Learn How ProHealth Care is Innovating Population Health Management with Clinically Integrated Insights
 

Learn How ProHealth Care is Innovating Population Health Management with Clinically Integrated Insights

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Christine Bessler, CIO at ProHealth Care,demonstrates how ProHealth Care became the first healthcare system to produce reports and data out of Epic's Cogito data warehouse in a production environment. ...

Christine Bessler, CIO at ProHealth Care,demonstrates how ProHealth Care became the first healthcare system to produce reports and data out of Epic's Cogito data warehouse in a production environment. In this slideshare, you'll learn:

How they delivered clinically integrated insights to 460 physicians

How access to analytics allows their physicians to easily see which patients need important health screenings or care interventions, setting the stage for enhanced preventive care and better management of chronic diseases

ProHealth Care's strategy to integrate data from Epic with information from other EMRs and data sources to deliver clinically integrated business intelligence

How the organization is positioning itself to deliver against an advanced self-service BI capability in the future

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Learn How ProHealth Care is Innovating Population Health Management with Clinically Integrated Insights Learn How ProHealth Care is Innovating Population Health Management with Clinically Integrated Insights Presentation Transcript

  • facebook.com/perficient twitter.com/Perficient_MSFTlinkedin.com/company/perficient ProHealth Care - Innovating Population Health Management with Clinically Integrated Insights Christine Bessler, CIO, ProHealth Care Juliet Silver, Director, Perficient
  • Perficient is a leading information technology consulting firm serving clients throughout North America. We help clients implement business-driven technology solutions that integrate business processes, improve worker productivity, increase customer loyalty and create a more agile enterprise to better respond to new business opportunities. About Perficient
  • • Founded in 1997 • Public, NASDAQ: PRFT • 2013 revenue ~$373 million • Major market locations throughout North America • Atlanta, Boston, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Dallas, Denver, Detroit, Fairfax, Houston, Indianapolis, Los Angeles, Minneapolis, New Orleans, New York City, Northern California, Philadelphia, Southern California, St. Louis, Toronto and Washington, D.C. • Global delivery centers in China, Europe and India • >2,100 colleagues • Dedicated solution practices • ~90% repeat business rate • Alliance partnerships with major technology vendors • Multiple vendor/industry technology and growth awards Perficient Profile
  • BUSINESS SOLUTIONS Business Intelligence Business Process Management Customer Experience and CRM Enterprise Performance Management Enterprise Resource Planning Experience Design (XD) Management Consulting TECHNOLOGY SOLUTIONS Business Integration/SOA Cloud Services Commerce Content Management Custom Application Development Education Information Management Mobile Platforms Platform Integration Portal & Social Our Solutions Expertise
  • Our Microsoft Practice
  • Strategic Business Consulting Project Management Information Exchange BI & Analytics HIPAA 4010/5010 & ICD-10 Compliance System Interoperability Connected Health Technical Consulting Knowledge Transfer & Delivery Healthcare Solution Offerings
  • Select Healthcare Clients
  • Introduction • Christine Bessler, PMP CIO / VP of Information Technology ProHealth Care - Responsibility over information systems, telecommunication, informatics (business and clinical) and project management office - Involved in many professional and charitable organizations - Serves on several boards involved in employee assistance and promoting technology in healthcare - Contributes as a mentor and educator in teaching opportunities to students and other professional networks focused on topics on her expertise in technology, governance, strategic planning, and project management - Has developed accredited courses on the topics of change management, as well as portfolio and project management
  • Introduction • Juliet Silver, MBA, FCMI, PMP Director, Healthcare Strategic Advisory Services Perficient, Inc. - Healthcare Analytics Strategist and Management Consultant - Supports ProHealth Care and other clients with guidance on BI program leadership, establishing the Data Governance framework, and creating the roadmap to operationalize the BICC - Specializes in the development of strategic roadmaps and implementation plans for providers, with specific focus on data warehousing, clinical data models, healthcare business intelligence and data analytics
  • Agenda • Introduction • An Innovative Approach • The Result and Solution • ProHealth’s Journey • Risks and Lessons Learned • BI Program • Data Governance • Business Intelligence Competency Center • Q & A
  • AN INNOVATIVE APPROACH TO POPULATION HEALTH MANAGEMENT Christine Bessler, CIO, ProHealth Care
