HOW A RENAL REGISTRY CAN

Transcription

1 HOW A RENAL REGISTRY CAN INFORM AND IMPROVE PRACTICE Damian Fogarty Chairman, United Kingdom Renal Registry Consultant Nephrologist and Senior Lecturer Queen s University Belfast and Belfast City Hospital, Northern Ireland, UK. d.fogarty@qub.ac.uk damian.fogarty@belfasttrust.hscni.net SpR Club Belfast Saturday 26 th February 2011

2 OUTLINE Why have a renal registry? How does the UK Renal Registry (UKRR) work? Achievements of renal registries What is missing? How can you help?

3 WHY HAVE A RENAL REGISTRY? Record and compare activity Achievement of clinical markers of care Outlining differences between units Exploring differences between units Changing practice Education on practice and differences Stimulating change Measuring the change

4 MANAGERS AND CLINICIANS WILL BE EXPECTED, IN THE FACE OF A GROWING AND INCREASINGLY COMPLEX DISEASE BURDEN, TO PRESERVE THE GAINS MADE IN RECENT YEARS, BUT WITH SLOWING RATES OF INVESTMENT.

5 HOW DOES THE UK RENAL REGISTRY DO THIS? Every renal centre in the UK has an IT system that allows capture of a UKRR dataset (16 systems across the UK) Data on all RRT patients extracted quarterly Fully electronic Extensive data validation Funding by capitation fee ( 19 per patient per annum) 100% coverage of UK units achieved in 2007 Data submission-department of Health requirement Data Protection Act Approval to use identifiable data through Section 251 of the Health and Social Care Act (2006)

6 Paper records multiple, unstructured, disorganised, illegible, often garbled Patient has left white blood cells at another hospital She has no rigors or shaking chills, but her husband states she was very hot in bed last night The patient has been depressed since she began seeing me in 1993 Healthy appearing decrepit 69-year old male, mentally alert, but forgetful She is numb from her toes down Patient was alert and unresponsive When she fainted, her eyes rolled around the room Between you and me, we ought to be able to get this lady pregnant

7 Sample Proton screens

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9 Takes minutes to load some systems, if the PC works 3 passwords to get to the RRT patients Additional 5 minutes to double check notes Then you start ticking boxes-easy

10 ANNUAL REPORTS A resource in the development of patient care in renal disease comparative data for audit, benchmarking, planning, policy and research.

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12 CLINICAL DATA VOLUME AND main units 4 quarters per year 300 files Hundreds fields/file ~50,000 patients 10 million elements/file Encryption Validation steps Cc last years file Timelines/transfers Modalities Biochemistry Haematology Access

13 60 Million people 75 Main Renal Units Quarterly data downloads 47,525 prevalent patients 31 st December 2008 Annual report on unit activity-incidence, prevalence, modalities Unit performance displayed as caterpillar plots and funnel charts

14 HOW TO IMPROVE PRACTICE National policy Regional comparison E.g. transplant outcomes Local Unit level improvement Study the clinical processes of care in different centres, Regular internal audit Computer-aided prescription Reminder systems Individual patient level improvement Staff resources Referral /reminders to transplant/access etc

15 Bangladesh Finland NZ UK Australia Norway Netherlands Spain Poland Sweden Malaysia Uruguay Republic of Korea Belgium (French) Belgium (Dutch) Greece Japan USA Taiwan Acceptance rate (pmp) Figure 16.1: Annual RRT acceptance rate (pmp) by country in Country UK Renal Registry 12th Annual Report

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17 Number of patients Figure 4.3: Growth in prevalent patients, by treatment modality at the end of each year ,000 40,000 35,000 30,000 25,000 20,000 15,000 10,000 5,000 0 PD Home HD HD Transplant Year UK Renal Registry 12th Annual Report

18 P r e v a l e n t r a F i g u r e 4. 1 : P r e v a le n t r a t e o f R R T p e r m i lli o n p o p u la t i o n b y a g e b a n d a n d U K c o u n t r y 2, , , , , N o r t h e r n Ir e la n d W a le s S c o t la n d E n g la n d A g e g r o u p UK Renal Registry 12th Annual Report

19 Months TIMELINE DATA: VARIATION IN PRE-DIALYSIS TIME ATTENDING THE NEPHROLOGY TEAM Figure 3.13: Median duration of pre-rrt care by age Age band UK Renal Registry 11 th Annual Report 2008

20 CENTRE VARIATION IN QUALITY MEASURES: CATERPILLAR PLOT-HOW TO INTERPRET? Dialysis dose

21 CENTRE VARIATION IN SURVIVAL: FUNNEL PLOT-HOW TO INTERPRET?

22 Rate per million population Figure 3.4: Change in rate of UK incident RRT patients between 1980 and Diabetics Total Year UK Renal Registry 12th Annual Report

