Innovation, data science & risk in healthcare

Bern Shen MD

HISA Health Data Analytics

Brisbane 11 Oct 2017

2

Policies & interventions

Health status

Access to quality healthcare

Technology

Physical environment

Behavior

Biology

Social environment

Individual

Adapted from Healthy People 2010

Source: : Mokdad, et al. 2004. Actual causes of death in the United States, 2000. JAMA. 2004;291:1238-45.

3

See Understand Predict Control

“Illness is about learning to live with lost control.”- Arthur Frank. The Wounded Storyteller: Body, Illness & Ethics.

“It may not be dying we fear so much, but the diminished self.”- Anatole Broyard. Intoxicated by My Illness.

Analytics & algorithms are beautiful…

…but only useful if they effect benefit in the real world.

4

(DCF startup valuation)

(SVM classifier for machine learning)

5Population Health FrameworkSource: Care Continuum Alliance. Outcomes Guidelines Report, Vol. 5. Washington, DC: Care Continuum Alliance. 2010.

Translation, implementation, dissemination

• NIH National Center for Advancing Translational Sciences (2011)

• Centres in Australia including Queensland Translational Research Institute

6

7

Data science

Risk Innovation

Top risks

“Second on the list is the one we haven’t thought of, and at the very top is the one we can’t imagine.” – David Morens, US NIAID

8Source: : Mokdad, et al. 2004. Actual causes of death in the United States, 2000. JAMA. 2004;291:1238-45.

9

Adapt (anticipate?) or die

10

Identify the tree shrew

Or better, be the next apex predator

Context & Pasteur’s prepared mind

“Dans les sciences d'observation le hasard ne favorise que des esprits préparés.”-Louis Pasteur, 1854

11

Data points (analytical) → data clouds (ecological)

12

Data points (analytical) → data clouds (ecological)

13Time

Disease signalDisease driver signal

Signal strength

Disease detected

Disease anticipated

(Noise)

Poverty, social inequalityWeather, climate changeMalnutrition, famineCrowding, human/wildlife contactLand use/ecosystem changeDisaster…

“Complexity rheostat”

14

Doctor

Patient

Med

Similarly for diagnostics, devices, services…

Decision support, practice guidelines, care pathways, etc.

Adherence, health beliefs & behaviors, social determinants, etc.

15

Map of science derived from

clickstream dataBollen J, Van de Sompel H, Hagberg A, Bettencourt L, Chute R, et al. (2009) Clickstream Data Yields High-Resolution Maps of Science. PLoS ONE 4(3): e4803. doi:10.1371/journal.pone.0004803 http://127.0.0.1:8081/plosone/article?id=info:doi/10.1371/journal.pone.0004803

Geographic → genomic

16Source: http://rocs.hu-berlin.de/complex_sys_2015/resources/Presentations/C_Mueller.pdf

a

Kwang-Il Goh, and In-Geol Choi Briefings in Functional Genomics 2012;11:533-542

Human disease network graph

17

• 67% of disorders linked to

at least one other

• Giant cluster contains 516

of 1284 (40%)

18

Health risks…

19Source: Univ. of Washington IHME. http://vizhub.healthdata.org/gbd-compare/

…change over time...

20

1990 2010

Source: R Lozano, et al. 2012. Global & regional mortality from 235 causes of death for 20 age groups in 1990 & 2010. Lancet 380:2095-128.

…with age...

21Source: R Lozano, et al. 2012. Global & regional mortality from 235 causes of death for 20 age groups in 1990 & 2010. Lancet 380:2095-128.

…by gender & place…

22

…by wealth & place

23

Malaria

Neonatal sepsis

TB

HIV/AIDS

Diarrhea

Malnutrition

Meningitis

Interpersonal violence

Pancreatic cancer

Breast cancer

Dementias

Prostate cancer

Diabetes

Neck pain

Lung cancer

AnxietyDrug use

Colon cancerAlcohol use

Self-harm

Lung cancer

Alcohol use

Colon cancer

Stomach cancer

Forces of nature in Caribbean

Wealthier Poorer

Global

Liver cancer in China

Interpersonal violence in Central & South America

Technobiome

24

“A House is a machine for living in.”-Le Corbusier. Vers Une Architecture. 1923.

“… joining and separation of human and nonhuman are everyday affairs.”-Suchman. Human-Machine Reconfigurations. 2007.

Unintended consequences, ethics

“We are building a civilization that is deeply connected yet technologically insecure…

in other words, we are constructing a world that is wired for crime.”

25

Dealing with bad data

• Unintended

• Deliberate

26

Toward Precision Medicine: Building a knowledge network for biomedical research & a new taxonomy of disease. National Academies Press, 2011.

New data, new connections

27

• New data types Beyond usual text, tracings, & images

• New data sources Outside of the hospital, clinic & lab

• …create new information management challenges

28

29

Data (test) Insight (diagnose) Action (treat)

30