Big Data for Rehabilitation: Promises, Pitfalls, and ... Annual...
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Kenneth J. Ottenbacher University of Texas Medical Branch
Big Data for Rehabilitation: Promises,
Pitfalls, and Future Potential
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Outline
1. Introduction
2. Challenges & Opportunities
3. Resources – Center for Large Data Research & Data Sharing (CLDR)
4. Questions
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“The march of quantification, made possible by enormous new sources of data, will sweep through academia, business, health care and government. There is no area that is going to be untouched.”
Science 2011
Data Discovery
Background
2008
2011
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The Challenges
Large datasets can be overwhelming
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The Challenges
Rehabilitation investigators are trained to conduct (prospective) clinical, patient-oriented research...
not comprehensive or secondary analysis of large data.
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The Opportunities
• Health and biomedical data are available that include informa:on related to rehabilita:on, recovery, and disability
• Advances in bioinforma:cs, sta:s:cal compu:ng, informa:on technology and the internet have resulted in access to large amounts of data
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Large Data Analytics is an Evolving Field
EMC Educational Services. Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data. John Wiley & Sons, Hoboken, NJ, 2014. ISBN 9781118876220
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NIH Big Data to Knowledge (BD2K)
Areas of BD2K 1. Facilita:ng Broad Use of Data
2. Analysis Methods and SoFware
3. Enhancing Training
4. Centers of Excellence
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What is “Big Data”?
“Big Data refers to the complexity, challenges, and new opportunities presented by the combined analysis of data. In biomedical research, these data sources include the diverse, complex, disorganized, massive, and multimodal data being generated by researchers, hospitals, and mobile devices around the world.”
https://datascience.nih.gov/bd2k/about/what
NIH BD2K Definition
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Includes everything from Twitter to the Genome
Characteristics of “Big Data”?
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Large Data vs. Big Data
Adapted from: Roski J et al. Health Aff 2014;33:1115-1122
Big Data Analy:cs
Analyzes different data types on massive scale resul6ng in predic6ve and real 6me analyses
Big Data Compu:ng
Data consolidated, allows analy6cal work to be streamlined
Basic Analy:cs
Includes tradi6onal observa6onal and so>ware based sta6s6cal approaches
Large Data Analy:cs
Includes advanced sta6s6cal approaches involving sophis6cated so>ware
Size of Data
Analy:
cal Com
plexity
Data of same form Mega-‐bytes to tera-‐bytes
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Personal Mo:on Technology
Con:nuous recording of biological or performance informa:on generates large amounts of data.
Opportuni:es (Example)
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Opportuni:es (Example)
PCORnet, the National Patient-Centered Clinical Research Network, is an initiative of PCORI. It is designed to make it faster, easier, and less costly to conduct clinical research than is now possible by using the power of large health data and patient partnerships.
http://www.pcornet.org/
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What we have done … Link research to Federal healthcare legislation & priorities:
Opportunities
1. ACA – Hospital Readmission Reduction Program
2. ACA – Bundled Payment for Care Improvement • Comprehensive Care for Joint Replacement
3. ACA – Value-based Healthcare - Quality Measure Reporting
4. MedPAC Reports to Congress
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We examined na:onal data from 1.7 million Medicare files to determine rates of hospital readmission for the six largest impairment groups receiving inpa:ent medical rehabilita:on in the U.S.
Example – Large Data Research
Hospital Readmission is a National Quality Indicator for Healthcare Reform
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Cumula:ve 30 Day Readmission aFer IRF Discharge
Debility
JAMA 2014;311(6):604-‐614
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Resources
NIH (P2C-HD065702)
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Activities - CLDR
• Web Site http://rehabsciences.utmb.edu/cldr
• Educa:on & Training
• Data Directory
• Pilot Projects
• Visi:ng Scholars Program
• Data Archiving & Sharing Program
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Education & Training
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Data Directory
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Pilot Projects
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CLDR Pilot Projects
Category 1: Large Data Pilot Studies
These include traditional pilot studies examining a research question using large data (e.g., survey or administrative dataset) that address an issue related to rehabilitation, recovery, or disability. Funding up to $25,000
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Category 2: Data Sharing and Archiving Pilot Studies Category 2 projects are focused on archiving data from a completed rehabilitation study with support being given to either the PI or a member of their research team.
• Funding up to $10,000 • Applications accepted year-round
CLDR Pilot Projects
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Visiting Scholars
Visiting Scholars Program Investigators can be supported for periods of up to six months at one of the consortium institutions to work with experienced investigators using large datasets.
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New CLDR activity related to federal mandates for data sharing
White House Office of Science and Technology Policy (February 22, 2013)
IOM Report: Sharing Clinical Trial Data: Maximizing Benefits, Minimizing Risk. National Academies Press, Washington, DC 2015
Resources – Data Sharing Archiving & Data Sharing
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NICHD Data and Specimen Hub (DASH)
DASH is a resource to store and access de-identified data from NICHD-funded research studies for secondary research use.
https://dash.nichd.nih.gov/
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Federal Interagency Traumatic Brain Injury Research
https://fitbir.nih.gov/
FITBIR functions as a repository for data from TBI studies and supports a free web-based application with an interface that allows investigators to contribute and access data.
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Where is the wisdom we have lost in knowledge?
Where is the knowledge we have lost in informa8on?
T.S. Eliot (The Rock) Where is the informa:on we have lost in data?
Large/Big Data Caveat
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Information
Rehabilitation Sciences Academic Division & Research Center Phone: (409) 747-1637 Email: [email protected]
http://rehabsciences.utmb.edu/cldr
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Related Grants & Support
• Research P2C-‐HD065702 (PI, NIH) R01-‐HD069443 (PI, NIH) R01 MD-‐010355 (PI, NIH) H133G140127 (PI, NIDILRR) R24-‐HS022134 (Core, AHRQ) P30-‐AG024832 (Core, NIH) • Training K12-‐HD055929 (PI, NIH) H133P110012 (PI, NIDILRR)
Anne Deutsch, RN, PhD, CRRN Brian Downer, PhD Karl Eschbach, PhD James Goodwin, MD James Graham, PhD Ickpyo Hong, PhD, OTR* Bret Howrey, PhD Jessica Jarvis, MS* Amol Karmarkar, PhD, MPH Amit Kumar, PT, PhD, MPH* Yong-‐Fang Kuo, PhD Chih-‐ying (Cynthia) Li, PhD, OTR* Yi-‐Li Lin, MS Addie Middleton, PT, DPT, PhD Tim Reisteker, PhD, OTR Jie Zhou, MS * Postdoc or Graduate Student
Disclosures (PI or core leader)
ASNR Disclosures & Acknowledgements
Large Data Research Team Soham Al Snih, MD, PhD Winston Chan, PhD Nai-‐Wei Chen, PhD