Data Accuracy of the Bubble Sheet Ambulatory Data System and the KG-Ambulatory Data System in the Internal Medicine Clinic, Bayne-Jones Army Community Hospital, Fort Polk, Louisiana

Abstract

Abstract : The purpose of this project was to determine the coding accuracy of the Evaluation and Management (E&M), diagnosis, and procedure codes as reported in the Ambulatory Data System (ADS) for the Internal Medicine Clinic at Bayne-Jones Army Community Hospital, Fort Polk, Louisiana. A secondary purpose was to determine the financial impact of inaccurate coding through the use of the Ambulatory Payment Classification (APC) and Ambulatory Patient Group (APG) outpatient prospective payment system (OPPS). Three data sets were examined at different points in time based on type of ADS used and implementation of data quality management efforts. The data quality management efforts included training, template development, customization of diagnosis and procedure code selection lists, and management controls. The management controls consisted of the ADS compliance metric, KG-ADS reports, and ad hoc ADS reports. Analysis of the data revealed that the use of data quality management efforts did increase the accuracy of data in the ADS database. Analysis of the financial data indicated that the hospital was minimally at risk for either fraudulent billing or loss of revenue. However, as the Internal Medicine Clinic only accounts for 6.3% of outpatient workload, coding behaviors similar to those observed practiced in other high volume clinics would result in an increased annual impact. In order for data quality to be important for the staff of the hospital, command support of data quality management efforts is imperative. Command support combined with aggressive training on coding procedures and medical record documentation and the use of management controls will significantly increase the quality of data, thus decreasing the probability of inappropriate resource levels for mission accomplishment.