Improving mid stream urine sampling: reducing labelling error and laboratory rejection

A urine sample is vital in older patients with pyrexia or acute confusion, and commonly directs clinicians towards a source of infection. Not only can the organism be identified, but sensitivities to antibiotics can also guide prescribing. A high number of urine samples were not being processed on the medicine for older people wards at St. James's Hospital due to incomplete hand-written request forms not complying with trust policy. Previous attempts to re-educate staff had failed to improve acceptance rates. Rejected samples delay diagnosis, identification of organisms and subsequent sensitivities, as well as increasing staff workload. A total of 72 urine samples were audited from our wards in March 2013; 12 (17%) rejected. Clinicians were notified of rejected samples within one to four days. An electronic-requesting system was implemented in April 2013. Once implemented, a further two data collection cycles of 72 urine samples were completed from the same wards. In December 2013, 55 (76%) were electronically requested and 17 (24%) hand-written. Four (5%) samples were rejected and were all hand-written. In August 2014, 61 (85%) were electronically requested and 11 (15%) hand-written. No samples were rejected. The electronic-requesting system has effectively reduced the number of rejected urine samples. No electronically requested samples were rejected, therefore 100% sample acceptance is achievable. It is more effective than re-educating staff alone and ensures requests meet trust policy. Clinicians were notified of a samples rejection after one to four days. By this time patients may have started antibiotic therapy, decreasing the likelihood of isolating the causative organism in subsequent samples. All urine samples requested must meet a high standard and comply with trust policy in order to be processed. An electronic-requesting system removes errors of omission and ensures policy compliance, ultimately leading to improved patient care. Now our processes are reliable we will go onto measure changes at patient level, e.g. confirmed diagnoses of urine infection, outcomes of earlier narrow spectrum antibiotics, and length of stay.