1. UK Renal Registry 2013 Annual Informatics Meeting UK Renal Data Collection and Information Model 1 Dr Keith Simpson, Medical Advisor UKRR Peter Nicklin, Business Analyst, HSCIC Birmingham, 25 September 2013

5. National & regional Renal registries affiliated to the ERA EDTA. Individual patient data Aggregated data

9. Survival of all RRT patients by PRD Scottish renal units November 2009

14. Mars Climate Orbiter NASA 1998

15. N s

16. Ft Lb s

18. Dr Alison Almond SRA 2008

19. UKRR Report 2011 % HD patients with PTH within range (16 – 32 pmol/L

20. UK Renal Registry UKRR Scottish Renal Registry SRR Renal Patient View RPV Renal PatientView UK Registry for Rare Kidney Diseases RaDaR British Association for Paediatric Nephrology BAPN UK Renal Data Collaboration (UKRDC)

21. RPV. Labs Renal Units UKRR SRR RaDaR NHSBT Other National data BAPN UK Renal Data

24. BAPN RaDaR Who sees the data UK Renal Data Collaboration SRR UK RR RPV Patient Research and Audit Renal Units LABS Primary care – prescribing etc HES, RGOS etc NHSBT

26. BAPN RaDaR UK Renal Data Collaboration SRR UK RR RPV Patient Research and Audit Renal Units LABS Primary care – prescribing etc HES, RGOS etc NHSBT meta data

27. International Health Terminology Standards Development Organisation

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33. BAPN RaDaR UK Renal Data Collaboration SRR UK RR RPV Patient Research and Audit Renal Units LABS Primary care – prescribing etc HES, RGOS etc NHSBT EPRs SNOMED CT NLMC dm+d meta data

36. BAPN RaDaR UK Renal Data Collaboration SRR UK RR RPV Patient Research and Audit Renal Units LABS Primary care – prescribing etc HES, RGOS etc NHSBT EPRs SNOMED CT NLMC dm+d granular data data id GUID meta data

38. BAPN RaDaR UK Renal Data Collaboration SRR UK RR RPV Patient Research and Audit Renal Units LABS Primary care – prescribing etc HES, RGOS etc NHSBT EPRs SNOMED CT NLMC dm+d standard messages eg FHIR granular data data id GUID meta data

40. BAPN RaDaR UK Renal Data Collaboration SRR UK RR RPV Patient Research and Audit Renal Units LABS Primary care – prescribing etc HES, RGOS etc NHSBT EPRs SNOMED CT NLMC dm+d standard messages eg FHIR granular data data id GUID intelligent validation real time messages data ownership, provenance, governance meta data

43. BAPN RaDaR UK Renal Data Collaboration SRR UK RR RPV Patient Research and Audit Renal Units LABS Primary care – prescribing etc HES, RGOS etc NHSBT EPRs SNOMED CT NLMC dm+d standard messages eg FHIR granular data data id GUID intelligent validation real time messages data ownership, provenance, governance meta data home dialysis drug reconciliation symptom reporting

44. Quality in Medicine Bristol was awash with data. There was enough information from the late 1980s onwards to cause questions about mortality rates to be raised both in Bristol and elsewhere had the mindset to do so existed’ Prof Sir Ian Kennedy The Bristol Royal Infirmary Inquiry. 2001 BrWsDif

45. Information Model Why have a model? What the Model is and what it is not What is in it? State of Development

46. Why have a model? An orderly way of specifying information Say things only once Identify and understand the relationships between things

47. Responsibility ** Specify things only once Person Name Address Telephone email Patient NHS no DoB Sex Ethnicity Clinician Registration Title Role Clinical Team Team Name Clinical Agent Team Membership * * * * Related Person

48. Why a Model? Link things to each other

49. Model will link things: Dialysis & samples Before dialysis starts Patient id 7309276388 Test requested U&E Time 08:17 25 Sep 13 Sampler Nurse E McKay Stage Pre dialysis During dialysis Patient id 7309276388 Test requested U&E Time 10:58 25 Sep 13 Sampler Nurse E McKay Stage During dialysis After dialysis Patient id 7309276388 Test requested U&E Time 13:26 25 Sep 13 Sampler Nurse J Pugh Stage Post dialysis Dialysis Start: 08:22 25 Sep 13 End: 13:22 25 Sep 13

50. And as it appears in the model

51. Linking: Observation as an outcome of a procedure Patient id: 7309276388 Procedure: dialysis Time: 13:26, 25 Sep 13 Outcome 14:00, 25 Sept 13 Creatinine: 200 µmol/L

52. Linking: Drug Indication Indication Arrythmia Prescribe Beta blockers Dr Brian Smith Consultant Nephrologist Glasgow Western Infirmary 23 Sept 2013

53. The Model is intended to support the transmission of renal care data from Renal Units to the UKRDC data warehouse makes no assumptions about the technical nature of the UKRDC database or about the message method that may be adopted

54. Model Is Not It is not a database design It is not a message design

55. What is in it: coverage Peritoneal Dialysis and Haemodialysis –Prescription –Session –Access Measurements –Lab –Image –Vital Signs (height, weight, BP etc.) Link Measurements Precisely to Dialysis (before, after etc.) Primary Renal Diagnosis and other diagnoses Drugs Basic Admission Discharge and Transfer (ADT)

56. What is in it: Vocabularies VA 91 – Removal Reason (i.e. Temporary catheter) –Venous thrombosis –Use of alternative vascular access –Recovery of renal function –Switched to PD –Switched to HD –Renal transplantation –Accidental removal –As per Access complication

57. State of Development The model is not complete: –Scope (Transplant, Paediatrics, Genetics etc.) –Need further verification However, even as it is, implementing its scope will take a lot of effort Do it in chunks

58. What could go wrong?

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65. http://www.theguardian.com/world/2013/sep/05/nsa-gchq-encryption-codes-security

66. p1 06 Sept 2013

68. BAPN RaDaR UK Renal Data Collaborati on SRR UK RR RPV Quality Improvement LABS Primary care – prescribi ng etc HES, RGOS etc NHSBT Clinical care Teaching Learning Running service Research