Cookie policy notice

By continuing to use this site you agree to our cookies policy below:
Since 26 May 2011, the law now states that cookies on websites can ony be used with your specific consent. Cookies allow us to ensure that you enjoy the best browsing experience.

This site is intended for health professionals only

At the heart of general practice since 1960

Focus on… Playing the long game on referrals

Professor Martin Roland explains why CCGs need to avoid looking for quick wins on referral numbers

http://www.pulsetoday.co.uk/practical-commissioningl

CCGs aren't responsible for managing their local practices – not yet anyway. However, it's pretty clear that you can't manage a budget if you don't have any control over the people who spend the money. And in the case of secondary care, it's GPs who spend money by referring or admitting patients to hospital.

Anyone who thought CCGs weren't going to be trying to manage GPs' clinical decisions was probably being naïve. This month's ‘Focus on…' includes the ‘referral management' experience of two CCGs.

Referral management has a bad name.

It smacks of a managerial organisation wanting to restrict GPs' freedom to refer without any reference to clinical need.

Referral management has a reputation of feeding a commissioner's desire to create a ‘quick win' in stopping the referral tide, rather than playing the longer game where the quality of referrals truly improves.

Some of the early schemes justifiably earned a bad name, but the two schemes described in this month's issue are different. First, they are run by GPs. In Manchester (page 26), it's a central group of GPs who look at all referrals, but in Corby (page 32), GPs review referrals within the practice before they are sent out.

My practice in Cambridge operates a similar scheme – each morning, two partners review referral letters from the day before and in some cases suggest alternatives. Then they'll discuss it with the doctor. The scheme works in my practice, and the authors of the descriptions of Corby and Manchester sound enthusiastic. The key is that these schemes are clinically led and designed to find the best way of managing patients within available resources.

Ah yes, that last bit – ‘within available resources'. We aren't going to be allowed to forget that we're now in charge of finite budgets, so let's not pretend this isn't rationing. Sure, there is wide variation in patterns of referral and there are probably patients from high referrers who needn't see a specialist. But there are also probably patients from low referrers who would benefit from being referred, but aren't. Referral management is about trying to make the best use of the resources we've got.

One of the real dangers is relying on statistics without looking at patients. Many practices get quarterly feedback on referral numbers from their PCT, and much of the supposed quarter-to-quarter ‘variation' we are shown is just due to chance. This is because the numbers are often just too small. The table below shows the range in numbers of referrals within which variation is just as likely to be due to chance as to differences in doctors' behaviour. For example, where there are an average of five referrals to a specialty from an average practice in a given period – say a month or a quarter – then half of the time variation within the range of three to six will simply be due to chance. So don't look at single specialties over short periods of time and, if necessary, combine time periods to construct a rolling average.

The over-riding message is simple: if you want to ‘manage' referrals, don't get obsessed with numbers – think about the needs of individual patients and keep it clinically led.

Professor Martin Roland is professor of health services research at the University of Cambridge and a GP in the city. He was a main architect of the new 2004 GMS contract and a member of the expert panel that decided the first QOF indicators

 

Variation due to chance

Expected number of events (such as referrals for a certain size of practice)

Expected range (variation within this range is as likely as not to be due to chance)

5

10

25

50

100

200

500

1,000

3-6

8-12

22-28

45-54

93-106

190-209

485-515

979-1,021

Rate this article 

Click to rate

  • 1 star out of 5
  • 2 stars out of 5
  • 3 stars out of 5
  • 4 stars out of 5
  • 5 stars out of 5

0 out of 5 stars

Have your say