The document discusses the challenges in reducing the gap between data generation and knowledge in healthcare, highlighting regulatory, technical, and cultural barriers. It advocates for a systems approach in healthcare IT and biomedical informatics to create a learning healthcare system that improves patient care through better data usage. The author emphasizes the need for collaboration among various informatics disciplines and stakeholders to address these challenges and enhance knowledge generation.

1. Reducing The Distance Between Data & Knowledge: Realizing the Promise of HIT and Biomedical InformaticsPhilip R.O. Payne, Ph.D.Associate Professor & Chair, Department of Biomedical InformaticsExecutive Director, Center for IT Innovations in HealthcareCo-Director, Center for Clinical and Translational Science, Biomedical Informatics ProgramCo-Director, Comprehensive Cancer Center, Biomedical Informatics Shared ResourceOSU Center for Personalize HealthcareNational ConferenceOctober 6, 2011

2. OutlineProblem StatementThe Promise of HIT and Biomedical InformaticsCreating a Learning Healthcare SystemGenerating KnowledgeStrategies and Future DirectionsHITBiomedical InformaticsCulturalDiscussion2

3. The ProblemData GenerationEHRIncreasingDistanceManagement,Integration,DeliveryEDWKnowledgeGeneration3

4. Contributing Factors (1)Regulatory, Technical, and Cultural Barriers Between Data and Knowledge GenerationHigh performance systems require rapid adaptationIncreasing demand for better, faster, safer, more cost effective therapiesSimultaneous demand for increased controls over secondary use of clinical dataArtificial partitioning of access to data for knowledge generation purposesCritical overlaps and potential sources of conflict between these factorsCI, Imaging, CRI, TBI, PHI Clinical InvestigatorsBioinformatics, TBI, CRI

5. Contributing Factors (2)5Historical precedence for reductionism in the biomedical and life sciencesBreak-down problems into fundamental unitsStudy units and generate knowledgeReassemble knowledge into systems-level modelsInfluences policy, education, research, and practiceRecent scientific paradigms have illustrated major problems with this type of approachSystems biology/medicineReductionist approach to data, information, and knowledge management is still prevalentHIT vs. InformaticsInformatics sub-disciplines

6. Point“The whole is more than the sum of its parts.” - AristotleCounter-Point“To make progress in understanding all this, we probably need to begin with simplified (oversimplified?) models and ignore the critics' tirade that the real world is more complex. The real world is always more complex, which has the advantage that we shan't run out of work.” - John BallIs it time for a systems-approach to secondary use of data in healthcare? If so, how do we reduce the “distance” between data and knowledge generation?

7. The Promise of Healthcare IT (HIT)Delivering timely and contextually appropriate data, information, and knowledge in support of basic science, clinical and translational research, clinical care, and public health.

8. Creating a Learning Healthcare System: Learning from Every Patient and Improving CareClinical InformaticsPublic Health InformaticsTranslational BioinformaticsClinical Research InformaticsLearn from every patient encounter so that we can improve their care, their families care, and their communities care

9. Many Sources of Data9Emergent SourcesPHR, Instruments, Etc.Molecular PhenotypeEnterprise Systems and Data Repositories:EHR, CTMS, Data WarehousesEnvironment

10. The Biomedical Informatics Continuum: From Data to Knowledge10+ Application+ Context

11. Significant Barriers11Technical

12. Regulatory

13. Cultural

14. Achieving shared language and understanding between stakeholdersThe Construction of the Tower of Babel (Hendrick van Clev) Source: Wikimedia Commons

15. Strategies & Future Directions: HIT12Eliminating traditional boundaries

16. Focusing on economies of scale across mission areas

17. Bridging applied informatics and HIT practice