The Impact of Cognitive Computing on Healthcare Final

The Impact of
Cognitive Computing
on Healthcare
Craig Rhinehart
Director, IBM Watson Health Strategy
and Market Development
Watson: The Next
Grand Challenge
Session Description
The Impact of Cognitive Computing on Healthcare
Complex care coordination requires significant time
and can tax the resources of even the most versatile
organizations. IBM’s Watson computer can rapidly,
intelligently parse through disparate data to help
coordinate care. Learn how this new evolution of
computers featuring natural language processing,
hypothesis generation and evaluation, and dynamic
learning can augment efforts to improve health
information sharing for better patient outcomes.
© 2015 International Business Machines Corporation
3
“Have You Started Your Data Expedition Yet?”
§ Blog: h#p://craigrhinehart.wordpress.com/ Craig Rhinehart s Intrapreneurial Insights on Business Innova5on, Strategy and Growth § Twi=er: @CraigRhinehart § Email: [email protected] 4
#WatsonHealth #MiHIN
New Post Topics
•  Introduce Cognitive Computing
•  Why Cognitive Computing in Healthcare?
•  An Explosion of Data and Costs
•  IBM’s Approach and Role in Healthcare
•  How Customers Are Transforming With
Cognitive Computing
5
Topics
•  Introduce Cognitive Computing
•  Why Cognitive Computing in Healthcare?
•  An Explosion of Data and Costs
•  IBM’s Approach and Role in Healthcare
•  How Customers Are Transforming With
Cognitive Computing
6
The Era of Cognitive Computing Will Transform Our Future
Tabulating
Systems Era
Programmable
Systems Era
Cognitive
Systems Era
7
What is Cognitive Computing?
•  Cognitive computing is the simulation of human thought processes in a
computerized model.
•  Cognitive computing involves self-learning systems that use data mining,
pattern recognition and natural language processing to mimic the way the
human brain works. The goal of cognitive computing is to create automated IT
systems that are capable of solving problems without requiring human
assistance.
•  Cognitive computing systems use machine learning algorithms. Such systems
continually acquire knowledge from the data fed into them by mining data for
information. The systems refine the way they look for patterns and as well as
the way they process data so they become capable of anticipating new
problems and modeling possible solutions.
•  Cognitive computing is used in numerous artificial intelligence (AI)
applications, including expert systems, natural language programming, neural
networks, robotics and virtual reality. The term cognitive computing is closely
associated with IBM’s cognitive computer system, Watson.
http://whatis.techtarget.com/definition/cognitive-computing
Medical(Transcrip.on(Discharge(Summary(Sample(#(2:!
Cardiology(Consulta.on(Transcribed(Medical(Transcrip.on(Sample(Reports
!
REFERRING PHYSICIAN: !John Doe, MD!
CONSULTING PHYSICIAN: !Jane Doe, MD!
DATE(OF(ADMISSION:!!MM/DD/YYYY!
HISTORY OF PRESENT ILLNESS: !This (XX)-year-old lady is seen in consultation for Dr. John
!
Doe. She has been under consideration for ventral hernia repair and has a background of aortic
DATE(OF(DISCHARGE:!!MM/DD/YYYY!!
valve replacement and known coronary artery disease. !The patient was admitted with complaints
!
of abdominal pain, anorexia, and vomiting. She underwent a CT scan of the abdomen and pelvis
ADMITTING(DIAGNOSIS:!!Syncope.!
and this showed the ventral hernia involving the transverse colon, but without strangulation. There
!
was an atrophic right kidney. She had bilateral renal cysts. The hepatic flexure wall was thickened.
There was sigmoid diverticulosis without diverticulitis. It has been recommended to her that she
CHIEF(COMPLAINT:!!Ver0go!or!dizziness.!
undergo repair of the ventral hernia. For this reason, cardiology consult is obtained to assess
!
whether she can be cared from the cardiac standpoint.
HISTORY(OF(PRESENT(ILLNESS:!!This!is!an!(XX)<year<old!male!with!a!past!medical!history!of!coronary!artery!disease,!CABG!done!a!few!
PAST CARDIAC HISTORY: !Bypass surgery. She underwent echocardiography and cardiac
years!ago,!atrial!fibrilla0on,!peripheral!arterial!disease,!peripheral!neuropathy,!recently!re0red!one!year!ago!secondary!to!leg!pain.!!The!
catheterization prior to the operation. Echocardiography showed an ejection fraction of 50%. There
pa0ent!came!to!the!ER!for!an!episode!of!ver0go!while!reaching!for!some!books.!!The!pa0ent!was!able!to!reach!the!books,!to!support!self,!
was marked left ventricular hypertrophy with septal wall 1.60 cm and posterior wall 1.55 cm.
