the changing face of data quality within vha n.
Skip this Video
Loading SlideShow in 5 Seconds..
The Changing Face of Data Quality Within VHA PowerPoint Presentation
Download Presentation
The Changing Face of Data Quality Within VHA

The Changing Face of Data Quality Within VHA

600 Vues Download Presentation
Télécharger la présentation

The Changing Face of Data Quality Within VHA

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. The Changing Face of Data Quality Within VHA Presented by: Elizabeth Franchi, Director, HDI, Data Quality Program Sara Temlitz, Business Product Manager, HDI, Data Quality Program Jackie Houston, Identity Management Data Quality (IMDQ) Program Manager

  2. Topics of Discussion • Provide an overview of the Data Quality Program • Review the existing and new programs within the Data Quality Program • Discuss the overall structure and framework being developed to provide business benefits of a formal Data Quality Program throughout VHA enterprise

  3. Data Quality Program Overview

  4. DQ Program: Mission Mission • “Manage and implement a data quality framework to improve and ensure comprehensive and accurate VHA data for clinicians, administrators, veterans, sharing partners and business stakeholders.”

  5. DQ Program: Overview The Veterans Health Administration (VHA) Data Quality Program: • Is part of the Office of Information (OI) Health Data and Informatics Office (HDI) and • Provides, facilitates and supports strategic direction for data management • Provides VHA with operational support to improve the quality of data required to provide and manage health care information • Includes several key components to help formalize and establish accountability for management of VHA data

  6. Information is an enterprise-wide business asset and resource; Decision-making and business planning are based on information which is derived from data; Technical and business strategy are connected; Technology plays a supportive role in the data quality process; Data governance and stewardship programs formalize accountability and management responsibilities for data; Management of data is a method to achieve the data quality needed to support the delivery of health care. DQ Program Guiding Principles

  7. Develop and manage programs for continuous data quality improvements Provide guidance and consultation to Lines of Business Manage data quality activities in support of VHA’s business VHA’s data steward for Patient Identity Data ensuring the availability of the longitudinal health record across our enterprise and with other business partners, like DoD Support VHA EHR integrity within the MPI and other applications Subject matter expert for selected national VHA reference tables Serves as key member of domain action teams and other VHA committees Data Quality – Roles & Responsibilities

  8. Health Data and Informatics • Health Information Services • Health Information Management • Patient Safety IT, • Section 508 Compliance • Corporate Information Services • Data Quality • National Data Systems • Health Information Resources • VA Central Office Library • VA Library Network • VHA Forms, Publications, and Records • Management • Health Information Governance • Information Access and Privacy • Health Care Security Requirements OI HDI Data Quality Program Overview

  9. DQ Program: Structure

  10. Data Governance Oversight & Support Profiling & Analysis Assessment Data Quality Communication Education & Training Requirements & Guidance Certification, Compliance, Audit Quality Improvement Business Involvement Business Involvement Data Quality Functional Areas

  11. DQ Program Business Benefits Reduction of inconsistent, inaccurate incomplete and/or untimely data to provide higher quality data that better meets business needs; Coordinated data quality efforts within VHA; collaboration and participation in enterprise efforts; Authoritative and participative data governance structure with business community involvement; and Common data quality principles and best practices including resolution processes.

  12. VHA Planning Strategy Data Quality Goal

  13. VHA Planning Strategy Data Quality Goal

  14. DQ Strategies Flow from Goals DQ 1: Improve the comprehensiveness, timeliness, consistency, and accuracy of VHA data for clinicians, researchers, administrators, veterans, sharing partners and lines of business. Work with management And decision bodies to establish And formalize enterprise-wide DQ responsibilities. 1.1 Support excellence in business practices through a comprehensive VHA Data Quality Program. Define governance communication and prioritization process. 1.1.1 Establish and maintain DQ governance structure… including stakeholders, roles, responsibilities, etc. Establish a mechanism to collect data quality analysis and improvement candidates for each domain/system. Implement and maintain VHA Data Stewardship Program. Identify and define roles and responsibilities of DQ stakeholders Including field reps.

  15. Systematic Activities support a Proactive Approach to Managing DQ DQ 3: Maintain and ensure the integrity of Patient identity for health care delivery, management and patient safety (PS). Facilitate identification/resolution of duplicate patient records, catastrophic edits and other identity-related anomalies. Maintain and improve formal Identity Management (IdM) practices Participate as IdM Stewards in MPI, Person Service, ADR and Toolkit UAT. Provide IdM stewardship input to Identity Management requirements And Use Cases. Participate in Patient Safety incident reviews related to IdM. Participate in retrospective review of PS incidents to identify systemic DQ issues..

