1. Academic Computing Daniella Meeker, PhD Director, Clinical Research Informatics SC-CTSI Assistant Professor of Preventive Medicine and Pediatrics

2. Why doesn’t health care work like google?

3. Clinical Algorithms vs. Recommender Algorithms GoogleHealth System Platforms for data collection1 per application1000s without interoperability Accumulation of dataContinuous Randomized Trials to improve performance Continuous inexpensive implicit consent Expensive rare, ethical concerns, consent? Number of competing objectives and incentives 2 – user, advertiser5-6, patient, clinician, insurer, pharma, hospital, caregiver Cost of mistakesLow – Learning OpportunitiesHigh Authority for data accessSingleMultiple, including lawyers Distribution of dataMultiple Locations Computation architecturemaster-worker coordinationsilo Analysis execution environment ControlledSerendipitous Incentives for Research Participation HighLow* Distribution and comparison of algorithms softwareliterature

4. Optimization, Evolution & Dissemination of Tools o Optimizing requires an evaluation step o No evaluation platform to analyze next steps o Evaluation requires data

5. Machine Learning/System Science o “Machine” ~ Automation/Efficiency o “Learning” ~ Optimization and improvement

6. What is Data Science? o What is the source of data for data science? –Data about Data (Metadata) o Applications and tools generate metadata about workflow, user experience, and effectiveness –How can we use this to optimize USC use of tools? –Breadcrumbs for collaboration and improvement opportunities come in our application use Time tracking software can do this automatically o Where are incentives for such evaluations in academic computing?

7. Clinical Data Research Networks

8. Common problem in clinical informatics o No platform to compare applications and tools in a head-to-head competition o Tools are developed and not matured after publication o Collaboration costs are even higher than other disciplines…how do we reduce the costs of collaboration? o Need to distribute both master and worker software to collaborate

9. What is global, what is local? o Algorithms are global –Execution environments (software) may be local o Workflow specifications can be global –Workflow execution is local o Data specifications can be global –Data storage can be local or global –Security policies may be local o Regulations for security and privacy are global –Interpretations may be are local

10. Distributing Innovation & Evaluation in Clinical Informatics Tool developers