quality to Support Health Care Modeling and Microsimulation Efforts
|
|
9:05 AM |
Using the COMPARE Microsimulation Model to Evaluate Health Reform Legislation: Challenges and Contributions
|
|
9:35 AM |
The Health Insurance Policy Simulation Model and Its Applications
|
|
10:05 AM |
Discussant: Michael L. Cohen, Committee on National Statistics, National Academy of Sciences
|
|
INV8 Data Confidentiality: Do We Really Want to Disturb a Sleeping Bear? |
8:30 AM - 10:15 AM
|
|
Organizer(s): Ofer Harel, University of Connecticut |
||
Chair(s): Juned Siddique, Northwestern University |
||
|
||
8:35 AM |
Using Multiple Imputation to Protect Participants' Confidentiality When Sharing Data
|
|
9:05 AM |
Pinning Down "Privacy" in Statistical Databases
|
|
9:35 AM |
Assessing Privacy Using the Area Under the Receiver-Operator Characteristic Curve
|
|
10:05 AM |
Discussant: Robert Aseltine, University of Connecticut Health Center
|
|
Special Panel Discussion: Putting the Research into Comparative Effectiveness Research |
10:15 AM - 12:15 PM
|
|
Organizer(s): Therese Stukel, Institute for Clinical Evaluative Sciences |
||
Health care systems worldwide grapple with the need to offer the best healthcare to all citizens at an affordable price. Development of rigorous methods and well-defined metrics to measure and compare the outcomes and costs of competing interventions and policies remain the core of health policy statistics. This panel comprising representatives of three different health care systems – American, Canadian and British – will discuss the contributions of methods research to the health policy debate and the knowledge gaps whose solution could most inform the public debate. |
||
10:15 AM |
Putting the Research into Comparative Effectiveness Research
|
|
WK6 The Medical Expenditure Panel Survey (MEPS): a National Data Resource to Inform Health Policy |
1:45 PM - 3:30 PM
|
|
Statement of Purpose and Institute Overview:The purpose of this Workshop is to facilitate the use of the Medical Expenditure Panel Survey Household Component (MEPS HC) public use data files by the health services research community. To meet this objective participants are provided with a general overview of the MEPS, a description of available data files, information about on-line data tools, and some examples of the type of research projects the MEPS data can support. In addition, attendees will be introduced to other Agency for Healthcare Research and Quality data sets such as the Healthcare Cost and Utilization Project (HCUP) and the Consumer Assessment of Healthcare Providers and Systems (CAHPS). Major changes have taken place in the Nation's health care delivery system over the last decade. The most notable is the rapid expansion of managed care arrangements such as health maintenance organizations, preferred provider organizations, and other provider networks that seek to minimize increases in health care costs. The MEPS is a vital national data resource designed to continually provide health service researchers, policymakers, health care administrators, businesses, and others with timely, comprehensive information about health care use and costs in the United States. Newly released MEPS public use files provide analysts with opportunities to create unique analytic files for policy relevant analysis in the field of health services research, such as access to care and health disparities. In order to capture the unparalleled scope and detail of the MEPS HC, analysts need to understand the complexities of MEPS data files and data file linkages. This workshop will provide the knowledge necessary to formulate research plans utilizing the various MEPS HC files and linkage capabilities |
||
1:45 PM |
The Medical Expenditure Panel Survey (MEPS): a National Data Resource to Inform Health Policy
|
|