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Automated Cancer Registration N.Ireland Experience

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vthomason
17 diapositives · 191 Views · Jan 03, 2020

This case study presents the experience of Colin Fox (IT Manager) and Richard Middleton (Data Manager) in establishing an automated cancer registration system in Northern Ireland. They discuss the background, sources used, registration process, outputs, quality assurance, and the challenges faced in implementing and maintaining the system. This text is in English.

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  1. Automated Cancer RegistrationN.Ireland Experience Colin Fox (IT Manager) Richard Middleton (Data Manager)

  2. N.I. Cancer Registry Background • Serves 1.6 million population • 1959 Card Registry • 1994 New Registry set up • 1996 Computer System installed • 1997 Report Incidence 1993-1995 • 8500 Malignant Registrations including NMS • 7000 Non Malignant Conditions

  3. Why did we choose this route? • Electronic sources available • Patient Administration System (PAS) • Laboratory Systems covering all Histopathology & Cytopathology • Death Certificates available electronically • No resources for manual data input • Old Registry incomplete

  4. Sources used by NICR • Histopathology • SNOMED Coded Topography & Morphology • Cytopathology (both Gynae. & Non-Gynae.) • SNOMED Coded Topography & Morphology • Hospital Discharge (PAS) • ICD9 & ICD10 • Death Certificates • ICD9 & ICD10

  5. NICR Registration Process Raw Source Table Automatic Data Load from 13 PAS sites, 5 Pathology labs, Radiology, General Register of Deaths, Minor Sources Supplier Data Files OUTPUTS:• IARC (CI5C, ACCIS, EUROCIM)• Reports (Incidence, Mortality,Survival)• Queries (Medics, Government) Revalidate Validation Modules IARC Checks Fail Types of validation include simple (eg. dates), cross (eg. site/sex) & minimum dataset (eg. topography) Data Extracts Feedback to Data Suppliers (completeness, etc) Pass QUALITY ASSURANCE AutomaticMatchingRoutines Registration Database • Search for duplicates • Check of Death Initiated Cases by inspection of GP notes • PAS only registrations - inspection of hospital notes

  6. Rules for Updating • Patient details • PAS details preference over Pathology • Site and Morphology • Pathology details over PAS • Date of Diagnosis (almost identical to ENCR) • Date of First Microscopic verification • Date of Test (e.g. XR) leading to diagnosis • Method of Diagnosis • As ENCR/ IARC rules • Multiple Primary Rules (IARC based) • E.g. NMSkins 1 Basal Cell +1 Squam. Cell

  7. Hospital Discharge Histopathology Histopathology C18.4 TSNOMED = T67010 TSNOMED = T67000 Date Admission 29.5.2000 MSNOMED =M81403 MSNOMED = M84803 C18.4 Biopsy on 15.6.2000 Biopsy on 22.6.2000 Transverse Colon 15.6.2000 Mucinous Adenocarcinoma Steps to make Electronic Tumour Registration

  8. Records processed per Year (2000) • Patient Administration System (13 Hospitals) 53,000 episodes (increasing) • 5 Laboratories • Histopathology 20,700 reports • Cytopathology (Gynae) 1,700 • Other Cytopathology 1,900 • Death Certificates 15,000 deaths • 3,500 Cancer Deaths

  9. Some Processing Stats • >99% notifications received electronically • >80% pass validation (most fails relate to lookups eg. GPs, Clinicians) • >65% automatically matched - others require manual intervention • Category PAS Path - New patient/tumour 8% 47% - Exist. Patient New tumour 10% 26% - Exist. Patient/tumour 82% 27%

  10. Quality Control • Roles of Registry Staff • Quality of Information • Histopathology • Cytopathology • Hospital Discharge (PAS) • Death Certificates

  11. Data Quality Staff (Tumour Verification Officers) • Resolve electronic data on system • Examine Hospital and GP notes • Extract Staging information from pathology reports • Carry out Audit projects

  12. Data Manager • Train and Supervise Staff • Resolve difficult cases • Up-date Coding Tables • Plan work for staff • Liaise with IT and Statistical Staff • QA work of staff

  13. Types of Information from different Sources

  14. Don’t Check PAS + Path. PAS + Cyto. Do Check PAS only Certain Path only Death Cert. Initiated Certain Cyto. + Path. All Multiples Certain “Problem” sites (e.g. bladder, bone, pleura, peritoneum, liver) Checks

  15. Burden on IT Staff • Ensuring suppliers provide data extracts on a timely basis • Correcting invalid records • No “Date of Birth”, Site/Sex validation fails • New Topography/Morphology combinations • New Clinicians, GPs • Batch Updates • Miscellaneous (de-duplication, extracts, etc)

  16. Current State • 2000 Incidence Data Ready • 2001 All data processed through • 2002 All pathology reports within one month • All PAS detailed at least 6 months behind current date

  17. Development • Part of User Group • Part of ENCR Automated C R Group • Software being updated to CACHÉ