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Health IT Summit Atlanta 2014 - Keynote Presentation "Big Data, Value Analysis and Population Health...
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Transcript of Health IT Summit Atlanta 2014 - Keynote Presentation "Big Data, Value Analysis and Population Health...
©2014 MFMER | 3338355-1
Ryan Uitti, M.D.Deputy Director, Kern Center for the Science of Health Care Delivery
IHT2– April 16, 2014
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The Science of Hitting – Ted Williams
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The Science of Hitting – Ted Williams
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Use of Home Telemonitoringin the Elderly to Prevent Readmissions
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Comparison:Telemonitoring + Versus Usual Care
Telemonitoring InterventionRN/MD team oversaw apx 100patients and communicatedwith them via phone or video-conference if alerts aroseDaily telemonitoring sessions(5-10 minutes) includingweekends and holidaysCollected weight, blood pressure,blood sugar, pulse and peak flow dataCould arrange outpatient visits
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Results: Telemonitoring +Versus Usual Care
Telemonitoring +Telemonitoring + Usual CareUsual Care StatisticsStatistics
Emergency Dept Visits
35% 28% No difference
Hospitalization 52% 44% No difference
ED + Hospitalization
64% 57% No difference
Note: Results are for a one-year period
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Results: Telemonitoring +Versus Usual Care
Telemonitoring +Telemonitoring + Usual CareUsual Care StatisticsStatistics
Emergency Dept Visits
35% 28% No difference
Hospitalization 52% 44% No difference
ED + Hospitalization
64% 57% No difference
Deaths 15% 4% Very significant
Note: Results are for a one-year period
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Epilogue – What Next?
Not ready for prime-time
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Center for the Scienceof Health Care Delivery
Improve patient health experience
Improve population health
Improve quality, control cost
Improve medical practice throughanalysis and scientific rigor
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Value Framework
Patient
Provider Payer
Quality
Cost over time(outcomes, safety, service)
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Quality Quality MeasuresMeasures
PatientPatientSatisfactionSatisfaction
CostsCosts
Big DataBig Data Health andHealth andQuality of LifeQuality of Life
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Value:In the Eye of the Beholder The importance
of reflecting andrespecting multipleperspectives
Appreciating whatwe don’t know aboutthe care experience
Embracing multipleaims for improvement concurrently
Source: Bellows J, Sullivan MP. Could a quality index help us navigate the chasm? http://xnet.kp.org/ihp/publications/docs/ quality_background.pdf. Accessed July 11, 2012.
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Patient Patient SatisfactionSatisfaction
CostsCostsQuality Quality MeasuresMeasures
Big DataBig Data Health andHealth andQuality of LifeQuality of Life
Example: AWARE
Quality
Cost over time(outcome, safety, service)
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Critical Care – Quality Care Crisis
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Critical Care UnitSituational AWAREness
DATA
Analytics
Metrics Outcomes
Thousandsof data points
About 200 actions/day
1.7 errors/day
29% potentiallyserious injury
or death
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Paradigm ShiftsClinical Management – EMR
Developed by intensivists
Organ/system based information organizer
DatabaseDatabasecentered centered
Provider Provider centeredcentered
PatientPatientcenteredcentered
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Provider Built
Fieldobservation
Surveys &interviews
Workflow &workshops
Simulatedtests
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AWARE GoalsBetter Care>90% adherence to best ICU practices
DVT prophylaxis Stress ulcer prophylaxis Lung protective mechanical ventilation Daily assessment of – continuous
sedation; ventilator weaning; needfor intravascular devices and urinary catheter; physical therapy goals
Better Health50% reduction of preventableICU complications5% increase in discharge homevs other health care facilityLower CostCumulative $$ decrease up to 20%– length of ICU stay; length of hospitalstay; resource utilization
AreasAdministrative
PatientClinical
DoeDoeJohnJohn0-000-0000-000-000
DoeJane0-000-000
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DoeJane0-000-000
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DoeJane0-000-000
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DoeJane0-000-000
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DoeJane0-000-000
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DoeDoeJohnJohn0-000-0000-000-000
DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
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DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
DoeJane0-000-000
Home Screen Patient Box
After selecting a unit, the roomsare shown with current patients. When placing your pointer over
the patient (not clicking)it will enlarge (as shown)
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Level of care – Click on to select ICU, PCU, or Floor
Indicators for ventilators, vasopressors, dialysis, etc
Icons (left to right):Discharge, Task List, Rounding Tool, Problem List, Med List, Claim Patient,
and Room Number
Patient name and MC#
Primary service – Click on the service to text page
Service Pager
7 system review – Placing pointer over a system will
reveal why it is yellow or red.