  • ProHealth Care Overview • Community-focused healthcare system • Regionally focused IDN in Waukesha, WI • 15 primary care facilities, 3 hospitals, home health care, hospice services, long term care and senior residence communities, health and fitness center • Not-for-profit organization • 1000 physicians and 4800 employees • Attested to Meaningful Use Stage 1 for hospitals and physicians • Attained Stage6 designation on the HIMSS Analytics EMR Adoption Model (EMRAM)
  • An Innovative Approach to Population Health Management Why Innovative? • ProHealth Care is the first to use Epic’s Cogito data warehouse in conjunction with the Microsoft BI stack to manage population health • ProHealth Care is the first health care system to use Epic’s Cogito data warehouse in a production environment
  • The Result • Physicians can easily identify gaps in care • Physicians have analytics tools to enhance preventive care and the management of chronic diseases
  • The Solution • Providers and/or their administrator(s) can assess the system only via supplied credentials and secure login process which ensures the confidentiality of the Protected Health Information (PHI) contained within the system • Upon login, users must specify parameter values to run their report(s), including provider specialty, provider name and measurement period month
  • The Solution • After selecting the desired report parameter values, the physician performance profile is displayed for the user. Measure are arranged by domain (e.g. Access, Administrative, Community Benefit, Safety, Satisfaction, etc.) to assist in report organization and comprehension. • Key report elements include: • Metric-specific performance targets, total metric population, and specialty average and rank
  • The Solution • Some metrics allow users to drill-down on their performance to display patients with gaps in care that require additional action or documentation during the selected measurement period. These are displayed via underlined hyperlink. • Users can click those hyperlinks to get their list of patients that are in that particular metric:
  • The ProHealth Care Journey
  • • Derive increased enterprise information value from existing investments in EPIC EHR • Enhance the level of clinical integration • Address population health initiatives and proactive care management of chronic conditions • Provide data collection, measurement and analysis for ACO measures Key Objectives
  • Business Challenges • Initial challenges on the business side: • Unable to monitor quality measures for ACO in a timely fashion • Unable to monitor operational data in a timely fashion • Inability to properly determine the cost of care (by business unit, physician, etc.) • Lack of personnel and funding • Centralized model supporting report creation not sufficient • Lack of decentralized reporting tool expertise within the various business units • Scope and competing priorities • Need to align with key business initiatives/strategic plan • Siloed culture • Limited collaboration
  • Clinical Challenges • Initial challenges on the clinical side: • Data Use • Information not actionable due to timeliness of data availability • Workflow/Process • Various Epic workflows not implemented • Processes not always aligned with best practices • Documentation • Inconsistency in data and terminology causing confusion by providers
  • Technology Challenges • Initial challenges on the technology side: • Integration • Clinical, operational and financial data not integrated • Excessive manual touch points • Data Integrity • Mistrust of data • Data definitions need to be defined, agreed and socialized • Assessment of current tools • Various best-of-breed still being utilized • Multiple clinical systems (Epic, Centricity, McKesson, “homegrown”) • Multiple reporting tools (Workbench, Crystal, Deski, Webi, Excel) • Epic EHR not fully utilized • Lack of standardized delivery platform • Resources • Skillsets not aligned with current needs and priorities
  • The Strategy • Establish organizational commitment to develop an Business Intelligence Strategic Roadmap and Implementation Plan • Engage a national systems integrator to facilitate strategy development and support implementation • Implement the plan in a phased approach
  • The Focus:  Analytic capabilities  Data governance  Business Intelligence Competency Center  Organizational change management  Reference architecture & technical foundation  Data foundation Plan and Roadmap for Enterprise BI, Data Warehousing and Data Governance:  Improve enterprise accessibility to trusted data, ensuring data quality, and establishing confidence in the data for improved business performance  Translate complex BI Program and Data Governance vision and strategy into manageable, phased deliverables  Establish the enterprise BI technical foundation and reference architecture  Realize transformational enterprise information management, cultural change management and organizational readiness GOVERNANCE CHANGE MANAGEMENT BI COMPETENCY CENTER TECHNICAL FOUNDATION DATA FOUNDATION ANALYTIC CAPABILITIES BI Strategic Plan
