Chapter 4
The Enterprise Solution:
A Modern Model of HIM Practice
EIM Team Questions
How is the management of digital data different from the management of paper records?
What are differences and similarities?
What is traditional HIM practice?
What type of practices are needed to manage information in a digital era?
Traditional him practice
Traditional HIM Practice
Departmental focus
Synergy among people, processes, and documents
Management of physical records (objects)
Concerned with tracking, filing, and retrieving records, not information
Contemporary Model of Enterprise Health Information Management (EHIM) Practice
Focus on enterprise management
Synergy among people, processes, content, and technology
Data management functions across many domains
Ehim domains
Data Life Cycle ManagementManaging data from beginning to end points
Establishes:
What data are collected
Standards for data capture
Standards for data storage and retention
Processes for data access and distribution
Standards for data archival and disposal
Data Architecture ManagementIntegrated specification artifacts
Establishes:
Standards, policies, procedures for data collection, storage, and integration
Standards for information storage (IS) design
Identifying and documenting requirements
Developing and maintaining data models
Metadata ManagementStructured information that describes, explains, locates, or helps retrieve, use, or manage an information resource
Manage data dictionaries
Establish enterprise metadata strategy
Develop policies and procedures for metadata identification, management and use
Establish standards for metadata schemas
Establish and implement metadata metrics
Monitor policy implementation
Master Data ManagementManagement of key business entity data
Identifying reference data sources (databases, files)
Maintaining authoritative value lists and metadata
Establishing organization data sets
Defining and maintaining match rules
Reconciling system of record
Master Data
Patients
Vendors
Employees
Providers
Products
Location
Reference Data
Business Units
Content and Record ManagementManagement of unstructured data
Developing and implementing policies and procedures for the organization and categorization of unstructured data (content) in electronic, paper, image, and audio files for its delivery, use, reuse, and preservation
Developing and adopting taxonomic systems
Developing and maintaining an information architecture and metadata schema that identify links and relationships among documents and defines the content within a document
Data Security ManagementProtection measures and safeguards for data
Data security planning and organization
Developing, implementing and enforcing data security policies and procedures
Risk management
Business continuity
Audit trails
Information Intelligence and Big DataManagement of applications and technologies for gathering, storing, analyzing, and providing data for decisions
Assessing current intelligence needs, resources, and use
Determining scope, requirements, and architecture for enterprise intelligence
Developing and implementing policies and procedures for enterprise information intelligence
Data Quality ManagementEnsure data are meeting quality characteristics
Identifying data quality requirements and establishing data quality metrics
Identifying and carrying out data quality projects
Profiling data and measuring conformance to established quality metrics and business rules
Identifying data quality problems and assessing their root cause
Managing data quality issues
Implementing data quality improvement measures
Providing training for ensuring data quality
Terminology and Classification Management Provide a central terminology authority for the enterprise
Ensuring appropriate adoption, maintenance, dissemination, and accessibility of vocabularies, terminologies, classification systems, and code sets for semantic interoperability and data integrity
Developing algorithmic translations, concept representations, and mapping among clinical nomenclatures
Providing oversight for clinical and diagnostic coding to ensure compliance with established standards
Data GovernanceOverarching authority ensuring cohesive operation and integration of the EIM domains
Advocating for the data asset
Establishing data strategy
Establishing data policies
Approving data procedures and standards
Communicating, monitoring, and enforcing data policy and standards
Ensuring regulatory compliance
Resolving data issues
Approving data management projects
Coordinating data management organization
EIM Organization and Structure
EIM Structure
No one structure
Usually includes:
Executive steering committee
DG board or advisory or coordinating group
Tactical teams
Network of data stewards
EIM or DG office
EIM Benefits
EIM Benefits
Making information management a key organizational initiative
Increasing organizational awareness of the importance of information management
Promoting collaboration and cooperation to create a single enterprise view of an organization’s information asset
Establishing formal organizational structure tasked with authority and responsibility for EIM
EIM Benefits
Improving data quality by consolidating data sources, establishing consistent business rules for managing data, developing guidelines for data quality, and establishing authority for data ownership
Increasing efficiency and effectiveness of data used for business planning, operations, and patient care by an integrated, cross program view of enterprise data, providing an information delivery framework that accommodates easy access to data by all users
EIM Benefits
Optimizing enterprise information delivery, reducing the amount of time stakeholders spend trying to obtain data
Safeguarding data from misuse
Improving organization flexibility and agility by providing an organizational data model, improving processes and procedures, and supporting unstructured data
St. rita’s eim team Conclusions and next steps
St. Rita’s EIM Team Conclusions
EIM involves coordination of multiple domains
EIM is cross-functional and requires collaboration rather than a command and control structure
EIM requires establishing a vision and mission, and developing a strategy and goals
EIM can provide organization effectiveness and efficiency and can solve many of St. Rita’s data problems
EIM Team Next Steps
Investigate the purpose, scope, and functions of each of the EIM domains:
Data architecture management
Metadata management
Master data management
Content and record management
Data security management
Information intelligence and big data
Data quality management
Terminology and classification management
Data governance
