Registries and Biobanks

The Basics Nuts and Bolts

Sharon F. Terry, MA

Registries Registries for Evaluating

Patient Outcomes: A User's Guide. 2nd edition.

Gliklich RE, Dreyer NA, editors.

Rockville (MD): Agency for Healthcare

Research and Quality (US); 2010 Sep.

Registries •  Geographically based population registries •  Public health reporting (e.g., vaccine registries, pregnancy

registries) •  Outcome registries

–  Interventions –  Adverse events –  Products –  Prevention

•  Specific disease registries –  Listing –  Cohort building –  Natural history –  Epidemiology

More Registries •  Hospital based

–  Improvement of patient care –  Professional education –  Administrative information –  Clinical research

•  Population-based registries –  Cancer prevention –  Early detection –  Determination of cancer rates and trends –  Patterns of care and outcomes –  Research –  Evaluation of control efforts

For this Discussion Disease registries •  Organized system •  Specific and meaningful questions –  Though sometimes open-ended as well

•  Standardized data

Registry types and perspective

Disease registry

Procedure registry

Device

Drug registry

Clinical event registry

Pregnancy registry

Procedure B

Good Practice for Patient Registries"AHRQ Annual Meeting"

Bethesda, MD| September 9, 2008"Speaker: Richard Gliklich, MD, "

Principal Investigator, Outcome DEcIDE Center,"President, Outcome"

Cambridge, MA "

The Handbook •  Creating a Registry

•  Planning •  Design •  Data Elements •  Other Data Sources •  Ethical and Legal Issues

•  Operating Registries •  Evaluating Registries

– State the purpose –  Identify stakeholders – Establish governance – Define scope of registry – Define target population – Assess feasibility – Secure funding

Planning

Design – Design registry with respect to its major

purposes • Hypothesis testing • Hypothesis generating

– Choose a study design – Select data sources, populations, comparison

groups – Determine whether sampling is needed –  Identify possible sources of bias (systematic

error) and address them to the extent that is practical and achievable

Data Elements –  Importance and relationship to the primary

outcome – Assess data collection burden and incremental

costs for collection – Standards and common data definitions or

validated instruments – Pilot test: feasibility and burden as well as

reliability, validity, and potential for missing data

Data Sources Primary data: collected for direct purposes of the registry Secondary data: collected for other purposes • Medical records •  Institutional or organizational databases • Administrative and claims data • Death and birth records • Census databases • Existing registry databases

Consider cost, timeliness, structure, availability and quality

Ethics, Sharing & Data Access

Review ethical and data privacy requirements early in planning phase to ensure compliance • Common Rule • HIPAA • Community rubrics

Ethics, Sharing & Data Access"Beyond Traditional Regulatory Systems

Fair Information Practice Principles 1. Notice/Awareness

–  identification of the entity collecting the data; –  identification of the uses to which the data will be put; –  identification of any potential recipients of the data; –  the nature of the data collected and the means by which it is collected; –  whether the provision of the requested data is voluntary or required; –  the steps taken by the data collector to ensure the confidentiality, integrity

and quality of the data.

Fair Information Practice Principles, Continued

2. Choice/Consent –  Opt-in –  Opt-out –  Granular preference setting

3. Access/Participation 4. Integrity/Security 5. Enforcement/Redress

–  Self regulation –  Private Remedies –  Government enforcement

•  Operating Registries •  Recruitment and management of

participants •  Data collection and quality assurance •  Adverse event collection and

management •  Data analysis and interpretation

•  Evaluating Registries

Recruitment and management of participants"

Recruitment occurs at many levels •  Facilities (hospital, practice, pharmacy) •  Providers •  Disease Advocacy Organizations •  Social networks •  Other places of social and business interaction

Motivation for participation at each level differs Goals for recruitment, retention and follow-up should be explicit and deviations continuously evaluated for risk of introducing bias

Data Collection & Quality Assurance

Data collection –  Includes collecting, cleaning, storing, monitoring and reporting

registry data –  Broad range of data collection procedures and systems available

Critical factors in data quality –  Data element structure and definition, training of personnel, how

data problems are handled

Quality assurance –  Define requirements at registry creation –  Risk-based approach

•  Most important or likely sources of error or potential lapses in procedures that may impact quality in the context of intended purpose

Adverse Event Detection, Processing, & Reporting

–  Important for any registry, especially with direct participant and/or physician contact

– Collection of spontaneously reported or solicited safety information •  Protocol-defined procedures strongly recommended •  Investigators and site staff appropriately trained

– Processing, coding and managing of AE data – Reporting and regulatory requirements

Analysis and Interpretation Analysis

•  Importance of a statistical analysis plan –  Analytic plans and statistical techniques for primary and secondary

objectives

•  Report on characteristics of the patient population, exposures of interest and endpoints "

Interpretation •  Who was studied?