Coronary arteriography showed 90% stenosis in the anterior descending artery, situated distally
but!did!not!have!any!syncope.!!No!nausea!or!vomi0ng.!!No!chest!pain.!!No!shortness!of!breath.!!Came!to!ER!and!had!a!CT!head,!which!was!
just before the apex of the left ventricle. Only mild to moderate narrowing was seen elsewhere in
within!normal!limits.!!The!impression!was!atrophy!with!old!ischemic!changes!but!no!acute!intracranial!findings.!!No!focal!weakness,!
the coronary circulation.
headache,!vision!changes!or!speech!changes.!!The!pa0ent!has!had!similar!episodes!since!one!year.!!Peripheral!neuropathy!since!one!year!
CORONARY RISK FACTORS: (Her father had an irregular heartbeat and her brother had a fatal
and!not!relieved!with!mul0ple!medica0ons.!!The!pa0ent!also!complains!of!weight!loss!of!25!pounds!in!the!last!6!months.!!No!colonoscopy!
heart attack. She herself has had high blood pressure for 20 years. She has elevated cholesterol
done.!!Recent!history!of!hematochezia!but!believes!it!was!secondary!to!proc00s!and!secondary!to!decreased!appe0te.!!No!nausea,!
and takes Lipitor. She has had diabetes for 20 years. She is not a cigarette smoker. She does little
vomi0ng,!no!abdominal!pain.!
physical exercise.
REVIEW OF SYMPTOMS: (CARDIOVASCULAR AND RESPIRATORY: !She has no chest pain. She
!
Cardiology(Consulta.on(Transcribed(Medical(Transcrip.on(Sample(Reports(
sometimes becomes short of breath if she walks too far. No cough. She has occasional swelling of
!
her feet. Occasionally, she gets mildly lightheaded. Has not lost consciousness. She tends to be
DATE OF CONSULTATION:! MM/DD/YYYY
PROCEDURES(PERFORMED:!!The!pa0ent!had!a!chest!x<ray,!which!showed!cardiomegaly!with!atherosclero0c!heart!disease,!pleural!
aware of her heartbeat when she is tired. She has no history of heart murmur or rheumatic fever.
REFERRING PHYSICIAN:! John Doe, MD!!!!
thickening!and!small!pleural!effusion,!a!leU!costophrenic!angle!which!has!not!changed!when!compared!to!prior!examina0on,!COPD!
CONSULTING PHYSICIAN: (Jane Doe, MD
GASTROINTESTINAL: !Recent GI symptoms as noted above, but she does not usually have such
paWern.!!The!pa0ent!also!had!a!head!CT!which!showed!atrophy!with!old!ischemic!changes.!!No!acute!intracranial!findings.!
REASON FOR CONSULTATION:( Surgical evaluation for coronary artery disease.!
problems. She has had no hematemesis. She has no history of ulcer or jaundice. She sometimes
HISTORY
OF
PRESENT
ILLNESS:!
The
patient
is
a
(XX)-year-old
female
who
has
a
known
history
coronaryNo
artery
!
has
looseofstools.
constipation and no blood in the stool. GENITOURINARY: !She tends to have
disease.! She underwent previous PTCA and stenting procedures in December and most recently in August.! Since that time,
!
urinary
frequency.
Shesome
gets up once at night to pass urine. No dysuria, incontinence. She has had
she has been relatively stable with medical management.! However, in the past several weeks,
she started
to notice
previous
urinary
infections. No stones noted. NEUROLOGIC: !She has occasional headaches. No
exertional dyspnea with chest pain.! For the most part, the pain subsides with rest.! For this
reason, she
was re-evaluated
CONSULTS(OBTAINED:((A!rehab!consult!was!done.!
with
a
cardiac
catheterization.!
This
demonstrated
3-vessel
coronary
artery
disease
with
a
70%
lesion
to
the
right
coronary
seizures.
