Clinical and TranslationalScience Institute / CTSIat the University of California, San Francisco

Informatics Technologies: From a Data-Centric View to a Hypothesis-Centric ViewIda Sim, MD, PhDProf Medicine, Co-Director of Biomedical Informatics, CTSI

• Where is the wisdom we have lost in knowledge?

• Where is the knowledge we have lost in information?

• Where is the information we have lost in Big Data?

The Rock, T.S. Eliot. 1934

What is Data, Information, Knowledge?

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9.8

Data-Information-Knowledge

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HgbA1c 9.8%

Data-Information-Knowledge

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HgbA1c 9.8% (normal 4.3% to 5.6%)

Data + Context = Information

• Data -- discrete, atomic, raw observations with no inherent structure

• Information – data related to other data in an interpretive context that is meaningful for a particular task, e.g., - normal range is meaningful for clinical care

- charge is meaningful for payment capture

Knowledge

• Data -- discrete, atomistic, raw observations with no inherent structure

• Information – data related to other data in an interpretive context that is meaningful for a particular task

• Knowledge – generalizable statements that allow you to make predictions about individuals

- e.g., people with diabetes are at higher risk of cardiovascular disease

Knowledge Through Hypothesis Testing

• Data supports or refutes hypotheses

• Hypotheses in translational medicine– T1: about mechanisms of disease– T2/T3 clinical research: treatment, diagnosis,

quality of care• within traditional health care settings• beyond hospital and clinic

Hypotheses-Centric View of EHR Data

• Observational studies– more prone to confounding and other biases– informatics needs include:1

• clean data and metadata

• accurate cohort selection and comparison (see Research Browser)

• Expect a Big Data flood of observational findings– many non-health data scientists flocking to health data – need to learn epi/biostats and domain experts to deal with

confounding, etc.

• Interventional trials will be at a premium to verify observational findings

Observational vs. Interventional

• In 2013, 84% of UCSF studies were non-interventional

• What's the right balance?– are PIs doing

observational research for the right reasons?

UCSF 2013 Clinical

Research Studies

Total = 1,380

Informatics for Interventional Research

• Traditional trials, parallel to clinical care– OnCore interoperation with APEX

• Virtual, community-based trials– e.g., recruited & screened via web, lab testing in their

community, run-in phase with e-diaries, informed consent via web, study medication shipped directly to participants1

• Point-of-care (POC) research– e.g., POC randomization2, alerts, patient support and care

coordination, capturing self-reports via MyChart/sensors, etc– care, QI, and research are on a spectrum3

1Orri, et al. Contemp Clin Trials 38 (2014) 190–197; 2Fiore, L. et al. Clin Trials, 2011 8:183-95; 3Pletcher, et al. JAMA Int Med 2014 174:668-670.

Functional View of POC E-Research Requests

• APEX: – programmatically sending patient-specific messages to targeted clinicians via

their Inbox– integration of existing risk calculators into APEX (with automated uploading of

clinical/lab data)– launching external websites from within APEX– offering structured note templates within APEX (e.g., PHQ-9)– introducing reminders (pop-ups) in APEX– adding documents to Notes or Scanned Outside Documents– insertion of new patient education materials into the After Visit Summary

• MyChart:– inserting patient-facing materials into MyChart – recruiting study subjects via MyChart and securing informed consent– mass messaging patients through MyChart– deploying surveys through MyChart

DGIM Survey Choices(n=16/28 researchers)

APEX Requests Votes for "Top 5"

Votes for "Top 1"

Integrate existing risk calculators into APEX 13 4

New structured note templates within APEX 8 2

MyChart Requests Votes for "Top 5"

Votes for "Top 1"

Deploying surveys through MyChart 9 2

Recruit study subjects via MyChart 8 3

Insert patient-facing materials into MyChart 8 1

Other Top 1 choice with 2 votes: launching external website from within APEX

Next Steps

• Build on data management foundation to increase hypothesis-centric use of informatics at UCSF– make point-of-care and other interventional

research easier, faster, cheaper

• Next CTSI proposal will emphasize e-research infrastructure– interventional, observational, community-based

• Need input from you!