Frequently asked questions

Where can I find the results?

View the latest result for a GP practice by entering practice name or postcode here.

The results of previous GP Patient Surveys can be found here.

How do you calculate what a practice does best and what a practice could improve?

These are calculated by comparing a practice’s results to the average results for the practice’s Clinical Commissioning Group (CCG).

What this practice does best: These are the three results for this practice that are the highest compared to the CCG average. These results may be above the CCG average, or if none of the results for a practice are above CCG average, then the results that are closest to the CCG average have been chosen.

What this practice could improve: These are the three results for this practice that are the lowest compared to the CCG average. These results may be below the CCG average, or if none of the results for a practice are below CCG average, then the results that are closest to the CCG average have been chosen.

What is a Clinical Commissioning Group (CCG)?

Clinical Commissioning Groups (CCGs) are NHS organisations set up to organise the local delivery of NHS services in England. They are GP-led organisations which have a duty to support NHS England in improving the quality of primary medical care and have taken on many of the functions of PCTs and in addition some functions previously undertaken by the Department of Health. Every GP practice must belong to a CCG, and there are currently 209 CCGs across England, all of which are overseen by NHS England. You can find your local CCG by going to: www.nhs.uk/Service-Search/Clinical-Commissioning-Group/LocationSearch/1

You can also find more information about CCGs: http://www.nhs.uk/NHSEngland/thenhs/about/Pages/nhsstructure.aspx

Some of the results filters are missing or greyed out, why is that?

Filters can only be selected when there is enough data to display results for that filter.

This may be because there are simply no survey responses from a particular group of patients at a practice. Or it may be because data has been suppressed.

If a filter is greyed out, it means that data for this filter is limited due to another filter you have added. Try removing any previous filter or filters.

Why is data sometimes suppressed?

In cases where fewer than 10 people have answered the question, the data has been suppressed. This is to prevent individuals and their responses being identifiable in the data.

In the weighted reports, there are some cases where this suppression is also applied to questions where the total number of responses is 10. This is again due to rounding. If the total number of responses when weighted is less than 10 (e.g. 9.856), but has been rounded to 10 in the report, then the data will be suppressed. If the weighted total number of responses is, for example, 10.245, then the total number of responses will also show as 10 but the responses will be shown.

The result shows that 0 people answered 'not very easy', but the percentage for this answer is showing as more than 0%. Why is this?

This is because in the unweighted data there may be a single person who has given a response. However, when weighted, this response has been given a value of greater than zero but less than 0.5 and, therefore, rounded to 0. Because the actual value is still greater than zero, in percentage terms this shows as a %.

There is a message saying that data for my practice is unavailable. Why is this?

Unfortunately, for a few practices data is limited or unavailable due to a small number of returned surveys.

I've seen cases where, when adding up the number of people who have selected each different response for a question, the total does not match the figure in the 'total number of responses' column. Why is this?

This can happen when weighted data is rounded to a whole number.

When weights are applied, decimals are added to the number of responses in each category and the total number of responses. This means that, occasionally, there can be cases where the number of responses differs from the base size. For example, if a report says that 59 people say ‘yes’ and 14 say ‘no’, but the number of responses is 74 (not 73), that means that the weighted values could actually be 59.345 and 14.456, which add up to 73.801 (which is then rounded up to 74).

I have seen cases where the same numbers of responses are given to two different answer categories, but the percentage values are different. Why?

There are examples in the reports where, for example, it looks like one person has selected 'Other' and one person selected 'I would prefer not to say', but their corresponding percentages are 1% and 2%. Again, this happens when the results and number of responses are rounded but the percentages are calculated on un-rounded data.

The CCG reports refer to ‘Local NHS England’ – what is this?

NHS England has made changes to its internal structure as part of its Organisational Change Programme 2014/15. These changes came into effect in April 2015. As part of this process NHS England’s Area Teams were integrated into the four existing regional divisions: London, Midlands and East, North and South. More detail on the changes and the role of the regional divisions is available here.

What are confidence intervals?

You may notice references to confidence intervals (lower and upper limits) for selected questions within the practice and CCG reports. These are reported to give users an indication of the accuracy of the findings for individual questions.

Because we hear from a sample of people at each practice, rather than all registered patients, we cannot be certain that the results to a question are exactly the same as if everyone had taken part. The confidence interval is a statistical measure that shows the range of values within which the true value is estimated to lie (i.e. what we would have found if everyone had been given and completed the survey).

In this survey, as in most other surveys, we use a “95% confidence interval” – this means that we are 95% sure that the true value lies within the upper and lower limits of the confidence interval. Another way of looking at this is that, if we were to re-run the survey over and over again, we believe we would get a result that falls within the confidence interval 95 times out of 100 (or 19 times out of 20).

For more information on statistical reliability and confidence intervals, please see the latest Technical Annex.