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AUTOMATION IN PRACTISE: The SWCIS Experience

AUTOMATION IN PRACTISE: The SWCIS Experience. Presentated By: Tina Ball …………Head Of Registration Gill Christmas ……Head Of IT. 4th December 2002. Automation In Practise - SWCIS. Where Did We Start From?. Merging of 2 Registries – Wessex (part auto) South West (fully manual).

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AUTOMATION IN PRACTISE: The SWCIS Experience

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  1. AUTOMATION IN PRACTISE: The SWCIS Experience Presentated By: Tina Ball …………Head Of Registration Gill Christmas ……Head Of IT 4th December 2002

  2. Automation In Practise - SWCIS Where Did We Start From? Merging of 2 Registries – Wessex (part auto) South West (fully manual) Auto load of Clearnet for at least 8 years No auto load of either pathology or deaths data Deaths – 6 weeks to process

  3. Automation In Practise - SWCIS Where Are We Now? Electronic Data Records Coverage Clearnet - 700,000 - 100% Pathology - 100,000+ (exp) - 83% Cancer Deaths - 22,000 - 100% X-regionals - 3,500 - 95%

  4. Automation In Practise - SWCIS Why Did We Go the ‘Auto’ Route? 1) Clearnet processing – 700,000+ records a year to handle - capture of clinical data 2) Speed up Registration – more timely + improve availability of information 3) Flexibility to handle constantly expanding data sources

  5. Automation In Practise - SWCIS The Auto Load Process 65 % Clearnet No manual intervention Overnight Batch Processing – 80 % Cancer Deaths Auto fill of demographics, some tumour details and all treatment (Clearnet) Manual intervention Recycled Records Rapid processing of pathology text

  6. Auto loaded

  7. Auto loaded

  8. Strip off Automation In Practise - SWCIS keep Processing Decisions – the ‘Markup’ process Report : SWCRF SWCRF Sort sequence : SWCRF SWCRF Run Number : 52 Originally reported : 07/08/2000 08:05 Report date : 09/08/2000 11:33 [1m[1MOF-NINESEVEN [2m F23/07/1956Q123456 THE STARSHIP THE ENTERPRISEDr B CrusherQAH ITUQ AA007007K/99 POST MORTEM HISTOLOGY Sections from the greater omentum show diffuse infiltration by a moderately differentiated adenocarcinoma as seen previously ………. ……………………….. Dr Test SHO in Pathology Test Hospital ALPHA QUADRANT DCT/GCS/JM 1.8.00 SNOMED CODES: Seq 2 T57000 - M81403, [1m [2m Dr I Test 847 25/05/2002 01/06/2002 [1m[1mBAGGINS BILBO [2m M 23/07/1956 P000000 Pathology word document

  9. Automation In Practise - SWCIS Text added to assist Registry officer End Result Q123456||19560723||F||THE STARSHIP,THE ENTERPRISE||OF-NINE|SEVEN|20020525|# Event Date: 20020525: # Hospital ENT02 : # Unit No: Q123456 # Clinician Name: B CRUSHER # Specimen Source: QAH # Pathologist Name: DR I TEST # Snomed Codes: T57000 - M81403, # Pathology Text: POST MORTEM HISTOLOGY ^ Sections from the greater omentum show diffuse infiltration by a ^ moderately differentiated adenocarcinoma as seen previously ………………^ Dr I Test ^ Test Hospital^ P000000|19560723|M|MIDDLE EARTH,THE LAND|BILBO|BAGGINS Decided to use PERL: Programming Extraction and Reporting Language

  10. NHS Number Unit Number Birth Date Surname Forename Address Post Code Morphology ICD Site Behaviour Laterality Automation In Practise - SWCIS Patient/Tumour Match Data clean & validation Data extraction Definate Match & New Clearnet Cancerbase Database Perl Markup Markup Database Auto InDefinate match Pool Database Path, pas etc Manual Business Rules / Data Validation Manual

  11. Automation In Practise - SWCIS Automated Validation Rules • 35 reference tables within Cancerbase • On line cross validation checking, examples are • - AD later than DoD • - Site and Morph compatible • - Site and Behaviour compatible • - Stage Type and Stage • Based on ONS and UKACR guidelines

  12. Automation In Practise - SWCIS Burden On IT Dept National GP, Consultant Hospital Codes OPCS 4 Codes ICD 10 Codes NHS no CLEARNET: - no names or addresses – nsts run - different formats received within each field - cleaning, validation and de-duplication - scripts not static – data formats & content change OTHER DATA SOURCES: - separate script for each data source - again scripts not static – data formats & content change - multiple applications

  13. Automation In Practise - SWCIS Burden On IT Dept - contd STAFF: - increase in IT staffing levels – faults/enhancements - availability & retention of skilled staff - on-going training costs

  14. Automation In Practise - SWCIS 3 Recommendations BEFORE developing an automated Cancer Registration System …………… 1) Do not under-estimate the complexity of automating the cancer registration process 2) Do not under-estimate the development costs and on-going costs of support & maintenance 3) Test , test and test again WE WISH YOU LOTS OF LUCK !

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