OBJECTIVE: To determine whether Clinical Terms Version 3 provides greater accuracy and consistency in coding electronic patient records than the Read Codes 5 byte set. DESIGN: Randomised crossover trial. Clinicians coded patient records using both schemes after being randomised in pairs to use one scheme before the other. SETTING: 10 general practices in urban, suburban, and rural environments in Norfolk. PARTICIPANTS: 10 general practitioners. SOURCE OF DATA: Concepts were collected from records of 100 patient encounters. MAIN OUTCOME MEASURES: Percentage of coded choices ranked as being exact representations of the original terms; percentage of cases where coding choice of paired general practitioners was identical; length of time taken to find a code. RESULTS: A total of 995 unique concepts were collected. Exact matches were more common with Clinical Terms (70% (95% confidence interval 67% to 73%)) than with Read Codes (50% (47% to 53%)) (P < 0.001), and this difference was significant for each of the 10 participants individually. The pooled proportion with exact and identical matches by paired participants was greater for Clinical Terms (0.58 (0.55 to 0.61)) than Read Codes (0.36 (0.33 to 0.39)) (P < 0.001). The time taken to code with Clinical Terms (30 seconds per term) was not significantly longer than that for Read Codes. CONCLUSIONS: Clinical Terms Version 3 performed significantly better than Read Codes 5 byte set in capturing the meaning of concepts. These findings suggest that improved coding accuracy in primary care electronic patient records can be achieved with the use of such a clinical terminology.
RCT Entities:
OBJECTIVE: To determine whether Clinical Terms Version 3 provides greater accuracy and consistency in coding electronic patient records than the Read Codes 5 byte set. DESIGN: Randomised crossover trial. Clinicians coded patient records using both schemes after being randomised in pairs to use one scheme before the other. SETTING: 10 general practices in urban, suburban, and rural environments in Norfolk. PARTICIPANTS: 10 general practitioners. SOURCE OF DATA: Concepts were collected from records of 100 patient encounters. MAIN OUTCOME MEASURES: Percentage of coded choices ranked as being exact representations of the original terms; percentage of cases where coding choice of paired general practitioners was identical; length of time taken to find a code. RESULTS: A total of 995 unique concepts were collected. Exact matches were more common with Clinical Terms (70% (95% confidence interval 67% to 73%)) than with Read Codes (50% (47% to 53%)) (P < 0.001), and this difference was significant for each of the 10 participants individually. The pooled proportion with exact and identical matches by paired participants was greater for Clinical Terms (0.58 (0.55 to 0.61)) than Read Codes (0.36 (0.33 to 0.39)) (P < 0.001). The time taken to code with Clinical Terms (30 seconds per term) was not significantly longer than that for Read Codes. CONCLUSIONS: Clinical Terms Version 3 performed significantly better than Read Codes 5 byte set in capturing the meaning of concepts. These findings suggest that improved coding accuracy in primary care electronic patient records can be achieved with the use of such a clinical terminology.
Authors: Peter Sharplin; Jason Gordon; John R Peters; Anthony P Tetlow; Andrea J Longman; Philip McEwan Journal: Cardiovasc Diabetol Date: 2009-02-16 Impact factor: 9.951
Authors: Peter Sharplin; Jason Gordon; John R Peters; Anthony P Tetlow; Andrea J Longman; Philip McEwan Journal: Cardiovasc Diabetol Date: 2009-01-19 Impact factor: 9.951