  • Plan Inputs and Drivers • Rapid time to market to provide PHC and ProHealth Solutions (our ACO) with the necessary data for the needed quality metrics • Leveraging resources and integrating services between PHC and PHS • Leveraging existing technology infrastructure and tools • Ability to extract information from non-Epic source systems (e.g., claims data, Press Ganey, etc.) • Ability to integrate operational, financial and clinical data into one data warehouse and report from a single source • A system that is flexible and scalable to promote the ability to adapt to changing requirements over time • A security framework which enables secure and appropriate access to the reports and analytics
  • Key Requirements Requirements: • Initial priority was to address ACO analytical and reporting requirements • Implementation timeline completion within six months • Minimize cost – look for most cost-effective approach • Enable expansion of analytical and reporting capabilities for future priorities
  • ACO Requirements • 33 required quality measures that are part of the quality performance standard, including: • Consumer Assessment of Healthcare Providers and Systems (CAHPS) patient experience survey measures • Claims-based measures • Electronic Health Record (EHR) Incentive Program measure • Required Group Practice Reporting Option (GPRO) web interface quality measures • Required for purposes of ACO participants earning a Physician Quality Reporting System (PQRS) incentive under the Medicare Shared Savings Program • Physician profiles to enable monitoring of screenings and care interventions
  • Analytical Needs Benchmarking Outcome Analysis ACO Analytics and Management Population Health Management Spend Analysis Value Based Pricing Claims AdjudicationValue Analysis Quality Labor Supply Optimization Supply Chain Optimization Waste and Harm Operations Management Optimization Efficiency & Effectiveness Analysis Disease Management Practitioner Profiling & Quality HEDIS 2010 (select measures) Savings Opportunities Harm Avoidance Safety Pharmacy Analysis AHRQ Harm Avoidance Alerting Actuarial Analysis Claims Handling Claims Adjudication P4P Patient Satisfaction Performance Improvement
  • How We Made Our Platform Choice Considerations: • Could we leverage Epic’s Cogito DW model? • What technology platform was needed (wanted to leverage existing investments in technology)? • If using Epic’s Cogito DW, how dependent would we be on Epic for future development? • Would we have real-time reporting? • What was the time to value proposition? • Would we have access to historical data? • What were the implementation and annual costs?
  • How We Made Our Choice Comparison of Options Considered: Option 1 Option 2 Option 3 Option 4 Option 5 Option 6 Full Cogito + custom clinical repository Full Cogito + packaged solution Partial Cogito + custom clinical repository Partial Cogito + packaged solution Custom EDW + custom clinical repository Packaged solution for clinical repository Leverage Epic's Cogito Yes Yes Yes Yes No No Database Platform MS SQL Server 2012 required MS SQL Server 2012 required MS SQL Server 2012 required MS SQL Server 2012 required Databased platform independence MS SQL Server 2012 required Epic dependency High High Medium Medium No No Near Real-Time Reporting No No No No No Yes Time to Value High Risk High Risk Medium Risk Quick Win High Risk Quick Win Historical Data Yes Yes Yes Yes Yes No Implementation Cost 5M 5M 6M 5M 11M 5M Annual Costs <20K 550K <20K 550K <20K 750K Narrowed options
  • How We Made Our Choice Criteria MS Stack Solution QlikTech QlikView SAP BI Dashboards Tableau Tibco Spotfire Cost of initial purchase and maintenance Low Medium High Low Medium Do we currently own it Partially No No No No Can current IT Infrastructure Support it Yes No Yes No No Scalability Good RAM Limited Good Good Hardware Limit Hiring related skill set (BA and Report Writers) Moderate Difficult Moderate Difficult Moderate Options Considered for Visualization Tools: Narrowed options
  • How We Made Our Choice Options Considered for BI Suite: Narrowed options Criteria MS SQL 2012 Business Objects (SAP) Oracle OBIEE IBM Cognos Cost of initial purchase and maintenance Medium Medium High High Do we currently own it Yes Yes No No Can current IT Infrastructure Support it Yes Yes No No Scalability Good Better Best Better Hiring related skill set (BA and Report Writers) Relatively Difficult Available Available Available Supports Self-Service Reporting Average Best Better Better NOTE: Considered other standard BI Suits like Microstrategy, SAS, etc. and ruled them out.
  • How We Made Our Choice Options Considered for Database Technology: Selected option Criteria MS SQL 2012 MS SQL 2008r3 Oracle 11g IBM DB2 Cost of initial purchase and maintenance Medium Medium High Very High Do we currently own it Yes Yes 10g No Can current IT Infrastructure Support it Yes Yes Yes No Scalability Good No Best Better Adequate data storage capability Good Worse Better Best Hiring related skill set (DBA and SA) Moderate Available Moderate Difficult Available HL7v3 RIM data model Feb. 2013 Yes Yes (costly) Yes Visualization and data discovery Yes No Yes Yes In-memory database technology Yes No Expensive Expensive Proven technology No Yes Yes Yes NOTE: Considered cloud solutions (Azure, Google etc) and appliances and ruled them out.
