{"title":"An EMR-enabled medical sensor data collection framework","authors":"Rakshit Wadhwa, Pushpendra Singh, Meenu Singh, Saurabh Kumar","doi":"10.1109/COMSNETS.2015.7098703","DOIUrl":null,"url":null,"abstract":"Availability of healthcare data allows governments to analyze effectiveness of their policies, monitor spread of a disease, etc. Data collection for public healthcare is still a big challenge, especially in developing countries where most of the data collection is still done on paper. Therefore, recently many tools, e.g. ODK, Commcare, have become available that allow data collection on mobile devices. Similarly, during data collection, use of health sensors to measure some of the health parameters, e.g. ECG, Oxygen Saturation, is increasing, but then the data measured by sensors is often entered manually to the mobile device. Finally, the data collected on a mobile device is then entered into a database (either an EMR or a general database) manually, which is time consuming and introduces error due to manual input. While partial solutions that enable connectivity of sensors to mobile device or mobile device to a specific EMR are available, there is a lack of a comprehensive end-to-end solution. In this paper, we present our framework which works on mobile devices to allow collection of sensor data at one end and stores data into an EMR on the other end, thus provides a comprehensive solution for data collection. The requirements of the framework were derived after interviewing healthcare workers who conduct regular field studies. We have tested our framework with a publicly available standard health sensor and OpenMRS.","PeriodicalId":277593,"journal":{"name":"2015 7th International Conference on Communication Systems and Networks (COMSNETS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 7th International Conference on Communication Systems and Networks (COMSNETS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMSNETS.2015.7098703","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Availability of healthcare data allows governments to analyze effectiveness of their policies, monitor spread of a disease, etc. Data collection for public healthcare is still a big challenge, especially in developing countries where most of the data collection is still done on paper. Therefore, recently many tools, e.g. ODK, Commcare, have become available that allow data collection on mobile devices. Similarly, during data collection, use of health sensors to measure some of the health parameters, e.g. ECG, Oxygen Saturation, is increasing, but then the data measured by sensors is often entered manually to the mobile device. Finally, the data collected on a mobile device is then entered into a database (either an EMR or a general database) manually, which is time consuming and introduces error due to manual input. While partial solutions that enable connectivity of sensors to mobile device or mobile device to a specific EMR are available, there is a lack of a comprehensive end-to-end solution. In this paper, we present our framework which works on mobile devices to allow collection of sensor data at one end and stores data into an EMR on the other end, thus provides a comprehensive solution for data collection. The requirements of the framework were derived after interviewing healthcare workers who conduct regular field studies. We have tested our framework with a publicly available standard health sensor and OpenMRS.