The Oxfordshire MAAG CHDGP Project

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The Oxfordshire MAAG CHDGP Project

• Presentation for the
• National Conference
• November 1998

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Oxfordshire CHDGP Project

• Where did we start from?
• Recruiting Practices
• Profile of Participants
• Project Milestones
• Key Messages

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Where did we start from? 1

• MAAG computer-based audits
• Audit criteria linked to Read Codes
• Suggested EMIS templates
• Diabetes
• Asthma
• Ischaemic Heart Disease

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Where did we start from? 2

• MAAG training courses for Practices on using
  computers for audit began in 1994
• Data management and quality
• Consistency and coding
• Searches and audits
• Analysis and presentation

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Where did we start from? 3

• MAAG Computer courses
• EMIS
• VAMP
• Meditel
• Read Codes
• Microsoft Excel

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Where did we start from? 4

• 60 of 89 Practices involved in MAAG computer
  training courses since 1994
• Free training - provided they participate in
  MAAG audits
• Established relationship between MAAG and
  Practices - trust and confidentiality

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Who is in the team?

• MAAG Audit Facilitator
• Project Data Analyst (20 hours)
• HA Data Analyst (half day)
• support from rest of MAAG team

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Recruiting Practices 1

• invitation letter sent to all 43 EMIS 9 Meditel
  Practices - July 1997
• 18 expressed interest by end of October
• all had previously participated in MAAG computer
  audit training
• all were visited for discussion and assessment

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Recruiting Practices 2

• 12 joined for the initial data collection
• 3 more joined for the 2nd collection
• Chosen for
• willingness to participate fully
• committment to make changes to improve data
  quality

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Profile of Practices 1

• Computer in use for
• 2 or 3 years 2 practices
• 5 to 7 years 9 practices
• 8 to 15 years 4 practices
• Level of computer use
• from Paperless toRegister and Repeat
  Prescribing only

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Profile of Practices 2

• 1 single-handed
• 4 with 2 to 4 partners
• 10 with 5 or 6 partners

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Profile of Practices 3

• 1 rural
• 2 small town
• 6 market town
• 4 suburban housing estate
• 2 city

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Profile of Practices 4

• 15 out of 89 Practices in county
• 18 of county population -c. 114,000 registered
  patients
• good mixture of size, area, experience and
  different Practice cultures

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Project Milestones 1

• First round of data collection -
• Completed in all 12 Practices
• Queries run in January - March 1998
• Diabetes queries re-run in 5 Practices
• Whole query set re-run in 1 Practice in May
• Local feedback report produced in June 1998

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Project Milestones 2

• Some examples of problems with first round
• first query in one Practice used wrong Read Code
  set - no Diabetics and other odd results!
• queries sometimes took over 24 hours to run
• one query in a Practice not finished after 3
  days- had to be aborted

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Project Milestones 3

• Second round of data collection -
• Completed in all 15 Practices
• Queries run during 2 weeks June/July 1998
• Local feedback report produced in September
• Feedback seminar for all Practices in October
• Rush software demonstrated by Notts team

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Project Milestones 4

• Some examples of problems with second round
• 5 of 6 EMIS 4 byte Read code sites failed to load
  the mental illness queries
• All 6 EMIS 5 byte Read code sites generated
  invalid responses to one query (incorrect date in
  query)
• A benign virus found at one Practice
• A few queries did not run properly - ? why

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Data quality issuesa couple of examples

• 7 out of 38 diabetic patients in one practice
  appeared to have had no follow up since
  diagnosis!
• Another Practice seemed to have a high prevalence
  of Ischaemic Heart Disease

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Too much I H D ?
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Hypertension Management
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Key Messages 1

• Beware comparison of data until quality has been
  verified at source
• Beware averages, means and calculated data
• Consistency of coding needs -education,
  education, education
• (and dont make up your own codes)

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Key Messages 2

• Only the obvious discrepancies are easy to spot -
  how many do we miss?
• How long does it take for meaningful, clinically
  relevant changes in data quality to be achieved
  in general practice?
• (how long should the data collection and
  feedback cycle be?)