The ISPOR BOOK:
Reliability and Validity of Data Sources for Disease and Health Management:

Section 4: Alternative Population-based Data Sources

Appendix 1
Section 4 Outline and Authors

1. Section 4 Outline & Authors
1. Introduction (Kristen Migliaccio-Walle)
1. Brief recap / summary of sources reviewed in Sections 1 – 3
2. What needs these fill
3. What needs / opportunities might be filled by other sources
4. Identification of alternate or non-traditional sources
2. Survey Data Sources from the National Center for Health Statistics (NCHS) and the Agency for Healthcare Research and Quality (AHRQ) (Jayashri Sankaranarayanan & Mariam Hassan) (Assuming Section 1 is covering HCUP; we will focus on the following)
1. Introduction to national survey databases from NCHS and AHRQ
1. What is NCHS
1. NCHS databases – With medication information (NAMCS, NHAMCS, others) and without medication information (NHIS, others): Description, Purpose, Use, Outcomes, Strengths and limitations (in Table format)
2. What is AHRQ?
1. AHRQ databases – With medication information (MEPS- household, nursing components): Description, Purpose, Use, Outcomes, Strengths and limitations (in Table format)
2. Discussion, Summary and Conclusions - How to use health survey evidence in disease management and health care decision-making?
3. Healthcare Cost and Utilization Project (HCUP) (Frank Ernst)
4. Medicare Databases (Tammy Curtice & Renee Arnold)
1. Introduction
1. Medicare description and history (depending on Ch. 1 content)
2. Types of Medicare data available
2. Medicare coordination of benefits (COB) data
1. Hospital data
1. Hospital cost reports
2. Hospital claims
2. Provider data
3. Medicare supplemental data
1. Medigap
2. Employer sponsored data
1. How employer paid data are captured
2. Description of population covered
3. Type of data included
4. Ways to access supplemental data
4. Suggestions for use of Medicare databases in health and disease management
5. Issues with Medicare databases for health and disease management
1. Access to various Medicaid databases
2. Gaps in Medicare databases
3. Other limitations


5. Veterans Healthcare Administration (VHA) (Mariam Hassan & Dennis Raisch)
1. Introduction
1. VA Health Care system
2. VA population
2. VA Data resources
1. National Databases
1. Hospital Data or Patient Treatment File
2. Outpatient Data or Outpatient Clinic File
3. Pharmacy Benefits Management
4. Vital Status File
2. Local Databases
1. Veterans health Information Systems & Technology Architecture (VISTA)
3. Other VA Databases
3. Utility of VA Databases in Disease and Health Management
1. How to access the data
2. How data can be linked
3. What variables are available
4. What are possible research questions and uses in healthcare decision making
4. Strengths and Limitations
6. Department of Defense (DOD) (Chris Blanchette)
7. Patient Registries (Jayashri Sankaranarayanan, William Crown and Teresa L Hartman, MLS)
1. Introduction – Definition, History and purpose
2. Types and common occurrences (in Table format too) in US and worldwide
1. Product–specific - Definition, Examples, sponsors, features, strengths and limitations for researchers/practitioners
2. Disease–specific - Definition, Examples, sponsors, features, strengths and limitations for researchers/practitioners
3. Health Service Registry
4. Federal registries - Definition, Examples, sponsors, features, strengths and limitations for researchers/practitioners
5. State registries - Definition, Examples, sponsors, features, strengths and limitations for researchers/practitioners
6. Specialist / Expert Investigator initiated registries - Examples, sponsors, strengths and limitations (e.g. COPD/smokers database by Hans Petersen etc.)
3. Discussion, Summary and Conclusions - How to use national survey evidence in disease management and health care decision-making? What improvements are needed?


8. Clinical Trial Data (Mariam Hassan & Jayashri Sankaranarayanan)
1. Introduction
2. Description of economics and outcomes data from clinical trials
1. Data type and source
1. Costs and resource utilization
2. Patient outcomes
3. Valuing resources and outcomes
2. Considerations in measurement (trial design, perspective, etc.)
3. Validity and reliability of data
3. Use of clinical trial data in health and disease management
1. Evaluations
2. PRO claims, etc.
3. Importance to healthcare decision maker
4. Strengths and limitations
9. Genomic Databases (Chris Frei)
1. Introduce (or review) the concept of “genome-directed therapeutics”
2. Name diseases where genome-based therapies have emerged
3. Describe currently available genomics databases (including COPD/smoker’s)
1. List the available data fields
2. Outline the steps required to access & utilize these data
4. Review national and international initiatives to develop genomic databases (including possible funding sources)
5. Comment on the potential applicability of current and future genomic databases for disease and health management
10. Observational & Naturalistic Studies (Krista Payne)
1. EMR, chart-review, time and motion studies



