Solving Healthcare Problems with Big Data Alicia d Empaire
Agenda Ø Introduction of Baptist Health South Florida Ø Healthcare Changes and Challenges Ø Role of Technology and Analytics Ø BHSF Big Data Analytics Strategy Ø Big Data Analytics Challenges Ø Questions
Bap*st Health South Florida Bap$st Hospital of Miami Doctors Hospital Homestead Hospital Mariners Hospital South Miami Hospital West Kendall Bap$st Hospital Bap$st Cardiac and Vascular Ins$tute eicu Medical Arts and Surgery Center at Bap$st Hospital Medical Arts and Surgery Center at South Miami Hospital Urgent Care Centers Imaging / Diagnos$c Centers Miami Cancer Ins$tute Sleep Centers Endoscopy Centers Home Care Interna$onal Center Employed Physicians BHMG - 163 physicians (41 prac$ces) Bap$st Health Quality Network (BHQN) - 850 community physicians Employee Health & Wellness
Bap*st Health Sta*s*cs Ø Admissions.. 71,681 Ø Pa*ent Days.. 342,942 Ø Births. 10,977 Ø ED Visits.. 313,116 Ø Urgent Care Visits. 242,177 Ø Total Surgical Cases. 64,662 Ø Interna*onal Pa*ents 7,710 Ø Licensed Beds 1,742 Ø BHMG visits.. 203,059
Bap*st Health Sta*s*cs Ø Medical Staff...... 2,211 Ø Employees....... 16,300 Ø Charity Care and uncompensated services (at cost).... $292,190,000
Healthcare Challenges Affordable Care Act o Access to & Affordability of Care and Quality & Cost of Care ü Medicare 1. Reduce Avoidable U$liza$on 2. Improve Coordina$on of Care 3. Quality, Service, & Cost Transparency ü Medicare popula*on + 1. Percentage increase of ages 65+ from 2014 2022: 27% increase (Coun$es: Miami Dade increase of 27%, Broward increase of 23%, Palm Beach increase of 32%) 2. Medicare is to become majority pa$ent volume by 2022 ü Medicaid Expansion
What is Consumer- Centric Healthcare Source: IBM
Consumers Key drivers and factors for Consumers in selec*ng healthcare services 1. Out of Pocket Expenses 2. Access 3. Convenience 4. Transparency
HCAHPS HCAHPS: a survey instrument and data collec1on methodology for measuring pa1ents' percep1ons of their hospital experience.
Role of Technology and Analy*cs Ø Use latest technology to track patient data throughout the continuum of care Home Health Devices, Wearables etc. Ø Integrate data from multiple data sources real time Ø Generate actionable insight using performance monitoring analytics and providing automated alerts Ø Optimize Outcome using Predictive Analytics Ø Improve Patient Experience by personalizing care Ø Reduce cost by analyzing data to identify cost saving opportunities
Role of Technology and Analy*cs Medical Non Medical Wearables Social Media Structured Unstructured Consumer Data Integrated Real Time Data HL7 ETL (Extrac$on, Transforma$on and Loading) Analy*cs tools Big Data Hadoop, Predic$ve Analy$cs, Machine Learning, NLP, Tableau etc. Mobile devices Email Text Messaging Marke*ng Campaign via mail Social Media Mul$ Channels to Consumer
Healthcare Big Data Use Cases Ø Admission/Readmission prediction Ø Telemedicine (Diabetes care & patient home monitoring) Ø Sepsis early detection (real time vital signs streaming) Ø Patient Engagement (Social Media) Ø Genomics Study
Data Analy*cs Maturity Model Repor$ng Enterprise Data Warehouse Business Performance Management Dashboards Scorecards Big Data Hadoop Advanced Analy$cs Predic*ve Analy*cs Machine Learning Natural Language Processing (NLP)
BHSF Data Analy*cs Future State ANALYTICS APPLICATIONS Reporting and Analytics Dimensional Insight Diver SAP BOE IBM Cognos IBM Watson Content Analytics MS SQL Reporting Services Data Visualization & Dashboards Tableau Xcelsius Research & Statistical Analysis SPSS Stata MCSS- PASS SAS Treeage R Advanced Analytics Predictive Analytics Machine Learning NLP (Natural Language Processing) DATA SYSTEMS Traditional Data Warehouse Independent Data Marts Big Data: DATA SOURCES Existing Sources (EMR, Ancillary Systems, Devices) Emerging Sources (Sensor Streaming,Social Media, Telemedicine, Unstructured)
BHSF Big Data Strategy Next Steps Ø Implementing Hadoop (Big Data) Ø Achieve cost savings via offloading storage Ø As we migrate to Cerner, Big Data is a great platform for us to store historical data from our existing clinical and financial applications
BHSF Big Data Strategy Next Steps Ø Pilot projects to begin: 1. Set up Hadoop environment and offload storage 2. Sepsis prediction by loading real time streaming vital signs, labs, orders, census data, etc.
BHSF Advanced Analy*cs Next Steps Ø Continue to expand our tools for Advanced Analytics: Predictive Analytics Machine Learning Natural Language Processing
Successful Strategy : 4 Key Pillars Data Informa*on Management Founda*on Data Governance Data Standardiza$on Technology Appropriate Technology Placorm People Organiza*on Organiza$onal structure & Role defini$ons Centers of Excellence Process Informa*on as an Enterprise Asset Standardiza$on of workflows Adop$on
Big Data Analytics Challenges Ø New Stack of Technology and Data Ø Lack of resources Ø Interoperability challenges Ø HIPAA restrictions Ø Lack of Data Governance
Key Take- Aways Ø Use the BI Maturity Model to ensure the value of your current Analytics investments while developing the capabilities for the Advanced Analytics and Big Data phases. Ø Although important, BI is not just about having the right tools. Address your biggest challenges of the BI Maturity Model, such as those related to data governance, cultural transformation, and BIrelated skills. Ø Plan for the future by developing plans that consider patient-reported data, events-driven architecture, social media, streaming data and machine learning. Ø Balance principles with pragmatism. Health care BI is an immature and rapidly evolving area so progress may be made by taking two steps forward and then one step back. SOURCE: The Advisory Board Company
Ques*ons