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AWARE overviewInformation organized by organ and systems
B) Historical contextual data
B) Historical contextual data
E) Provider actions/support
E) Provider actions/support
A) Organ identifier and status
A) Organ identifier and status
C) Current organ physiological status
C) Current organ physiological status
D) Status of relevant investigation
D) Status of relevant investigation
Redvalues are Critical
Yellow values are Abnormal
Redvalues are Critical
Yellow values are Abnormal
Patient ViewEvery value is clickable with trending options
Click on Bedside Monitor to see live or click back to this main
AWARE patient view.
White Board is a community area for communication. Each service can use it for different things. In 10-3/4 we use it for patient updated each shift.
Problem List, Procedures, Operative Notes,& Hospital Admission Everything is clickable linking to the note it originated from.
Cardiac – Shows cardiac labs, meds, access dates, ECG, and ECHOs.Cardiac is RED here because the Lactate is 9.1. Click on them!
Renal – Shows renal labs, and meds. Renal YELLOW because UO is low, noticeable change in wt, & electrolytes are abnormal.
Hem – Shows labs, meds, blood products received & transfusion review (gives suggestions for transfusing or not to transfuse.
Neuro – Shows meds, nursing assessment, neurology notes, pain, imaging, & EEG.Click on them!
Respiratory – Shows meds, nursing assessment, airway grade, pulmonary notes, vent/O2 settings, imaging, ABG, & PF ratio. Click them!
GI – Shows meds, nursing assessment, imaging, labs, & GI notes.
ID – shows antibiotics given in the last 24 hrs, labs, micro, temp, & meds. Also Braden score is listed here.
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Outcome:Everyone’s Happy
Reduced Cognitive Load(Happy Clinicians)
80
70
60
50
40
30
20
10
0
Application
NASA-TLX
StandardNovel
Reduced Errors(Happy Patients)
Application
Errors (no.)70
60
50
40
30
20
10
0
StandardNovel
Reduced Time(Happy Administrators)
Standard interface
Novel interface
Task attempt
Time (sec)250
200
150
100
50
01 2 3 4
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3 months to collect datato answer 2 questions
Seconds to collect and answer the same questions
20 Years Ago Today
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Cost of Whole Genome Sequencing
?
$1,000 to sequence one human genome
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OPTUM LABS
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Types of questions that may be pursued
Comparative EffectivenessComparative Effectiveness
Behavioral and Policy ResearchBehavioral and Policy Research
Variation in Care Research
Variation in Care Research
Heterogeneity of Treatment Response
Heterogeneity of Treatment Response
Optum Labs
HEALTHCARE
RESEARCH ANDINNOVATION
Provider
Academic
Professional/Consumer
Organization
Government
Payer
Pharma/Life
Sciences
An open, collaborative center for research and innovation for health care stakeholders interested in improving patient care.
Projects must be primarily to improve patient care and lower the cost of improved care, and be transparent to the entire collaborative.
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Optum Labs — Data and ToolsAdvanced Analytics and Data Visualization Data Growth Through Partnership
>149M“Administrative”
>149M“Administrative”
>30MClinical>30M
Clinical
315MUS Population
MayoMayoHealthSystem
2
HealthSystem
2
HealthPlan 1
HealthPlan 1
HealthPlan 1
HealthPlan 1
HealthSystem
3
HealthSystem
3
ClinicalResearchClinical
Research
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Optum Labs — Research Process
Data sets and resources are integrated into a separate “sandbox.” Data contributions are tagged and valued.
Contributor data is de-identified and stored in standardized data sets, on secure, private environments.
Project research is done in the “sandbox” environment only according to the Research Proposal.
Upon work completion,the “sandbox” is dissolved. Publications and clinical translation proceed as appropriate.
Integration Research & Analytics OutputsData
Health Economics Biostatistics
ActuarialEpidemiology
InnovativeHealth Care Insight
ClinicalData
AdminData
PharmacyData
PopulationData
Data Sets
Project“Sandbox”
Researchers
Real Estate
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Focuses on understanding the underlying behaviors driving patient and provider behaviors, as well as the evaluation of alternative policy initiatives
Example: Can the application of economic theory to the analysis of claims data improve our understanding of patient medication adherence? Does the use of copays alter conclusions about the effects of benefit design on initial prescription fills and refills?
Behavioral and policy researchBehavioral and policy research
Explores the well-documented extensive variations in treatment patterns by geography and other dimensions
Example: How are measures of geographic variation in care affected by the definition of geographic region?
Variations in careVariations in care
Seeks to understand what patient subpopulations are most likely to respond to a particular treatment
Example: Is a drug equally safe among all patient subpopulations? How could such information be used to design more efficient trials for future clinical development?