Appendix 2
Chapter Introduction Paragraphs

 

1. Introduction (Kristen Migliaccio-Walle)


2. Survey Data Sources from the National Center for Health Statistics (NCHS) and the Agency for Healthcare Research and Quality (AHRQ) (Jayashri Sankaranarayanan & Mariam Hassan)

   This chapter will provide an overview, description, purpose, strengths and limitations of the use of evidence from publicly available national survey databases from the National Center for Health Statistics (NCHS) and the Agency for Healthcare Research and Quality (AHRQ) in disease management and in the making and delivery of health care decisions.

3. Healthcare Cost and Utilization Project (HCUP) (Frank Ernst)


4. Medicare Databases (Tammy Curtice & Renee Arnold)

The chapter on Medicare databases within the Alternative Population-Based Data Sources section will focus on identifying the different types of Medicare databases available and explaining what types of data can be found within these sources. The chapter will highlight availability or access points to Medicare databases, as well as comparing and contrasting the data to suggest the best opportunity for using the data from a disease and health management standpoint. The direction of this chapter is to have an easy to interpret and quick reference guide for practitioners working on the development and application of disease and health management programs within a Medicare population. These practitioners will need to understand what types of data may be available for interpreting and analyzing the impact and outcomes of these programs.

5. Veterans Healthcare Administration (VHA) (Mariam Hassan & Dennis Raisch)

This chapter will begin with an introduction chapter that will provide the reader with information to understand the VA health system and VA population. The VA has various data resources at national and local levels. A section on VA data resources will provide the reader with a detailed description of these data sources. Finally, the chapter will conclude with a section on the utility of VA databases for disease and health management. This section will cover practical aspects of conducting research using VA data. It will cover health and disease management issues in this population, what possible research designs can be used to study them, what programs can be implemented and evaluated, what patient outcomes can be measured using the variables available, what are advantages and disadvantages of using the VA data.
           

6. Department of Defense (DOD) (Chris Blanchette)


7. Patient Registries (Jayashri Sankaranarayanan, Jasmanda Wu, & Hans Petersen)

This chapter will provide clinicians and decision-makers including payers and regulatory authorities an overview of the origin, type, occurrence, and real-world use of patient registries in the US and worldwide in disease management and in the making and delivery of health care decisions. As organized systems of collecting data for scientific, clinical, or policy purposes, patient registries are a valuable complement to randomized controlled trials. However, unlike randomized controlled trials, they have less restrictive inclusion or exclusion criteria, and do not specify what therapy the health care provider must adhere to.  Patient registries are prospective, observational cohort studies of patients with or at risk for a particular disease and/or receiving a specific treatment/intervention. In medical practice, they enable evaluation of real-world outcomes for diverse purposes ranging from understanding the natural history, assessing or monitoring real-world safety, and effectiveness, assessing quality of care and provider performance, and assessing cost-effectiveness of therapies, whether of drugs or devices.

8. Clinical Trial Data (Mariam Hassan & Jayashri Sankaranarayanan)

The chapter will open with an introduction section that provides information on different designs and trials on health and disease management. Then there will be a section that describes economic and outcomes data from trials. This section will include a description on what are the possible outcomes that can be measured through these trials and how to measure and analyze them.

9. Genomic Databases (Chris Frei)

Disease and health management programs of the future will utilize real-time, integrated data from administrative, clinical, laboratory, and social settings. Genomic data will become a central focus. Recent advances in genomic technologies, advanced computing, and bioinformatics have positioned society at the fringe of such possibilities. Challenges including timeliness, integration, and prudent application remain. This chapter will introduce the idea of “genome-directed therapeutics,” list diseases where genome-based recommendations have emerged, describe the current state of genomic databases, outline national and international initiatives to develop additional genomic databases, and speculate as to the potential application of such databases for disease and health management. Finally, this chapter will conclude with a discussion of available resources and formidable obstacles to developing and utilizing these data for disease and health management.   

10. Observational & Naturalistic Studies (Krista Payne)


11. Other Data Sources (Mariam Hassan & Jayashri Sankaranarayanan)