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UCSF Informatics Day 2014 - David Dobbs, "Enterprise Data Warehouse"
 

UCSF Informatics Day 2014 - David Dobbs, "Enterprise Data Warehouse"

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  • 5 Major Domains: <br /> Research <br /> Patient Care <br /> Finance/Admin <br /> Education <br /> GL/Payroll <br /> Domain foci will include UCSF internally generated data as well as external data such as data from research collaborators, ACO partners or external benchmarks. <br /> Enterprise Data Warehouse and Analytics team will have staff who work with domain areas to understand and document their source systems, data staging areas, data warehouse, data marts and key analytics. Doug Berman and the Academic Research Systems are responsible for interacting with UCSF’s Research community and performing this function. <br /> The Enterprise Data Warehouse and Analytics team will also be responsible for documenting data flow between and among both internal systems and with external systems. <br /> To help tie together and manage all these data sources and repositories the Enterprise DW and Analytics team will be responsible for building a fabric of processes and technologies. <br /> It starts with implementing a Data Governance process. This process ….. <br /> The data governance process will generate a tremendous amount of data about UCSF’s data, or metadata. The Enterprise DW and Analytics team will put in place a meta data management system to store and manage these data. This will allow UCSF researchers and staff to get up to date information on key data resources and be able to benefit from the understanding of those data created by others before them. <br /> Finally, the Enterprise DW and Analytics team will implement Master Data Management capabilities. This provides the ability to match data across systems and domain areas. <br /> Master Data includes: <br /> Identifiers: patient, provider, payer, facility <br /> Codes: GL account number, lab test, department, result status <br /> Hierarchies: reporting relationship, service line rollup <br /> Mappings: ICD-9 to ICD-10 code, prior GL code to current GL code <br /> As you can imagine, this is a monumental task. The approach that the EDW and Analytics team will take is to incrementally build these capabilities while meeting pressing research, clinical, financial, educational and human resource needs. <br />

UCSF Informatics Day 2014 - David Dobbs, "Enterprise Data Warehouse" UCSF Informatics Day 2014 - David Dobbs, "Enterprise Data Warehouse" Presentation Transcript