No
trouble
with
vision, hearing, or speech. No limb weakness. MUSCULOSKELETAL: !She
!
artery; this was a proximal lesion.! The left main had a 70% stenosis.! The circumflex also tends
had a 99%
stenosis.!
left
to have
jointOverall
and muscle
pains and has a history of gout. HEMATOLOGIC: !No anemia,
!
ventricular function was mildly reduced with an ejection fraction of about 45%.! The left ventriculogram
did
note
some
apical
abnormal bleeding, or previous blood transfusion. GYNECOLOGIC: !No gynecologic or breast
Echocardiogram(Sample(Report:!
hypokinesis.! In view of these findings, surgical consultation was requested and the patient was seen and evaluated by Dr.
PAST(MEDICAL/SURGICAL(HISTORY:!!Posi0ve!for!atrial!fibrilla0on.!!The!pa0ent!had!AVR!6!years!ago.!!Peripheral!arterial!disease!with!
problems.
Doe.
!!
hypertension,!peripheral!neuropathy,!atherosclerosis,!hemorrhoids,!proc00s,!CABG,!and!cholecystectomy.!
PAST MEDICAL HISTORY: !She has had shoulder and hand injuries and has had carpal tunnel
PAST MEDICAL HISTORY:(
DATE(OF(STUDY:!!MM/DD/YYYY!
1.! Coronary artery disease as described above with previous PTCA and stenting procedures.
!
surgery. She has been diabetic and has been on insulin. She has chronic renal insufficiency with
2.! Dyslipidemia.
creatinine around 2.2. She has had hypothyroidism. She has had morbid obesity. She has chronic
!!
!
3.! Hypertension.
obstructive sleep apnea and uses BiPAP. She has had hysterectomy and oophorectomy in the past.
FAMILY(HISTORY:((Posi0ve!for!atherosclerosis,!hypertension,!autoimmune!diseases!in!the!family.!
DATE(OF(INTERPRETATION(OF(STUDY:!!! 4.! Status post breast lumpectomy for cancer with followup radiation therapy to the chest.
Otherwise as noted above.
ALLERGIES:( None.
!
!!
MEDICATIONS:
(Prior
to hospital, she was taking glipizide XL 2.5 mg daily, metoprolol 50 mg
MEDICATIONS:( Aspirin 81 mg daily, Plavix 75 mg daily, Altace 2.5 mg daily, metoprolol 50
mg b.i.d. and Lipitor
10 mg
!
q.h.s.
b.i.d., Cipro 250 mg b.i.d., atorvastatin 40 mg daily, Synthroid 75 mcg daily, aspirin 81 mg daily,
Echocardiogram!was!obtained!for!assessment!of!leU!ventricular!func0on.!!
hadLantus
about a36
35-units
to 40-pack-year
SOCIAL(HISTORY:!!Never!smoked.!!Alcohol!socially.!!No!drugs.! SOCIAL HISTORY:! She quit smoking approximately 8 months ago.! Prior to that time, she
and
daily. Currently, she is taking Lipitor 40 mg daily, Lantus 10 units at bedtime,
The!pa0ent!has!been!admiWed!with!diagnosis!of!syncope.!!Overall,!the!
history.! She does not abuse alcohol.
!
Synthroid 75 mcg daily, metoprolol 50 mg b.i.d., and Zosyn 2.25 grams q.6h.
FAMILY MEDICAL HISTORY:! Mother died prematurely of breast cancer.! Her father died prematurely of gastric carcinoma.!
study!was!subop0mal!due!to!poor!sonic!window.!
SOCIAL HISTORY:
!She does not drink alcohol.
!
REVIEW OF SYMPTOMS:! There is no history of any CVAs, TIAs or seizures.! No chronic headaches.!
No asthma, TB,
PHYSICAL
EXAMINATION:
hemoptysis or productive cough.! There is no congenital heart abnormality or rheumatic fever
history.! She
has no
!!
ALLERGIES:!!NO!KNOWN!DRUG!ALLERGIES.!
palpitations.! She notes no nausea, vomiting, constipation, diarrhea, but immediately priorGENERAL
to admission,
she did develop!She is not currently dyspneic, in no distress. She is alert, oriented, and
APPEARANCE:
FINDINGS:!
!
some diffuse abdominal discomfort.! She says that since then, this has resolved.! No diabetes
or thyroid problem.! There is
pleasant.
no depression or psychiatric problems.! There is no musculoskeletal disorders or history of gout. There are no hematologic
!
!!
HEENT: !Pupils are normal and react normally. No icterus. Mucous membranes well colored.
problems or blood dyscrasias.! No bleeding tendencies.! Again, she had a history of breast cancer and underwent
REVIEW(OF(SYMPTOMS:!!Weight!loss!of!25!pounds!within!the!last!6!months,!shortness!of!breath,!cons0pa0on,!bleeding!from!
