1. The accuracy of clinical coding in a large DGH in East London
D. HOLLAND, W. ENGLISH, S. ANDREANI
Introduction:
Clinic coding is required for hospital trusts to effectively charge for the stay of inpatients and the treatment they receive. It is an important handover to GPs and community services. In principle clinical codes are generated from discharge summaries written by junior doctors but also from other databases and notes. The accuracy of these codes affects a hospital's income.
Methods:
A retrospective study examining three months of patient data from surgical patients at Whipps Cross Hospital. This included data from imaging systems, notes, discharge summaries and the final clinical codes. This study only examined patients under the care of one consultant surgeon.
Conclusions:
Discharge summaries are poorly completed.
There are more errors on days when surgeons are operating and there are more errors relating to patients who have long stays in hospital.
Key areas not coded included co-morbidities, procedures and common symptoms.
This leads to a large volume of lost income and also represents a poor handover to those in primary care.
If junior staff completed TTAs more fully then there would be an increase in hospital income and better continuity of care for patients returning to primary care.
Aims:
To determine the accuracy of clinical coding in Whipps Cross Hospital's surgical teams and determine if it could be improved.
Innovations:
We improved training for junior staff by presenting this data at a surgical teaching session and suggesting ‘tips’ on coding. We improved the teaching handout given to junior doctors at the beginning of the year and increased communication between doctors and clinical coders.
Fig. 2: Bar chart showing the number of omitted codes per TTA by day of the week. Friday was a designated ‘theatre day’.
Results:
On average 4.3 items with clinical codes were missed from discharge summaries. This included procedures, diagnoses and co-morbidities. This was worse on designated theatre operating days - Friday. On average there were 2.9 differences between all the data available to clinical coders and the codes generated.
There were more errors relating to patients who had longer stays in hospital with 4.88 errors on average in patients with stays >5 days while in patients with a stay of <3 days there were 2.4 errors.
Fig. 1: Bar chart showing the average number of errors coded by the length of stay
Fig. 3: An example of an information leaflet handed out to new doctors.