CMS Medicaid and CHIP Business Information Solutions (MACBIS) Transforming Medicaid and CHIP Data Collection
Charles a Medicaid Beneficiary Charles lives independently and now has a full time job at Long John Silver s in Landover, MD. 2
Setting the Stage Medicaid and CHIP today $400B annually 60M beneficiaries ~3M providers 500B medical services annually Medicaid and CHIP Tomorrow $500B 80M beneficiaries 3M++ providers 600B medical services annually 3
The Need for Change Resources are shrinking and data driven decisions need to be made to ensure value in health care services Today s Pain 1. Medicaid and CHIP state Data set is incomplete and it is not current 2. Multiple data collections 3. We and States are unhappy with results Today s Technology 1. Multiple databases on multiple platforms 2. A lot of manual operations in data collection and validation 3. Expensive, proprietary, contractor centric Today s Results 1. Reports are questionable and subject to interpretation 2. Difficulties in determining the cost, integrity or value of the purchased service 3. Decisions are not data driven 4
Actionable Business Intelligence Operations Data (Cost, Encounters/ Claims, Providers and Beneficiaries) Quality Data (Adult and children s measures, MU measures) Integrated View of How We are Doing: Performance Indicators and Analytic Capacity Business Process Performance Data (Timeliness and Accuracy of Business Functions) Program Data (Benefits, Eligibility, Payment) 5
High Performing Medicaid & CHIP Programs Resources are shrinking and data driven decisions need to be made to ensure value in health care services Tomorrow s Vision Tomorrow s Technology Tomorrow s Results 1. Medicaid and CHIP state data set complete and current 2. Federal and States are happy with LOE and results 3. Decisions can be made based on facts/information 1. A scalable, responsive, flexible, multi-user, and sustainable platform 2. Multiple database interconnectivity 3. Affordable, open source to extent possible 1. Federal and state reports are the same, correct and current 2. We can readily determine the cost, integrity or value of the purchased service 3. Decisions are data driven 6
CMS Vision Enhanced Data Provisioning Databases Data Warehouses Statistical Tools BI Tools Integration Tools Validated State Data Nimble, Flexible, Analytic Environment Uniform Metadata 7
CMS Vision MACBIS Service Communities & Data Enrichment Data Integration Analytics CMS ANALYTIC ENVIRONMENT / DATA LABS Data Dissemination Reporting 8
CMS Vision Direct Access Mechanisms End User Communities Medicaid.gov/ CMS Apps/ CMS Portal Web Services/ Portlets/BI Interfaces Operational Reporting Operational Querying Analytical Reporting Analytical Querying Exec Info Briefing Books Dashboards Scorecards Medicaid & CHIP Systems & Databases Data Mining Reusable Services 9
CMS Vision CMS Business Analytics and Data Quality Support Framework Data Quality Assurance Data and Document Mgmt Data Analytics Business Analytics and Data Quality Support Data Request Manager User Adoption and Training Adhoc Workspace Mgmt 10
Realizing the Vision Medicaid and CHIP Business Information Solutions (MACBIS) TODAY ISSUES TOMORROW SOLUTIONS Incomplete Data DEMONSTRATE!! Robust Data Up-to-Date Custom Data Validation Execute Transition Establish Plan Enterprise Medicaid and CHIP Data Validation/Rule Engine Limited Analytics Legacy Medicaid and CHIP T-MSIS Future - MACPRO Business Intelligence/ Reporting Data Silo ed Limited State Integration MSIS PERM WMS MFP Etc. Future Future Data Integration Comprehensive State Integration 11
Addressing Today s Medicaid & CHIP Data Issues (Operations Data: T-MSIS) Timeliness Move from quarterly data submissions to monthly Automate data quality checks at state and CMS; provide real-time feedback to states Reliability Define required data elements with all data users Define criteria, in collaboration with states, for successful submission Implement automated receipt, control and tracking of state submissions Implement ongoing data quality control through automation, reporting and building analytics expertise Robustness Define data across operational areas: beneficiaries, providers, claims and encounters 12
T-MSIS Pilot: Key Questions What does it take to get the data out of state systems into the T-MSIS format? Complex analytical task; multi-phased project for each state Requires technical assistance for states State information technology work funded by CMS at 90% - expedited APD available Do we have the right data to meet business needs? Consulted with states and external stakeholders Expanded MSIS structure of 200 data elements to over 600 data elements in T-MSIS Created a standard data dictionary for authoritative state data submissions Added additional files: Provider, Third Party Liability, Managed Care Plan file Created analytics and reports required by CMS stakeholders using the T-MSIS data elements Where should the data live at CMS? Improve efficiency of operational data submission and response to states on submission Scalability to handle larger volumes of data (assumption T-MSIS will handle data from all states) o Scalability to run static and ad-hoc reports/analytics 13