No lymphadenopathy. Jugular venous pressure not elevated. Carotids equal.!
1.!!Aor0c!root!appears!normal.!
lumpectomy procedures for this with followup radiation therapy.! She has been followed in NECK:
the past!Supple.
10 years and
HEART:changes
!The heart
rate is
hemorrhoids,!increased!frequency!of!urina0on,!muscle!aches,!dizziness!and!faintness,!focal!weakness!and!numbness!in!both!legs,!knees!
mammography shows no evidence of any recurrent problems.! There is no recent fevers, malaise,
in appetite
or 82 per minute and regular and the blood pressure 132/78. The cardiac
2.!!LeU!atrium!is!mildly!dilated.!No!gross!intraluminal!pathology!is!
changes in weight.
impulse has a normal quality. There is a grade 3/6 ejection systolic murmur heard medial to the
and!feet.!
PHYSICAL EXAMINATION:! Her blood pressure is 120/70, pulse is 80.! She is in a sinus apex
rhythmand
on the
EKG aortic
monitor.!
recognized,!although!subtle!abnormali0es!could!not!be!excluded.!!Right!
at the
area, with well heard radiation to the neck vessels.
!
Respirations are 18 and unlabored. Temperature is 98.2 degrees Fahrenheit.! She weighs 160 pounds, she is 5 feet 4 inches.!
CHEST: !Chest is clear to percussion and auscultation. Normal respiratory effort.
atrium!is!of!normal!dimension.!
In general, this was an elderly-appearing, pleasant female who currently is not in acute distress.! Skin color and turgor are
!
ABDOMEN:
!Soft
and nontender. The presence of a large ventral hernia is noted.
good.! Pupils were equal and reactive to light.! Conjunctivae clear.! Throat is benign. Mucosa
was moist and
noncyanotic.!
3.!!There!is!echo!dropout!of!the!interatrial!septum.!!Atrial!septal!defects!
PHYSICAL(EXAMINATION:!!VITAL!SIGNS:!!Blood!pressure!188/74,!pulse!62,!respira0ons!18!and!satura0on!of!98%!on!room!air.!!General!
EXTREMITIES:
!There is
no edema. Posterior tibial pulses were felt bilaterally, but I did not feel the
Neck veins not distended at 90 degrees.! Carotids had 2+ upstrokes bilaterally without bruits.!
No lymphadenopathy
was
could!not!be!excluded.!
Appearance:!!The!pa0ent!is!a!pleasant!man,!comfortable.!!HEENT:!!Conjunc0vae!are!normal.!!PERRLA.!!EOMI.!!NECK:!!No!masses.!!Trachea!
appreciated.! Chest had a normal AP diameter. The lungs were clear in the apices and bases,
no wheezing
dorsalis
pedis.or egophony
appreciated.! The heart had a normal S1, S2.! No murmurs, clicks or gallops.! The abdomen
was soft,
is!central.!!No!thyromegaly.!!LUNGS:!!Clear!to!ausculta0on!and!percussion!bilaterally.!!HEART:!!Irregular!rhythm.!!ABDOMEN:!!SoU,!
SKIN:
!Nonontender,
rash or significant lesions are noted.
4.!!Right!and!leU!ventricles!are!normal!in!internal!dimension.!!Overall!leU!
nondistended.! Good bowel sounds present.! No hepatosplenomegaly was appreciated.! No pulsatile masses were felt.! No
nontender,!and!nondistended.!!Bowel!sounds!are!posi0ve.!!GENITOURINARY:!!Prostate!is!hypertrophic!with!smooth!margin.!!
LABORATORY AND DIAGNOSTIC DATA: !Electrolytes are normal. BUN and creatinine 18/2.2.
abdominal bruits were heard.! Her pulses are 2+ and equal bilaterally in the upper and lower extremities.! No clubbing is
ventricular!systolic!func0on!appears!to!be!normal.!!Eyeball!ejec0on!
Blood
150. White
count is 7.6, hemoglobin 11.7 with hematocrit 34.9, platelets 187,000.
appreciated.! She is oriented x3.! Demonstrated a good amount of strength in the upper and
lowersugar
extremities.!
Face was
EXTREMITIES:!!Upper!and!lower!limbs!bilaterally!normal.!!SKIN:!!Normal.!!NEUROLOGIC:!!Cranial!nerves!are!grossly!within!normal!limits.!!
frac0on!is!around!55%.!!Again,!due!to!poor!sonic!window,!wall!mo0on!
