Monitoring the integration of hospital information systems: How it may ensure and improve the quality of data.

Integration of hospital departmental information systems (HDIS) has become a common but difficult issue. In May 2003, the Department of Biostatistics and Medical Informatics implemented a Virtual Electronic Patient Record (VEPR) for the Hospital S. João (HSJ), a university hospital with over 1350 beds. The system integrates clinical data from 10 legacy HDIS plus the Hospital Administrative Database (HAD), aiming to deliver all patient information to health professionals. Currently, around 500 medical doctors use the system on a regular basis and the HSJ-VEPR retrieves an average of 3,000 new reports per day, in PDF or HTML formats. This paper describes and discusses the role of monitoring in the assurance and improvement of data quality. Three approaches were put in place: (a) monitoring the HSJ-VEPR concerning the frequency of clinical records retrieved from the DIS by checking if the daily number of reports sent by the HDIS fell in the normal range from similar week days; (b) monitoring inconsistencies in the patient's identification by cross-checking between HDIS and HAD; and (c) monitoring the integrity of clinical records delivered to medical doctors through the HSJ-VEPR by checking their digital signature. During 2005, the monitoring system detected 53 unusual frequency patterns of which 44 corresponded to real problems. Over a 6 months period, more than 400 alerts were generated concerning inconsistencies in the patient's identification found in laboratory reports. Nevertheless, a significant reduction in the number of these inconsistencies occurred - from 116 in July to 10 in December 2005--due to implementation of preventive measures by the DIS. Finally, report's integrity was checked each time the report was asked to be visualized i.e. in more than one hundred thousand times during a one year period. In conclusion, all information available in hospital information systems can and should be used to trigger alerts of malfunctions and inconsistencies, in order to improve data quality and ensure a better health care.