Abstract
BackgroundComputerized decision support systems (DSS) have mainly focused on improving clinicians' diagnostic accuracy in unusual and challenging cases. However, since diagnostic omission errors may predominantly result from incomplete workup in routine clinical practice, the provision of appropriate patient- and context-specific reminders may result in greater impact on patient safety. In this experimental study, a mix of easy and difficult simulated cases were used to assess the impact of a novel diagnostic reminder system (ISABEL) on the quality of clinical decisions made by various grades of clinicians during acute assessment.MethodsSubjects of different grades (consultants, registrars, senior house officers and medical students), assessed a balanced set of 24 simulated cases on a trial website. Subjects recorded their clinical decisions for the cases (differential diagnosis, test-ordering and treatment), before and after system consultation. A panel of two pediatric consultants independently provided gold standard responses for each case, against which subjects' quality of decisions was measured. The primary outcome measure was change in the count of diagnostic errors of omission (DEO). A more sensitive assessment of the system's impact was achieved using specific quality scores; additional consultation time resulting from DSS use was also calculated.Results76 subjects (18 consultants, 24 registrars, 19 senior house officers and 15 students) completed a total of 751 case episodes. The mean count of DEO fell from 5.5 to 5.0 across all subjects (repeated measures ANOVA, p < 0.001); no significant interaction was seen with subject grade. Mean diagnostic quality score increased after system consultation (0.044; 95% confidence interval 0.032, 0.054). ISABEL reminded subjects to consider at least one clinically important diagnosis in 1 in 8 case episodes, and prompted them to order an important test in 1 in 10 case episodes. Median extra time taken for DSS consultation was 1 min (IQR: 30 sec to 2 min).ConclusionThe provision of patient- and context-specific reminders has the potential to reduce diagnostic omissions across all subject grades for a range of cases. This study suggests a promising role for the use of future reminder-based DSS in the reduction of diagnostic error.
Highlights
Computerized decision support systems (DSS) have mainly focused on improving clinicians' diagnostic accuracy in unusual and challenging cases
We aimed to perform an impact evaluation of ISABEL in a quasi-experimental setting in order to quantify the effects of diagnostic advice on the quality of clinical decisions made by various grades of clinicians during acute assessment, using a mix of easy and difficult simulated cases drawn from all pediatric sub-specialties
Clinicians were recruited by invitation from the ISABEL registered user database which consisted of a mixture of regular users as well as pediatricians who had never used the system after registration
Summary
Computerized decision support systems (DSS) have mainly focused on improving clinicians' diagnostic accuracy in unusual and challenging cases. Since diagnostic omission errors may predominantly result from incomplete workup in routine clinical practice, the provision of appropriate patient- and context-specific reminders may result in greater impact on patient safety In this experimental study, a mix of easy and difficult simulated cases were used to assess the impact of a novel diagnostic reminder system (ISABEL) on the quality of clinical decisions made by various grades of clinicians during acute assessment. Diagnostic errors of omission (DEO) during acute medical assessment, resulting from cognitive biases such as 'premature closure' and 'confirmation bias', lead to incomplete diagnostic workup and 'missed diagnoses' [8] This is especially relevant in settings such as family practice [9], as well as hospital areas such as the emergency room and critical care [11,12], 20% of patients discharged from emergency rooms raised concerns in a recent survey that their clinical assessment had been complicated by diagnostic error [12]. A number of DSS have been developed over the past few years to assist clinicians during the process of medical diagnosis [14,15,16]
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