LFTs were normal. Hemoglobin A1c 7.7. TSH 1.82. Troponin I was normal on three occasions.
symmetrical.! She had a normal gait.
No!nystagmus.!!DTRs!are!normal.!!Good!sensa0on.!!The!pa0ent!is!alert,!awake,!and!!oriented!x3.!!Mild!confusion.!
IMPRESSION:! This is a (XX)-year-old female with significant multivessel coronary arteryChest
disease.!
The patient
also
a
x-ray
showed
anhas
enlarged
heart with postoperative changes, but no evidence of acute
abnormali0es!in!the!distribu0on!of!lateral!and!apical!wall!could!not!be!
!
left main lesion.! She has undergone several PTCA and stenting procedures within the last pathology.
year to year and
half.! At probable
this
EKGa shows
left atrial enlargement. Low voltage QRS, probable inferior wall
excluded.!
point, in order to reduce the risk of any possible ischemia in the future, surgical myocardial revascularization is
!
myocardial infarction and anterior wall infarction, age undetermined.
recommended.!!!!!!!!
5.!!Aor0c!valve!is!sclero0c!with!normal!excursion.!!Color!flow!imaging!and!
LABORATORY(DATA(AND(RADIOLOGICAL(RESULTS:!!WBC!8.6,!hemoglobin!13.4,!hematocrit!39.8,!platelets!207,000,!MCV!91.6,!neutrophil!
ASSESSMENT:
PLAN:! We will plan to proceed with surgical myocardial revascularization.! The risks and benefits
of this procedure were
1. !Aortic valve replacement with bioprosthetic valve. Residual systolic murmur.
explained to the patient.! All questions pertaining to this procedure were answered.
Doppler!study!demonstrates!trace!aor0c!regurgita0on.!
percentage!of!72.6%.!!Sodium!133,!potassium!4.7,!chloride!104.!!Blood!urea!nitrogen!of!18!and!crea0nine!of!1.1.!!PT!17.4,!INR!1.6,!PTT!33.!
2.
!Arteriosclerotic
heart disease with severe stenosis in anterior descending artery, but this is
!
6.!!Mitral!valve!leaflets!are!also!sclero0c!with!normal!excursion.!!Color!flow!
situated distally and subtends only a small mass of myocardium.
!
imaging!and!Doppler!study!demonstrates!trace!to!mild!degree!of!mitral!
3. !Well preserved left ventricular systolic function. The EKG appearance of previous myocardial
The!pa0ent!had!a!chest!x<ray,!which!showed!cardiomegaly!with!atherosclero0c!heart!disease,!pleural!thickening!and!small!pleural!
regurgita0on.!
infarction is probably serious, indicating multiple other medical problems as listed above
effusion,!a!leU!costophrenic!angle!which!has!not!changed!when!compared!to!prior!examina0on,!COPD!paWern.!!The!pa0ent!also!had!a!
and also documented in the chart.
7.!!Tricuspid!valve!is!delicate!and!opens!normally.!!Pulmonic!valve!is!not!
head!CT,!which!showed!atrophy!with!old!ischemic!changes.!!No!acute!intracranial!findings.!
RECOMMENDATIONS: !It appears that she does not wish to proceed with the
clearly!seen.!!No!evidence!of!pericardial!effusion.!
!
surgery at this time, and if such surgery is not !
!!
!
HOSPITAL(COURSE(AND(TREATMENT:(!This!is!an!(XX)<year<old!male!with!syncope.!
CONCLUSIONS:!
1.!Syncope.!!This!may!be!secondary!to!ques0onable!cerebral!ischemia/atrial!fibrilla0on/hypotension,!so!Neurology!was!kept!on!board!
!!
and!the!pa0ent!was!scheduled!for!a!caro0d!Doppler!and!a!2<D!echo.!!Orthosta0cs!were!ordered.!!Vitamin!B12,!TSH,!free!T4!and!T3!were!
1.!!Poor!quality!study.!
ordered!along!with!cor0sol!level!in!the!morning.!!FOBT!x3!were!done!and!cardiology!followup!as!outpa0ent.!!The!pa0ent!had!a!caro0d!
