Design and implementation of a children vaccination reminder system based on short message service

Background: Most problems related to quality of care and patient safety are related to human negligence. One of the causes of these problems is forgetting to do something. This problem can be avoided with information technology in many cases. Some forgotten are very important. Among these is failure to comply with vaccination schedule by parents that can result in inappropriate outcomes. In this study,we developed and evaluated a SMS reminder system for regular and timely vaccination of children. Methods: In this developmental-applied research,firstly,a child vaccination reminder system was designed and implemented to help parents reduce the forgetfulness. This system based on the child�s vaccination history and the date of birth,offer time and type of future vaccines. Then the parents of 27 children,that their vaccination was between 22 June and 21 August 2015,referred to Children�s Medical Center,were sent text messages by using this system. We evaluated the accuracy of the system logic by using some scenarios. In addition,we evaluated parents� satisfaction with the system using a questionnaire. Results: In all cases but one,the system proposed the type and date of future children vaccines correctly. All the parents who have received text messages had good perception and satisfaction on the majority of questions (total mean score of 4.15 out of 5). Most parents (4.92 out of 5) stated that using the system to remind their visit for child immunization was helpful and willing to offer the system to their friends and other families. Conclusion: Using the short message system is beneficial for parents to remind their children�s vaccination time and increases their satisfaction. So,it can be considered as an important and essential tool in providing healthcare services. SMS is an easy,cheap and effective way to improve the quality of care services. � 2016,Tehran University of Medical Sciences. All Rights Reserved

Desarrollo e integración de ontologías para la representación de pacientes COVID-19

Desde que se identificó el primer caso conocido de síndrome respiratorio agudo severo coronavirus 2 (SARS-CoV-2) en Wuhan, China, en diciembre de 2019, la enfermedad se ha extendido por todo el mundo, dando lugar a la pandemia actual de COVID-19 que causa síntomas variables en las personas, pero a menudo incluyen fiebre, tos seca, dolor de cabeza, fatiga, dificultad para respirar, perdida del olfato y perdida del gusto, de aquellos que desarrollan síntomas lo suficientemente notables como para ser clasificados como pacientes, la mayoría desarrolla síntomas leves a moderados, mientras que el 14% desarrolla síntomas graves y el 5% sufre síntomas críticos, por lo que deben ser atendidos en centros especializados. De modo que cada paciente reacciona de forma diferente ante la enfermedad, el saber cuáles son los factores que determinan la condición de un paciente es importante para conocer el comportamiento de la enfermedad, por ello se considera implementar bases de conocimientos que permitan generar nuevo conocimiento en base a los hechos establecidos de la información de pacientes, por ejemplo, el tratamiento de los pacientes. Por tal motivo, en este proyecto de investigación se reporta el diseño y desarrollo un sistema de modelos ontológicos integrados para la representación y administración de perfiles de pacientes con COVID-19: diagnóstico y tratamiento, donde los resultados de las diferentes evaluaciones realizadas a dicho modelo, muestran la factibilidad de utilizar esta base de conocimiento integrada por ontologías para la representación de la información clínica del paciente y obtener nuevo conocimiento y servir como base para proyectos de investigación a futuro.Since the first known case of severe acute respiratory syndrome coronavirus 2 (SARSCoV- 2) was identified in Wuhan, China, in December 2019, the disease has spread throughout the world, giving rise to the current COVID pandemic. -19 which causes variable symptoms in people, but often include fever, dry cough, headache, fatigue, shortness of breath, loss of smell, and loss of taste, of those who develop symptoms notable enough to be classified as patients, the majority develop mild to moderate symptoms, while 14% develop severe symptoms and 5% suffer critical symptoms, so they must be treated in specialized centers. So that each patient reacts differently to the disease, adequate knowledge of the factors that determine the condition of a patient is important to know the behavior of the disease, for this reason, it is considered to implement knowledge bases that allow generating new knowledge is based on established facts of patient information, for example, treatment of patients. For this reason, this research project reports the design and development of a system of integrated ontological models for the representation and administration of profiles of patients with COVID-19: diagnosis and treatment, where the results of the different evaluations carried out on the said model, show the feasibility of using this knowledge base integrated by ontologies to represent the patient’s clinical information and obtain new knowledge and serve as a basis for future research projects