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Early and accurate diagnosis of Gaucher disease, a rare, autosomal recessive condition characterized by hepatosplenomegaly, thrombocytopenia, and anemia, is essential to facilitate earlier decision-making and prevent unnecessary tests and procedures. However, diagnosis can be challenging for non-specialists, owing to a wide variability in age, severity of disease, and types of clinical manifestation. The Gaucher Earlier Diagnosis Consensus (GED-C) scoring system was developed by a panel of 22 expert physicians using Delphi methodology on the signs and covariables considered important for diagnosing Gaucher disease. This study aimed to use the scoring system in a real-world dataset. We applied the GED-C scoring system to 265 confirmed cases of Gaucher disease identified in the Maccabi Health Services (MHS) database from 1998 to 2022. Overall Delphi scores were calculated using features applicable to type 1 Gaucher disease. Based on all available patient data up to one year after diagnosis, the median (interquartile range (IQR)) Delphi score was 8.0 (5.5–11.5), with patients reporting up to 15 variables each. A score of 9.5 (6.5–12.5) was determined for 205 patients diagnosed from 2000 to 2022. The overall GED-C score was highly dependent on the extraction of all relevant data. The number of features collected in the MHS database was fewer than those required to achieve a high score on the GED-C score.

BackgroundPreanesthesia evaluation is a basic practice preceding any surgical procedure, aimed at tailoring individualized anesthetic plans for patients, improving safety, and providing patients with educational knowledge and tools in preparation for the surgery day. In the last 2 decades, eHealth and mobile health (mHealth) settings have gradually replaced part of the face-to-face encounters as the platform for preanesthesia communication between doctor and patient, yielding a range of benefits as demonstrated in recent publications. Nevertheless, there is a lack of studies examining the effectiveness of surgical mHealth apps focusing on the pediatric preanesthetic setting and addressing their usability among families. ObjectiveThis study describes a dynamic approach for the development process of GistMD’s preanesthesia mHealth system, a mobile-based educational and management system designed for the pediatric setting. MethodsThe study was conducted in 4 departments at a 1500-bed quaternary, academic medical center in Tel Aviv, Israel. During the study period, the link to the preanesthesia system was sent via SMS text messages to families whose children were about to undergo surgery. The system included preanesthesia questionnaires, educational videos, downloadable instructions, and consent forms. Continuous collection and examination of usability data were conducted during the implementation term including responsiveness, effectiveness, and satisfaction indicators. The information collected in each stage was used to draw conclusions regarding potential usability gaps of the system and to plan product adjustments for the following period. ResultsDuring 141 days of implementation, the link to the GistMD preanesthesia management system was sent to 769 families, and product-fit actions were implemented during this term: (1) changing text message scheduling for addressing learnability and accessibility, resulting in a significant increase of 27% (χ21=12.65, P