  • Solution Defined  Option 3 • Use Cogito DW first release as initial framework, but don’t wait on future upgrades. Incorporate rest of Epic data elements, as needed • Have ability to expand on DW model with Financial, Operational and other data • Consolidate PHS (ACO) transactional data into Cogito DW. • Leverage existing technology • Take moderate approach to cost, addressing speed-to-market
  • Business Value • Use Cogito as the initial framework (lower cost of initial setup), but allow expansion of data model for loading other sources • No dependency on Epic upgrades to bring rest of data from Clarity • Leveraged existing infrastructure technologies (database, visualization, etc.) • Able to deliver initial program within six months • Quickest realization of ACO Quality Measures with lowest risk • Minimal cost
  • Phase 1: Solution Architecture
  • Tools Category Vendor Product Data Warehouse Model Epic Systems Cogito BI Reporting Microsoft SSRS Data Integration (ETL) Microsoft SSIS Presentation Microsoft SharePoint Database Microsoft SQL Server
  • Risks Leading Edge Technology (for ProHealth) • Cogito Data Warehouse (CDW) not in production for Epic at any location: • Starting early • Epic Systems assisting • Phased approach • SharePoint 2013 (initial introduction with 2013 BI Team Deliverables): • Augmenting team with SharePoint expertise • Minimal risk
  • Risks Leading Edge Technology (for ProHealth) • New Skills Required (SSRS, SSAS, PowerPivot) will require education of end users and IT – planning in process: • Consultants augmenting team with appropriate skills • New additions to team (e.g., PowerPivot trainer, etc.) • Dearth of data definitions and comprehensive data integration (e.g., profile measures by specialty, etc.): • Data elements in support of ACO metrics refined to smaller subset
  • Lessons Learned • Epic’s Cogito was in early stages of development: • Gap analysis of initial Cogito data model unveiled critical missing elements that needed to be built • This took an extra few weeks of development that was unplanned • Security needed on physician profiles was complex: • Enabling practice managers to have access to providers profiles required establishing new procedures for tracking provider to manager relationships  did not exist • Building business glossary was daunting task: • Organization not prepared for complexity in establishing common definitions for initial data elements
  • Lessons Learned • Enabling data dictionary was unplanned: • Did not prepare for how to track metadata in support of DW  tool needed to be selected • Budgeting for appropriate resources: • Due to timing of implementation of BI program, organization did not have time to appropriately plan for new roles needed (Data Quality Manager, BICC Manager, etc.) • Organization not prepared for time needed from data owners and data stewards
  • OPERATIONALIZING THE BI PROGRAM, DATA GOVERNANCE & BICC AT PROHEALTH CARE Juliet Silver, Director, Strategic Advisory Services, Perficient Inc.
  • BI Roadmap Work Streams Business Intelligence Roadmap Data Governance BI Program BICC Technology Foundation Stakeholder Engagement Release Master Plan Project and Program Management Information Life-Cycle Success Metrics Communication Plan Change Management  Governance Policies  Governance Charters  Data Quality Management Plan & Quality Assurance  Audit, Logging and Reporting  Master Data Management  Data Management  Classification and Metadata  Data Stewardship  Data Standards Data Architecture  Data Security  Governance Organization Framework and Processes Program Objectives  Organizational Structure  Resources, Roles, Responsibilities  Operational Framework  Processes  Service Catalogue  Functions  Architectural Review Board  Transactional Data Foundation  Data Integration/Distribution Framework  Data Storage Framework  Data Access Services  Information Delivery Framework  Data Structure  Systems and Tools Recommendations and Selection  Reference Architecture Implementation Release 1: Charter Domain Release 2 Refine Roadmap Move to Implementation Phase(s)
