Modernizing Data Systems in Environmental Public Health

Modernizing Data Systems in Environmental Public Health: A Blueprint for Action

□ Develop a Phased Implementation Plan ○ Create a realistic timeline with milestones ○ Identify pilot programs or departments for initial rollout ○ Plan for staff training and change management ○ Build in evaluation and adjustment periods Phase 2: Foundation Building 3. Data Literacy and Skills Development □ Assess Current Capabilities ○  Survey staff on existing data skills and comfort levels ○  Identify data champions within each program area ○  Evaluate training needs across different roles □ Deliver Foundational Training ○  Provide basic data literacy training for all staff ○  Offer specialized training for key personnel (e.g., GIS, visualization, analysis) ○  Establish ongoing professional development programs ○  Create internal knowledge sharing processes

5. Technology Infrastructure Planning □ Evaluate Technology Options ○  Research environmental health management systems ○  Assess cloud versus on-premise solutions ○  Verify if new systems can work with what you already use ○  Consider mobile-first approaches for field work □ Plan Security and Compliance Measures ○  Implement multifactor authentication ○  Plan encryption protocols for data at rest and in transit ○  Establish backup and disaster recovery procedures ○  Ensure compliance with relevant regulations Phase 3: Core Implementation 6. System Selection and Deployment □ Select Core Platforms ○  Choose a primary environmental health management system ○  Select a GIS platform

○  Identify preferred data visualization tools ○  Plan for mobile data collection solutions □ Implement Foundational Systems

4. Governance and Standards □ Establish Data Governance Framework ○  Set clear rules about who manages and uses the data ○  Decide who takes care of the data and how they should do it ○  Create data quality standards and procedures ○  Develop steps to protect private information and keep data safe ○  Establish data sharing agreements and policies □ Adopt Standardization Practices ○  Research relevant standards (e.g., HL7, LOINC, and ISO frameworks)

○  Deploy a centralized data storage and management system ○  Establish secure access controls and user permissions ○  Integrate systems where possible to reduce data silos ○  Set up automated backup and security monitoring 7. Data Migration and Refine Data Quality □ Plan Data Migration ○ Clean and standardize existing data before migration

○  Standardize data definitions and formats across programs ○  Create data dictionaries and documentation templates ○  Implement consistent naming conventions

○ Create comprehensive metadata for all datasets ○ Test data integrity throughout the migration process ○ Maintain parallel systems during the transition period

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