  • Enterprise Data Warehouse Informatics Day Presentation David Dobbs Interim Executive Director Networked Data Warehousing June 10, 2013 Information Technology
  • Introduction Interim Executive Director Networked Data Warehousing 2 • Expertise • Leading large-scale data integration & analytic programs • Understanding domain area needs • Engineer practical, technology solutions using health technology standards • Key Accomplishments • Nationwide syndromic surveillance system with 500+ hospitals • Developing community-based population health solutions • Professional Qualifications • Engineering background with a bachelor of arts in business administration in information systems. • Certified Six Sigma and Project Management Professional • Member HIMSS Clinical and Business Intelligence Committee • Co-Chair of the HIMSS Data and Technology Task Force
  • Topic Flow • Enterprise DW and Analytics Team • UCSF’s EDW Strategy • Epic Cogito DW • Questions 3
  • Enterprise DW and Analytics Team Objectives • Create a team with a passion for understanding and managing enterprise data • Partner with domain areas to understand their data and analytic needs • Implement highly professional data management practices – Well managed data architecture – Comprehensive and high quality metadata management – Strong data security and controls • Provide domain areas: – Easy and secure access to enterprise data – Expertise in developing analytic work products – Expertise on BI and analytic technologies 4
  • Increase Analytics Maturity Optimize What is my best alternative? Precision medicine Forecast & Predict What happens if trends continue? Population management and value-based reimbursements Decision Support What should I do? Applying evidence-based guidelines at the POC Statistical Analysis Why is this happening? Determining evidence-based guidelines Metrics and Dashboards Where is the problem? Quality and safety KPIs and benchmarks Reporting What happened? Standard retrospective reports INCREASINGVALUE 1 2 3 4 5 6 5
  • Domains Research Patient Care Finance/Admin Education HR/Payroll • IDR / UCReX • RDB • Oncore / REDCap • Clinical data marts • APeX, Clarity, Cogito EDW • Axiom Dental • ACO data • UCALL / OmniView • DART • Campus Fin DW • Registration System • Course Evaluation • Grades Mgmt • Peoplesoft HRMS • Peoplesoft Payroll • OLPPS / Integration Data Governance Metadata Management Master Data Management / Management 6
  • Epic Cogito DW 7 Based on Epic Cogito DW Presentation Dated 2014-05-27
  • Epic Cogito (ko-GEE-toe) DW • An analytical database combining Epic and Non-Epic Data – Pre-defined healthcare data model – Seamless flow of Epic data from APeX Clarity database – Extensible to include non-APeX data • Common data model across Epic Customers – Facilitates collaboration with other Epic customers (e.g., Other UCs, Children’s of Oakland, etc.) 8
  • Uses for Cogito EDW • Research – Sophisticated cohort selection (RDB) – Quality and clinical research • Population Health – Combining APeX clinical data with external clinical, claims and patient satisfaction data • Performance Improvement – Monitoring clinical and operational metrics for APeX and non-Apex data • Streamlined reporting for APeX data – Highly simplified version of Clarity 9
  • Information Flow 10 Chronicles Cache Chronicles Cache 95,000+ Data Elements Reporting Workbench Real-time operational reporting Clarity SQL Server Clarity SQL Server 12,000+ Tables 125,000+ Columns Clarity Reporting Enterprise reporting Cogito DW SQL Server Cogito DW SQL Server 19 Fact Tables 76 Dimensions Data Warehouse Reporting BI and Analytical Reporting
  • Data in Cogito EDW 11 Admissions & Visits Admissions & Visits DemographicsDemographics Providers & Departments Providers & Departments Patient Registries Patient Registries Patient Satisfaction Patient Satisfaction MedicationsMedications Lab ResultsLab Results DiagnosesDiagnoses FlowsheetsFlowsheets ProceduresProcedures ImmunizationsImmunizations AllergiesAllergies Patients & Encounters Clinical Financial AccountsAccounts TransactionsTransactions CoveragesCoverages DRGsDRGs Paid ClaimsPaid Claims Procedure & Encounter Cost Procedure & Encounter Cost
  • Data in Cogito EDW 1212 Admissions & Visits Admissions & Visits DemographicsDemographics Providers & Departments Providers & Departments Patient Registries Patient Registries Patient Satisfaction Patient Satisfaction MedicationsMedications Lab ResultsLab Results DiagnosesDiagnoses FlowsheetsFlowsheets ProceduresProcedures ImmunizationsImmunizations AllergiesAllergies Patients & Encounters Clinical Financial AccountsAccounts TransactionsTransactions CoveragesCoverages DRGsDRGs Paid ClaimsPaid Claims Procedure & Encounter Cost Procedure & Encounter Cost • Automated loading of APeX data • Combine APeX and non-APeX data
  • Data in Cogito EDW 1313 Admissions & Visits Admissions & Visits DemographicsDemographics Providers & Departments Providers & Departments Patient Registries Patient Registries Patient Satisfaction Patient Satisfaction MedicationsMedications Lab ResultsLab Results DiagnosesDiagnoses FlowsheetsFlowsheets ProceduresProcedures ImmunizationsImmunizations AllergiesAllergies Patients & Encounters Clinical Financial AccountsAccounts TransactionsTransactions CoveragesCoverages DRGsDRGs Paid ClaimsPaid Claims Procedure & Encounter Cost Procedure & Encounter Cost Prebuilt models for non-APeX data
  • Data Not Currently in Cogito* • Ambulatory – Provider metrics – Order sets • Anesthesia • ED – Chief Complaint • Inpatient – Clinical Notes – Medication Administration • Operating room administration • Obstetrics and Labor & Delivery 14 * Representative list of key data items14
  • Cogito DW Dimensions* Admission Profile Department Lab Component Appointment Diagnosis Lab Result Billing Area Diagnosis Hierarchy Medication Billing Account Discharge Profile Patient Attributes Billing Service DRG Patient Billing Status Duration Procedure Billing Procedure Employee Provider Attributes Cost Center Encounter Provider Coverage Encounter Profile Reaction Profile Date Guarantor Visit Attributes Time of Date Immunization Visit Profile 15 *Partial, representative list15
  • Cogito DW Data Dictionary 16
  • Cogito Timeline • Version 8 – Additional Epic Data • ED • Surgery • Coded Procedures – Non-Epic Data • CMS Medicate Shared Savings Plan Claims • Press Ganey – Additional Universes – Received Claims, Patient Satisfaction17
  • Summary • Creating an Enterprise DW and Analytics Team – Coordinate UCSF data architecture, metadata definitions and serve as a resource for available data sources • Cogito Data Warehouse is being implemented – Research Data Browser 1st use case – Understandable set of data structures – Extensible data model – Facilitates sharing of data with other Epic sites – Epic continues to refine and enhance • More information – Doug Berman - Academic Research Systems 18
  • Questions? 19 19 David.Dobbs@ucsfmedctr.org 404-514-6921