23 Centre UK Wales Scotland N Ireland England L Barts M Hope L Guys Bradfd L St.G Liv RI M RI Ipswi Dudley Prestn Donc L Rfree Newry Newc Airdrie Nottm Leeds L West Abrdn Covnt Plymth Cardff Bristol Glasgw L Kings B QEH Glouc Redng Sund Wirral Stevng Oxford Swanse Carlis Ports Hull Ulster Leic Edinb Wolve Liv Ain Sheff Stoke Derby Sthend Basldn Kent Middlbr Belfast B Heart Wrexm Inverns Clwyd Carsh Camb Exeter Shrew Norwch Klmarnk Dorset Colchr Dunfn Brightn D&Gall Antrim Dundee Tyrone Bangor Truro York Chelms Median age (years) 12th Annual Report Median age of new patients by centre

24 Proportion of patients (%) Figure 3.14: Change in rate of late presentation Year % 12 months % 6-12 months % 3-6 months % <3 months UK Renal Registry 12th Annual Report

25 CENTRE VARIATION IN QUALITY MEASURES: WHICH AREA(S) NEED ATTENTION? Dialysis dose Correction of anaemia Control of hyperphosphataemia Blood pressure

26 IMPROVEMENT OVER TIME UK Renal Registry 9 th Annual Report, 2006.

27 % of patients 80% Serum phosphate control chart, HD - Manchester West 70% 60% 50% 40% 30% U 3sd U 2sd Process Avg L 2sd L 3sd 20% Year

28 Blfst_P Bham_P Brstl_P Cardf_P L GOSH_P Glasg_P L Eve_P Livpl_P Manch_P Newc_P Nottm_P Soton_P Percentage of patients UK Figure 15.16: Percentage of patients with systolic blood pressure below the 90th percentile in Dialysis patients Transplant patients Centre

29 C e ntr e Lei c Leed s C a r s h B Q EH L B a r ts M H o p e L W es t L G u y s B r i s to l Li v R I L R fr ee H u l l B r i g h tn Tr u r o S u n d S tev n g P l y m th D u d l ey C o l c h r Yo r k W o l v e S to k e P o r ts O x fo r d M R I L K i n gs I p s w i D er b y W i r r a l S h r ew S h eff R ed n g P r es tn N o r w c h N ew c Li v Ai n D o r s et D o n c C o v n t C a r l i s C a m b B a s l d n S th en d N o ttm M i d d l b L S t.g K en t G l o u c Ex eter C h el m s B r a d fd B H ea r t UK Renal Registry 12th Annual Report MRSA BACTERAEMI A EPISODES BY CENTRE 08-09

30 VARIATION IN ACCESSING A TRANSPLANT Every renal centre in the UK has an IT system that supports care of RRT patients Mini-Electronic Patient Record Links to laboratories, PAS, dialysis machines etc Quarterly data extracts sent electronically (after encryption) to the UKRR in Bristol Data validation, error correction Pre-specified analysis Using RA audit standards where possible Target haemoglobin, biochemistry markers Listing for transplant Survival Modality use Timely treatment Access

31 Fig 1 Percentage registered for transplantation within two years of starting renal replacement treatment. Ravanan R et al. BMJ 2010;341:bmj.c by British Medical Journal Publishing Group

32 LIMITATIONS AT UNIT AND UKRR LEVEL IT infrastructure Dependence on paper for much inpatient work because it always works short term Incomplete data Inaccurate data Comorbidity Dataset omits important aspects of care, e.g Hospitalisation Quality of life Patient Reported Outcomes Measures (PROM) Nothing yet on AKI UKRR Delays in data submission Delays in responses to data validation queries Poor website and communications strategy

33 Liv Ain M Hope Clwyd Liv RI Camb Ipswi Antrim Donc Ulster Cardff Middlbr Carsh Bangor Kent Chelms Nottm Belfast Sthend Wolve Dudley Newry L Barts Redng L West Covnt Airdrie Basldn Plymth Shrew L Kings Stoke Sund Tyrone L Guys Wrexm B Heart Edinb Stevng Newc Derby Sheff Dorset Bradfd Ports Oxford L St.G B QEH Carlis Dunfn Swanse D&Gall Glasgw Norwch Brightn Prestn Glouc Hull Leic Abrdn Bristol York Inverns Wirral Dundee Leeds M RI Klmarnk Truro Exeter L Rfree Colchr England N Ireland Scotland Wales UK Percentage of patients Figure 3.9: Proportion of patients with primary renal diseases by centre Other =all other PRD categories, including: PKD, Pyelonephritis, HTN, RVD and Other 'Other' GN DM Uncert Missing 10 0 Centre UK Renal Registry 12th Annual Report

