A mobile electronic data capture solution for applications in public health

Abstract

Data collection is an important part of any research study in public health. Traditionally, researchers have used pen-and-paper-based systems for collecting raw data in the fi eld, and this data is then entered into an electronic format database by others, who may not have been involved in primary data collection. Transcribing data from paper to computer format is inherently error-prone, since the transcribers are far removed from the raw data collection process. It is expensive and time-consuming to go back to the fi eld force for problems in the fi eld data. Errors in data collection may result in duplication and unreliable data, which may then result in expensive data cleaning steps being applied, thereby increasing costs and latency in the system. The cost of correcting for errors is lowest when errors are detected at the source of input itself, and this cost increases progressively as data moves within the system further away from the source. Further, longitudinal studies, which require periodic followup of a cohort, pose additional challenges due to their long-term nature. Pen-and-paper-based studies are also not easily scalable and replicable. While electronic data capture (EDC) systems have become popular in recent times with the advent of low-cost mobile devices, most EDC systems are proprietary and not easily customisable. In this chapter, we present a generic and fl exible EDC solution which is based on open standards that enable the solution to be deployed on a variety of mobile devices.