An EMR-Enabled Medical Sensor Data Collection Framework Rakshit Wadhwa IIIT Delhi New Delhi, India Email: rakshitw@iiitd.ac.in Pushpendra Singh IIIT Delhi New Delhi, India Email: psingh@iiitd.ac.in Meenu Singh PGIMER Chandigarh, India Email: meenusingh4@gmail.com Saurabh Kumar PGIMER Chandigarh, India Email: saubkr@gmail.com 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. I. I NTRODUCTION Affordable and accessible public healthcare is a fundamental need of any modern society. The quality and accessibility of healthcare services directly affect the quality of life. However, with growing populations and increasing medical costs, providing quality healthcare has become a challenge, especially for developing countries. Recent technological advancements, e.g. health sensors, mobile technologies, have a potential to facilitate better healthcare. The quality of care should be improved while keeping the burden on health resources low. There is a dearth of doctors in developing countries. In India itself, the doctor to population ratio is 1:1800, and there is a predicted shortage of 600,000 doctors [1]. The role of health workers has become increasingly important to fill this gap. One of the key components of India’s National Rural Health Mission is to provide every village with a trained community health activist ASHA (Accredited Social Health Activist). Currently around 894525 ASHA activists are working across India [2]. This force of activists works as an interface between the community and the public health system. One of the tasks of community health workers is to collect health related data that can give deep insights into healthcare e.g. spread of disease or effectiveness of health programs. Mobile compatible medical sensors like Handheld Tele-ECG Instrument [3] and mobile phonebased data collection tools like CommCare [4] have improved the scope and efficiency of field health workers. However, most of the medical sensor mobile applications just display the sensor readings, these readings are then manually recorded either on paper or digitally through some data collection application, which stores data locally or to the application specific server. If these sensor readings can be stored directly to the EMR without the need to manually aggregate readings from different digital and non digital sources, then the accuracy as well as efficiency of the health workers can be improved. Our work aims to fill the gap between mobile sensor applications, data collection applications and EMRs. After finding the challenges that are commonly faced by health workers, as described in detail in section II, we realized the need of a comprehensive system which allows readings measured by medical sensors and manually entered data about the patient, to be directly stored into an EMR. As a solution to this problem, our system interacts with sensor specific applications to collect sensor readings, provides functionality of data collection applications by also allowing manual data entry, can be configured with different EMRs, push the sensor data and other data to the EMR, and takes into consideration poor network connectivity. Such a system facilitates better efficiency of the health workers, faster dissemination of information to the EMR and hence more prompt health services, and reduction in the number of unintended human errors. In this paper, we describe an EMR-enabled medical sensor data collection framework. In section II we describe the challenges which are generally faced by health workers during field studies, in section III we describe the requirements as derived from the challenges. Section IV describes the architecture of the framework. Section V describes an example to use the framework, section VI outlines the related work and further discusses the framework, and section VII concludes the paper. 978-1-4244-8953-4/11/$26.00 c  2015 IEEE