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IBM InfoSphere Clinical Analytics. There are growing pressures on providers to report publically. Medicare Says It Won’t Cover Hospital Errors By ROBERT PEAR
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There are growing pressures on providers to report publically Medicare Says It Won’t Cover Hospital Errors By ROBERT PEAR WASHINGTON, Aug. 18 — In a significant policy change, Bush administration officials say that Medicare will no longer pay the extra costs of treating preventable errors, injuries and infections that occur in hospitals, a move they say could save lives and millions of dollars. New York Times, August 19, 2007 Hospitals must report patient-satisfaction data or face a financial hit; for many it’s just business as usual, for others it poses some challenges By: Barbara Kirchheimer - Story posted: July 23, 2007 - 5:59 am EDT Modern Healthcare Hospitals blitz airwaves with ad campaigns Stiff competition as consumers gain more say in care By Christopher Rowland, Globe Staff | February 21, 2007 In an escalating advertising blitz, hospitals in the Boston area are trying to attract patients by pitching such services as knee replacements, cancer treatments, and liver transplants. 2 3
Healthcare Provider Challenges Healthcare Providers are faced with a growing number of challenges, including: Increased demand for care delivery with decreasing reimbursement Compliance monitoring on the increase Need to improve patient Safety and Outcomes Utilization of patient data (Longitudinal Patient Records) for Chronic Disease Profiling for better outcomes and reduced costs Provide data and analytical tools to a growing number of users within hospitals 3
To be successful in the future, organizations will need to use clinical data to improve operational efficiency and outcomes Financial & Ops Reporting • Available today • Standalone analysis Clinical Data Analysis • Calculate and benchmark financial and clinical productivity measurements • Compliance monitoring • Actionable analytics via management Healthcare Intelligence Dashboard • Conduct data mining • Safety and Outcomes • Disease Cubes Information Currently Accessible Hidden Information 4
Current strategies for reporting, analyzing and trending are costly and inefficient…. Operations Managers Quality Department Finance Department Analysis Create Report Analysis Create Report Analysis Create Report Lab System OR System ED System Pharmacy System RegistrationSystem Manual Data Capture Micro Results Hematology Chemistry Results Peri Op Documentation OR Med Admin Time ED Admit Time ED DC Time Medication Name Dispense Order MRN Name ICD 10 5
ICA Provides a Comprehensive Informatics Strategy across the Organization vs. Point Products which are Targeted at Specific Departments CLINICAL Informatics RESEARCH Informatics Point Solution Point Solution Enterprise Healthcare Analytics Data Not Validated Point Solution InfoSphere Clinical Analytics (ICA) ADMINISTRATIVE Informatics Data Not Validated Point Solution Point Solution 6
Solution Positioning Clinical Analytics Development Platform Single source of trusted administrative, clinical, and research information across the enterprise. Fully customizable and extensible solution Fully integrated analytics development platform Solution is optimized for healthcare analytic reporting, ad hoc analysis and research Solution is highly adaptive to local medical vocabulary - Standards mapping features allow for regional and national benchmarking 7
Clinical Analytics Solution: Analytics + Warehouse + B.I. • A fully integrated solution • Clinical Analytics + BI Applications + Healthcare Intelligence Dashboard Server + Data Warehouse + Server • Solution’s unique features: • Creates longitudinal record from inpatient, outpatient, specialty and ambulatory care setting • Patient record De-Id and Re-Id • 900+ procedures for data cleansing and validation • Medical vocabulary mapping • MPI mapping • Cohort record or encounter search • Analysis of whole organization down to physician and patients InfoSphere Clinical Analytics Cognos or other B.I. Infosphere Warehouse Balanced Warehouse 8
The Value of a Solution vs. a Build Approach Are Many • Delivers a cost-effective solution for patient & provider data analysis: Standardization: Common data model, data validation, medical terminologies mapping, privacy compliant, etc. Provides different views of patient data: Combines inpatient, outpatient, specialty care, ambulatory and financial data into a longitudinal patient record in a analyzable format. Supports analysis of multiple organizational models: Enterprise organizations, regions, single facility, departments, individual physician and patients. Installs once, use many times: Serves multiple stakeholders from a single validated healthcare data warehouse – quality, research, clinicians, nurses, business operations 9
The Value of Enterprise Healthcare Analytics Get additional value from your considerable CIS investment by creating a corporate data asset Monitor and manage on a more timely basis Population-level analysis, not just survey data ties process changes to patient outcomes Identify new revenue opportunities & cost controls Validate effectiveness of evidence-based practices Provide new tools to providers to improve treatment Reduce cost of patient recruitment for clinical research Operational deployment in as little as 16 weeks(single hospital with one data source) 10
