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1
Health Informatics
Prof. Timothy Bickmore
Health Informatics
US Healthcare Industry $2T/year
Much of the industry (especially delivery) remains in the dark ages of computing.
2
Pre-Computer Medical Information Processing
Paper-based Medical Records
19th century as a personalized “lab notebook” / memory aide
Electronic Medical Recordsaka Electronic Health Recordsaka Computerized Patient Record Sys
Data acquired and created during a patient’s course through the healthcare systemElectronically maintained informationLifetime healthIntegrated, managed, within reminders, alerts, and linkagesShared among all health providers
3
Integrated EMR
Example EHR – VA VistAVA cares for 26.5M US vets – largest provider in USVeterans Affairs Information System Technology and Architecture.Developed in early 1980s adopted by VA, DOD, HIS and a Finnish consortium.M-based application.Separate application packages: scheduling, pharmacy, text integration, radiology, lab, etc.
4
5
6
But… as of 2005
24% penetration of EMRs in outpatient clinics.5% of hospitals used computerized physician order entry
7
Major Areas of Health Informatics
Medicine (Physician & Nurse)Public healthInsurance & AdministrationResearch (e.g., health services)BioinformaticsConsumer Informatics
Behavioral Informatics
Top 10 Accomplishments in Medical Informatics ACMI ‘00
1. MEDLINE2. UMLS3. Integrated clinical decision support systems 4. MUMPS5. QMR, MYCIN, etc.6. EMR systems7. Visible Human, Digital Anatomist8. HL-7 9. General problem solving methods10. Human genome project’s data
8
UMLS Semantic Network
The Future (2008)(Greenes & Lorenzi ’98, JAMIA 5(5))
Deep integration of information technologiesAll research & collaboration mediated through digital information
Enterprise is fully networkedAnnual checkup: provider and patient review health logs and record of use, discuss patient’s understanding of health information, and model alternative health mgt strategies for the coming year
Health Care DeliverySystemic cost-effectiveness constant focus Delivery of care in ambulatory setting or home (telemed)
9
Consumer & Behavioral Informatics
Trends
As we do a better job of keeping people alive…
People live longerShift from acute to chronic care
As we do a better job controlling costs…Shift from inpatient to outpatient care
Projections indicate significant shortages in doctors and nurses in the future
10
(One) Motivation for Consumer Informatics
“I Have a Chronic Condition”
15%
24%
35%
58%66%
0%
10%
20%
30%
40%
50%
60%
70%
18-29 30-39 40-49 50-64 65+Chronic Illness and Caregiving Survey, Harris, 2000
Percentage of Americans Saying…
11
Medical Regimen Adherence
Medication adherence rates in monitored clinical trials range from 43%-78% (overall average ~50%).Rates drop for polypharmacy.33-69% of all medication-related hospitalizations are due to non-adherence, costing $100B/y30-80% of adults in US have functional health literacy problems
In 2000, Tobacco use leading cause of death, killing 435,000 people, or 18.1% of everyone who died (CDCP, 2004 Web site) Poor diet and physical inactivity caused 400,000 deaths, or 16.6% of the total (up 100,000 deaths since 1990)64% of the population, is overweight or obese, putting them at higher risk of heart disease, diabetes, some types of cancer Obesity & overweight cost the nation $117 billion in 2000 In 1998, the cost of obesity was about 78.5 billion which was 9% of the total annual US medical procedures (Finkelstein et al 2003)According to Rand Corporation that if Americans continue to get fatter at current rates, by 2020 about one in five health care dollars spent on people aged 50 to 69 could be due to obesity – 50% more than now.
“Lifestyle health behavior”
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Ramifications
People will need to take more responsibility for their own care.But, they can’t even take their medicine as prescribed, let alone stop smoking or avoid sun exposure, or eat well, or exercise…
Can technology help?
13
Behavioral Informatics
“the study of the uses of information and communication technologies by patients and health care providers as well as the study of the design, implementation, and evaluation of behavior change interventions delivered through advanced technologies...”
SBM Behavioral Informatics SIG
Early ExampleEarly example: tailored printInformation acquired from userInformation in letter or pamphlet is tailored based on
Stage of change (for example)Progress since last assessment
Several interventions and studies completed since 1990
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Tailored print - resultsReview of the literature - 6 out of 9 computer based materials had positive effects (p<.10). (Strecher, 1999)Tailored print material resulted in higher cessation rates for light-mod smokers vs. non-tailored material (Strecher, 1994)Prochaska and colleagues (2001) compared tailored print vs. tailored print plus telephone counselor vs. counselor only.