  • October 31st Q1 2014 Q2 2014 Q2 2014 Q3 2014 Q4 2014 Q1 2015Q1 2014Q4 2013 PROHEALTH BUSINESS INTELLIGENCE ROADMAP (DRAFT) Program Governance BICC Stakeholder Engagement Release Strategy Project Plan Information Life-cycle Analyze Phase 2 Report Requirements Huron Report Release Master Plan Program Visual and Narrative BI SharePoint Site Publish Release Master Plan Draft Project Plan Update Project Plan Model Flow – Part 1: ACO/ P4P Model Flow – Ad-Hoc Requests Deliver Phase 1 ACO/P4P Measures Deliver Phase 2 ACO/P4P Measures Report Requirements | Development | Test | Release Report Requirements | Development | Test | Release Report Requirements | Development | Test | Release Data Arch. | ETL | Quality | Classification | Bus. Glossary Phase 2 Phase 3 Phase 4 Data Arch. | ETL | Quality | Classification | Bus. Glossary Data Arch. | ETL | Quality | Classification | Bus. Glossary Communication Plan Comm. Plan Framework Publish Comm. Plan Socialize Phase 2 Release Demo Dashboards, Report etc. User Feedback & Champions Project Reporting Project Plan Phase Updates Project Retrospectives Project Reporting Project Plan Updates Project Retrospectives Project Plan Updates Project Reporting Project Retrospectives Model Flow Part 2: ACO/ P4P Refine Model Flow Phase 2 Refine Model Flow Ad-Hoc Align Comm. Plan to Program User Training Program Status & Phase 2 Emails, presentations Announcements BI SharePoint Site Socialize Phase 3 Release Demo Dashboards, Report etc. User Feedback & Champions User Training CohortCohortCohort Socialize Phase 4 Release Demo Dashboards, Report etc. User Feedback & Champions User Training Program Status & Phase 3 Emails, presentations Announcements BI SharePoint Site Program Status & Phase 3 Emails, presentations Announcements BI SharePoint Site Metrics Develop Draft Metrics/ Scorecard Verify Measures Build System of Measurement Publish Program Measurement Model Flow Phase 3 Refine Model Flow Phase 3 Refine Model Flow Ad-Hoc Model Flow Phase 4 Refine Model Flow Phase 4 Refine Model Flow Ad-Hoc Policies Classification and Metadata Data Stewardship Data Architecture & Security Data Quality Governance Framework, Audit, Logging and Reporting Validated data set for self- service Human Resources BICC Framework and Process Functions and Service Catalogue Tools/Platform (Technical Foundation) ARB Staff Key Positions, Role Definitions Training & Education Support Release Mgmt. ACO/P4P Business Glossary Draft Draft Policies Review, update, approve Publish Policies Review ACO/ P4P Business Glossary Approve and Publish Glossary Assign Stewards for ACO/P4P Data Governance Workshop Cogito Technical Metadata Data Modelling for extended Model Establish New Classification Priorities Assign Stewards for Priorities Develop Stewardship Guidelines DQ Management Plan Draft Update with ACO DQ Standards Review with Data Stewards Revise and publish DQM Plan (1st Ed.) Approve ACO/P4P Data Security Deliver Phase 1 Data Snr. Executive Sign-Off Review Policies Revise and publish policies Iterate through classification priorities BICC Mgr, DQ Lead, Architect, Testers, Support & Training Release Mgr, Infrastructure, Security, ARB Training/ Education Demand Management Quality Assurance User Support and Help Desk QA for ACO/ P4P Modify Help Desk System SharePoint KM and BI Reporting Environment Business Glossary Repository Report Developers, Analysts Demand Management Demand Management app. Report Request Delivery BI Developers Dataflow and DQM Reports Repository ARB Process Metadata Admin. Protoyping / App Dev. BI Dev. BI Dev Studio, PowerPivot Approve and Publish updated Glossary Data Quality Management Workshop Establish New Classification Priorities Iterate through classification priorities Approve and Publish updated Glossary & Metadata Assign Stewards to Priorities Perform DQM Tasks Document Data Quality Assurance Establish New Classification Priorities Iterate through classification priorities Approve and Publish updated Glossary & Metadata Assign Stewards for Priorities Perform DQM Tasks Document Data Quality Assurance Risk Register, Audit and Reporting Issues and Decisions Information Risk Management Risk Register, Audit and Reporting Issues and Decisions Information Risk Management Revise and publish DQM Plan (2ndt Ed.) Metadata Integration & Data Standards Risk Register, Exception Reporting Issues and Decisions Information Risk Management Revise and publish DQM Plan 3rdt Ed.) SLA’s Data Architecture Phase 2 MDM Security Architecture Phase 2 Elaborate Phase 2 Technical Requirements Technical Requirements TBD Elaborate Phase 3 /Ad-hoc Technical Requirements Technical Requirements TBD Elaborate Phase 4/ Ad Hoc Technical Requirements Technical Requirements TBD MDM Admin. Master Data Management Phase 3 Data Architecture, Security and MDM Review and Approval Phase 4 Data Architecture, Security and MDM Review and Approval Review and update Human Resources and Organization Chart Review and update Framework and Processes Review and update service catalogue Phase 1 Solution Architecture Phase 2 Solution Architecture Solution & Enterprise Information Architecture Information Life-cycle and Data Lineage Solution & Enterprise Information Architecture ProHealth Care Roadmap Work Streams
