Coding productivity in Sydney public hospitals.
The aims of this study were to compare Sydney public hospitals regarding medical record coding times to compare observed coding times with coding times necessary to avoid backlog and to evaluate the impact on coding time of casemix complexity, coder age, experience, job satisfaction, employment status, and salary. Coding time (in minutes) for each medical record over a two-week period was documented by 61 coders employed in 13 hospitals: six principal referral (PR), six major metropolitan (MM), and one paediatric specialist (PS) hospitals. The mean coding time for each coder was estimated by averaging across coding times for all records during the two-week period. In order to compare hospital mean coding times, the hospitals were grouped into PR and MM/PS groups. The mean coding time necessary to avoid coding backlog (expected coding time) for each hospital group was based on the total number of annual separations and filled full-time equivalent coding positions. The observed mean coding time was longer in the PR group than in the MM/PS group (p = 0.019); however, the observed coding time was within the expected coding time limit in both the PR and MM/PS groups. Casemix complexity tended to influence coding time, but neither age, experience, job satisfaction, employment status nor salary had any impact. In conclusion, the expected coding times, if reliable, indicate that coders in the two hospital groups were keeping coding up-to-date. Thus, the variation between hospital groups in coding time is of little importance, given that the main objective in coding productivity is to maintain the coding workload.
Dimitropoulos
Vera
V
School of Health Information Management, Faculty of Health Sciences, The University of Sydney, Lidcombe NSW. V.Dimitropoulos@cchs.usyd.edu.au
Bennett
Adam
A
McIntosh
Jean
J
D001315:Australia; D059019:Clinical Coding / Q000706:statistics & numerical data*; D003953:Diagnosis-Related Groups; D017598:Efficiency, Organizational / Q000706:statistics & numerical data*; D006779:Hospitals, Public; D006801:Humans; D038801:International Classification of Diseases; D008499:Medical Records; D010564:Personnel, Hospital; D011795:Surveys and Questionnaires; D013997:Time Factors; D000078329:Workforce; D016526:Workload