What Makes T-MSIS Better? Fewer Reports Required from States All Medicaid reports will be derived by CMS based upon the T-MSIS data, eliminating several tasks and decreasing the burden for states; Fewer Data Requests T-MSIS will be the source for granular CMS Medicaid operational data needs vastly reducing the number of ad hoc data requests; More Frequent Data Refreshes Monthly, not quarterly; Enhanced Fraud, Waste & Abuse Capabilities With expanded, more timely data, CMS and the states will be better able to detect and recover/prevent losses due to fraud, waste & abuse; Expanded Access to Data In time, states will be able to see high-level data from adjoining states, cross walked with Medicare, program, quality, and performance data. 14
Data Exchange Interoperability Current State MSIS Flat File T-MSIS Future State Flat File Custom Format Non Standards Based Limited Adaptability Limited Extensibility XML Flexible Format Standards Based Adaptable Extensible 15
T-MSIS Operational Framework Overview State Data Submission 16
Success Criteria T-MSIS Data Submission Readiness for Production Sustaining Quality and Timely Submissions Successfully submitting via EFT Meet data population requirements Meet business rules validation Up- to-date with historical data Defined operational schedule for all files 2 consecutive submissions using EFT software Maintaining timeliness - current on monthly submissions Maintaining data quality standards per business rules Maintaining release schedules for future changes advancing data quality Maintaining communications with CMS for outstanding issues 17
T-MSIS National Roll Out Accomplishments Issued State Specification documentation April 30, 2013 Revised T-MSIS data dictionary File processing specification State Data Quality business rules State Collaboration/Support Site Created State T-MSIS Collaboration Workgroup 10 participating States comprising varying levels of T-MSIS progress - AZ, FL, GA, ME, PA, SC, TN, TX, VA, WA T-MSIS State Progress 3 States participating in Beta testing - AZ, TN, VA Technical assistance ongoing with all States Release of SMD Letter 8/23/2013 18
T-MSIS National Roll Out Upcoming Activities Project communication to States via webinars on relevant project status Schedule monthly meetings with State T-MSIS Collaboration Workgroup CMS review and approval of State source-to-target mappings Roll out testing environment for state file processing and operational readiness testing Historical Data migration conversion routines to maintain downstream systems Instituting Change and Release Management 19
T-MSIS Progress Towards Implementation As of mid-august: 6 states - Design/Development Phase - 3 of these states are BETA testing with CMS 20 states - Requirements/Design Phase (Source-to-target mapping) 10 states Planning Phase 15 states - Re-plan/Project Startup 20
TIMELINE: T-MSIS PROJECT Jan 2013 April 2013 July 2013 Oct 2013 Nov 2013 Dec 2013 Jan 2014 Apr 2014 July 2014 12 Pilot States 4/30 issue DD, Rules, Tech specs Project Evaluation 8/29 Revised DD updates 8/15 9/30 Beta Testing 10/1 Re-Plan 11/1 Final Error Messages 11/15 State Operational Readiness Checklist Source-to-Target Mapping Review/Approval State File Testing w/ CMS 12/1 State Operational Readiness Testing CMS Approval Execute 2/1/2014 CMS production Go-Live 1/2 MSIS Data migration T-MSIS National Go-Live State-side States Onboarding Onboard Plan Execute Onboard Plan Execute 21
Actionable Business Intelligence Transformation Core principles Current Future Data Timeliness Quarterly Submission Latent data from states Monthly Submission Edit rejections at record level Data Robustness Limited set of MSIS elements Lack of data integration Manual program data Robust set T-MSIS elements Data integration Data Completeness Data Quality Data submitted incomplete Limited data quality rules applied at state Data Validation at state level Tier 2+ at CMS level Improved error processing Data Accessibility and Usability Foundational Technology Limiting data analytics Minimal end user access Lack of stakeholder adoption for data use Lack of data integration Manual Processes Inefficient data schemas Robust analytics Data Labs Stakeholder adoption of enterprise data Scalable Enterprise Technology Automation of processes 22
Getting There...the Road to Our Future 2014 T-MSIS National cutover Migration of MSIS historical data since 1999 Limited analytic tools available 2015 T-MSIS continuous data quality improvement Integrated Medicaid & CHIP Data Environment Subset of targeted legacy systems integrated into data environment e.g. EPSDT Continued maturity of Business Analytics and Data Quality Support Team 2016 Targeted legacy systems integrated into data environment Achieve Integrated Data Environment that supports robust data analytics 23 23
State T-MSIS Q &A Panel State experience to date Dos and don ts for T-MSIS progress Considerations for success Open discussion 24
QUESTIONS 25