  • Data Creation Data Storage Data Movement Data Usage Data Archiving • Data Modeling • Data Taxonomy • Data Migration • Data Storage • Data Access • Data Archiving • Data Retirement • Data Profiling • Data Cleansing • Data Monitoring • Data Compliance • Data Traceability DATA STRUCTURE DATA ARCHITECTURE DATA QUALITY • Data Privacy • Data Retention • DSP Data Sharing • Dealer Data Sharing • Data Ownership • Data Stewardship • Data Policies • Data Standards • Data Legalization • Master Data Management • Reference Data Management • Metadata Management DATA SECURITY DATA GOVERNANCE MASTER DATA & METADATA Managing Data Data Governance & Managing Data
  • Data Governance Committee • Chair and Executive Sponsor: • Chief Innovation Officer • Co-Chairs: • Director, Performance Excellence • Director, Business Intelligence • Standing Members: • CIO / VP of Information Technology • Dir. Behavioral Hlth/Staffing, Hospital Division Directors • Director, HIM • Manager, Strategic Workforce Planning & HR Business Intelligence • Director, Business Development • Director, Finance • Medical Informaticist • BICC Manager, Data Architect and Data Quality Lead will be in attendance at Governance meeting, providing linkage back to the BICC • Ad Hoc Members: • Additional data owners and data stewards attend governance meetings, as needed, to discuss relevant issues
  • Data Governance Initiation • Charter with scope, guiding principles, scheduled activities, voting and decision rights – Steering Committee and Data Governance Committee, informs data strategy, prioritize work/project requests, address data quality and information assurance concerns, approves business metadata • Policy Development – Develops policies that encourage the desired organizational behavior with respect to information security and data classification, data quality and standards, life-cycle management • Change Management, Stakeholder Engagement & Communication – Change Control, Visuals/Narrative, BI Demo Showcase
  • Data Governance Priorities Examples of initial deliverables: • Development of data governance policies • Establish role of data stewards • Ensuring that the data is properly defined and used throughout the enterprise • Development of business glossary and data dictionary • Survey of power users and analysts to determine data owners • Training for appropriate end users (e.g., for executives, data stewards, etc.) • Development of Release Master Plan • Development of Data Quality Management Plan
  • Data Governance / BICC Data Governance • Approve BICC estimates on Strategic requests • Define Information requirements • Control Change management process • Define Data policies and standards • Define Data Quality BICC • Manage Operational Resources • Take decisions on day-to-day operational issues based on Governance guidelines • Approve Work group estimates • Manage Work Group resource utilization • Track and Complete demand request • Make recommendations on technology/ processes/standards
  • BICC • The (BICC) is responsible for promoting optimal use of business intelligence across the organization. • The BICC provides a central location for driving and supporting the organization’s overall information delivery strategy. • Staffed with representatives from the business and IT, the BICC enables the organization to coordinate and complement existing efforts, reducing redundancy and increasing effectiveness.
  • BICC Framework Education & Support Training, Development and Implementation Ad Hoc End User Support Communication, Newsletters and users groups Advanced AnalyticsBI Program Management Data Stewardship Intake & Prioritization Requirements and Prototyping Application Development Business Metadata Quality Assurance Data Governance Data Preparation Data Mining Statistical Modeling
  • BICC Priorities Examples of initial deliverables: • BICC role definitions • Intake, Prioritization and Escalation process • ‘Building and Maintaining Business Glossary’ training for data stewards • Ensuring that the data is properly defined and used throughout the enterprise • Selecting and implementing a tool to manage metadata • Establishing the help desk and support function for BI related issues • Forming the DW and BI development team and executing on operational requests and delivering Phase 1 requirements • Developing prioritized requirements for a Release Master Plan • Development of Data Quality Management Plan
  • Connect with Perficient
  • Thank You! For more information contact: Christine Bessler CIO / VP of Information Technology, ProHealth Care christine_bessler@phci.org Juliet Silver Director, Healthcare Strategic Advisory Services, Perficient juliet.silver@perficient.com www.facebook.com/perficient www.perficient.com www.twitter.com/perficient_msft