‘Hybrid Doctors’ Can Fast Track the Evolution of a Sustainable e-Health Ecosystem in Low Resource Contexts: The Sri Lankan Experience

Although e-health is an area recognized as essential in the rapid development of healthcare systems in low resource contexts, many challenges prevent the emergence of an effective e-health ecosystem. Lack in capacity around health informatics is one of the main challenges. Based on a longitudinal case study gathering data pertaining to a master’s program in biomedical informatics in Sri Lanka designed for doctors, in this paper we demonstrate that creating ‘hybrid doctors’ may be the way forward. We illustrate how hybrid doctors conversant in healthcare and information and communication technology (ICT) are able to facilitate the creation of an e-health ecosystem in a way that it would contribute significantly to the ICT driven healthcare reforms. Through this case study we highlight the importance of multidisciplinarity, participatory design, strategic investments, learning that aligns with developmental needs, networking, gaining legitimacy and re-packaging perspectives on ‘health informatics capacity development’

Cornelia de Lange syndrome in diverse populations.

Cornelia de Lange syndrome (CdLS) is a dominant multisystemic malformation syndrome due to mutations in five genes-NIPBL, SMC1A, HDAC8, SMC3, and RAD21. The characteristic facial dysmorphisms include microcephaly, arched eyebrows, synophrys, short nose with depressed bridge and anteverted nares, long philtrum, thin lips, micrognathia, and hypertrichosis. Most affected individuals have intellectual disability, growth deficiency, and upper limb anomalies. This study looked at individuals from diverse populations with both clinical and molecularly confirmed diagnoses of CdLS by facial analysis technology. Clinical data and images from 246 individuals with CdLS were obtained from 15 countries. This cohort included 49% female patients and ages ranged from infancy to 37 years. Individuals were grouped into ancestry categories of African descent, Asian, Latin American, Middle Eastern, and Caucasian. Across these populations, 14 features showed a statistically significant difference. The most common facial features found in all ancestry groups included synophrys, short nose with anteverted nares, and a long philtrum with thin vermillion of the upper lip. Using facial analysis technology we compared 246 individuals with CdLS to 246 gender/age matched controls and found that sensitivity was equal or greater than 95% for all groups. Specificity was equal or greater than 91%. In conclusion, we present consistent clinical findings from global populations with CdLS while demonstrating how facial analysis technology can be a tool to support accurate diagnoses in the clinical setting. This work, along with prior studies in this arena, will assist in earlier detection, recognition, and treatment of CdLS worldwide

Cornelia de Lange Syndrome in Diverse Populations.

Cornelia de Lange syndrome (CdLS) is a dominant multisystemic malformation syndrome due to mutations in five genes—NIPBL, SMC1A, HDAC8, SMC3, and RAD21. The characteristic facial dysmorphisms include microcephaly, arched eyebrows, synophrys, short nose with depressed bridge and anteverted nares, long philtrum, thin lips, micrognathia, and hypertrichosis. Most affected individuals have intellectual disability, growth deficiency, and upper limb anomalies. This study looked at individuals from diverse populations with both clinical and molecularly confirmed diagnoses of CdLS by facial analysis technology. Clinical data and images from 246 individuals with CdLS were obtained from 15 countries. This cohort included 49% female patients and ages ranged from infancy to 37 years. Individuals were grouped into ancestry categories of African descent, Asian, Latin American, Middle Eastern, and Caucasian. Across these populations, 14 features showed a statistically significant difference. The most common facial features found in all ancestry groups included synophrys, short nose with anteverted nares, and a long philtrum with thin vermillion of the upper lip. Using facial analysis technology we compared 246 individuals with CdLS to 246 gender/age matched controls and found that sensitivity was equal or greater than 95% for all groups. Specificity was equal or greater than 91%. In conclusion, we present consistent clinical findings from global populations with CdLS while demonstrating how facial analysis technology can be a tool to support accurate diagnoses in the clinical setting. This work, along with prior studies in this arena, will assist in earlier detection, recognition, and treatment of CdLS worldwide.Supplementary Table 1 Participants with photographs in Figures 2-5 from 10 countries. Supplementary Table 2. Geometric and texture feature comparison of Global (combined African descent, Asian, Latin American, Caucasian) CdLS individuals with normal controls using digital facial analysis technology. The ranges of the geometric linear features were normalized by the ear‐to‐ear distance. Geometric angle features are presented in degrees. Texture features were computed at three scales (r1, r2, and r3). Features are presented in order of their relevance for the diagnosis of CdLS. Supplementary Table 3. Geometric and texture feature comparison of African descent CdLS individuals with normal controls using digital facial analysis technology. The ranges of the geometric linear features were normalized by the ear‐to‐ear distance. Geometric angle features are presented in degrees. Texture features were computed at three scales (r1, r2, and r3). Features are presented in order of their relevance for the diagnosis of CdLS. Supplementary Table 4. Geometric and texture feature comparison of Asian CdLS individuals with normal controls using digital facial analysis technology. The ranges of the geometric linear features were normalized by the ear‐to‐ear distance. Geometric angle features are presented in degrees. Texture features were computed at three scales (r1, r2, and r3). Features are presented in order of their relevance for the diagnosis of CdLS. Supplementary Table 5. Geometric and texture feature comparison of Latin American CdLS individuals with normal controls using digital facial analysis technology. The ranges of the geometric linear features were normalized by the ear‐to‐ear distance. Geometric angle features are presented in degrees. Texture features were computed at three scales (r1, r2, and r3). Features are presented in order of their relevance for the diagnosis of CdLS. Supplementary Table 6. Geometric and texture feature comparison of Caucasian CdLS individuals with normal controls using digital facial analysis technology. The ranges of the geometric linear features were normalized by the ear‐to‐ear distance. Geometric angle features are presented in degrees. Texture features were computed at three scales (r1, r2, and r3). Features are presented in order of their relevance for the diagnosis of CdLS. Supplementary Figure 1. Global: Graph of area under the ROC curve (AUC), accuracy, sensitivity, and specificity versus the number of features selected. Supplementary Figure 2. African: Graph of area under the ROC curve (AUC), accuracy, sensitivity, and specificity versus the number of features selected. Supplementary Figure 3. Asian: Graph of area under the ROC curve (AUC), accuracy, sensitivity, and specificity versus the number of features selected. Supplementary Figure 4. Latin American: Graph of area under the ROC curve (AUC), accuracy, sensitivity, and specificity versus the number of features selected. Supplementary Figure 5. Caucasian: Graph of area under the ROC curve (AUC), accuracy, sensitivity, and specificity versus the number of features selectedPK and MM are supported by the Division of Intramural Research at the National Human Genome Research, NIH. Partial funding of this project was from a philanthropic gift from the Government of Abu Dhabi to the Children's National Health System. VS is supported by the Chulalongkorn Academic Advancement Into Its 2nd Century Project and the Thailand Research Fund. We would also like to acknowledge other clinicians who supported this work—MZ, JP, and GC. We would like to acknowledge that IDK, LD, MK, and SR are supported by the CdLS Center Endowed Funds at The Children's Hospital of Philadelphia and PO1 HD052860 from the NICHD. ES is supported by a fellowship from PKS Italia and PKSKids USA. LD was also supported by a postdoctoral training grant (T32 GM008638) from the NIGMS.http://wileyonlinelibrary.com/journal/ajmga2020-02-01hj2019Genetic