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1 New York Metro Chapter Business Intelligence & Predictive Analytics in the Healthcare Environment Paul Savage; Director Center for Health Analytics Iona College, Hagan School of Business, Healthcare Management Program President: Healthcare Intelligence, LLC
2 Agenda: Healthcare Industry Context: Fundamental Transformation & Social Commitment Identify the Scope & Sources of Data Resources Regulatory Environment (HIPAA & HITECH) Recognize Problems Associated with: Data Management, & IT Systems infrastructure Including: clean up, exploring & analyzing Big Data Data Mining Goals & Objectives (beyond Spreadsheets) Descriptive, Predictive and Prescriptive Analytics Business Intelligence vs Clinical Decision Support Promote Critical Thinking, Analytical & Research Skills Promote Quantitative Management Skills (Identify Questions)
3 National Health Expenditures* Health care not only is the key to our fiscal future, but also contains a massive opportunity to improve efficiency, with credible estimates suggesting that as much as $700 billion per year, or 5 percent of GDP, of healthcare services delivered in the United States don t improve health outcomes. * Beyond Economics 101: Insights into Healthcare Reform from the Congressional Budget Office, Peter R. Orszag, October
4 The US Health Care Delivery System Scope, Size & Description $2.9 Trillion, $9,255/person, 17.4% GDP Twice the median per capita of 30 Industrialized Nations Fragmented Components & Providers Hospitals & Institutions (Nursing Homes, Specialty Hosp) Physicians & Clinical Services Other Professional Services & Personal Health Care Prescription Drugs, Durable Medical Equipment Public Health, Research, etc. National Health Expenditures at 19.6% in Ten Yrs. Technology, Chronic Diseases, Aging Population, Administrative Costs Integrated & Accountable Care Organization Initiatives
5 U.S. Health Care Spending vs. Other Countries 5
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7 We have to bring the science of management back into Healthcare Donald Berwick, MD Institute of Healthcare Improvement
8 The Future of Personalized Community-based Health Care 8
9 The Big Data Challenge Transaction Based Systems (Billing) & EMR s Population and Clinically Based Analytics Community Health Status Longitudinal Episodes of Care Data Scientist Perspective Data Governance, Business Understanding Systems, Data & Analytics capabilities
10 Health Care Data Evolution Medical and Billing Records Traditional Paper Medical & Billing Records Electronic Billing Records (Insurance & State Repository) Professional Credentials State Department of Education Economic & Competitive Metrics Institutional Cost Reports (CMS) American Hospital Assoc. Survey Commercial Data Sources (i.e.. Truven HC) Insurance Intermediary Transactions
11 Big Data Healthcare Environment One State of: 24 Million Lives 15 years transactional activity across venues 180 million records: 5,000 characters/450 fields: 20 Terabyte Future: Multiple States All-Claims to include Physician offices, Pharma & Diagnostics All-Claims DB: 1.2 Billion records per year
12 Demonstration Overview Exploratory Data Analysis (EDA) Descriptive Inpatient Activity: Service & Use Trends Emergency Room Activity: Dependence Care Continuum: Home Care, LTC/SNF Amb. Surgery Payor/Population Mix: Shift to Medicare Predictive Analytics: State-Space Forecasting Models (Univariate Family of Exponential Smoothing & ARIMA) Multi-Variate/Simulation Models (Longer term environmental & systems change) Prescriptive/Machine Learning Analytics A Branch of AI; Decision tree, Neural Networks, Inductive Logic, Association Rules, Clustering, Bayesian Network. Pattern Recognition. Natural Language Processing
13 In-Patients per Month Long Term Trends All New York State Hospitals Westchester County-Total Inpatient Discharges Jan-97 Jan-98 Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 6% Decline Jan-11 Jan-12
14 Service Length of Stay Trends Psychiatry Average LOS Medicine Maternit Surgery 0 Jan-97 Jan-98 Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Medicine Surgery Pediatrics Maternity New born Psy
15 Inpatient Hospital Beds Physical Resources In Use Jan-97 Jan-98 Jan-99 Jan Westchest County-Occupied Beds 6% Decline in Discharges 13% Decline in Length of Stay Higher Intensity of Services Jan-01 Jan-02 Jan-03 Jan-04 15% Overall Decline in Utilization Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12
