How improving referral quality enables better demand management
The NHS faces a myriad of issues today. Referral rates are increasing, hospitals are at capacity, and patient waiting times have been pushed to the extremity (to name but a few). At the heart of this is the need to better manage demand.
In a King’s Fund report published in 2012, Candace Imison identified four areas where we can influence demand. These areas included elective care, non-elective inpatients, ambulance callouts, and A&E. In elective care, it is estimated that around 40% of all referrals are avoidable.
Several years on from the report, the opportunities to better manage demand remain, though the need to execute on them has grown. National data indicates that between May 2015 and May 2016, GP referrals increased by 8.5% and first outpatient attendances grew by 8.6%. It is this growth that is driving even more pragmatic thinking from CCGs and Trusts.
One of the best methods for managing demand, as identified by Trusts and CCGs alike, is improving referral quality. Evidence suggests that there are two dominant ways of achieving this; peer review and the use of a referral management centre. Though the overriding approach varies, the aim of both is the same. To ensure that the right patient, is seen in the right place, first time. Fundamentally, this should be considered as the basis for managing elective demand.
By improving referral quality, we can begin to address some of key issues facing elective care today. Intrinsically, by eliminating inappropriate referrals and ensuring use of the most value effective pathway, we alleviate demand on hospitals, reduce waiting times and ultimately improve patient experience. In addition, through the use of a referral management service, we can extract valuable, real-time data which can be used to analyse trends and forecast future demand.
As alluded to here, it is not just demand for elective care that requires rethinking, and already we have seen valuable work take place elsewhere in the NHS. Risk stratification for instance, has proved a useful tool for limiting non-planned admissions for patients identified as being at most risk of requiring emergency care.