Facilitator Handbook 2005 - PRIMIS

Data Analysis, Interpretation and Feedback
PRIMIS Facilitator Handbook
Data Analysis, Interpretation and Feedback
Background
The use of MIQUEST in the PRIMIS process is twofold. Firstly, it provides a mechanism for the
easy extraction of data recorded on a practice’s clinical system, enabling the practice to
examine and improve data recording techniques. This method can be supplemented by using
various analysis software tools such as CHART, the use of which is covered in a later module.
Secondly, it enables practices to compare their data recording to that of other practices or
against their own recording over time. In order to enable the effective use of MIQUEST,
PRIMIS has developed several query sets. Each set has a different focus and is designed to
meet a variety of needs.
A key query set, and the one used most
frequently, is the PRIMIS Data Quality set.
This set has been designed to enable
facilitators and participating practices to
begin to identify areas where the data
recorded on the clinical system is not of
good quality: that is, it does not have the
five characteristics of good quality listed in
the box to the right.
Five characteristics of good quality data
• Completeness • Accessibility
• Accuracy • Timeliness
• Relevance
The PRIMIS Data Quality query set is one of the most valuable sets in supporting information
facilitators in their role. Facilitators run this set with all new practices joining the scheme, and
repeat the run at regular intervals. Once a practice has identified the strengths and
weaknesses of their data capture methods, they are then in a position to make improvements.
The queries are intended to provide a basis for discussion and debate from which an action
plan can be derived. By repeating data extractions at regular intervals, the practice will be able
to demonstrate improvements over time and see the effectiveness of actions taken.
The Training
The training takes place over a half or full day and is run on an individual scheme basis. Data
extracted from practices and submitted to PRIMIS by a scheme are analysed and reported
back to the facilitator in an Excel format known as Rush. This format enables the facilitator to
view the data in a variety of ways. Throughout the training, the facilitator is taken through their
own practices’ data and shown how to use the analyses listed in the box below to identify
where there are potential data quality issues.
Analyses used in the PRIMIS Data Quality
query set to highlight potential quality issues
• Baseline prevalence • Risk factor recording
• Apparent prevalence • Screening data recording
• Comparison with proxy indicators • Data validity checks
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