seattle code camp 2016 - role of data science in healthcare

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DATA SCIENCE IN HEALTHCARE Seattle Code Camp 2016 1

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Page 1: Seattle code camp 2016  - Role of Data Science in Healthcare

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DATA SCIENCE IN HEALTHCARE Seattle Code Camp 2016

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ABOUT THE SPEAKERGaurav Garg “GG” is a business savvy IT 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.

• P&L responsibility managing application development up to $45MM.

• Presented and won Phase I, Phase II 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

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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 AnatomicPathology(6 vendors)

EMPI(5 vendors)

Dictation(4 vendors)

Interface Engines

(7 vendors)

AmbulatorySpecialty

(4 vendors)

Hospice(5 vendors)

AdvancedVisualization(5 vendors)

Budgeting(3 vendors)

Labor andDelivery

(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 medicalDevices

Ventilators Fetal monitors

CoreMeasures

Rapid Response

PHR integration

Ambulatory Inpatient

Throughput Tracking

Infection Tracking

Quality Scorecard

Care Quality

Analysis

Charge & Payment Analysis

IHI Triggers

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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 PIPELINEEMPI Staging Enterprise

Service BusData

Warehouse

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 on the following slide

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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 on the following Slide

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CHANGING BUSINESS MODEL

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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

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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