tailored + counselor outperformed tailored alone at 0,6, 12 but not 18 month. At 18 months the tailored print had abstinence rates of 23.2%
Some Other Examples of Behavioral Informatics
Intelligent biomedical devicesOn-line support groupsAutomated therapyPedagogical dramaWeb-based content
15
Focus
Automated Systems that interact directly with patients using natural language to achieve health behavior change
Allows application of widest range of behavior change theories to widest range of patientsLowest cost (no provider in the loop)Most analogous to “gold standard”
Example –Telephone Linked Care (TLC)
• Series of studies by Dr. Robert Friedman and colleagues at Boston University• Since 1990’s
16
Telephone Linked Care
TLC
EMR
CMSServer
DB
CMSClient
Applied To• Exercise adoption• Smoking cessation• Diet (general, low fat)• Weight management• Antidepressant adherence• Mammography screening• Alcohol use screening• Hypertension med adherence• Angina Pectoris management• CHF management• COPD management• Asthma management• Diabetes management• Depression management• High risk pregnancy mgt• Chronic disability mgt• Alzheimer’s caregiver support
17
Typical TLC Conversation
Asks Questions of the UserTLC Comments on User’s Responses to Its QuestionsProvides Information to UserCounsels UserGoals and/or Homework is setPrevious Goals / Homework is reviewed and adjusted
HUMAN TLC
* p < .04 vs. Control
Control
Baseline
6 mos.
Mod
+ A
ctiv
ity (
min
/wk)
0
30
60
90
120
150
180
210(186)
(170)
(101)
TLC-Physical Activity
(122)
(164)
(183)
12 mos.
King AC, Friedman RH, et al. Annals of Behavioral Medicine. Spring 2003
****
18
Health Buddy
State of the Art:Scripted Interactions
Scripts written by teams of expertsRepresented as flow charts or Augmented transition networksImplemented as state machines / ATNs / VXML
GetCommitment
GC_6
I'm going to workout at the gym.
Great. How much aerobic exercise do you plan to do?
GC_4
X again?
No
How long do you plan to play for?
Yes
GC_END
Great. How long do you plan to go for?
GC_7
I'm going to go for a walk.
Great. How long do you plan to go for?
GC_8(null)
(below exp)
(at exp)
Yes
Do you think you can go for X minutes?Do you think you can increase your time a little today/tomorrow?Can you keep up the same time as yesterday/etc?
GC_12(null)
GC_10
if REL & know location
No
yes
Where are you going to walk?
Are you going to (location X) again?
Who?
(if REL & know buddy)
(else)
No
Yes
yes
No
(loner)
MotivateDuration
No
MotivateToExercise
GC_1(null)
I'm going to play a sport.
if REL & know sport
GC_2
GC_3
GC_5
GC_9
GC_11
GC_13
GC_14
GC_15
What kind of exercise are you going to do?
Are you going to workout tomorrow?
Yep
GC_START(null)
Are you going to get some [more] exercise today?
(time2bed<2)
(time2bed > 2)
no yes
GC_16
GC_17
GC_18
Something else.
(TEXTENTRY)What kind of exercise?
GC_19
Great.
Which one?
Are you going to gowith X again?
Are you going togowith anyone?
I can't
Is it becuaseof your illness/injury?
(no illness/injury)
(illness|injury)
Yes
No
GC_19
GC_20
GC_21
GC_22
(above exp)
No, I really want to.OK
You shouldn't try to do somuch so soon... How about
X minutes this time?
OK, but you should tryto increase gradually..
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(some) Research inBehavioral Informatics
Helping Relationships
Therapeutic/Working alliance has significant effects on
Client satisfactionClient adherenceOutcomes
Most importantfactor in buildingalliance is providerempathy
20
Embodied Conversational Agents(ECAs)
Emulate human face-to-face conversationFocus on nonverbal communicative behavior
Hand gestureGazeEyebrow and head motionPosture shiftsIntonationFacial display
Relational Behavior
Health CommunicationIdentifying empathic opportunities
PsychotherapyUnconditional positive regardEmpathic listening
Social Psychology Social penetration theory / self-disclosureMeta-relational communicationContinuity behaviors
SociolinguisticsPoliteness theory
Linguistics / Conversation Analysis
Structure & function of social dialogue
CommunicationComforting behaviorNonverbal immediacy behavior
Change Over TimeIncreasing common groundIncreasing intimacyDecreasing politeness
21
Geriatric FitTrack Study
H1 – Older adults will accept, use and enjoy the relational agent system.
H2 – Users will perform more physical activity compared to a control group.
BickmoreCHI ‘05
22
Study Protocol
BMC – South Boston Safety Net HospitalTwo month daily contact interventionSubjects referred from geriatric clinicStand-alone computer & table providedControl: standard-of-care (brochure)Measures
Pedometer readings (steps)Likert scale questions about system & LauraComputer logsDemographics & SF-12Semi-structured interviews
Subjects
Randomized 10 to RELATIONAL 11 to CONTROL
2 men, 19 womenAge 63-85 (mean 74)76% African American77% Overweight or Obese86% Low Reading Literacy
38% Never Used a Computer (50% in REL)29% Used Computer a “Few Times”
23
Results: Ease of Use
Easy Difficult1 2 3 4 5 6 7
“That is so easy. That is so good. Regular computers I don't do. But, that was so easy, even a baby could do that.”
