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CHDGP

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Data analysed and fed back to 84 practices, 650,000 patients ... Analysis and interpretation of clinical data. Collection of Health Data from General Practice ... – PowerPoint PPT presentation

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Title: CHDGP


1
CHDGP
  • Collection of Health Data
  • from General Practice Project
  • Professor Mike Pringle
  • CHDGP Team Leader
  • Division of General Practice, University of
    Nottingham

2
Outline of session
  • Outputs to date
  • Lessons so far
  • Improving data quality

3
CHDGP output to date
  • MIQUEST query software / interpreter software
  • Guidelines
  • Overview booklet
  • Co-ordinators Handbook
  • Websites http//www.nottingham.ac.uk/chdgp ht
    tp//www.clinical-info.co.uk/
  • and ...
  • Data analysed and fed back to 84 practices,
    650,000 patients
  • Data from 2nd extraction analysed and fed back
    to 136 practices

4
Some examples of analyses
  • Comparative prevalence data
  • Data quality issues
  • Quality of care issues

5
Comparative prevalence data
6
Data quality
7
Quality of care
8
What skills are needed?
  • Facilitators
  • Communication and teaching skills
  • Technical skills
  • Knowledge of GP clinical systems
  • Read Code
  • MIQUEST
  • Data quality issues
  • Analysis and interpretation of clinical data

9
What skills are needed?
  • Practices
  • Commitment to learning and change
  • Knowledge of own GP clinical system
  • Impact of data quality on clinical care
  • Read Code
  • MIQUEST interpreter
  • Analysis and interpretation of clinical data

10
What skills are needed?
  • PCGs
  • Commitment to support the process
  • Knowledge of GP clinical systems
  • Understanding of data quality
  • Limits and constraints on interpretation of
    clinical data

11
Improving data quality
  • What is high-quality data?
  • Accurate
  • Complete
  • Relevant
  • Timely
  • Accessible

12
Improving data quality
  • Why does it matter?
  • Good patient care
  • Medicolegal record
  • Decision support
  • Communication of clinical data
  • Other uses of clinical data

13
Improving data quality
  • How can it be improved?
  • Education (concepts, coding)
  • Feedback
  • Analyse information needs
  • Model information flows
  • Implement electronic guidelines
  • Communicate, communicate, communicate!

14
Key messages
  • Data quality and information flows need
    attention
  • Skilled facilitators required
  • Good clinical systems needed
  • Training takes time to show effects
  • Good data is being used already
  • Poor data is being used constructively
  • Increasing motivation to learn

15
CHDGP
  • Collection of Health Data
  • from General Practice Project
  • CONCLUSIONS
  • Professor Mike Pringle
  • CHDGP Team Leader
  • Division of General Practice, University of
    Nottingham
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