Validation of biochemical laboratory results using the DNSev expert system

摘要

In a modern hospital biochemical laboratory, the efficiency and quality of the analysis result production process are fundamental. With respect to quality, an important step in the process is validation. In this step, laboratory physicians, who are physicians specialized in laboratory work, check the analysis result reports in order to verify that no error has occurred during their production. The application described in this paper is an expert system named DNSev. DNSev has been developed in order to improve the quality of the validation process performed by a specific laboratory information system (LIS), called ITALAB C/S, a system used in about thirty percent of Italian hospital laboratories. Objectives achieved by DNSev are: analysis result validation support (medical laboratory expertise in the process is translated into rules and automatically applied by DNSev), help for laboratory automation (checks that are usually manually executed are now automatically executed), clarity (reasoning performed by DNSev in issuing alarms is documented in order to explain it to laboratory physicians), flexibility (new types of reasoning can be easily added to the system by simply upgrading its knowledge base), reliability (checks may be tailored, based on patient characteristics) and time saving and cost reduction. During the development of DNSev, the knowledge acquisition and elicitation task was performed by interviewing laboratory physicians, and also by using available documents and laboratory guidelines. In order to conduct a significant trial test, we installed DNSev in the centralized biochemical laboratory of ‘Sant'Orsola-Malpighi’ Hospital in Bologna (Italy). This is one of the largest Italian biochemical laboratories, managed entirely by ITALAB C/S LIS. During this test we achieve a time saving of around 63% for each analysis request and a reduction on the overall number of analysis requests to be manually examined by laboratory physicians by around 20–25%. About performance of DNSev checks we achieved good accuracy and sensibility levels and a very low false normal level. These results demonstrate that an expert system may be a valid solution for improving quality and efficiency of well-defined medical tasks.