1.9
Results: Satisfaction
Satisfaction with Laura
Not at all Very1 2 3 4 5 6 7
5.4
Desire to Continue
Not at all Very1 2 3 4 5 6 7
6.4
Satisfaction with Overall System
Not at all Very1 2 3 4 5 6 7
6.3
24
Results: Relationship with Laura
Liking of Laura
Not at all Very1 2 3 4 5 6 7
6.3
Relationship with Laura
Stranger Close Friend
1 2 3 4 5 6 7
5.6
6.4
Trust in Laura
Not at all Very1 2 3 4 5 6 7
Results: Impressions of Laura
Friendly
Not at all Very1 2 3 4 5 6 7
6.8
Repetitive
Not at all Very1 2 3 4 5 6 7
4.8
Understands Me
Not at all Very1 2 3 4 5 6 7
5.4
25
Results: Walking
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
0 2 4 6 8 10
R
Week
Ste
ps W
alke
d
RELATIONAL
CONTROL
Difference In slopes p=.004
Geriatrics Study Results
H1: Most subjects liked the system & Laura“I enjoyed her, I enjoyed Laura, and I'm quite sure somebody else would.”
H2: Intervention subjects performed more physical activity.
“It was the best thing that happened to me, to have something that pushed me out and get me walking.”
Continuing work under NSF CAREER grant.
26
Just-in-Time Informationfor Exercise Adoption
NLM R21
Why Wearable?
Available at time and place of need
With integrated sensors ⇒Able to initiate interactionAble to conduct context-tailored interaction
Better relationshipAvailability & Contact time
27
Just In TimeField Study
Research questions:Is intervening at the moment of decision making more effective than at the end of the day?Is a relational agent more effective than text?
28
PDA-based Health AdvisorDesign Studies
Modality StudyTask Interruption Studies
Modality Study
Compared 4 modalities:Text onlyText + Static agent imageAnimated agentAnimated agent + nonverbal sounds
Backchannels, Discourse markers, etc.
29
Modality Study
Animated agent also scored higher (approaching significance) on credibility of health information and comfort using in the workplace.
11.5
22.5
33.5
44.5
5
TEXTIMAGE
ANIMFULL
WAI (p=.008)
11.5
22.5
33.5
44.5
5
TEXTIMAGE
ANIMFULL
WAI (p=.008)
11.5
22.5
33.5
44.5
5
TEXTIMAGE
ANIMFULL
CARING (p<.05)
11.5
22.5
33.5
44.5
5
TEXTIMAGE
ANIMFULL
CARING (p<.05)
Task Interruption and Health Regimen Adherence
30
Cueing
aka Stimulus ControlBehavioral Technique Presenting a conditional stimulus to perform a desired health behaviorUsed by most people changing health behaviorOne of the most effective techniques
Task Interruption
31
Research Question
What is the best way to interrupt someone at work get them to perform a healthy behavior?
Hypotheses
Politeness
Shor
t-ter
m C
ompl
ianc
e
Politeness
Long
-term
Usa
ge
Politeness
Long
-term
Adh
eren
ce
32
Experimental Design
Series of Studies with Common Framework
Primary task: web browsing & typing on PCSecondary task: “wrist rests”
Experimenter: motivates performance of primary taskAgent: interrupts periodically and motivates performance on secondary task
Experimental DesignMeasures
Manipulation checkSelf-reported politeness/annoyingness of agent
Short-term complianceRest timeSelf-reported effectiveness of agent
Long-term adherenceSelf-reported desire to continue
Attitude towards agentLiking, satisfaction, comfort, etc.
33
Studies
Each 4-treatment counterbalanced within-subjects designEach treatment:
Intro dialog with agentWork at primary task for 10 minutesAgent interrupts twice and asks them to take a wrist rest
Studies
Study 1: Vary politeness of interrupt audio tone
4 tones pre-tested on annoying-polite scale
AUDIO1 AUDIO2 AUDIO3 AUDIO4
34
Studies
Study 2: Compare 4 methods from literature on task interruption
BaselineForewarningNegotiated (“snooze” button)Social
More chatty/empathetic introApologize for interrupt Ask how feeling & empathize
Sorry to interrupt, but it’s time for your next rest. …How stressed are you feeling right now? …Sorry to hear…
Participants
Study 1N=2952% female, 83% students, aged 18-30 StageOfChange: preparation (but wide variation)
Study 2N=16Demographics identical
35
Results – Study 1Self-report Measures
1
2
3
4
5
6
7
AUDIO1 AUDIO2 AUDIO3 AUDIO4
Mea
n R
atin
g
P OLITEANNOYINGSATISFIEDCONTINUECOMFORTLIKE
N=29
Results – Study 1Behavioral
10
11
12
13
14
15
16
17
18
19
20
AUDIO1 AUDIO2 AUDIO3 AUDIO4
Res
t Tim
e (s
econ
ds) T1 (n.s.)
