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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

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

DoeJane0-000-000

DoeJane0-000-000

DoeJane0-000-000

DoeJane0-000-000

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DoeDoeJohnJohn0-000-0000-000-000

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

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