Unstructured data is messy but
filled with key medical facts
Medications, diseases, symptoms, nonsymptoms, lab measurements, social history,
family history … and much more
Real Language is Real Hard
Chess (Traditional Computing)
•  Finite, precise and mathematically well-defined
•  Limited number of moves and states
•  Grounded in explicit, unambiguous
mathematical rules
Human Language
•  Ambiguous, contextual and implicit
•  Contains slang, riddles, idioms, abbreviations,
acronyms, negation and more
•  Grounded only in human cognition
•  Seemingly infinite number of ways to express
the same concepts and meaning
10
Remember to Answer in the Form of a Question …
In May 1898 Portugal celebrated
the 400th anniversary of this
explorer’s arrival in India
11
Answering Complex Natural Language Questions
Requires More Than Keyword Based Evidence
In May 1898 Portugal celebrated the
400th anniversary of this explorer’s
arrival in India
In May, Gary arrived in India after
he celebrated his anniversary in
Portugal
Legend
Keyword “Hit”
arrived in
Reference Text
celebrated
celebrated
Answer
Red Text
In May
1898
In May
400th
anniversary
anniversary
Portugal
in Portugal
arrival in
India
explorer
12
Weak evidence
India
Gary
This evidence suggests
“Gary” is the answer
BUT the system must
learn that keyword
matching may be weak
relative to other types of
evidence
Just Like The Human Brain … Watson Leverages
Multiple Algorithms to Gather Deeper Evidence
In May 1898 Portugal celebrated the
400th anniversary of this explorer’s
arrival in India.
On the 27th of May 1498, Vasco da
Gama landed in Kappad Beach
Legend
Temporal Reasoning
Statistical Paraphrasing
celebrated
GeoSpatial Reasoning
landed in
Reference Text
Portugal
Answer
May 1898
400th anniversary
arrival in
27th May 1498
Date
Match
Stronger evidence can
be much harder to find
and score …
Paraphrases
§  Search far and wide
§  Explore many hypotheses
§  Find judge evidence
India
explorer
13
Geo-KB
Kappad Beach
Vasco da
Gama
§  Many inference algorithms
… and the evidence is still
not 100% certain
Topics
•  Introduce Cognitive Computing
•  Why Cognitive Computing in Healthcare?
•  An Explosion of Data and Costs
•  IBM’s Approach and Role in Healthcare
•  How Customers Are Transforming With
Cognitive Computing
14
Numerous Innovations in Healthcare for 100+ Years
•  First Related Research
Published in 1957
•  First NLP Solution in Healthcare in 1997
•  Mapping the Human Genome in 2005
•  Watson Wins on Jeopardy! in 2011
TED: Cognitive
Computing Video
Leading Institutions Recognize The Promise and Value
of Watson ...
Ongoing Training
Partner
Watson for Oncology,
trained by Memorial Sloan
Kettering
available in clinical use in
lung, breast, colon and
rectal cancer
Bumrungrad
International Hospital
5 year agreement for
Watson for Oncology
MD Anderson
Introduced proprietary
solution with Watson for
clinical use for Leukemia
and Molecular Targeted
Therapies
Baylor College of
Medicine
Published results of use with
Watson Discovery Advisor –
identified 7 targets for P53
activation within weeks
Watson Genomics
Advisor
Secured 13 Cancer and
Academic medical centers
for beta testing
Department of Veterans
Affairs
Selected Watson to analyze
EMRs in a demo project
© 2015 International Business Machines Corporation
Mayo Clinic
Completed testing with
Clinical Trial Matching for
lung, breast, colon and
rectal cancer
Mayo Clinic
Selected Watson to analyze
EMRs for Clinical Efficiency
and Effectiveness Program
17
IBM Watson Solutions for Healthcare and Life Sciences
"Imagine having the ability within three seconds to look through all of that (medical) informa5on … at the moment you're caring for that pa5ent.” Dr. Sam Nussbaum, WellPoint's Chief Medical Officer, Anthem (formerly WellPoint) R&D Produc5vity Improve Outcomes Improve Engagement Discovery Advisor to enable researchers to uncover new insights into relaBonships between genes, proteins, pathways, phenotypes and diseases Clinical Trial Matching to opBmize paBent selecBon and recruitment for clinical trials Oncology to assist in the creaBon of individualized treatment plans and enhance paBent / physician experience Engagement Advisor to transform interacBons and experiences with paBents and physicians EMR Advisor to idenBfy criBcal a#ributes of a paBent case and provide easy-­‐to-­‐
consume summaries U5liza5on Management to streamline and automate authorizaBons and ensure adherence to guidelines IBM Watson Content Analy5cs Core NLP soluBon plaMorm for extracBng and leverage medical facts from unstructured data Paths Clinical reasoning for Medical EducaBon & top of license care delivery Healthcare Transformation: A Work in Progress
