Health Analytics

ALEX LEUNG

APRIL 19 2016 @ THE GARAGE SOCIETY

Medical

LifeWellness

Outpatient Fitness

Dental

Vision

AccidentHospitalization

Maternity

Protection

PROVIDERS

DATA &ANALYTIC S

FLEXIBLEBENEFIT

INSU RANC EBROKING

W ELLNESSMARKETPLAC E

BENEFITADMIN

ALEX LEUNG

HEALTHCARE PROVIDERS HEALTH INSURANCE COMPANIES

EMPLOYERS

LIFE SCIENCES

NGOS

HEALTH TECH STARTUPS

Medical datais expectedto double every 73 days by 2020.

Source: University of Iowa, Carver College of Medicine, 2014

W hat is health analytics?

LOWERCOST OF CARE

IMPROVEPOPULATIONHEALTH

ENHANCEPATIENT CARE

Source: Institute for Healthcare Improvement Triple Aim

HEALTH ANALYTICS is the systematic use of patient data and related insights to drive evidence-based decision making for care management, operations improvement, and outcomes measurement

INTERNATIONAL COMPARISON OFHEALTHCARE SPENDING

W hy it matters?

Unsustainable growth.

There is an urgency to transform the fundamentallyunsustainable healthcare model by providing higher quality care at a lower price—care that improves the overall health, outcome, and experience for the average individual.

W hy it matters?

Insufficient evidence.

There have been a significant amount of healthcare innovations over the last few decades. We now have more preventive, diagnostic, and treatment alternatives than ever before, with more being developed all the time. Despite this, the healthcare system remains starved for evidence of what works.

The two sides of analytics

DESCRIPTIVE

• Historical• Reactive• Static Reporting• Measurement• Business

Intelligence

PREDICTIVE

• Future facing• Proactive• Trending• Pattern Analysis• Recommendation• Segmentation

HINDSIGHTWhat happened?

INSIGHTWhy did it happen?

FORESIGHTWhat could happen?

Health analytics is beyond medical conditions

Individual-specificGroup-based

Genetic

Environment & Behavior

Genetic Markers

Medical Conditions

Family History

Demographics

Comorbidities Adverse Reactions

Adherence

Lifestyle

GeographyProfession

Subscriptions

Social Network

Health analytics span across…

BUSINESSANALYTICS

CLINICALANALYTICS

IMPROVEPERFORMANCE

LOWERCOST

IMPROVEOUTCOME

Ex. Health Management,Fraud Detection,

Supply Chain Management

Ex. Financial Reporting,Business Optimization,

Utilization Management

Ex. Clinical Performance,Patient Adherence,Clinical Research

Health analytics & information value chain

Performance Objectives

Evidence-Based Rules

Data

Analytics InsightsDecision /

ActionEvaluation

WELLNESS DATA WORKSITE DATA

CENSUS DATA CLAIMS DATA CLINICAL DATA

OTHER DATA

PAYMENT

RESOURCE MANAGEMENT

CLINICAL DECISION

CARE COORDINATION

HEALTH MANAGEMENT

PAYERS

• Financial management

• Member engagement

• Provider management

• Performance monitoring

• Wellness, prevention and disease management

• Regulatory compliance

PROVIDERS

• Financial management

• Clinical decisions support

• Care management

• Operations improvement

• Performance monitoring

• Regulatory compliance

GOVERNMENTS

• Financial management

• Provider credentialing

• Quality monitoring

• Health promotion

• Adverse event reporting and disease surveillance

• Policy design and research

LIFE SCIENCES

• Product development

• Comparative effectiveness research

• Value demonstration

• Business intelligence

Health analytics in practice

Organizations are increasingly using analytics to consume, unlock, and apply new insights from healthcare data and related information for driving clinical and operational improvements to meet top business goals and challenges.

