Ethnicity data consultation findings - Implications for ethnicity data users and recorders

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    Ethnicity data consultation findings - Implications for ethnicity data users and recorders - Presentation Transcript

    1. Ethnicity data consultation findings Implications for ethnicity data users and recorders Alicia Webb Team Leader - Identity Data Management, Information Directorate HINZ Conference, 2008 © 2003 melissa gardi
    2. Health System ethnicity data
      • Uses
      • Trend tracking by ethnicity
      • Health outcomes improvement monitoring
      • Health service targeting
      • Ethnic group participation and contribution
      • Role of Standards
      • Data accuracy and consistency
      • – time and datasets
      • Consistency with Statistics NZ
    3. About the Consultation
      • Series of questions on proposed changes to align Statistics NZ and Health ethnicity Standards
        • advantages & disadvantages
        • information and training needs
        • challenges for implementation
      • Stakeholder responses
        • Wide variety, mostly collective
        • responses
        • 38 submissions in total
    4. Key response themes
      • Poor understanding of ethnicity
      • Variable collection and recording processes
      • Ethnicity data highly valued
      • Acceptance of codeset changes
      • Concerns about New Zealander category
      • Preference for Level 4 recording
      • Preference for not increasing number of ethnicity fields
      • Preference for retaining multiple response prioritisation
      • Importance of co-ordinated change management
      • Criticality of training and support
    5. Understanding of Ethnicity
      • Not a specific question within consultation but extensive comment
      • Meaning of ethnicity – conceptual and contextual leads to complexity
      • Purpose and benefits of ethnicity data collection and recording
      • Public perception about the politics of ethnicity
    6. Variable collection & recording processes
      • Situational context – frontline tension and confusion
      • Standards and training to guide behaviours
      • Standardised tools and processes
      • IT systems support
      • Administrative vs survey settings
    7. Ethnicity data highly valued
      • Despite inherent difficulties, high value placed on ethnicity data by Health System stakeholders
        • strong reaction to threats to time-series data quality (ie inclusion of New Zealander category)
        • strong desire for improving granularity ie Level 4 recording
        • strong desire for improving understanding, processes and training
    8. Acceptance of codeset changes
      • Mandatory new codeset – technical changes across whole of Health System
      • Concern about potential for New Zealander category future visibility at Level 2
      • Varied views on residual codes
        • correct use, value and training burden
        • improve granularity, reduce collection tension, specificity for health
    9. Concerns about New Zealander category
      • Not a specific consultation question but considerable feedback received
      • New Zealander as an ethnic category - introduction of code at Level 4 and aggregation to Other at Level 2
      • No change in collection process but social marketing @ census
      • Potential impact on data quality and time-series data – consistency and continuity
    10. Preference for level 4 recording
      • General agreement but need to assess costs/benefits
      • Improved information to support planning, funding and service delivery
      • Improved granularity supports ability to reduce inequalities
      • Need ability to continue outputting ethnicity data at all levels as appropriate
    11. Preference for not increasing number of ethnicity fields
      • Mixed views indicate need to assess costs/benefits
      • Accuracy improves information to support planning, funding and service delivery
      • Completeness improves comparability with other Government datasets
      • Need to relate number of fields to changes in response prioritisation process
    12. Preference for retaining multiple response prioritisation
      • Unanimous disagreement with input randomisation method introduced within the Standard
      • Data loss issues
      • Strong support to maintain existing prioritisation methods in Health System
    13. Importance of co-ordinated change management
      • Challenges of change funding
      • Challenges of staff support and training
      • Desire for leadership and co-ordination of all agreed ethnicity changes
      • Desire to reduce risks around systems development and change
      • Desire for staged implementation to reduce cost and resource burden
    14. Criticality of training and support
      • Role of frontline staff
      • Potential exacerbation of existing collection and recording issues
      • Great variance in preferred methods of training and support
      • IT support and enablement
    15. Implications for the Health System
      • Continue coding at Level 2 with new codeset from 1 July 2009
      • Adoption of all residual codes within new codeset with guidance for use in Health System
      • Continue recording up to 3 ethnicities from 1 July 2009
      • Continue practice of input prioritisation
      • Enable reporting and outputting of ethnicity data at all levels held
    16. Implications for the Health System
      • Future system development capability and change
      • Further work required on
        • Consideration of optional to mandatory requirements for the Health System
        • Possible use of input randomisation
        • Assessment of ongoing training and support needs
      • Ministry-led change co-ordination
    17. Next Steps
      • Scoping activity - Stage 1 implementation proposed for 1 July 2009, including:
        • Codeset changes
        • Ethnicity Data Protocols revision
        • Training and support for new codeset implementation and to sustain ongoing data quality
      • Further work on impact and cost-benefit analysis and associated training needs
      © 2003 melissa gardi
    18.  

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    Alicia Webb
    Identity Data Management
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