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Using Real-Time Analytics ANNA DALY, Director of Clinical Data Management (HCA) VICTORIA WEAVER, Assistant Vice President of Clinical Data Management (HCA) to Understand Clinical Data 1

Using Real-Time Analytics to Understand Clinical Data

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Page 1: Using Real-Time Analytics to Understand Clinical Data

Using Real-Time Analytics ANNA DALY, Director of Clinical Data Management (HCA)

VICTORIA WEAVER, Assistant Vice President of Clinical Data Management (HCA)

to Understand Clinical Data 1

Page 2: Using Real-Time Analytics to Understand Clinical Data

Founded in 1968, Nashville-based HCA was one of the nation's first hospital companies. Today, we are the nation's leading provider of healthcare services. Making 18 million patient contacts a year with:

• 164 hospitals in 20 states and England • 125 free-standing surgical centers • 550+ physician practices • Approximately 200,000 employed physicians • Approximately 35,000 affiliated physicians

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Page 3: Using Real-Time Analytics to Understand Clinical Data

Transforming the industry from being reactionary and illness-focused

In this model, the hospital is passive – it is simply the place the physician goes to treat

the patient upon illness.

• Patients are readmitted frequently • Hospital stays are expensive

• Physicians are the primary decision makers • Physicians largely determine value of care given

• Patients are passive in their health

photo courtesy of noblehospital.org 4

Page 4: Using Real-Time Analytics to Understand Clinical Data

to being proactive and wellness-focused

In this model, the hospital is

active - managing the post-acute

hospitalization discharge to reduce overall spend and

eliminate readmission.

• Less frequent readmissions • More affordable care • Value of care determined by performance and

outcome • Patients are active in their healthcare plan

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Page 5: Using Real-Time Analytics to Understand Clinical Data

OUR APPROACH • Build a vendor-agnostic Clinical Data Warehouse with analytics for harvesting data

• Lay the foundation for Health Information Exchange

• Integrate financial, supply chain and clinical data

• Better manage operations across the continuum of care

• Persist data in a standardized manner

• Provide near real-time discrete data reporting

• Define an interoperability roadmap to further expand CDM’s functionality

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Page 6: Using Real-Time Analytics to Understand Clinical Data

OUR CHALLENGES

Scalability its difficult scaling to our needs in terms of support and timing

Standardization implementing an enterprise-wide standard is a huge undertaking

The Unknown we’ve never implemented a clinical design of this kind - limited lessons learned

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Page 7: Using Real-Time Analytics to Understand Clinical Data

OUR VENDORS

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Page 8: Using Real-Time Analytics to Understand Clinical Data

Improving quality using real-time data to reduce variation geographically, between facilities and between practioners.

Resulting in: • increased efficiency due to performance feedback • more affordable care due to reduced waste and risk • consistent outcomes

Improved Patient Value

THE VALUE OF QUALITY

Improved Hospital Value

Improved Physician

Value

Improved Patient Value

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Page 9: Using Real-Time Analytics to Understand Clinical Data

QUALITY

Stored in Clinical Database

Outcomes = Lagging Indicators

Consistently deliver correct

outcomes

Basic Science Outcome Analysis

Create clinical

evidence for best practices

Consistently apply best practices

Clinical Trial

Process = Leading Indicators QUALITY IN CONSISTENCY

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Page 10: Using Real-Time Analytics to Understand Clinical Data

Real-time Clinical Decision Support - Diagnostics

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Page 11: Using Real-Time Analytics to Understand Clinical Data

Real-time Clinical Decision Support - Therapeutics

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Page 12: Using Real-Time Analytics to Understand Clinical Data

IT’S ALL ABOUT THE DATA

- Ronald Coase

Tips » Be specific in focus » Establish a benchmark » Define “acceptable” » Define “outliers”

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Page 13: Using Real-Time Analytics to Understand Clinical Data

OPERATIONAL EFFICIENCIES

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Page 14: Using Real-Time Analytics to Understand Clinical Data

MEANINGFUL USE

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Page 15: Using Real-Time Analytics to Understand Clinical Data

ACUITY MODELS

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DATA HURDLES

Message Volumes • Over 8 million transactions per day • On average 450 clinical data elements per encounter

Data Latency • Initial goal of 4 hour data latency • Assessing the specific data is needed in < 4 hours • Longer than expected processing times

Alerting and Monitoring • Establish a monitoring and control framework • Focus on various factors:

• Completeness • Consistency • Timeliness • Accuracy • Validity

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Page 17: Using Real-Time Analytics to Understand Clinical Data

STANDARDIZATION

original image courtesy of singingthroughtherain.net

INDUSTRY STANDARDS

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Page 18: Using Real-Time Analytics to Understand Clinical Data

1 2 3 Identify clinical variation Gather clinical evidence Conduct Assessments Review organizational structure Define strategic goals Clarify project structure

Initiate and train teams Observe/validate processes Review order sets Review clinical pathways Review data and EBM Generate portfolio Design solutions Write implementation plans

Continued solution design Engage implementation plans Monitor clinical indicators Track quantifiables Define escalation protocol Develop sustainability plan Clarify ongoing structure

THE HCA APPROACH

DEFINE AND DISCOVER DISCUSS AND DECIDE DELIVER AND DRIVE

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Page 19: Using Real-Time Analytics to Understand Clinical Data

IDENTIFY OPPORTUNITIES

Goals

Identify keys to effective physician/facility engagement and partnership

Demonstrate improved clinical performance and reduced clinical variation

Assess impact on physician satisfaction

Findings

Data, analytics and clinical evidence along with administrative support throughout the change process

Aligned practices with best evidence improved utilization and LOS and costs decreased

Physicians and Operators who took active roles in the pilot phase felt engaged and assured that the hospital cared about quality

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TIE TO OUTCOMES

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Of 17 high-income countries studied by the National Institutes of Health in 2013, the United States had the highest or near-highest prevalence of:

• Infant Mortality • Heart and Lung Disease • Sexually Transmitted Infection • Adolescent pregnancies • Injuries • Homicide • Disability

DOLLARS DO NOT EQUAL HEALTH

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Page 23: Using Real-Time Analytics to Understand Clinical Data

Be Transparent with Data • Communicate performance and cost standings to physicians • Identify opportunities, quantify value and prioritize efforts

Track Performance • Track intiatives and report metrics back to facility and division • Routinely provide data-driven feedback to encourage dialog

Transfer Clinical Knowledge • Establish a single source for clinical knowledge • Provide a guide for implementing initiatives

Data

-Driv

en

Phys

icia

n-Le

d

Patie

nt-F

ocus

ed

CLI

NIC

AL

BUSI

NES

S IN

TELL

IGEN

CE

HOW TO IMPROVE PERFORMANCE

CLIN

ICAL

BU

SIN

ESS

INTE

LLIG

ENCE

DATA

-DRI

VEN

PHYS

ICIA

N-L

ED

PATI

ENT-

FOCU

SED

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Page 24: Using Real-Time Analytics to Understand Clinical Data

“If we are to achieve things never before accomplished, we must employ methods never before attempted.”

-Francis Bacon

QUESTIONS

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