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Admission Rates – an example of ‘Intelligent Information’. Dr Rod Jones (ACMA) Healthcare Analysis & Forecasting [email protected] Aims. Often we need to know, ‘how many do we expect’ versus ‘how many are there’ Illustrate some of the issues using acute data

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Admission rates an example of intelligent information

Admission Rates – an example of ‘Intelligent Information’

Dr Rod Jones (ACMA)

Healthcare Analysis & Forecasting

[email protected]


Aims Information’

  • Often we need to know, ‘how many do we expect’ versus ‘how many are there’

  • Illustrate some of the issues using acute data

  • Suggest an approach to clinically meaningful comparisons for wider healthcare data sets


From experience
From experience Information’

  • The benchmarks are flawed

    • Supposed differences are often artefacts of the benchmark!

      • Capitation formula allocation to PCT and subsequent PBR payment to Trusts rely on different assumptions financial asymmetry

    • Serious problems with the Data Definitions

    • NHS site-based processes of counting & coding are different

      • Each site has a unique signature (especially small PCT run units!)

      • Analyse zero day admissions separately

      • Greater effect on the ‘diagnosis-based’ HRG and on specific ‘procedure-based’ HRG

  • What works?

    • Adjust for age, sex, deprivation (IMD), ethnicity & students

    • Analyse using both HRG and OPCS procedure code

      • HRG are composites & the language of finance


From experience contd
From experience (contd) Information’

  • Look at the trend over time

    • Step changes & trends

  • Use FCE (not Spell) especially for procedures

  • Add EL + EM for final analysis

    • EL/EM boundary is not the same in all hospitals

  • Use persons if fundamental disease incidence is the issue


  • Zero day stay elective 30 above expected
    Zero day stay ‘elective’ >30% above expected Information’

    Acute site No I is a high PbR cost site. The real surgical day case rate at this site is low yet it counts very high volumes of events as a ‘day case’.


    Index of multiple deprivation
    Index of Multiple Deprivation Information’

    Intervention rates are only as good as the adjustment used to account for deprivation

    IMD is very important and is highly non-linear


    The danger of averaging modifiable areal unit property
    The danger of averaging Information’(Modifiable Areal Unit Property)

    The average IMD for this LSOA is 29.9 The HRG described by red line has an apparent rate of 3 but a real rate of 3.7 for the benchmark



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