improving data recording in primary care data michelle page & hassy dattani thin
Post on 21-Dec-2015
216 views
TRANSCRIPT
Improving Data Recording in Primary Care Data
Michelle Page & Hassy Dattani
THIN
THIN
• The Health Improvement Network
• Joint venture with Cegedim (InPS)
• Create a new primary care data source
• Improve quality of data recording
• Feedback service to GPs
• Help GPs to recognise value of Vision
Benefits to GPs of Joining THIN
• Free general training sessions on aspects of Vision supported by THIN
• Payment– Cash– Equivalent amount in training vouchers
• Free verification of back up tape• Contribution to valuable public health
research
THIN Data
• Population based data - 5% UK population
• Practices geographically representative of England and Wales
• Anonymised at source• Simple flat file structure• Regularly updated• Collection scheme approved by MREC
Patient Records
Patient identifier
Year of birth (month also included for children)
identifier shared by patients living at same address
Sex of patient
Patients registration date with the practice
Date of transfer out of practice
(if applicable)
Medical Records
Patient identifier
Event date
Read medical code
Variable indicating origin of record
Episode type
Secondary care speciality
Therapy Records
Patient identifier
Prescription date
Multilex drug code
DOSAGE instruction string
Quantity prescribed
Daily dosage evaluation
Additional Health Data Records
• Immunisations
• Blood pressure
• Test results
• Smoking
• Height and weight
Background & Importance
• New GP Contract– greater emphasis on quality of clinical care– can be demonstrated through data recording– practices provide high quality care but not
reflected in data recording – data quality linked to financial benefits to
practice
• NSF compliance
Study Objective• To investigate the feasibility of
independently assessing and reporting on specific criteria in GP data in order to improve quality (completeness) of recording of clinical information – comparing data from THIN GPs with national
statistics and other THIN contributors– specifically for demography, death and
diabetes
Method
• Demography (128 practices)
– Age gender profile of all active patients by
practice for 2001 only
• Death (128 practices)
– All patients registered with a practice for a
calendar year (1985 to 2001) including death
within year
• transferred out of practice due to death
• + a medical record entry of death
Method
• Diabetes (154 practices)– Study period: 15 months prior to last collection date
– Base population: registered for entire study period or
died during
– Diabetic population: at least two records indicating
diabetes at any time
• those with treatment but no medical record entry
– Evidence of quality indicators taken from GP contract
and NSF measured during study period
Indicators Measured for Diabetes
• Smoking record (and smoking advice)
• Urine dipstick test (glucose, protein etc.)
• HbA1C
• BMI, blood pressure
• Cholesterol
• Serum creatinine, fructosamine
• Eye test, foot check
Results - DemographyThe Population of the United Kingdom (2001) Compared to the Population
of THIN
5.93
12.9612.26
14.22
12.02
9.13
6.60
2.55
14.93
13.23
10.58
8.40
1.91
5.58
4.06
12.2611.56
12.97
15.37
13.47
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
16.00
18.00
0-4 5-14 15-24 25-34 35-44 45-54 55-64 65-74 75-84 85+
Age Groups Years
Po
pu
lati
on
in
%
Population of UK Population of THIN
Results – Death Recording
Percentage of Registered Deaths with a Recorded entry of "Death"
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
Time
All THIN practices Practices who have contributed to GPRD
Practices who have never contributed to GPRD
Results - Diabetes
Registered Diabetics as a percentage of the base population
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
Total GPRD non GPRD
Min
Max
Average
Results - Diabetes
Percentage of registered diabetics with a BP record in the past 15 months
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
120.0%
Total GPRD non GPRD
Min
Max
Average
Results - Diabetes
Percentage of registered diabetics with a smoking record in the past 15 months
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
Total GPRD non GPRD
Min
Max
Average
Conclusion
• GP Data can be independently assessed to measure completeness of data recording
• Demographic profile of THIN practices is consistent with UK population
• Data recording in non-GPRD practices within THIN is of a similar quality to that in GPRD practices in some cases
Conclusion
• THIN practices will benefit from training
provided by THIN
• THIN analysis can be used by GPs to
identify patients requiring follow up in
order to meet standards within GP
contract and NSF
Further Research
• Compare recording in THIN practices with a control group to assess validity of THIN feedback to GPs
• Ongoing analysis of data collected from THIN practices –– Asthma– Coronary heart disease