34 Centre B Heart Edinb Stevng Newc Derby Sheff Dorset Bradfd Ports Oxford L St.G B QEH Carlis Dunfn Swanse D&Gall Glasgw Norwch Brightn Prestn Glouc Hull Leic Abrdn Bristol York Inverns Wirral Dundee Leeds M RI Klmarnk Truro Exeter L Rfree Colchr England N Ireland Scotland Wales UK UK Renal Registry 12th Annual Report with primary renal diseases by centre : PKD, Pyelonephritis, HTN, RVD and Other

35 Percentage of patients Liv Ain M Hope Clwyd Liv RI Camb Ipswi Antrim Donc Ulster Cardff Middlbr Carsh Bangor Kent Chelms Nottm Belfast Sthend Wolve Dudley Newry L Barts Redng L West Covnt Airdrie Basldn Plymth Shrew L Kings Stoke Sund Tyrone 'Other' GN DM Uncert Missing UK Renal Registry 12th Annual Report Figure 3.9: Proportion of patie Other =all other PRD categories, incl

36 Percentage DECLINE IN COMORBIDITY REPORTING Median percentage amongst only centers returning comorbidity Percentage of patients with co-morbid data Year

37 LEVELS OF CONFOUNDING Comorbidity information that is present in our files Survival or other outcome Missing information within centres at patient level- e.g. if sicker patients don t get recorded Proportion of missing information at centre level as a possible indicator of quality of care

38 Relationship between serum phosphate and outcome N=1961 PD, 4712 HD UK Renal Registry 6 th Annual Report 2003 p 133

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40 90% of population attributable risk of MI explained by 9 risk factors 1. Dyslipidaemia 49% (apob/apoa1 ratio) 2. Smoking 36% (current and former) 3. Hypertension 19% (self-reported) 4. Diabetes 10% (self-reported) Psychosocial factors, abdominal obesity, exercise, fruit and vegetable intake and alcohol explained the remainder The first four had greater effects in younger patients Yusuf et al Lancet 2004; 364:

41 IF THE UTILITY IN COMORBIDITY RECORDING IS TO INTERPRET SURVIVAL THEN Don t forget Patient factors Pre-dialysis vintage Dialysis vintage Severity of what we already measure Unmeasured comorbidity Drug therapy and compliance for these disorders Unit factors Survival to dialysis bias Take on rates Modality choice and changes Workforce issues 41

42 IMPROVING COMORBIDITY DATA RETURNS Shaming and shouting for more data does not work Understanding the relationship with the renal Clinical Information System may help What works in other disciplines? Understanding variation in systems and process Linkage HES data?? GP data NICN, ICNARC, MINAP, NDA Use of surrogates-hba1c and DM, BNP and CCF, LFTs, CEA, 42

43 14,000 PATIENTS/FAMILY/STAFF REGISTERED WITH

44 THE FUTURE FOR THE UKRR Keep doing what we do but do it better Increased sharing with other National Clinical Audits, Hospital Episodes Statistics, other registries More hard outcomes required? Leave laboratory data audit at local level None of this would happen without reliable Renal Unit IT systems and dedicated Renal Unit staff

45 WHAT CAN I DO? GET INVOLVED WITH THE IT Ye must return data to Get involved Know the IT staff Lab, xray, PAS, cardiac, diabetes, dialysis machines and any other links Remove redundancy Use system for efficiency letters drug surveillance risk management. 45

46 MIND THE GAP! - THE DATA GAP Primary Renal Disease Other conditions (comorbidity) Dates they saw staff first Incident/prevalent vascular access Drug treatment Quality of life Patient reported outcomes Use of palliative/conservative care

47 Thank you for all your hard work supplying the data

48 Renal Registry Management Board (Renal Association Trustees) Registry Chairman Dr Damian Fogarty Registry Committee/Study Groups General Manager Hilary Doxford Director Professor Terry Feest Deputy Director Chris Maggs Registry Registrars Dr Clare Castledine Dr Dan Ford Dr Lynsey Webb A big THANKS to all the Registry Staff and collaborators Systems & Data Manager David Bull Clinical Informatics Manager Fiona Braddon Project Manager Sue Shaw Senior Statisticians Julie Gilg Margaretha Steenkamp External Project Contractors Statisticians Anna Casula Dirk van Schalkwyk Senior Clinical Data Manager Paul Dawson Programmers (p/t) Matthew Brealey Andy Langdon External IT Contractors Clinical Data Management Becky Blackwell Lynsey Billet Fran Benoy-Deeney