Development of mHealth for public health information collection, with GIS, using private cloud: A case study of Saraphi district, Chiang Mai, Thailand

Abstract

Geographical Information System (GIS) is a designated system widely used for collecting and analyzing geographical data. Since the introduction of ultra-mobile, "smart" devices, investigators, clinicians, and even the general public have had powerful new tools for collecting, uploading and accessing information in the field. Epidemiology paired with GIS will increase the efficacy of preventive healthcare services. The objective of this study is to apply GPS location services that are available on common mobile device with district health systems, storing data on our private cloud system. The mobile application has been developed for use on iOS, Android, and web-based platforms.The system consists of two parts of district health information, including recorded resident data forms and individual health recorded data forms, which were developed and approved by opinion sharing and public hearing. The application's graphical user interface was developed using HTML5 and PHP with MySQL as a database management system (DBMS). The reporting module of the developed software displays data in a variety of views, from traditional tables to various types of high-resolution, layered graphics, incorporating map location information with street views from Google Maps. Multi-extension exporting is also supported, utilizing standard platforms such as PDF, PNG, JPG and XLS.The data was collected in the database beginning in March, 2013, by district health volunteers and district youth volunteers who had completed the application training program. District health information consisted of patients' household coordinates, individual health data, social and economic information. This was combined with Google Street View data, collected in March, 2014. Studied groups consisted of 16,085 (67.87%) and 47,811 (59.87%) of the total 23,701 households and 79,855 people were collected by the system respectively, in Saraphi district, Chiang Mai Province.The report generated from the system has had a major benefit directly to the Saraphi District Hospital. Healthcare providers are able to use the basic health data to provide a specific home healthcare service and also to create health promotion activities according to medical needs of the people in community.

Influenza, dengue and common cold detection using LSTM with fully connected neural network and keywords selection

“…The data used in this research is from medical records from Saraphi Hospital, Chiang Mai Province, Thailand Between 2015 and 2020 [ 3 – 5 ]. We use only records of patients diagnosed with three diseases.…”

mHealth Technology Translation in a Limited Resources Community—Process, Challenges, and Lessons Learned From a Limited Resources Community of Chiang Mai Province, Thailand

“…The mHealth application, “CMDigiHealth”, was previously developed as a mobile information management application, supporting both iOS and Android platforms. The application is described in detail in our previous report [10] . Briefly, the application served as a platform to distribute health surveys quickly and easily to large groups.…”

“…In 2014, an interdisciplinary research team from Chiang Mai University, addressed these issues and developed first ever community healthcare profiling system using mHealth technology [10] . This system allowed trained data collectors to gather data from community members and upload that data directly into a cloud-based database.…”

“…This project focused on the semi-rural district of Saraphi in Chiang Mai province and aimed to give healthcare providers in Chiang Mai geographically indexed and easily searchable information to profile the public health of their communities using an up-to-date digital format. Since our original report [10] , the project has scaled up from 1 province to 52 provinces over the past five years.…”

“…In light of the public health need presented by the current COVID-19 pandemic, and the increasing worldwide penetration of smartphone ownership, we believe that successes like those accomplished in Thailand can be accomplished elsewhere. To address a lack of practical advice on mHealth and GIS public health system implementation, this paper will share an updated review of our experiences implementing Thailand’s first ever community healthcare profiling system [10] . To highlight the type of insight made possible through the collection of this type of dataset, we will share an example analysis of dengue fever prevalence.…”