DATA SCIENCE IN HEALTHCARE

Seattle Code Camp 2016

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ABOUT THE SPEAKER

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Gaurav Garg (GG) is a business/technology leader playing the role of trusted

advisor and product development manager.

• Leads a Healthcare consulting practice for a national IT consulting firm

(www.calance.com).

• Participated in product strategy team - identified High Value Questions resulting in

150+ new products and features in $16B GE Healthcare product portfolio.

• Played the role of IT Director at UCLA Health System, acting as an interface

between the Clinical Directors and the IT Department.

• Led the delivery of 8 products and 70+ Enterprise Data Warehouse projects in the

Healthcare industry.

• Presented and won grants from the NIH under SBIR funding to build a product in

partnership with UCLA Health System.

• As a thought leader, GG publishes white papers, appears in speaking

engagements and guides healthcare startups at Cambia Grove.

Gaurav Garg (GG)

https://www.linkedin.com/in/gauravkinatus @gaurav_kinatus

PAST PROJECTS

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USCUNIVERSITY

HOSPITAL

HEALTHCARE BASICS Technologies & Flow of

Information

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WHY IS HEALTHCARE DATA MESSY?

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Integrated

Clinical

Information

System

Financial

System

Lab

Anatomic

Pathology

(6 vendors)

EMPI

(5 vendors)

Dictation

(4 vendors)

Interface

Engines

(7 vendors)

Ambulatory

Specialty

(4 vendors)

Hospice

(5 vendors)

Advanced

Visualization

(5 vendors)

Budgeting

(3 vendors)

Labor and

Delivery

(7 vendors)

Time and

Attendance

(3 vendors)

Ambulatory

EMR

(Small

practice)

(18 vendors)

Anesthesia

(1 vendor)

PACS

(31 vendors)

Patient

Monitoring

System

(1 vendor)

Laboratory

Blood Bank

(9 vendors)

CT Ultrasound

Other

medical

Devices

VentilatorsFetal

monitors

CoreMeasures

Rapid Response

PHR integration

Ambulatory Inpatient

Throughput Tracking

Infection Tracking

Quality Scorecard

Care Quality

Analysis

Charge & Payment Analysis

IHI Triggers

BI & DATA WAREHOUSE EXAMPLES

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Clinical and Syndrome

Surveillance

MEWS; HAC Risk Scoring (DVT, DU, CLBSI, CA-UTI, CTI, PU, Wound); Sepsis; school absenteeism; bio-surveillance

1 Patient 1 Chart

Optimizing Resource

Utilization

Imaging Tracking; Room Utilization; Capital

Investment Optimization; Payer Compliance; Leakage;

LOS; Re-Admissions Manager (RAM)

Improving Physician

Satisfaction

Protocol Compliance

Tracking

Pharmacy Protocol, Core Measures (AMI, HF, PN, SCIP, MU), Nurse Admission Tracking

Improving Patient

Satisfaction

Data explosion from EMR adaption has created lots of data. Calance has implemented over data warehouse projects in over 70 hospitals and HIEs.

• EMPI Integration – we have experience integrating with popular EMPI solutions and troubleshooting performance issues.

• Enterprise Interface Engine – implementation, upgrade, migrate, configure interfaces. Caradigm Intelligence Platform (aka Amalga), Orion Rhapsody, eGate, Intersystem Ensemble, BizTalk, SSIS.

• Data Warehouse/Data Lake – we have implemented and managed some of the largest data warehouse/data lake infrastructure in the healthcare industry (largest @ 3 petabyte data).

• Scorecard/Reports – data visualization for scorecards, dashboards and reports on SharePoint, Roambi, tableau.

• Predictive Analytics – build risk stratification and other predictive analytics algorithms using hadoop ecosystem and RStudio.

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DATA PIPELINE

EMPIStaging Enterprise

Service Bus

DataWarehouse

BI Analytics,Dashboards,Visualization& Report

Coordination

Browser

Mobile DeviceRedshift, NoSQL,

SQL Server

Authorization and DevOpsData GovernanceProducts and Logos acknowledged to respective owners. Logos used to for illustration purpose.

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ESB VS. INTERFACE ENGINE

Courtesy of

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ESB VS. INTERFACE ENGINE

Courtesy of

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FINANCIAL FLOW

https://www.youtube.com/watch?v=RJKIjxl1KeE

Who is paying for your healthcare?

Watch the Video

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CASE STUDIES Retrospective & Predictive

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PREDICTIVE ANALYTICS EXAMPLE –AUTOBED

https://www.youtube.com/watch?v=eI1l_s4zo_s

Predictive Analytics Example –AutoBed

Watch the Video

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CHANGING BUSINESS MODEL

Know Your Patients Clinical ProtocolsBusiness Intelligence & Predictive Analytics

Cohort Identification Standardized Care PathPatient Demographics

Lifestyle

Medical History

Risk Stratification

Adverse Event Prediction

Family History

Proactive Appointments

Treatment Effectiveness

Patient Generated Data

Variance Management

Financial Review

Patterns

Treatment Adjustment

Actionable Intelligence

POPULATION HEALTH EXPLAINED

PROTOCOL COMPLIANCE

Clinical desktop integration using “Knowledge

Hub”

Protocol Definition and Matching

Clinician view, compliance officer view,

reporting moduleLanguage & Terminologies

Data Aggregation

TouchPoint360

Data existing in hospital systems

Calance Protocol Compliance Framework

IDEAS High Value Questions

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AMBULATORY• Is my practice setup to be successful as a Pay-

for-Performance contract or should I stay as pay per service?

• Should I go an form an Accountable Care Organization (ACO) with 75 other physicians or join an Integrated Delivery Network (IDN)?

• What are my compliance requirements with different contracts?

• How do I rapidly understand the business implications of (program de jour) for my specific practice so I can rapidly make informed decisions to participate (or not)?

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HIGH ACUITY CARE• What is the probability of patient developing

an infection?

• Do I have everything for tomorrow?

• How are we doing on infection management (SEPSIS)? Is there anything we can do to use the devices to proactive alerts?

• What is the correlation between cost index and length of stay?

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DIGITAL PATHOLOGY• Find similar cases

• What other information do you need for diagnosis? Additional images, molecular image, additional test results, additional symptoms

• How to close the loop between Radiologist and Pathologist to reduce discordance?

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RADIOLOGY• Automatically detect abnormalities in the

image

• Which Radiologist results in good/bad follow-up actions?

• What are my compliance requirements with different contracts?

• Is this the right procedure, modality and protocol?

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REVENUE CYCLE• Recommend an immediate step to avoid

hospitalization. e.g. cab for picking up Rx

• Who is the best provider to treat this patient?

• What is the best site for this patient?

• Coding accuracy dashboard