Post on 07-May-2020
transcript
Data, Outcomes, and Evidence: Data Science in The Life Cycle of Evidence Based Medicine
Johannes Starlinger
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 2
Important notice: Several slides contained in the original, oral
presentation which showed copyrighted material and/or unpublished results have
been redacted/removed.
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 3
About me
Studied Medicine
Studied Computer
Science
PhD Computer
Science
Biomedical Data
Researcher
Clinical Data
Researcher
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 4
About me
Studied Medicine
Studied Computer
Science
PhD Computer
Science
[Health]Data
Software
Freelance
[Health]Data
Software
Biomedical Data
Researcher
Clinical Data
Researcher
Start-up
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 5
About me
Studied Medicine
Studied Computer
Science
PhD Computer
Science
[Health]Data
Software
Freelance
[Health]Data
Software
Biomedical Data
Researcher
Clinical Data
Researcher
Start-up
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 6
The Life Cycle of Evidence Based Medicine
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 7
The Life Cycle of Evidence Based Medicine
Assessment SOPs Care Planning Care Pathways Outcomes
Observations
New Evidence Clinical Studies Hypothesis Geneartion Outcome Analysis
Summarization Synthesis of Recommendations COI Assessment Consensus Process Evidence Rating Evidence Review
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
Approval Storage Versioning Archival Indexing Publication Searchability
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 8
The Life Cycle of Evidence Based Medicine
Assessment SOPs Care Planning Care Pathways Outcomes
Observations
New Evidence Clinical Studies Hypothesis Geneartion Outcome Analysis
Summarization Synthesis of Recommendations COI Assessment Consensus Process Evidence Rating Evidence Review
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
Approval Storage Versioning Archival Indexing Publication Searchability
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 9
The Life Cycle of Evidence Based Medicine
Assessment SOPs Care Planning Care Pathways Outcomes
Observations
New Evidence Clinical Studies Hypothesis Geneartion Outcome Analysis
Summarization Synthesis of Recommendations COI Assessment Consensus Process Evidence Rating Evidence Review
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
Approval Storage Versioning Archival Indexing Publication Searchability
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 10
The Life Cycle of Evidence Based Medicine
Assessment SOPs Care Planning Care Pathways Outcomes
Observations
New Evidence Clinical Studies Hypothesis Geneartion Outcome Analysis
Summarization Synthesis of Recommendations COI Assessment Consensus Process Evidence Rating Evidence Review
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
`
Approval Storage Versioning Archival Indexing Publication Searchability
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 11
The Life Cycle of Evidence Based Medicine
Assessment SOPs Care Planning Care Pathways Outcomes
Observations
New Evidence Clinical Studies Hypothesis Geneartion Outcome Analysis
Summarization Synthesis of Recommendations COI Assessment Consensus Process Evidence Rating Evidence Review
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
`
Approval Storage Versioning Archival Indexing Publication Searchability
Clinical Practice
Guidelines
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 12
The Life Cycle of Evidence Based Medicine
Assessment SOPs Care Planning Care Pathways Outcomes
Observations
Approval Storage Versioning Archival Indexing Publication Searchability
New Evidence Clinical Studies Hypothesis Geneartion Outcome Analysis
Summarization Synthesis of Recommendations COI Assessment Consensus Process Evidence Rating Evidence Review
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
`
Clinical Practice
Guidelines
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 13
The Life Cycle of Evidence Based Medicine
Assessment SOPs Care Planning Care Pathways Outcomes
Observations
Approval Storage Versioning Archival Indexing Publication Searchability
New Evidence Clinical Studies Hypothesis Geneartion Outcome Analysis
Summarization Synthesis of Recommendations COI Assessment Consensus Process Evidence Rating Evidence Review
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
Clinical Practice
Guidelines
`
Data Science?
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 14
The Life Cycle of Evidence Based Medicine
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
`
Clinical Practice
Guidelines
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 15
The Life Cycle of Evidence Based Medicine
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
`
Future
Clinical Practice
Guidelines
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 16
The Life Cycle of Evidence Based Medicine
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
Clinical Practice
Guidelines
`
Data
Future
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 17
The Life Cycle of Evidence Based Medicine
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
Clinical Practice
Guidelines
`
Data
Future
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 18
The Life Cycle of Evidence Based Medicine
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
Clinical Practice
Guidelines
`
Data
Future
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 19
The Life Cycle of Evidence Based Medicine
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
Clinical Practice
Guidelines
`
Data
Future
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 20
The Life Cycle of Evidence Based Medicine
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
Clinical Practice
Guidelines
`
Data
Future
DataScience!
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 21
The Life Cycle of Evidence Based Medicine
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
Clinical Practice
Guidelines
`
Data
Future
Data
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 22
Weber et al. Finding the Missing Link for Big Biomedical Data, JAMA June 25, 2014, Volume 311, Number 24, pp. 2479
About the patient
Graphic and commentary removed, please refer to
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 23
Evidence Personalized Based Medicine
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 24
Evidence Personalized Based Medicine
Co
ho
rt S
ize
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 25
Evidence Personalized Based Medicine
Co
ho
rt S
ize
Number of Features
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 26
Evidence Personalized Based Medicine
Co
ho
rt S
ize
Number of Features
DataScience!
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 27
Unpublished example removed
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 28
Evidence Personalized Based Medicine
Co
ho
rt S
ize
Number of Features
DataScience!
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 29
Evidence Personalized Based Medicine
Co
ho
rt S
ize
Number of Features
DataScience!
DataScience!
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 30
Evidence Personalized Based Medicine
Co
ho
rt S
ize
Number of Features
DataScience!
DataScience!
DataScience!
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 31
Unpublished example removed
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 32
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
Clinical Practice
Guidelines
`
Data
DataScience!
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 33
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
Clinical Practice
Guidelines
`
Data
DataScience!
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 34
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
Clinical Practice
Guidelines
`
Data
DataScience!
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 35
Analysis
Intensive Care
Anesthesia
Routine Care
Notes, letters, reports
DataScience!
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 36
Plotting
Analysis
Intensive Care
Anesthesia
Routine Care
Prep
Notes, letters, reports
DataScience!
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 37
Plotting
Analysis
Intensive Care
Anesthesia
Routine Care
Prep
Notes, letters, reports
Created by Freepik
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 38
Plotting
Analysis
Intensive Care
Anesthesia
Routine Care
Prep
Notes, letters, reports
Created by Freepik
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 39
Plotting
Analysis
`
Intensive Care
Anesthesia
Routine Care
Prep
Notes, letters, reports
OutcomesResearch
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 40
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
Clinical Practice
Guidelines
`
Data
DataScience!
Johannes Starlinger – Data Science in the Life Cycle of Evidence Based Medicine – 2019 41
Synth
esis
Managem
ent
Im
plem
enta
tion
Evaluation
Clinical Practice
Guidelines
`
Data
DataScience!