–  Is the actual population representative of the target population?

•  How were the data collected, edited and verified? –  Completeness of data collection and data quality –  How were missing data handled and reported

•  How were the analyses performed?

Evaluating Registries Quality component analysis

Research quality (scientific process) Planning; design; data elements & data sources; ethics, privacy and governance

Evidence quality (data/findings) Patients; data elements & data sources; QA; analysis; reporting

Components classified as Basic Practice (draft names) Future Directions/Potential Enhancement (draft names)

Biobanks

“Biobanks” are repositories which assemble, store, and manage collections of human specimens and related data.

Henderson GE, Cadigan RJ, Edwards TP, Conlon I, Nelson AG, Evans JP, Davis AM, Zimmer C, Weiner BJ. Characterizing biobank organizations in the U.S.: results from a national survey. Genome Med. 2013 Jan 25;5(1):3. PMID: 23351549

Henderson GE, Cadigan RJ, Edwards TP, Conlon I, Nelson AG, Evans JP, Davis AM, Zimmer C, Weiner BJ. Characterizing biobank organizations in the U.S.: results from a national survey. Genome Med. 2013 Jan 25;5(1):3. PMID: 23351549

Henderson GE, Cadigan RJ, Edwards TP, Conlon I, Nelson AG, Evans JP, Davis AM, Zimmer C, Weiner BJ. Characterizing biobank organizations in the U.S.: results from a national survey. Genome Med. 2013 Jan 25;5(1):3. PMID: 23351549

Henderson GE, Cadigan RJ, Edwards TP, Conlon I, Nelson AG, Evans JP, Davis AM, Zimmer C, Weiner BJ. Characterizing biobank organizations in the U.S.: results from a national survey. Genome Med. 2013 Jan 25;5(1):3. PMID: 23351549

Henderson GE, Cadigan RJ, Edwards TP, Conlon I, Nelson AG, Evans JP, Davis AM, Zimmer C, Weiner BJ. Characterizing biobank organizations in the U.S.: results from a national survey. Genome Med. 2013 Jan 25;5(1):3. PMID: 23351549

Henderson GE, Cadigan RJ, Edwards TP, Conlon I, Nelson AG, Evans JP, Davis AM, Zimmer C, Weiner BJ. Characterizing biobank organizations in the U.S.: results from a national survey. Genome Med. 2013 Jan 25;5(1):3. PMID: 23351549

Henderson GE, Cadigan RJ, Edwards TP, Conlon I, Nelson AG, Evans JP, Davis AM, Zimmer C, Weiner BJ. Characterizing biobank organizations in the U.S.: results from a national survey. Genome Med. 2013 Jan 25;5(1):3. PMID: 23351549

Terry, et al. Personalized Medicine. March 2011, 8(2): 207-13.

Horn, et al. Biopreservation and BioBanking. June 2010, 8(2): 115-117.

Advocacy owned and managed data repository and samples

Clinical Information Medical Records DNA/RNA Self-reported Data Cell Lines Tissue / Organs

30,000 samples + 20,000 clinical records

BioBank.org

Established in 2003 to accelerate drug development, knowing a key rate-limiting step is the availability of well-characterized clinical data and biospecimens

–  Assemble cohorts –  Collect data –  Collect biospecimens

•  Blood •  Tissue •  Surgical samples

–  Secure research collaborations –  Access expertise

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Reg4ALL.org  

biobank.org

Lessons learned •  Don’t duplicate efforts – registries and biobanks are

expensive and administratively burdensome •  Develop partnerships to share data and resources •  Ensure registry/biobank is sustainable over time •  Use common data fields/controlled vocabulary/standards for

interoperability •  Follow best practices •  Engage participants, keep them, attract new ones •  Prior proper planning prevents poor performance •  Stewardship is important •  People matter •  Governance must be dynamic, culturally appropriate and

responsive

BioTrust Ethics Team

•  Kelly Edwards, University of Washington, Chair •  Nicholas Anderson, University of Washington •  Greg Biggers, Genomera •  Leila Jamal, Johns Hopkins University •  Jane Kaye, Oxford University •  Kieran O’Doherty, University of Guelph •  Suzanne D. Vernon, CFIDS Association of

America •  David Winickoff, University of California at

Berkeley

Registries for Reporting Patient Outcomes = http://effectivehealthcare.ahrq.gov/search-for-guides-reviews-and-reports/?pageaction=displayproduct&productID=531 Henderson paper on biobanks: http://genomemedicine.com/content/pdf/gm407.pdf Genetic Alliance Registry and BioBank = BioBank.org Registries for All = Reg4all.org