using big data to improve individual health and health ...€¦ · practice patterns of physicians...

Using Big Data to Improve Individual Health and Health Care Systems

Jukka-Pekka “JP” OnnelaDepartment of Biostatistics

Harvard T. H. Chan School of Public HealthHarvard University

April 17, 2015

DATA

• Progress in science always driven by data• Dramatic increase in data volume and type

• Big Data refers to large and complex data sets• Data: Sensors are cheap, small, everywhere• Analysis: Computational capacity

http://news.nationalgeographic.com/news/2009/08/photogalleries/galileos-telescope-pictures-anniversary/

CONSEQUENCES

• Increasingly rich data in real-world contexts

• Biology has become information / computational science• Social and behavioral sciences heading in this direction• Public health and medicine

• Two different levels:• Health of individuals and Structure of healthcare systems

Health of Individuals (Digital Phenotyping)

Structure of Healthcare Organizations (Network Science)

Future

• Surveys (like PHQ-9) are the standard approach in mental health: diagnosis, monitoring, etc.

• Completed during office visits• Difficult to collect high frequency longitudinal data• Rely on retrospective recollection and may be inaccurate• Conformation to expectations or avoidance of responses• This is an “in vitro” as opposed to an “in vivo” approach

CURRENT APPROACH

DIGITAL PHENOTYPING

• Digital phenotyping

• Moment-by-moment quantification of the individual-level human phenotype in vivo using data from digital devices (smartphones)

• Digital Phenotyping Project (NIH Director’s New Innovator Award 2013):• Develop scientific smartphone application (data generation engine)• Develop statistical methods and software (data analysis)

• Data + Methods = Digital Phenotyping

• Initial application area is psychiatric and neurological disorders

• Diagnosis and monitoring of mental illnesses is currently based on patient-reported symptoms and patient-reported accounts of behavior

• Diagnostic and Statistical Manual of Mental Disorders (DSM) is controversial• Introduce a data-driven approach (active & passive)

• Objectives:(1) Classify psychopathologies based on observable behavior(2) Monitor treatment response(3) Deliver treatments and interventions

SMARTPHONES AND MENTAL HEALTH

PILOT USING SURVEY RESPONSES ONLY

“Utilizing a Custom Application on Personal Smartphones to Assess PHQ-9 Depressive Symptoms in Patients with Major Depressive Disorder” by J Torous, P Staples, M Shanahan, C Lin, P Peck, M Keshavan, and JP Onnela, in press (2015).

BEIWE APP

BEIWE APP

Data streams

• Accelerometer (x acceleration, y acceleration, z acceleration)• GPS (latitude, longitude, precision)• Phone / screen usage (screen on/off, phone on/off, reboots, plug in/unplug)• Nearby WiFi routers (hashed MAC address, signal strength)• Bluetooth scan & other Beiwe phones (hashed MAC address)• Phone call logs (incoming, outgoing, missed; time, call duration, hashed number)• Text message logs (incoming, outgoing; time, message length, hashed number)• Survey data (daily & weekly; survey metadata)• Voice recording (daily; MP4 file)

• Notifications to the user (daily & weekly survey, voice recording)



Future

NETWORKS• Nodes and edges

• Social, biological, technological, information, etc.

• Meaning of edges

• Network structure

WEAK TIES

• Historically hard to collect data on social networks at scale• Until about 10 years ago, we could only examine the tip of the iceberg

Mark Granovetter, The strength of weak ties, American Journal of Sociology 78, 1360, 1973

MACROSCOPIC NETWORK STRUCTURE

MACROSCOPIC NETWORK STRUCTUREMACROSCOPIC NETWORK STRUCTURE

PAST LARGE-SCALE WORK

PRACTICE PATTERNS OF PHYSICIANS

• Local practice patterns of physicians are known to vary• Quantified for the first time in 1973 across towns in Vermont• Subsequent research has shown that local norms play an important role in

determining physician practice patterns• Physicians may come to conform to the behavior of other nearby

physicians

• Could account for a large proportion of the variability in health care


• When physicians provide care to shared patients, they share clinical information through informal discussions and observations

• This leads to the formation of informal information-sharing networks• These networks are organic in nature (vs. hospitals etc.), and may not

conform to formal organizations• Understanding informal networks is important for day-to-day practice, and for

understanding how physicians exchange information with one another


• Used existing administrative data, physician encounter data from Medicare claims from 2006, to construct networks

• Ties have weights equal to the number of shared patients: more shared patients implies a stronger connection between physicians


• Among all physicians and ties across the 51 HRRs, male physicians were more likely to have ties with other male physicians (65.1% of connected pairs were male-male vs. 54.6% of unconnected pairs)

• Female physicians were less likely to have ties with other female physicians (3.8% of connected pairs vs. 6.4% of unconnected pairs)

• Physicians with ties were also closer in age (mean difference of 11.5 years for those with ties vs. 12.5 years for those without ties)

• The mean distance for connected pairs was 21.1 km vs 38.7 km for unconnected pairs

• Physicians with ties to each other were far more likely to be based at the same hospital (69.2% of unconnected pairs vs 96.0% of connected pairs)

• Cost and coordination of care



Future

FUTURE

• New types of behavioral data

• “Space age methods”

• Health of individuals• Digital phenotyping (genotype vs. phenotype)

• Structure and performance of healthcare organizations• Electronic medical records

FUTURE

• Data integration• Clinical, genomic, and behavioral data

• Data ownership and privacy• Development vs. discrimination

• Data sharing• Reproducibility, replicability, and public trust in science

THANKS!

www.hsph.harvard.edu/onnela-lab/

http://www.hsph.harvard.edu/onnela-lab/

using big data to improve individual health and health ...€¦ · practice patterns of physicians...

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