title: mHealth App for iOS to Help in Diagnostic Decision in Ophthalmology to Primary Care Physicians.
abstract: Decision support systems (DSS) are increasingly demanded due that diagnosis is one of the main activities that physicians accomplish every day. This fact seems critical when primary care physicians deal with uncommon problems belonging to specialized areas. The main objective of this paper is the development and user evaluation of a mobile DSS for iOS named OphthalDSS. This app has as purpose helping in anterior segment ocular diseases' diagnosis, besides offering educative content about ophthalmic diseases to users. For the deployment of this work, firstly it has been used the Apple IDE, Xcode, to develop the OphthalDSS mobile application using Objective-C as programming language. The core of the decision support system implemented by OphthalDSS is a decision tree developed by expert ophthalmologists. In order to evaluate the Quality of Experience (QoE) of primary care physicians after having tried the OphthalDSS app, a written inquiry based on the Likert scale was used. A total of 50 physicians answered to it, after trying the app during 1 month in their medical consultation. OphthalDSS is capable of helping to make diagnoses of diseases related to the anterior segment of the eye. Other features of OphthalDSS are a guide of each disease and an educational section. A 70% of the physicians answered in the survey that OphthalDSS performs in the way that they expected, and a 95% assures their trust in the reliability of the clinical information. Moreover, a 75% of them think that the decision system has a proper performance. Most of the primary care physicians agree with that OphthalDSS does the function that they expected, it is a user-friendly and the contents and structure are adequate. We can conclude that OphthalDSS is a practical tool but physicians require extra content that makes it a really useful one.
authors.affiliation: Department of Signal Theory and Communications, and Telematics Engineering, University of Valladolid, Paseo de Belén, 15, 47011, Valladolid, Spain.
authors.forename: Marta Manovel
authors.initials: MM
authors.lastname: López
authors.affiliation: University Institute of Applied Ophthalmobiology (IOBA), University of Valladolid, Paseo de Belén, 17. Campus Miguel Delibes, 47011, Valladolid, Spain.
authors.forename: Miguel Maldonado
authors.initials: MM
authors.lastname: López
authors.affiliation: Department of Signal Theory and Communications, and Telematics Engineering, University of Valladolid, Paseo de Belén, 15, 47011, Valladolid, Spain. isator@tel.uva.es.
authors.forename: Isabel
authors.initials: I
authors.lastname: de la Torre Díez
authors.affiliation: University Institute of Applied Ophthalmobiology (IOBA), University of Valladolid, Paseo de Belén, 17. Campus Miguel Delibes, 47011, Valladolid, Spain.
authors.forename: José Carlos Pastor
authors.initials: JCP
authors.lastname: Jimeno
authors.affiliation: Department of Signal Theory and Communications, and Telematics Engineering, University of Valladolid, Paseo de Belén, 15, 47011, Valladolid, Spain.
authors.forename: Miguel
authors.initials: M
authors.lastname: López-Coronado
mesh_terms: D020000:Decision Support Systems, Clinical; D003941:Diagnostic Techniques, Ophthalmological; D005128:Eye Diseases / Q000175:diagnosis*; D006801:Humans; D063731:Mobile Applications; D058007:Physicians, Primary Care; D011320:Primary Health Care / Q000379:methods / Q000592:standards*; D013030:Spain; D017216:Telemedicine / Q000379:methods / Q000592:standards*
keywords: App; Decision support system (DSS); Mhealth; Ophthalmology; iOS