Enterprise Analysis Use Cases Example Use Cases Domains Outcomes Management; e.g. Diabetes, surgical Clinical Use Cases Quality & Best Practices Identify Variations in Healthcare Delivery Safety & Surveillance Business Analysis Business Use Cases Patient Flow / Capacity Management Service Line Measurement Exploratory Analysis Research Use Cases Clinical Trial Study Design Cohort Identification Patient Recruitment InfoSphere Clinical Analytics 11
InfoSphere Clinical Analytics ICA Dashboard Cognos (or Other B.I.) InfoSphere Warehouse Server Platform 12
Healthcare Analytics Architecture Data Sources Analysis Hospital InfoSphere Clinical Analytics Quality Improvement Quality Improvement Care & Ops Improvement Separate Systems & Siloed Data Mapping – Validation - Normalization Hospital Outcomes Analysis Analytic Environment Dashboard Local Vocabulary Normalized Vocabulary Patient Safety Operations Clinic Disease Cubes Physician Performance Clinic Consolidate Clinical Data Across Entire Organization Into ‘Central Source of Truth’ Compliance Monitoring 13
ICA– Integrated, Ready to Use Features ICA Inpatient & Outpatient Vocabulary Mapping Data Model Common Patient Identification Privacy Compliant Ambulatory De-ID Patients Data Cleansing Disease Profiles Re-ID Patients Clinical Query Identity Mgmt Data Export Research Pathology Analytics 14
High Level Data Model Clinical & Operational Data Pharmacy • Days Supply • Refill # • Ordering MD • Dose/Strength • Route • Drug Code • Provider • Specialty/Sub • Admit/Attend • Cons/Order • Prescribing • Procedural Laboratory • Orders & Results • Microbiology Patient Characteristics • Age • Gender • History • Geography Facility Details • Inpatient • Outpatient • Geography • Urban/Rural • Dept, # Beds Pathology Imaging Studies Clinical Data Model Medical Devices • Mfg. Name • Model, type • Serial number • Implant date ICD-10/CPT • Diagnosis • Procedure • DRG123 (inpatient) • Date/time stamp • Encounter link Encounter • Admit info • Discharge info • Financial • CCR • Dept • CPT Codes • Facility ID • G/L and HR • Productive FTE Insurance • All Payers • Plan ID EMR • Problem list • Med list • Allergies • Chief complaint Nursing Notes • Height, weight • Blood pressure • Temp., HR, RR 15
ICA is Easily Extensible “Site Specific” Metadata Supplemental Core 16
Core Analytic Services ICA DBF DBF ICA EMR CV view DBF DBF ICA HIS DBF DBF ICA PMS -x- view Diabetes view SourceSystems On-site System Custom Analytics • Access to own data • Extract standardized datafor internal analysis • Query and analysis tools • Re-identify patients forclinical studies • Re-identify providers forperformance improvementstudies Elements of InfoSphere Clinical Analytics (consolidated) InfoSphere Clinical Analytics Fullyde-identified data Hospitals • Routine reports, with • comparative data • Physician feedback reports • Selected care processes and patient populations • Selected quality andperformance indicators • “Community” • collaboration portal • Web-based exploratory analysis, with comparative data at every level • Selected care processes and patient populations • Network with colleagues,share best practices, andfoster improvement • Download comparative • data for local analysis • Selected care processes and patient populations • Data extracts or cubes foradditional care processes orpatient populations • Operational/revenue analysis • Registry reporting (external) • Adverse event ID, analysis • Individual and comparativeanalyses 17
InfoSphere Clinical Analytics Sample Implementation TimelineTypical Single Hospital – Single Source (16 Wks) Single Source Application Or Data Warehouse ICA - 16 Week Implementation Proposed ICA Clinical Information, 23 Tables (53%) Discovery 60% Week 1-9 1 Hospital/Clinic Feed 60% Single Vocabulary/Catalog ICA Finance Information, 12 Tables (27%) Implementation 30% Week 10-14 Analytics Discovery and Measures Delivery 30% ICA Patient Information, 9 Tables (20%) Operational 10% Week 15-16 30% ICA Go-Live Dashboard Delivery Live 18
InfoSphere Clinical Analytics - Sample Implementation TimelineTypical Multiple Hospital – Multiple Source Medipac IDX Cerner 13 Hospital Feeds • Site Statistics • 1.6m Patients • 94 Satellite Clinics • 13 Hospitals • 700+ Physicians • 1,767 Beds • Cerner System • ICA Master Patient Index (MPI) implemented (system did not implement Cerner EMPI) • ICA Provided Consolidated Warehouse and Analytics Catalog Three Catalog One Catalog Two ICA, MPI Inbound only ICA Clinical Information, 23 Tables (53%) Professional Billing Unique MRN for all source systems Outpatient ADT, Rx ADT, Lab ORD/OBX ADT, EHR ICA Finance Information, 12 Tables (27%) Multiple Databases and Catalogs ICA Patient Information, 9 Tables (20%) eGate Interface 19
Healthcare Analytics Strategy ICA Key Quality Measures • Comparative performance data forselected indicators • Advance view for externally visiblemeasures • Monitor trends over time Opportunity Analysis • Look across the organization to findopportunities for improvement Dashboard Variation—is it real? • Consider internal variance in light of variation within comparative data Clinical Query What’s causing it? • Distinguish true process–outcomerelationships from “noise” Cognos • Central Source of Truth • No Copy Analytics • Actionable Analysis Exploratory Analysis Excel / Other How to improve? • Encourage creative thinking, rapid hypothesis testing • Measure impact of process changes • Monitor to sustain improvement 20
Main Dashboard InfoSphere Clinical Analytics Drill-down tocompliance by surgery type 21
Compliance Monitoring with Actionable Analytics Drill-down (System – Facility – Provider – Patients) 22
For Further Information • External URLhttp://www-01.ibm.com/software/data/infosphere/clinical-analytics 23