Example: Health analytics applications

COST BENCHMARKING

• Competitive analysis for operational improvements• Size and prioritize opportunities

CLINICAL DECISION SUPPORT

• Clinical support for patient assessment• Identify diagnosis, recommendation & treatments• Systematic applied learning based on action taken

and outcome derived

Source: Bowen J. New England Journal of Medicine 2006

Key Elements of Clinical Diagnostic Reasoning Process

Healthcare data comes from a variety of sources

CLINICAL

Example datasets:• EMR• Clinical notes• Medical imaging

PHARMACEUTICAL

Example datasets:• Clinical trials• Patient registries• Patient drug history

CLAIMS & COST

Example datasets:• Medical claims• Provider contracts• Financial reports

BEHAVIOR

Example datasets:• Health questionnaire• Worksite activities• Exercise data

of healthcare data is unstructured, including texts, images, and sounds~ 80%

Mining unstructured healthcare data

Source: Talix

Example: Standard coding systems used in the US

International Classification of Diseases (ICDs)

Healthcare Common Procedure Coding System (HCPCS)

Diagnosis Related Groups (DRGs)

Ambulatory Patient Classification (APC)

National Drug Codes (NDC)

Diagnosis Treatment

International Classification of Diseases (ICDs)

Facility Professional

Inpatient – Hospital

Outpatient –Surgery Center

Outpatient –Emergency Room

Skilled Nursing Facility

Physician

Specialist

OthersMajor Diagnostic

Categories (MDCs)

Primary obstacles to widespread analytics adoption

Ability to get data

Culture does not encourage sharing information

Lack of understanding of how to use analytics to improve the business

Lack of executive sponsorship

Lack of management bandwidth due to competing priorities

Lack of skills internally

Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute of Business Value study. 2010. Sample size Healthcare n = 116.

Today most healthcare spend is focused on sickness

HealthyLow Risk At Risk

Chronic

High Risk

Acute

End of Life

Healthcare Status 20% of population generate 80% of healthcare costs

Hea

lth

care

Cos

t

Prevention Treatment

CXA’s unique position in data aggregation

InsurersEmployers

Employees Providers

• Claims data• Premiums data • Enrollment data• Benefit data

• Demographic data• Payroll data• Performance data• Enrollment changes

• Encounters data• Biometrics data• Lab data• Cost data

• Benefit utilization data• Health risk assessment data• Wellness activities data• Portal utilization data

HEALTH ASSESSMENT

RISK STRATIFICATION

TARGETED INTERVENTION

IMPACT EVALUATION

+ Comprehensive understanding of individual health/risk+ Risk factor identification+ Behavior monitoring

+ Consumer health segmentation+ Risk stratification+ Prioritization of opportunities+ Track population trends

+ Personalized recommendations+ Campaign management & targeted outreach+ Chronic disease management

+ Track program participation & engagement+ Outcomes measurement+ ROI calculations+ Benchmarking

CXA’s health analytics capabilities

Lifestyle risks that correlate to chronic conditions

SmokingPhysical

InactivityExcessive Alcohol

Poor DietInadequateScreening

Poor Stress Management

Insufficient Sleep

Diabetes 5 5 5 5 5

Hypertension 5 5 5 5 5

Hyperlipidemia 5 5 5

Asthma 5 5

Cancer 5 5 5 5

Bronchitis 5

Gastritis 5 5 5 5

CXA’s personalized health recommendations

Prioritize wellness programs using analytics

Healthy At Risk Unhealthy

Low Risk

Moderate

High Risk

Disease Management

Keep Healthy

Lifestyle Modification

Diagnosis (Claims)

Beh

avio

r (H

RA

)

CXA’s health analytics reporting

CXA’s benefit analytics capabilities

Plan Design Modeling

Benefit Benchmarking

Insurance Renewal & Projections

Flex Feasibility Study

Cost & Utilization Analysis

Self-funding Analysis

Benefit Harmonization

Benefit Diagnostics

Questions & Discussion