State of West Virginia DW/DSS Bureau for Medical Services RFP MED11015

Transcription

1 Vendor Qualifications and Experience Section 8.0 RFP reference: 4.1.8, Vendor Qualifications and Experience, Page 51 Proposals should provide a comprehensive profile of the organization that includes a description of the management structure and ownership. Proposals should include at least three (3) business references that demonstrate the Vendor s prior experience in administering Data Warehouse/Decision Support System programs. Each reference should include the contact name, address, telephone number and address of the client, organization, and the responsible project administrator familiar with the organizations performance, and brief description of services that are provided to the reference. The Bureau reserves the right to request additional references. The Deloitte team is submitting three references with our proposal in response to the RFP for DW\DSS implementation services. These project references were chosen because they showcase our depth and breadth of data warehousing and health care experience not only with State governments, but with large national health plans. Our references clearly demonstrate our ability to successfully deliver DW\DSS consulting services to complex organizations and demonstrate our experience working with a state Medicaid programs. We believe that these references demonstrate that we have the knowledge, skills, and experience to deliver a flexible and BMS specific DW\DSS solution on time and on budget. West Virginia, Department of Health and Human Services RAPIDS Suite Development and Implementation West Virginia Department of Health and Human Services Cecilia Matheny, RAPIDS Project Manager, (304) , ext. 880 October 1994 to Present In 1994, the State of West Virginia contracted Deloitte to develop the State s first integrated eligibility system. The system was born from the State s desire to reduce the amount of manual intervention required to determine eligibility with the ultimate goal being to reduce error rates across all three eligibility programs. Deloitte transferred, designed, developed, and implemented a large-scale, comprehensive integrated eligibility system for the State of West Virginia. Deloitte also developed the automated approach for transferring appropriate data from the existing systems and converting that data into the newly developed database. In 2006, the State of West Virginia engaged Deloitte to provide a strategy and implementation plan to transform the current mainframe based integrated eligibility system to a Web-based system using J2EE technologies. The resulting initiative gave birth to erapids. The project vision is to incrementally upgrade the RAPIDS subsystems over the next 3 years. In August, 2006, DHHR launched the building of a data warehouse, the RAPIDS Analysis and Formatting Tool (RAFT). The team has delivered two releases of the warehouse, which DHHR has demonstrated at several industry conferences, consistently receiving accolades, and interest from other agencies. RAFT Our approach to developing the data warehouse followed our proven methodology for developing data warehouses. The work involved in this approach was broken down into four logical threads: Business Thread, Data Thread, Technology Thread and Project Management Thread. Vendor Qualifications and Experience Section 8.0 Page 97

2 West Virginia, Department of Health and Human Services RAPIDS Suite Development and Implementation Business Thread The Business Thread focuses on the business objectives of the user base, and generates user interfaces to reporting and analysis information which satisfies those objectives. Much of the work of this thread involved the Cognos 8 Business Intelligence package. Cognos provides a package of reporting and analysis tools which simplify end user access to key business information. Using Cognos, the business thread delivered powerful capabilities to DHHR. Major activities of the business thread included: Solicitation, scoping and prioritization of business objectives Documentation of environmental requirements, such as security, metadata and data audit Design of Data Access and Delivery components, such as standard reports and OLAP cubes Construction of Data Access and Delivery components using Cognos tools Production of end-user and help desk documentation Coordination of end-user and help desk training Data Thread The Data Thread focuses on the design of the data warehouse database, and the delivery of source information to that environment. The data thread interfaces with the business thread to capture end user requirements, and then delivers data to be accessed by Cognos reporting and analytic tools. The work in the data thread is centered on an Extract, Transform and Load (ETL) tool. This tool extracts selected data from the RAPIDS data source on DB2, moves the data to a data warehouse environment, transforms the data to meet specific data warehouse needs, and then performs a controlled load of the transformed data into the production data warehouse database tables. This process involves auditing and error handling to confirm that data quality is maintained. Major activities of the data thread included: Development of a conceptual data model based on identified LOCHHRA reports Development of logical and physical data models based on needed data transformations, calculations, summarizations and aggregations. This will include both relational and multidimensional data models as needed Development of data mappings from source to target Development of ETL processes using mappings, and including quality management and auditing modules Development of system documentation Technology Thread The Technology Thread focuses on the infrastructure supporting the data warehouse, including the installation and configuration of associated hardware and software, and the utilization of network and database capacity. Procurement of needed components was identified through the technology thread, and the technology thread validated that environments have been established and available for development, test and production at the needed times. Major activities of the technology thread included: Documentation of the technology architecture, including the interaction and components required to integrate data sources, ETL, the data warehouse target database, Cognos business intelligence tools and end users accessing data Technical specifications for any components which must be procured Installation and configuration of development, test and production environments Documentation of data center operational processes Performance monitoring and tuning New York State Department of Health, Medicaid Data Mart New York State Department of Health Patrick J. Roohan Director, Division of Quality and Evaluation Office of Health Insurance Programs New York State Department of Health Corning Tower, Room 1938, Albany, NY Phone: (518) ; Fax (518) pjr02@health.state.ny.us 1998 to Ongoing Vendor Qualifications and Experience Section 8.0 Page 98

