Diagnosis of Rare Diseases: a scoping review of clinical decision support systems

Abstract

Background Rare Diseases (RDs), which are defined as diseases affecting no more than 5 out of 10,000 people, are often severe, chronic and life-threatening. A main problem is the delay in diagnosing RDs. Clinical decision support systems (CDSSs) for RDs are software systems to support clinicians in the diagnosis of patients with RDs. Due to their clinical importance, we conducted a scoping review to determine which CDSSs are available to support the diagnosis of RDs patients, whether the CDSSs are available to be used by clinicians and which functionalities and data are used to provide decision support. Methods We searched PubMed for CDSSs in RDs published between December 16, 2008 and December 16, 2018. Only English articles, original peer reviewed journals and conference papers describing a clinical prototype or a routine use of CDSSs were included. For data charting, we used the data items “Objective and background of the publication/project”, “System or project name”, “Functionality”, “Type of clinical data”, “Rare Diseases covered”, “Development status”, “System availability”, “Data entry and integration”, “Last software update” and “Clinical usage”. Results The search identified 636 articles. After title and abstracting screening, as well as assessing the eligibility criteria for full-text screening, 22 articles describing 19 different CDSSs were identified. Three types of CDSSs were classified: “Analysis or comparison of genetic and phenotypic data,” “machine learning” and “information retrieval”. Twelve of nineteen CDSSs use phenotypic and genetic data, followed by clinical data, literature databases and patient questionnaires. Fourteen of nineteen CDSSs are fully developed systems and therefore publicly available. Data can be entered or uploaded manually in six CDSSs, whereas for four CDSSs no information for data integration was available. Only seven CDSSs allow further ways of data integration. thirteen CDSS do not provide information about clinical usage. Conclusions Different CDSS for various purposes are available, yet clinicians have to determine which is best for their patient. To allow a more precise usage, future research has to focus on CDSSs RDs data integration, clinical usage and updating clinical knowledge. It remains interesting which of the CDSSs will be used and maintained in the future.

Evaluation of a clinical decision support system for rare diseases: a qualitative study

“…Therefore, we decided to use a “User-Centred Design Process” (UCD) for the development of DISERDIS. In the context of the UCD, we took several steps to identify user-requirements and needs, including a scoping review of literature about CDSS for RDs [ 17 ], a cross sectional survey [ 18 ], a qualitative study with expert interviews [ 19 ] and a focus group. Based on the results of these studies, DISERDIS is developed as a high fidelity prototype that addresses the requirements of the UCD phases, but is not yet a fully developed software system [ 20 ].…”

“…Usability refers to the quality of a system, which allows users to complete a task effectively, fast, and with high satisfaction [ 22 ]. While many studies propose methods to improve the performance and accuracy of diagnostic CDSS, to our knowledge, there is no study available that focuses on the design of a CDSS for RDs [ 17 ]. Moreover, we could not identify any study that assesses the usability and acceptance of a CDSS for RDs amongst users.…”

Evaluation of a Clinical Decision Support System for Rare Diseases - A Qualitative Study

“…Within an UCD, software prototypes are designed, developed and tested on a multi-level approach together with users according to their requirements and needs [16]. In the context of the UCD, we took several steps to identify user-requirements and needs, including a scoping review of literature about CDSS for RDs [17], a cross sectional survey [18], a qualitative study with expert interviews [19] and a focus group. As a result, a high delity prototype was developed that addresses the requirements of the UCD phases, but is not yet a fully developed software system [20].…”

“…To our knowledge, there is no study available that has assessed a CDSS for RDs regarding the usability and the acceptance by the users. However, several CDSS have been developed, whereof studies have been published, but only about the performance and accuracy of the diagnosis of the CDSS [17]. Therefore, we performed an evaluation study of our CDSS within the UCD, with the goal to get feedback for the further development of our prototypical CDSS and to increase the user satisfaction.…”

Adaption of the OMOP CDM for Rare Diseases

“…Clinical decision support systems (CDSS) could be an option to overcome these challenges. A recent study shows that currently 19 CDSS are available to support the diagnosis and therapy of rare diseases [5], for which reliable information and data are needed. However, studies show the lack of a large amount of real world data in the context of rare diseases [2,6,7].…”