  16. Data Quality Program Activities From the mission - Providing comprehensive and accurate VHA data for clinicians, administrators, veterans, sharing partners and business stakeholders.

  17. VHA’s Electronic Health Record VHA is recognized as a leader in the world of electronic health records “VHA’s integrated health information system, including its framework for using performance measures to improve quality, is considered one of the best in the nation.” • Institute of Medicine (IOM) Report, “Leadership by Example: Coordinating Government Roles in Improving Health Care Quality (2002)”

  18. VHA’s Electronic Health Record features: • More than 100 separate applications that support day-to-day activities of healthcare operations, including: • Registration/enrollment/eligibility ; • Provider systems; and • Management and financial systems • Through the Computerized Patient Record System (CPRS): • Delivers an integrated electronic health record covering all aspects of patient care and treatment; and • Provides access to remote data through Remote Data Views, Inter-facility Consults, VistAWeb

  19. Business Benefits of the electronic health record • Improves quality and safety of healthcare to veterans; • Seamlessly provides health records and images when needed/authorized; and • Enhances interoperability among VA and other business stakeholders • VHA implemented an electronic Master Patient Index (MPI) to facilitate the sharing of a patient centered longitudinal health record within VHA and with external business partners such as DoD

  20. VHA Data Quality Efforts • VHA’s Master Patient Index • Uniquely identifies patients; • Assigns a unique identifier (the Integration Control Number or ICN) • Holds roughly 15 million unique patients • Part of data quality efforts are to: • Ensure the availability of the electronic health record for patient care and related activities • Manage the unique identifiers and patient identity traits • Maintain record correlations across VHA systems like VistA, and • Enable external linkages with DoD and other business partners

  21. DQ Program: Clinical Data Quality Develops clinical data quality guidance and operating policies for VHA. Establishes and maintains mechanism to identify, resolve and monitor clinical data quality opportunities.

  22. Clinical Data Quality Program • Emerging program within Data Quality • Provides framework to identify and support activities to resolve clinical data quality issues within VHA • Collaborate in the development of overall data quality metrics and goals for prioritized data quality opportunities • Identify problem areas for audit and analysis for data verification and correction • Monitor and resolve data quality integrity issues, conduct studies and other analyses

  23. DQ Program: Program Analysis • Review, monitor, and resolve data quality issues. Performs data quality analysis on existing administrative and healthcare data throughout VHA.

  24. Program Analysis • Program Objectives • Provide support to program areas within DQ • Assist in the development of overall data quality metrics and goals for prioritized data quality opportunities • Provide audit and analysis for data verification and correction • Monitor and resolve data quality integrity issues, conduct studies and other analysis

  25. What is Data Quality Analytics? • Applies techniques to: • Analyze the quality of data, • Determine its ability to be used for its intended purpose, and • Recommend corrective action when needed • Example techniques include: • Data profiling • Process assessments, e.g., • Healthcare Failure Mode and Effect Analysis (HFMEAs) • Root Cause Analysis (RCAs)

  26. What is Data Profiling? • Assessment of data: • Content/values within databases • The data’s defined characteristics (or metadata), e.g., data type (a date field must include month, day and year) • Profiling activity may be initiated: • To analyze a reported issue (assertion testing) • To proactively discover data characteristics and anomalies

  27. Data Profiling Benefits • Enables a better understanding of the data’s quality and ability to be used for its intended business purpose • Identifies problematic areas and enables recommendations to be developed and implemented to improve inconsistent, inaccurate, and/or incomplete data • Enables data descriptions and business rules to be verified and improved

  28. Recent DQ Analytics Activity • Profiling patient identity traits (e.g., Mother’s Maiden Name) • Comparing metadata (dictionaries, models, Primary View) • Running queries against Corporate Data Warehouse (CDW) data from the VistA Patient file to: • Determine if the data meets the metadata description • Identify other data anomalies • Results will be used to improve Primary View business rules, e.g, Identification of additional blank equivalents for Mother’s Maiden Name

  29. Recent DQ Analytics Activity • Initiating a HFMEA for Date of Death • Erroneous Dates of Death cause cancellation of medications, future appointments, etc. • Incorrect Dates of Death lead to data integrity errors, such as: • Vitals exist for after DOD • Encounters exist after DOD • Omission of Dates of Death cause business processes to continue, such as: • Appointment letters sent to deceased patients • Medications delivered for deceased patients • Appointment slots not available for waiting patients

  30. DQ Program: Identity Management Responsible for integrity of patient identity data within Master Patient Index (MPI). The Identity Management Data Quality (IMDQ) team supports VHA site personnel and is the primary liaison with the MPI.