3 New York State Department of Health, Medicaid Data Mart For over 10 years, CMA has played a lead role in design, development, and operation of the current OHIP Data Mart. This work began in 1998 under a contract with Oracle. It eventually resulted in CMA being tasked with assisting NYSDOH in extricating itself from the serious constraints which the Teradata-based emedny Data Warehouse imposed on its ability to access and use MMIS and related NYS Medicaid program data. CMA gained unparalleled experience with the intricacies of NYS Medicaid data and led the design, development and implementation of the OHIP Data Mart, leveraging a very scalable, robust and successful technology platform. CMA also led the design, development and implementation of six (6) of the eight (8) downstream Data Marts fed by the NYS Medicaid Data Warehouse. In the process CMA developed close working relationships with NYSDOH staff and project stakeholders and applied their knowledge and requirements in developing the OHIP Data Mart. The current Data Mart maintains over 15 years of detailed historical Medicaid claims and makes it available on line for various NYS and County agencies to support Medicaid program management. Users run an average of 2,000 queries a week against the Data Mart to support policy decisions about eligibility, utilization, provider participation, health care quality and outcomes, cost containment, and fraud and abuse detection and prevention. In addition, the Data Mart supports the quarterly drug rebate invoicing process for both regular and supplemental rebates. Building on this experience and the current OHIP Data Mart technology, the CMA Team has already fully architected and engineered a highly scalable, robust enterprise class data warehouse technical architecture which CMA knows, with 100 percent certainty, will meet the requirements outlined in the RFP and readily accommodate 25 years of Medicaid and other data with rapid access and response times. This new BI platform and infrastructure represents the next generation of the proven platform CMA has implemented and upgraded in consultation with NYSDOH over these 10 years in support of the OHIP Data Mart. The proposed CMA Team, led by Project Manager John Kazunas and Technical Architect, Brian Dougherty, includes a majority of Key and Core staff members who have carried out this work, including two outstanding technical experts, with in-depth knowledge of NYS Medicaid data, who have worked on the Data Mart project since the beginning. The Team has considerable working experience with NYSDOH staff and stakeholders. Because of CMA s in-depth experience with the OHIP Data Mata and familiarity with the current data warehouse, the proposed CMA technical solution also represents the lowest risk option for NYSDOH. NYSDOH will not incur problems by converting to a new technology platform or be constrained by a packaged warehouse database which has been designed to support a vendor s reporting system, rather than the more diverse needs of NYS Medicaid program operations. To meet the aggressive project schedule indicated in the RFP, a new vendor will face a steep learning curve, but the CMA Team can hit the ground running because it is already largely in place. Most importantly, the solution has been pre-engineered as a build out to extend capabilities of the current highly successful OHIP Data Mart platform to the new NYSDOH MDW. CMA s Chief Warehouse Architect played a key role in designing this robust Data Mart technical architecture, using enterprise class servers and storage, to support large volumes of Medicaid data spanning approximately 100 terabytes. The technical architecture implemented by CMA includes large-scale IBM and Sun Servers along with sophisticated EMC storage solutions using Oracle database technologies. In addition to the primary production environment, CMA also implemented a failover environment, using similar enterprise class hardware and software. CMA played a key role in supporting all components of design, implementation, and operations including: Requirements analysis Technical architecture design Schema development Hardware/Software acquisition, implementation, and periodic technology refresh Physical database design and implementation Data extract, transformation and loading Performance tuning End-user access tool evaluations and recommendations Data analysis, reporting and query development Technical support for application development Comprehensive deployment and training for more than 200 end-users Vendor Qualifications and Experience Section 8.0 Page 99

