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Midwest Hospital
Cloud Forum
September 9, 2013
Closing the Loop in Healthcare Analytics - Correlating Clinical
and Adminis...
Learning Healthcare
System
• Adaptation to the pace of change
Stronger synchrony of efforts
Culture of shared responsibili...
Grand Challenges in Clinical
Decision Support
• Improve the human-computer interface
• Disseminate best practices in CDS d...
Big Data To
Knowledge – BD2K
• NIH initiative
• http://commonfund.nih.gov/bd2k/
• aims to facilitate broad use of biomedic...
IBM Watson
• Clinical Decision support
• Artificial intelligence
• add a natural language and semantic layer on top
of a s...
Query Health
• http://wiki.siframework.org/Query+Health
Distributed
Queries
• Distributed Query Challenges
• Absence of standards
• Integrating each data source is a heavy
lift
•...
Distributed Query Example
Mini-Sentinel & PopMedNet
• PopMedNet is proven across
several distributed query
networks, inclu...
A Vision for Broader Use of Electronic Health Information
in Evidence Development
10
Hospital Cloud Forum - thoughts for panel
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Hospital Cloud Forum - thoughts for panel

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Closing the Loop in Healthcare Analytics - Correlating Clinical and Administrative Systems with Research Efforts to Deliver Clinical Efficiency in Real Time

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Transcript of "Hospital Cloud Forum - thoughts for panel"

  1. 1. Midwest Hospital Cloud Forum September 9, 2013 Closing the Loop in Healthcare Analytics - Correlating Clinical and Administrative Systems with Research Efforts to Deliver Clinical Efficiency in Real Time John Sharp, MSSA, PMP, FHIMSS Cleveland Clinic
  2. 2. Learning Healthcare System • Adaptation to the pace of change Stronger synchrony of efforts Culture of shared responsibility New clinical research paradigm Clinical decision support systems Universal electronic health records Tools for database linkage, mining, and use Notion of clinical data as a public good Incentives aligned for practice-based evidence Public engagement Trusted scientific broker Leadership
  3. 3. Grand Challenges in Clinical Decision Support • Improve the human-computer interface • Disseminate best practices in CDS design, development, and implementation • Summarize patient-level information • Prioritize and filter recommendations to the user • Create an architecture for sharing executable CDS modules and services • Combine recommendations for patients with co- morbidities • Prioritize CDS content development and implementation • Create internet-accessible clinical decision support repositories • Use free text information to drive clinical decision support • Mine large clinical databases to create new
  4. 4. Big Data To Knowledge – BD2K • NIH initiative • http://commonfund.nih.gov/bd2k/ • aims to facilitate broad use of biomedical big data, develop and disseminate analysis methods and software, enhance training for disciplines relevant for large-scale data analysis, and establish centers of excellence for biomedical big data.
  5. 5. IBM Watson • Clinical Decision support • Artificial intelligence • add a natural language and semantic layer on top of a search engine • evaluates each potential answer based on evidence it can gather through refined secondary search • http://www.ibm.com/developerworks/library/os-ind- watson/
  6. 6. Query Health • http://wiki.siframework.org/Query+Health
  7. 7. Distributed Queries • Distributed Query Challenges • Absence of standards • Integrating each data source is a heavy lift • cross-organizational governance • Yet, path-breaking work is underway • ISDS Distribute • Primary Care Information Project • FDA’s Mini-sentinel • HMO Research Network • MDPHNet • i2b2 / SHRINE networks • DARTNet • OMOP • CDC’s BioSense 2.0 • Questions that return population measures (aggregate results) related to disease outbreaks, post-market surveillance, prevention, quality performance, etc. 8
  8. 8. Distributed Query Example Mini-Sentinel & PopMedNet • PopMedNet is proven across several distributed query networks, including Mini- Sentinel • Uniquely supports the policy guidance from HIT Policy Committee • Targeting full implementation of the Query Health proposed standards 9
  9. 9. A Vision for Broader Use of Electronic Health Information in Evidence Development 10
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