| Title |
mHealth App for iOS to Help in Diagnostic Decision in Ophthalmology to Primary Care Physicians
|
|---|---|
| Published in |
Journal of Medical Systems, March 2017
|
| DOI | 10.1007/s10916-017-0731-6 |
| Pubmed ID | |
| Authors |
Marta Manovel López, Miguel Maldonado López, Isabel de la Torre Díez, José Carlos Pastor Jimeno, Miguel López-Coronado |
| 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. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | <1% |
| Unknown | 101 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 16 | 16% |
| Student > Ph. D. Student | 13 | 13% |
| Student > Bachelor | 10 | 10% |
| Researcher | 10 | 10% |
| Other | 9 | 9% |
| Other | 19 | 19% |
| Unknown | 25 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 27 | 26% |
| Computer Science | 13 | 13% |
| Nursing and Health Professions | 11 | 11% |
| Engineering | 5 | 5% |
| Social Sciences | 5 | 5% |
| Other | 12 | 12% |
| Unknown | 29 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 May 2017.
All research outputs
#1,783,055
of 22,962,258 outputs
Outputs from Journal of Medical Systems
#36
of 1,157 outputs
Outputs of similar age
#36,950
of 309,402 outputs
Outputs of similar age from Journal of Medical Systems
#1
of 26 outputs
Altmetric has tracked 22,962,258 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,157 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done particularly well, scoring higher than 96% of its peers.
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We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.