4 Capital Blue Cross, Inc. Enterprise Information Management System Capital Blue Cross Joseph N Romano, Senior Vice President and Chief Actuary Capital Blue Cross 2500 Elmerton Ave. Harrisburg, PA Phone: (717) Joe.Romano@CapBlueCross.com January 2005 to July 2006 Capital Blue Cross was at an important junction to accept information management best practices as a meaningful goal. To achieve this transformation, Deloitte was engaged to perform the following: Phase 1. Perform a comprehensive assessment of the current information management intellectual capital and help develop an implementation plan for the development of the data warehouse (EIM: Enterprise Information Management System) architecture Phase 2. Following the release planning activities, Deloitte facilitated the formulation of the approach and the selection of the package solutions that set the implementation process in motion. Additionally, due diligence and selection of other tools (e.g., DBMS, BI, ETL, etc.) was performed The client engaged Deloitte to manage the scope, planning, delivery, and rollout of the initial releases of Enterprise Information Management (EIM). This includes Release 1.0 (medical release), Release 2.0 (pharmacy release), maintenance releases, as well as planning for future releases. During Phase 1, we were involved in the following activities: Guided client through the requirements gathering to determine strategic business questions from the areas and functional requirements of solution Identified the key corporate drivers (based on strategic goals) that would be used to objectively evaluate and prioritize business requirements Lead client through development of a phased implementation plan that developed the completed warehouse incrementally and included identification, evaluation, and selection of vendors for industry package solutions for warehouses vs. individual components to build the warehouse Performed assessment of data sources to determine volumes, data quality, and retention of information types During Phase 2, we were involved in the following activities: Provided the client with structure and clarity around the various components in the EIM architecture (Business Intelligence tools, DBMS, Metadata, and ETL tools) of the data warehouse Performed vendor analysis to assist the client in selecting the optimal package solution to accelerate implementation. Deloitte was involved in this effort in the following capacity: Developing RFP documentation Facilitating vendor communication Consolidating vendor responses and feedback Synthesizing vendor responses and performing comparative vendor analysis Assisting the client to rate the vendors and ultimately facilitate and reach consensus on the final decision Facilitated activities to assist the client to define interim and long term solutions for EIM in terms of infrastructure, package solutions and architecture Our Role in Release 1.0 (Medical), Release 2.0 (Pharmacy) and Maintenance release: Following the completion of Phase 2, the client positioned Deloitte in a leadership role to help manage and deliver Release 1.0 and Release 2.0 which were the first foundational releases. Deloitte helped drive the activities across the phases of the releases and was commended for delivering on-time and within budget. Key activities included: Helped the client determine scope with focus on functionality that would derive the maximum benefits within a shorter time frame Assisted the client to determine the right sources of key information (legacy or third party sources) and how the data needs to be integrated into the warehouse Determine resource needs for implementation (including environment needs, hardware and teams of people with representation from the business areas and the right skill set for data stewardship, validation of requirements and acceptance) Developed timelines and work plan to manage implementation Managed the requirements phase that included strong interaction across the client business areas to collect various perspectives Vendor Qualifications and Experience Section 8.0 Page 100

5 Capital Blue Cross, Inc. Enterprise Information Management System and viewpoints and consolidate and analyze to formulate key requirements deliverables. Requirements included: Data Mapping Requirements in order to map source data to the data warehouse The development of a Data Dictionary that was a result of bringing consensus to business terminology and definitions after facilitating the resolution of a large volume of controversial terms. The data dictionary formed the foundation of the metadata in the data warehouse Facilitating the business rules and logic in the development of the extracts that extracted, transformed, and populated the data in the data warehouse Leading sessions to identify and design key business reports for appropriate business areas for targeted use after Release 1.0 go-live Managed the testing phase to prepare the client for User Acceptance as well as provide oversight on the test execution activities. The key success factor during the testing phase was the timely resolution of critical issues between Pilot and Production validation. Deloitte was instrumental in driving and managing the issue resolution process and facilitating the right level of communication that resulted in timely user acceptance and sign-off from the client. Key activities included: Development of the Testing approach, methodology, and plan Development of a framework for Test Cases and scripts Assist client in determining the Acceptance Criteria for Go-Live Facilitate test preparation Manage test execution activities and track progress through Pilot and Production Manage Issue Resolution, research and data quality Track and measure client satisfaction, feedback, and issues Solicit and obtain sign-off from the relevant parties Vendor Qualifications and Experience Section 8.0 Page 101