title: Development of a clinical decision support system for diabetes care: A pilot study.
abstract: Management of complex chronic diseases such as diabetes requires the assimilation and interpretation of multiple laboratory test results. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion. This makes the assembly and interpretation of results related to diabetes care challenging. We developed a diabetes-specific clinical decision support system (Diabetes Dashboard) interface for displaying glycemic, lipid and renal function results, in an integrated form with decision support capabilities, based on local clinical practice guidelines. The clinical decision support system included a dashboard feature that graphically summarized all relevant laboratory results and displayed them in a color-coded system that allowed quick interpretation of the metabolic control of the patients. An alert module informs the user of tests that are due for repeat testing. An interactive graph module was also developed for better visual appreciation of the trends of the laboratory results of the patient. In a pilot study involving case scenarios administered via an electronic questionnaire, the Diabetes Dashboard, compared to the existing laboratory reporting interface, significantly improved the identification of abnormal laboratory results, of the long-term trend of the laboratory tests and of tests due for repeat testing. However, the Diabetes Dashboard did not significantly improve the identification of patients requiring treatment adjustment or the amount of time spent on each case scenario. In conclusion, we have developed and shown that the use of the Diabetes Dashboard, which incorporates several decision support features, can improve the management of diabetes. It is anticipated that this dashboard will be most helpful when deployed in an outpatient setting, where physicians can quickly make clinical decisions based on summarized information and be alerted to pertinent areas of care that require additional attention.
authors.affiliation: Department of Biochemistry, National University of Singapore, Singapore.
authors.forename: Livvi Li Wei
authors.initials: LL
authors.lastname: Sim
authors.affiliation: Department of Biochemistry, National University of Singapore, Singapore.
authors.forename: Kenneth Hon Kim
authors.initials: KH
authors.lastname: Ban
authors.affiliation: Department of Biochemistry, National University of Singapore, Singapore.
authors.forename: Tin Wee
authors.initials: TW
authors.lastname: Tan
authors.affiliation: Department of Laboratory Medicine, National University Hospital, Singapore.
authors.forename: Sunil Kumar
authors.initials: SK
authors.lastname: Sethi
authors.affiliation: Department of Laboratory Medicine, National University Hospital, Singapore.
authors.forename: Tze Ping
authors.initials: TP
authors.lastname: Loh
mesh_terms: D015415:Biomarkers; D020000:Decision Support Systems, Clinical; D003920:Diabetes Mellitus / Q000097:blood / Q000175:diagnosis* / Q000628:therapy; D057286:Electronic Health Records; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D008077:Lipoproteins, LDL / Q000097:blood; D010865:Pilot Projects; D017410:Practice Guidelines as Topic; D014584:User-Computer Interface
chemical_list: D015415:Biomarkers; D006442:Glycated Hemoglobin; D008077:Lipoproteins, LDL; C517652:hemoglobin A1c protein, human