1st <5 $585B 37th 21.7 $7T+ US rank in Healthcare spending 1 US rank in quality of care delivered 2 73 … the number of days it will take for medical data to double by 2020 4 1 
2 
3 
4 
Hours or less per month spent reading medical journals by 81% of reporBng physicians Hours required to meet the paBent care guidelines each day 3 (Billion) Wasted on missed opportuniBes, unnecessary, error-­‐prone and inefficiently delivered services 3 The cost for health and social programs worldwide … and it is rising 80% of the world’s healthcare data is unstructured World Health Statistics 2011 from World Health Organization
The World Health Report 2000 – Health Systems: Improving Performance from World Health Organization
Best Care at Lower Cost: The Path to Continuously Learning Health Care in America from Institute of Medicine / National Academy of Sciences
University of Iowa, Carver College of Medicine 2014
An Ocean of
Unused Data
The Current Spending Projections Are Not Sustainable
Healthcare as % of US GDP
US National Health Expenditure
Source: Centers for Medicare and Medicaid Services
Leveraging Big Data – The Impossible Task Without
Analytics and New Computing Models
Facts per Decision 1000 Internet of Things (Exogenous Data) The Human Genome (Genomic Data) 100 Electronic Health Records (Clinical Data) 10 Human Cogni7ve Capacity 1990 2000 2010 2020 Capturing the Value of Big Data: Big Changes Ahead 21 Personal Data is Exploding
Impact on a person’s
health status
In their lifetime, the
data an average
person will generate
Exogenous Factors
1,100 TB
60%
Environment & Social
Context, Behavior
Genomic Factors
30%
Clinical Factors
10%
© 2015 International Business Machines Corporation
Volume, Variety, Velocity,
Veracity
Educational records,
Employment Status, Social
Security Accounts, Mental
Health Records, Caseworker
Files, Fitbits, Home Monitoring
Systems, and more…
6 TB
Volume
0.4 TB
Variety
Electronic Medical / Health
Records, Physician Management
Systems, Claims Systems and
more…
Enormous Opportunity to Leverage Big Data
A Decade of Reversal: An Analysis of 146 Contradicted Medical Prac5ces “40.2% reversed the original standard of care … and only 38.0% reaffirmed the original standard of care” Medicine has become too complex (and only) about 20% of the knowledge clinicians use today is evidence-­‐based.” Steven Shapiro, Chief Medical and Scien5fic Officer, UPMC Is This Really an Opportunity?
“Before The Beginning of Great Brilliance … There Must Be Chaos” Chinese Proverb Unsustainable
Operating Models
Diagnosis and
Early Intervention
Late
Late Stage/
Stage
Co-Morbidity
Co-Morbidity
Mgmt.
Disease Maintenance
Unfathomable
Information Volumes
1000#
Facts#per#Decision#
Wellness
Internet#of#Things#
(Exogenous#Data)#
The#Human#Genome#
(Genomic#Data)#
100#
Electronic#Health#Records#
(Clinical#Data)#
10#
Human#Cogni7ve#Capacity#
1990#
The Need for Better
Outcomes
2000#
2010#
2020#
An Ocean of
Unused Data
Topics
•  Introduce Cognitive Computing
•  Why Cognitive Computing in Healthcare?
•  An Explosion of Data and Costs
•  IBM’s Approach and Role in Healthcare
•  How Customers Are Transforming With
Cognitive Computing
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Healthcare Industry Taps
Into the Power of Watson
New York Genomics
Center and IBM Watson
Big Data Analytics and Cognitive Computing Enable
New Insights and Engagement
Wellness
Diagnosis and
Early Intervention
Disease Maintenance
Late
Late Stage/
Stage
Co-Morbidity
Co-Morbidity
Mgmt.
Engagement
•  Enable providers to act on meaningful insights
•  Drive to outcomes: monitor results and payment flows,
benchmark performance
Insights (Cognitive and Data Driven)
•  Real-world evidence improves care pathways and service delivery
•  Combine personal and population health data with new sources
•  Apply advanced analytics and cognitive computing for transformational insights
Data
•  Structured and unstructured
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Integrated Care Approaches Improve Health and
Reduce Costs
Costs
Address the whole patient with
proactive approaches across the
continuum of care
Costs increase due to:
•  Aging
populations
•  Chronic
disease
•  Complex
conditions
Unchecked, costs increase across the continuum of care
Wellness
Proactive,
evidence-based
approaches
Promote healthy
behaviors
© 2015 International Business Machines Corporation
Diagnosis and
Early Intervention
Proactive
early
detection
Disease Maintenance
Best
practice
care
protocols
Out
patient
support
Late Stage,
Stage/
Co-Morbidity
Co-morbidity
Mgmt.
