03426nas a2200397   4500000000100000008004100001260001200042653002400054653005700078653004000135653001200175653001200187653001500199653001600214653003900230653001200269653001300281653001300294100001400307700001500321700001100336700001100347700001300358700001300371700001900384700001700403700001300420700001300433700001400446245013500460856006500595300000700660490000600667520234100673022001403014       2024                            d  bMDPI AG10aInfectious Diseases10aPublic Health, Environmental and Occupational Health10aGeneral Immunology and Microbiology10amHealth10aeHealth10ahealth app10adermatology10aNeglected tropical diseases (NDTs)10aleprosy10aEthiopia10aTanzania1 aMwageni N1 avan Wijk R1 aDaba F1 aMamo E1 aDebelo K1 aJansen B1 aSchoenmakers A1 avan Hees CLM1 aKasang C1 aMieras L1 aMshana SE00aThe NLR SkinApp: Testing a Supporting mHealth Tool for Frontline Health Workers Performing Skin Screening in Ethiopia and Tanzania  uhttps://www.mdpi.com/2414-6366/9/1/18/pdf?version=1705039991  a180 v93 a<p><strong>Background:</strong> The prevalence of skin diseases such as leprosy, and limited dermatological knowledge among frontline health workers (FHWs) in rural areas of Sub-Saharan Africa, led to the development of the NLR SkinApp: a mobile application (app) that supports FHWs to promptly diagnose and treat, or suspect and refer patients with skin diseases. The app includes common skin diseases, neglected tropical skin diseases (skin NTDs) such as leprosy, and HIV/AIDS-related skin conditions. This study aimed to test the supporting role of the NLR SkinApp by examining the diagnostic accuracy of its third edition.</p>

<p><strong>Methods:</strong> A cross-sectional study was conducted in East Hararghe, Ethiopia, as well as the Mwanza and Morogoro region, Tanzania, in 2018–2019. Diagnostic accuracy was measured against a diagnosis confirmed by two dermatologists/dermatological medical experts (reference standard) in terms of sensitivity, specificity, positive predictive value, and negative predictive value. The potential negative effect of an incorrect management recommendation was expressed on a scale of one to four.</p>

<p><strong>Results:</strong> A total of 443 patients with suspected skin conditions were included. The FHWs using the NLR SkinApp diagnosed 45% of the patients accurately. The values of the sensitivity of the FHWs using the NLR SkinApp in determining the correct diagnosis ranged from 23% for HIV/AIDS-related skin conditions to 76.9% for eczema, and the specificity from 69.6% for eczema to 99.3% for tinea capitis/corporis. The inter-rater reliability among the FHWs for the diagnoses made, expressed as the percent agreement, was 58% compared to 96% among the dermatologists. Of the management recommendations given on the basis of incorrect diagnoses, around one-third could have a potential negative effect.</p>

<p><strong>Conclusions: </strong>The results for diagnosing eczema are encouraging, demonstrating the potential contribution of the NLR SkinApp to dermatological and leprosy care by FHWs. Further studies with a bigger sample size and comparing FHWs with and without using the NLR SkinApp are needed to obtain a better understanding of the added value of the NLR SkinApp as a mobile health (mHealth) tool in supporting FHWs to diagnose and treat skin diseases.</p>
  a2414-6366