  31. Identity Management Stewardship The Identity Management Stewardship Program is responsible for the business stewardship of identity data as part of the electronic health record within VHA. A major component of this program is the Identity Management Data Quality (IMDQ) team, which provides specific stewardship for the data required to link patient identities to their related information in VHA and other systems. The team is responsible for the data integrity and business analytics support of VHA’s Master Patient Index (MPI), the unique identifier system for all patient records within VHA.

  32. IMDQ Team Responsibilities • Defines business rules and processes governing identity management to ensure accuracy and integrity of VHA’s longitudinal health record • Monitors and resolves data integrity issues and conflicts on the MPI and local VistA systems • Resolution of duplicates • Mismatches and catastrophic edits • Ensure the quality of data • Improve process and method of entering patient record data • Facilitate information dissemination and training • Improve the understanding of the MPI and identity management and it’s direct relation to the patient record

  33. Identity Management Activities • Management of Catastrophic Edits and other data quality issues • Support of Master Patient Index (MPI) development • Enhancements to existing software, including Primary View Implementation • Re-hosting to Administrative Data Repository (ADR) • Assistance for implementation of Person Service Identity Management (PSIM) • IMDQ Toolkit development • Non-person enumeration • Enrollment System Redesign implementation • Other HeV application development support

  34. Jane Q. Doe 000-00-0001 01-01-1901 Female John Q. Doe 000-00-0001 01-01-1901 Male Catastrophic Edits Common Causes of a Catastrophic Edit • Erroneous Patient Selections • Patient Records Used as Templates • Erroneous or Catastrophic Duplicate Record Merges • “Recycling” of old patient records CatastrophicEdit

  35. Catastrophic Edits to Identity • Effects of Catastrophic Edits • Incorrect association of patient medical record data to a different patient’s record • Intermingling of two different patients’ records • Actions taken to reduce Catastrophic Edits • Changes to VistA software to warn of potential catastrophic edits • Distribution of notifications of occurrences to local management • Tracking of resolution to ensure medical records are restored • National staff within the Identity Management Data Quality group monitor alerts about potential problems daily • Patient safety risk is high • Treatment may be administered to wrong patient • May not have complete or accurate information about patients, including allergies, current medications • Electronic health record may become fragmented or have conflicting data

  36. DQ Program: Data Stewardship Establishes and formalizes accountability for the characteristics and management of VHA data and ensures business stakeholders fully participate in decision-making regarding data essential to them.

  37. Data Stewardship Objectives • Develop an effective data stewardship program for the organization, leveraging existing activities; • Coordinate/support business and technical stewardship efforts for VHA business community • Work with Line-of-Business (LOB) Data Stewards and subject matter experts and ensure that they have necessary knowledge, training, and support to fulfill stewardship responsibilities; • Lead/coordinate stewardship activities for the domains defined in enterprise information models and by LOB managers; and • Collaborate with DoD, Indian Health Service, business partners, VA technical teams and external data architecture and standards organizations. * Emerging program; not yet fully staffed

  38. DQ Program: Business Products Ensures business stakeholder DQ requirements are identified and communicated; Liaison for data quality issues between business groups, technical communities and the DQ program.

  39. Business Product Management The Business Product Management Program ensures that business stakeholder data quality requirements are identified and communicated through appropriate processes, and monitors progress to ensure business needs are met. This Program serves as a liaison between business stakeholder groups, technical communities and the Data Quality Program in issues related to data quality, including those involving identity management.

  40. Business Product Management Program • Provides expertise to business stewards on: • Business requirements development, • Enterprise requirements management process, and • IT development process • Works with stewards and other stakeholders to: • Define detailed business requirements specifications for both legacy VistA and HealtheVet applications • Develop and obtain approval of overarching data quality requirements • Collaborate with ESMs, architects, developers and other technical staff to develop formal business models and technical specifications • Participate in design validation and user acceptance testing

  41. Enterprise DQ Requirements • Develop Requirements for Enterprise Repository • Integrate DQ requirements into the development lifecycle • Inception • Elaboration • Construction • Transition • Provide guidance and support to development and program staff

  42. Summary • The VHA Data Quality Program continues to develop and expand its role in improving data for all aspect of healthcare within VHA and with other business partners • High quality data is essential for the provision of quality healthcare for our patients and for other business needs • Collaboration with others within our organization is critical in ensuring data quality

  43. Resources Data Quality Identity Management Data Quality Administrative Data Quality Council Data Consortium

  44. Contacts Beth Franchi, Director, VHA Data Quality Program(414) 389-4191Elizabeth.Franchi2@va.govSara Temlitz, Business Product Manager(414) 389-4192Sara.Temlitz@va.govJackie Houston, Identity Management Data Quality Program Manager(205)