16 Westchester Population Out-Migration 90% 80% NORMET 70% 60% 50% 40% 30% 20% 10% D I S C H A R G E S P A T I E N T D A Y S Bronx Manhattan 0% Region 5 Region 6 Region 8 & 9
17 Dependence on Emergency Services 6000 Westchester County - Emergency Room Admisions 60% Emergency Room Admission Ratio % % % % 35% 30% 25% ER to Total Admissions Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12
18 Inpatient Discharge Referrals Inpatient Discharges per Month Jan-97 Jan-98 Jan-99 Jan-00 Jan-01 Home Care Skilled Nursing Facility Home Care Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Skilled Nursing Facility Jan-10 Jan-11 Jan-12
19 Population:961,670 Density: 1879/Sq.Mi
20 Births that occurred prior to 37 weeks of gestation, as percent of live births,
21 Predictive Modeling Application
22 Geographic Mapping Primary Markets by Hospital
23 Hospital Admissions & LOS 1600 Length of Stay Patients/Mo Jan-97 Jan-98Jan-99 Jan-00 Jan-01 Jan-02Jan-03 Jan-04 Jan
24 Hospital OCCUPANCY Jan-97 Jan-98 Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05
25 Hospital Forecast Patient Activity Jan-97 Jan-98 Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Best Case Expected Worst Case History Imputed
26 Hospital Forecast Patient Activity 2000 Patients/Mo ,000 Pts/Yr 20,000 Pts/Yr 1400 Jan-06 Jan-07 Jan-08
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30 Intelligent Dashboard History, Adjustments & Forecasts Customer Segmentation Product Hierarchy History (light Blue) Forecast (Dark Blue)
31 Environmental Change Berger Commission Modeling of Closures Demonstration Predictive Modeling: Rules & Ratios Monte Carlos Modeling: Multiple Distribution Models & Random Cycles
32 Berger Commission Model
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34 Intermediate Decisions 1. Initial Normal Competition in Market Place 2. Mercy & Franklin: Close Trauma, Pediatrics & Maternity Services 3. Long Beach Hospital Closure 4. Mercy Hospital Closure
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39 Population Health Perspective (DSRIP) Collaboration & Coordination of Care $350 Million in Funding Service Demand & Utilization Risk Stratification & Community Markets
40 Project Selection: Respiratory Health 40
41 Respiratory: Total Hospital IP Activity Hudson Valley (5 Years)
42 Respiratory: Total Hospital IP Activity Hudson Valley (5 Years) 800 InPatient Discharges 101,000 Discharges 67,700 Unique Patients: ER Visits (w/o IP Admit) 351,000 ER Visits (w/o IP Admit)
43 Total Emergency Room Encounters: Respiratory Conditions Hudson Valley, Admitted Patients from ER & Other ER Visits Patients/Month Highly Seasonalized
44 Respiratory: Multiple Inpatient & ER Visits/Discharges % IP/Resp. Patients with Multiple Visits % ER/Resp. Patients with Multiple Visits Exceed 20 Visits Exceed 20 Visits
45 Respiratory Conditions: InPatient Discharges Hudson Valley (5 Years) 122 Pneumonia ( excep t t hat caused b y t ub erculo sis o r sexually t r Influenza Acute and chronic tonsillitis Acute bronchitis COPD: C hro nic o b st ruct ive p ulmo nary d isease and b ro nchiect as Asthma Aspiration pneumonitis; food/vomitus Respiratory failure; insufficiency; arrest (adult) Other lower respiratory disease Other upper respiratory disease Other upper respiratory infections Pleurisy; pneumothorax; pulmonary collapse Lung disease due to external agents Tuberculosis (Prod Code 1: Inf Disease Cancer Bronchus or Lung (Prod Code 2: Cancer) Cancer Other Respiratory (Prod Code 2: Cancer)
46 Hudson Valley View Project Selection: Respiratory Health Geo-level of Analysis: Zip Code 46
47 Geographic Profile: Respiratory Patients 47
48 Geographic Profile: COPD Patients 48
49 Geographic Profile: Pneumonia Patients 49
50 Geographic Profile: Respiratory Cancer Patients 50
51 Geographic Profile: Asthma Patients 51
52 Geographic Hotspots: Asthma Patients 52
53 Next Steps Define Hotspots for all conditions Continue to gather data, information and knowledge from other sources Circulate and share all aspects of CNA Identify issues and service challenges Cross walk DSRIP project selection/plans with CNA findings 53
54 Thank You Discussion & Questions
55 Paul Savage, MBA (914) Iona College, Hagan School of Business Director, Health Care Management Program, MBA Director, Center for Health Analytics Adjunct Professor: Hofstra University, New York Medical College President, Healthcare Intelligence, LLC
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