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Enhancing Neonatal Care Outcomes: Understanding Risk Adjustment and Reporting Issues

This presentation by Shalini Santhakumaran, a statistician at Imperial College London, explores critical reporting issues in neonatal outcome assessments. It emphasizes the need for accurate data reporting, addressing challenges such as completeness and accuracy, case definitions, and variations in care. Unadjusted data can be valuable for certain analyses, while detailed statistical modeling is essential for others. The importance of understanding variations in outcomes due to case mix differences, random variation, and care practices is discussed, along with the relevance of the National Neonatal Database for population-based reporting.

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Enhancing Neonatal Care Outcomes: Understanding Risk Adjustment and Reporting Issues

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  1. Risk adjustment and other reporting issues Shalini Santhakumaran NDAU Statistician Imperial College London

  2. Why report outcomes ? Comparison Transparency Audit Commissioning Accountability Improvements in neonatal care and outcomes

  3. Data Issues • Completeness • Accuracy

  4. Data Issues Completeness Accuracy • Agreed case definitions

  5. Data Issues Completeness Accuracy • Agreed case definitions • Neonatal transfers

  6. Analysis issues • Unadjusted data is useful for some purposes • For others a more detailed analysis is required

  7. Analysis issues • Unadjusted data is useful for some purposes • For others a more detailed analysis is required • 3 reasons for variation in outcome:

  8. Analysis issues • Unadjusted data is useful for some purposes • For others a more detailed analysis is required • 3 reasons for variation in outcome: • Differences in case-mix • Random variation • Differences in care provided

  9. Analysis issues • Differences in case-mix • Random variation • Differences in care provided • Selection of variables • Use of appropriate statistical models • Cannot completely control for case-mix

  10. Survival Probability Calculator

  11. Survival Probability Calculator

  12. Survival Probability Calculator

  13. Analysis issues • Differences in case-mix • Random variation • Differences in care provided • Occurs by chance even if the underlying mortality rate is the same for all providers • Illustrate significance using funnel plots

  14. Funnel plot for adjusted SMR 95% confidence interval limits = “warning” 99.8% confidence interval limits = “alarm” ●= complete networks ○= incomplete networks

  15. Analysis issues • Differences in case-mix • Random variation • Differences in care provided • Not necessarily due to good/poor performance • ‘Constant risk fallacy’ and other local effects • Cannot tell us whether deaths were preventable • Needs to be linked to process measures

  16. The National Neonatal Database • Individual, not aggregated • Population-based • Detailed clinical record • Electronic • Collaborative access to denominator data

  17. The National Neonatal Database • Individual, not aggregated • Population-based • Detailed clinical record • Electronic • Collaborative access to denominator data • …ideal for reporting outcomes

  18. Acknowledgements • All neonatal units contributing to the NDAU • NDAU Team • NDAU Steering Board • Jane Abbott (BLISS) Jacquie Kemp • Prof. Peter Brocklehurst Prof. Azeem Majeed • Prof. Kate Costeloe Prof. Neena Modi • Prof. Liz Draper Prof. Andrew Wilkinson • Imperial College London Academic Neonatal Medicine Unit

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