Care management
for complex
conditions
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What Is IBM Doing in Healthcare?
•  Long history of selling to Information Technology infrastructure (systems, software and
service) to Healthcare, Life Sciences and Government customers
•  IBM Research focuses on “Healthcare Informatics” (2010) to develop next generation
healthcare analytics such as “Patient Similarity Analytics”
•  IBM forms IBM Watson Group (post-Jeopardy 2011) to commercialize Watson –
Healthcare is first industry chosen to focus on for suite of new solutions
•  IBM makes acquisitions (2011) specific to support specific Healthcare and
Government solutions
Master Patient Index
Social Program and Care Management
•  IBM forms Watson Health Group with multiple acquisitions, partnerships and new
health cloud capabilities and offerings:
Patient Engagement
PCMH Focus, 40M Lives
Big Data Analytics,
Applications, 50M Lives
Ranking'of'Strength'of'Model'Variable'
Value of Unstructured Data and
Social Determinants
The Data We Thought Would Be Useful … Wasn’t
18"
17"
16"
15"
14"
13"
12"
11"
10"
9"
8"
7"
6"
5"
4"
3"
2"
1"
0"
0"
1"
2"
3"
4"
5"
6"
Projected'Odds'Ra9o'
18"
9"
17"
8"
16"
7"
15"
6"
14"
5"
13"
4"
12"
3"
11"
2"
10"
1"
•  Structured data not available, not accurate, without the unstructured data - which was more trustworthy
What We Thought Was Causing 30 Day Readmissions … Wasn’t
•  113 possible candidate predictors expanded and changed after mining the data for hidden insights
New Hidden Indicators Emerged … Social Determinants Were Essential
•  Social indicators were important to identifying patients most at risk (most came from unstructured data)
1. Jugular Venous Distention Indicator
2. Paid by Medicaid Indicator
3. Immunity Disorder Disease Indicator
4. Cardiac Rehab Admit Diagnosis with CHF Indicator
5. Lack of Emotion Support Indicator
6. Self COPD Moderate Limit Health History Indicator
7. With Genitourinary System and Endocrine Disorders
8. Heart Failure History
9. High BNP Indicator
10. Low Hemoglobin Indicator
11. Low Sodium Level Indicator
12. Assisted Living
13. High Cholesterol History
14. Presence of Blood Diseases in Diagnosis History
15. High Blood Pressure Health History
16. Self Alcohol / Drug Use Indicator
17. Heart Attack History
18. Heart Disease History
Predictor Analysis
% Encounters
Structured Data
% Encounters
Unstructured Data
Ejection Fraction (LVEF)
2%
74%
Smoking Indicator
35%
(65% Accurate)
81%
(95% Accurate)
Living Arrangements
<1%
73%
(100% Accurate)
Drug and Alcohol Abuse
16%
81%
Assisted Living
0%
13%
The Impact – What Happened to Patient X?
PaBent X was hospitalized 6 5mes over an 8 month period. The same basic informaBon was available at each encounter and PaBent X’s readmission predicBon score never dropped below 95% (out of possible 100%) 98% 96% 98% 24 days Apr-­‐18-­‐2009 8 days May-­‐12-­‐2009 May-­‐20-­‐2009 96% 95% 144 days 44 days Oct-­‐11-­‐2009 100% 26 days Nov-­‐24-­‐2009 Dec-­‐20-­‐2009 Individual PaBent Data at Each Encounter (PaBent X @ Dec 20, 2009) PaBent PopulaBon Monitoring Clinical and OperaBonal Data Admit / Readmission 30-­‐Day Readmission MD Anderson Cancer
Moonshot
Smarter Care and Social Programs
IBM Cúram
Thank You
Craig Rhinehart
Director, IBM Watson Health Strategy and Market Development
[email protected]
Find out more about IBM Watson Health
http://www.ibm.com/smarterplanet/us/en/ibmwatson/health/
Visit my blog or follow me on Twitter
http://craigrhinehart.com
@CraigRhinehart
33
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2014
IBM Corporation
©
Corporation
© 2015
2013IBM
Corporation