T2 (p<.05)
Rest Time
3.2
3.25
3.3
3.35
3.4
3.45
3.5
3.55
3.6
3.65
3.7
3.75
AUDIO1 AUDIO2 AUDIO3 AUDIO4
Prim
ary
Task
s Com
plet
ed
(n.s.)
Primary Tasks
36
Conclusions – Study 1
Politeness was perceivedPoliteness / Long-term Adherence relationship confirmedPoliteness / Short-term Compliance relationship more complex
Hypothesized relationship seems to hold on first exposure, but not significantBy second exposure, may be seeing longer-term effects of very annoying => non-use relationship
Results – Study 2Self-report Measures
1
2
3
4
5
6
7
BASELINE FOREWARN NEGOTIATED SOCIAL
Mea
n R
atin
g
ANNOYPOLITEEFFECTIVECONTINUE
(a.s.)
N=16
37
Results – Study 2Behavioral
15
17
19
21
23
25
27
29
31
BASELINE FOREWARN NEGOTIATED SOCIAL
Res
t Tim
e (s
econ
ds)
T2 (n.s.)
T1 (a.s.)
Rest Time
3.5
3.7
3.9
4.1
4.3
4.5
4.7
4.9
BASELINE FOREWARN NEGOTIATED SOCIALPr
imar
y Ta
sks C
ompl
eted
Primary Tasks
(p<.001)
Conclusions – Study 2SOCIAL was most polite; FOREWARN least.
FOREWARN had greatest compliance on first exposure, but lowest on second (similar to AUDIO4).
Desire to CONTINUE greatest for SOCIAL; lowest for BASELINE. SOCIAL resulted in greatest compliance (T2, but n.s.) NEGOTIATED had high levels of compliance AND low disruption to primary task.Conclusion: Combination of Social & Negotiated may be best
38
Overall Conclusions
Politeness important for maintaining long-term adherence (desire to continue use).Social/empathic behavior important for maximizing compliance.
Next Steps
Manipulate social distanceBrown & Levinson Politeness Theory predicts less politeness will be acceptable
Combine with contextual informationLongitudinal trials
39
In collaboration with Boston Medical Center
Funded by NHLBI
“Virtual Nurse”
Hospital DischargeHospital Discharge is a ‘Transition’ leading to:High rates of medical errorsBy 30-days:-- 20% Adverse Events (1/3 preventable)-- 17% Visit ED-- 19.7% Rehospitalized
Problem
40
Are Patients Well Prepared For
Discharge?
Of post-hospital patients:
37.2% able to state the purpose of their medications
41.9% able to state their diagnosis
Mayo Clinic ProceedingsAugust 2005; 80(8):991-994
Principles of the Re-Engineered Hospital
Discharge
Ten discrete, mutually reinforcing, components:
Patient EducationReconcile Discharge Plans with National GuidelinesOutstanding Tests and StudiesMedication ReconciliationPost Discharge ServicePhysician AppointmentsWhat to do if a problem arisesAssess understandingDischarge Plan to Pt and Summary to PCPTelephone re-enforcement
41
Adopted by the National Quality Forum as one of 30 "Safe Practices" (SP11)
Passed period of public comment (by the several thousand hospitals involved) and is now awaiting approval by the executive committee.
AHRQ-funded study now underway at BMC to evaluate manual implementation of this practice.
Current Status
Automated Discharge Nurse
NHLBI-funded study: Automate the Discharge Education Process to make the practice easier to disseminate
Focus on chronic cardiopulmonary diseasesEnsure reach to patients with low health literacy
Review with patient prior to hospital discharge:Medical conditionMedications & regimenetc
Confirm comprehensionRelay questions to human nurseFollow-up reminders with IVR system
42
Planned Study (’07-’09)
Automated DA
Control
Human DA Total N=760
• Outcomes: AEs, ED visits, hospital re-admits • Substudies: relational behavior (“bedside manner”)
ethnic concordance
43
Medication Adherence for Young Adults with Schizophrenia
Funded by Eli Lilly Pharmaceuticals - In collaboration with University of Pittsburgh School of Nursing
30 day interventionPilot study: 20 subject quasi-experimental trial
Trust & Social support especially importantIntervening on 3 behaviors in parallel
Medication adherence (one tracked med)System usePhysical Activity
Conclusion
• Behavioral informatics is an important interdisciplinary area of research.
• More [email protected]/home/bickmore/