Heterogeneity of treatment responseHeterogeneity of treatment response
Improves the quality of research from observational studies more generally through fundamental research on data infrastructure and statistical methodologies
Example: What is the potential value of multiple imputation methods to fill gaps in the data?
Methodology researchMethodology research
Research Themes: Areas of Focus
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Use of new anticoagulants in atrial fibrillation
Longitudinal variation in care analysis of hip and knee surgery
• National trends in the screening, diagnosis, and treatment of localized prostate cancer
• Unplanned hospital readmission and emergency department care for acute diabetes complications
• Utilization and variations in uses of proton beam therapy
Step-down protocols in asthma medication
• Diagnosis, treatment, and service utilization for spine-related problems
• GLP-based anti-hyperglycemic medications and risk of acute pancreatitis and pancreatic cancer
Currently underway or awaiting publicationCurrently underway or awaiting publication
Likely candidate for clinical translation project
Sample Research Projects
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• American Medical Group Association, Alexandria, Va.• Boston University School of Public Health, Boston, Mass.• Lehigh Valley Health Network, Allentown, Pa.• Pfizer Inc. (NYSE: PFE), New York, N.Y.• Rensselaer Polytechnic Institute (RPI), Troy, N.Y.• Tufts Medical Center, Boston, Mass.• University of Minnesota School of Nursing, Minneapolis, Minn.
Seven Leading Health Care Organizations Join Optum Labs
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Patients are seen by outside providers/physicians.Optum Labs data
Patients call and are given an appointment at Mayo.
Example in Action
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Patients are seen by initial Mayo team.
Document patient expectations – “Pt Exp’n”
Patients indicate their expectations.
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Patients are presented medical vs. surgery informationDocument education
Patients make a decision about their care: medical/surgery
Shared decision making – SDM
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Patients receive care … some being treated medically, others with surgery
Collect risk factors and other dataPatients see medical/pre-operative Mayo team
Collect treatment data
Mean length of stayfor primary TKA
OPTUM (x age = 56.6)
3.0 daysOPTUM (x age = 56.6)
3.0 daysMAYO CLINIC (x age = 70)
2.85 daysMAYO CLINIC (x age = 70)
2.85 days
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Patients complete care at Mayo
Collect discharge disposition data
Patients might be seen by outside providers
Post-Mayo – Optum Labs data
Patients later report their outcomes from medical care/surgery
Patient-reported outcomes – PRO
Discharge to home
OPTUM (x age = 56.6)
81.4%OPTUM (x age = 56.6)
81.4%MAYO CLINIC (x age = 70)
63%MAYO CLINIC (x age = 70)
63%
30-day readmissions
OPTUM (x age = 56.6)
4.4%OPTUM (x age = 56.6)
4.4%MAYO CLINIC (x age = 70)
1.6%MAYO CLINIC (x age = 70)
1.6%
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Surgical Process Flow
for Costing- TDABC method
C (Circulator Nurse)Surgical AssistantScrubs Technician
RN Anesthetist-NARadiology TechnicianS (Surgeon)
A (Anesthesiologist)AR (Anesthesiologist Resident)R (Resident/Fellow)
Inpatient SpaceOperating Room
SurgeryProcess
PostSurgery
E22
Patient Prepfor Surgery
C AR20
A5 20
20 R20
C20 E22
Operation(Incision
to Closure)
CAR91
A46
S73
91 R86
C91
91
E28
Operation(Incision
to Closure)
CAR88
A44
S71
88 R83
C88
88 10
E30
EMR documentation
and contact family, supervision time, post procedurenote, order tests
S10
R5
Hip orKnee?
Hip
Knee
FLOW 1
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The Value Equation Comes to Life
Quality outcome data:
Patient-centric outcomes
Practice performance outcomes
Cost:
Outside Mayo
At Mayo
“Cost avoidance”
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Data are collected from all Mayo Clinic sites
Comparing and adopting best practicehelps improve value for all
THA +22 +120% TKA +14 +110% PHM +0.96 +5.36% HD +3.34 +5.23% DHI +0.81 +3.79% LEN +1.34 +3.66% MAS +0.66 +3.69% EXPD -3.45 -8.61% APOL -0.66 -3.70% FSLR -1.21 -3.70% TDC -2.32 -3.69% OKE -1.42 -3.06% THA +22 +120% TKA +14 +110% PHM +0.96 +5.36% HD +3.34 +5.23% DHI +0.81 +3.79%
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AgeAge BMIBMI StrengthStrength ExerciseExercise
85% probabilityof going home 3 days postopAND being able to stand/walk
without pain for 30-min 3 months postop
Knee Replacement Value Proposition
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Questions and Answers