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Linking Data Quality and Clinical Audit to Support Diabetic Care

Linking Data Quality and Clinical Audit to Support Diabetic Care. Bev Ellis Senior Lecturer in Health Informatics University of Central Lancashire. SETTING THE SCENE SHARING ACROSS HEALTH COMMUNITIES. Health Community C. Health Community B. Health Community A. 6. Specific Functions.

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Linking Data Quality and Clinical Audit to Support Diabetic Care

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  1. Linking Data Quality and Clinical Audit to Support Diabetic Care Bev Ellis Senior Lecturer in Health Informatics University of Central Lancashire

  2. SETTING THE SCENE SHARING ACROSS HEALTH COMMUNITIES Health Community C ... Health Community B Health Community A 6. Specific Functions 5. User Environment 7. NSFs Information Diabetes Social Care Acute Care Mental Health Pathology Primary / Community Capture Mental Health Information Reporting 4. Generic Functions Older People Clinical Governance Analysis Knowledge Management Cancer Digital Imaging Prescribing User Tools CHD Ordering and Reporting Booking and Scheduling Information Etc. Diagnosis and Care Governance Service User Index e-learning Finance e- commerce Analytical NHS Direct Population e-Staff ETP . Finance Record Services CAS Record 3. Application Services Access Reference Nhs.uk NeLH Network Security E-mail Directory Files Control 1. Infrastructure Services 2. Information Services Local Services Standards National Services With acknowledgment to Jeremy Thorp, NHSIA

  3. Working in Partnership • Facilitation can help a practice establish how it can achieve its own goals • Turning ideas into ACTION • Effective meetings • Consensus • Training, guidance, experience and reflection

  4. The Audit Process Audit definition Data capture during care process/admin process Audits generated Results monitoring Practice Team Meetings Output from audit is validated Aggregated then made available for analysis Results fed back to practices

  5. Diabetic Registers With acknowledgement to Dr Mike Robinson IPS

  6. Identify Priorities

  7. [D21] HbA1c <=7.5 in last year: Percentage within subset [D3] Diabetes mellitus diagnosis code ever recorded

  8. Practices P4 and P7 have some BMI data to add. Currently on paper - or not recorded? Practices P4 and P7 have some BMI data to add. Currently on paper - or not recorded?

  9. Communicate … • Practice comparison tailor approach to each practice • Practice prevalence show changes for practice over time • Group prevalence aggregate group performance over time

  10. Reasons for data inconsistencies • The data is not being recorded but the care is given • The care has not been given • Read codes differ from MIQUEST query

  11. Diagnostic term “Diabetes mellitus” correctly identified

  12. Summary Measurable change is a reality, not an ideal, given assistance Improved patient care

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