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Pragmatic use of data for research, audit and revalidation Will Dixon Health Informatics Unit 10 th anniversary Royal College of Physicians, 15 th Sept.

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Presentation on theme: "Pragmatic use of data for research, audit and revalidation Will Dixon Health Informatics Unit 10 th anniversary Royal College of Physicians, 15 th Sept."— Presentation transcript:

1 Pragmatic use of data for research, audit and revalidation Will Dixon Health Informatics Unit 10 th anniversary Royal College of Physicians, 15 th Sept 2011

2 Outline Sources of information – Clinical care, audit & research eHealth observational research – Potential – Barriers Harmonised data collection – Arthritis Research UK’s INBANK project – DANBIO

3 Information sources Audit & Revalidation Research Clinical care

4 Rheumatology new patient Demographics Symptoms onset; site; severity; disability Co-morbidity Family history Social history Medication Examination Clinical care

5 BSR Biologics Register Research Anti-TNF treated RA cohort (n=4000) Infliximab Etanercept Adalimimab Biologic-naïve active RA cohort (n=4000) VS Incidence of serious adverse events

6 BSR Biologics Register Demographics Symptoms onset; site; severity; disability Co-morbidity; adverse events Social history (occupation) Medication Examination (DAS28 score) Research

7 BSR National Audit 2010 Early RA: NICE CG79 Demographics Symptoms onset; severity; disability Medication Access to MDT Audit

8

9 Demographics ✓✓✓ Symptoms ✓✓✓ Co-morbidity ✓✓ Family history ✓ Social history ✓✓ Medication ✓✓✓ Examination findings ✓✓✓ Multidisciplinary team ✓✓ Clinical ResearchAudit

10 Demographics ✓✓✓ Symptoms ✓✓✓ Co-morbidity ✓✓✓ Family history ✓✓✓ Social history ✓✓✓ Medication ✓✓✓ Examination findings ✓✓✓ Multidisciplinary team ✓✓✓ Investigations ✓✓✓ Clinical ResearchAudit

11 Information sources Audit & Revalidation Research Clinical care Structure clinical information systems to generate high-quality data for audit and research

12 Opportunity in UK Universal access to healthcare ‘Cradle to grave’ records Electronic patient records in primary care Other eData e.g. PACS EPR in secondary care coming… Huge potential for eHealth observational research

13 Observational research What data is needed? Shallow & wide ‘Whole health experience’ e.g. GPRD HES Deep and narrow Disease-specific e.g. Secondary care records National registers Research databases “T-shaped data”

14 Observational research Steroid safety in patients with RA Exposure Steroid therapy Outcome Serious infection Confounder Disease severity

15 Observational research Steroid safety in patients with RA Shallow & wide GPRD HES Deep and narrow National registers Research databases Secondary care records Steroid therapy Prescriptions ? Serious infection GP visits / HES data Disease activity Problem - GP prescriptions - Hospital administration

16 Research & audit using eHealth data Obstacles Secondary care records often paper-based EPRs not structured to collect information for research Solutions Include research and audit requirements in EPR architecture Need to harmonise research data

17 Pharmacogenetics of methotrexate therapy Prospective study of RA-associated interstitial lung disease Synovial predictors of EIA outcome n=100n=400 n=500 Disease characteristics Disease severity Drug therapy n=1000 Question Predictors of drug response Studies in rheumatoid arthritis For all future studies in RA Define minimum core dataset Collect in harmonised way

18 Harmonised data Audit & Revalidation Research Clinical care Min. Cor e Rheumatoid arthritis Min. Cor e VasculitisMSk pain Min. Cor e Osteoarthritis SLE Common minimum core

19 INBANK A national research infrastructure to facilitate musculoskeletal research, including i)a searchable catalogue of extant studies and ii)a prospective research database of clinician- and patient-reported outcomes with linked biological samples

20 Centralised informatics platform Centralised biobanking Disease hubs RA

21 Centralised informatics platform Data collectionData linkageData provision INBANK Extant Inventory of extant collections Meta-data about studies - Clinical - Samples INBANK Prospective Web-based data collection Minimum core dataset + ‘bolt-on’ sub-studies Tracking biological samples Link to national datasets GPRD National joint register etc. Datasets to researchers Clinical reports Patient identification for trials Tracking of study progress National audit Vasculitis Sys sclerosis Others… Disease hubs Centralised biobanking RA ADRs to MHRA

22 Research data collection in NHS practice Opportunities ‘Real-world’ data across UK Single data entry for clinical, research and audit purposes – National audit using INBANK platform – Automation of O/P letters Augments clinical record – Patient-reported outcomes – Longitudinal record

23 DANBIO Courtesy of Merete Hetland

24 DANBIO Courtesy of Merete Hetland

25 Data collection in NHS practice Opportunities Threats Time – not greater than current paper Existing databases Administrative burden – NHS IT; R&D departments Integration with NHS systems ‘Real-world’ data across UK Single data entry for clinical, research and audit purposes – National audit using INBANK platform – Automation of O/P letters Augments clinical record – Patient-reported outcomes – Longitudinal record

26 INBANK A national research infrastructure to facilitate musculoskeletal research, including i)a searchable catalogue of extant studies and ii)a prospective research database of clinician- and patient-reported outcomes with linked biological samples

27 Patient-reported outcomes Data from the source Informs consultation Collect outcomes important to patients – Quality of care Reduces burden of clinician data entry Two-way communication – Data collection – Dissemination of knowledge

28 DANBIO Courtesy of Merete Hetland

29 INBANK Long-term vision Engagement of the clinical and research communities – Proof of clinical, research and audit benefits from single data entry – High-quality data becomes standard of care Influence disease-specific EPRs in secondary care Structure clinical information systems to generate high-quality data for audit and research

30 Outline Sources of information – Clinical care, audit & research – Overlap eHealth observational research – Potential – Barriers Harmonised data collection – Arthritis Research UK’s INBANK project


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