Disease surveillance and patient care in remote regions: an exploratory study of collaboration among health-care professionals in Amazonia

Abstract

The development and deployment of information technology, particularly mobile tools, to support collaboration between different groups of healthcare professionals has been viewed as a promising way to improve disease surveillance and patient care in remote regions. The effects of global climate change combined with rapid changes to land cover and use in Amazonia are believed to be contributing to the spread of vector-borne emerging and neglected diseases. This makes empowering and providing support for local healthcare providers all the more important. We investigate the use of information technology in this context to support professionals whose activities range from diagnosing diseases and monitoring their spread to developing policies to deal with outbreaks. An analysis of stakeholders, their roles and requirements, is presented which encompasses results of fieldwork and of a process of design and prototyping complemented by questionnaires and targeted interviews. Findings are analysed with respect to the tasks of diagnosis, training of local healthcare professionals, and gathering, sharing and visualisation of data for purposes of epidemiological research and disease surveillance. Methodological issues regarding the elicitation of cooperation and collaboration requirements are discussed and implications are drawn with respect to the use of technology in tackling emerging and neglected diseases.

nu-view

“…Epidemiological work, specially in the area of emerging and neglected tropical diseases involves intense teamwork, relying on cooperation within multidisciplinary teams which comprise medical doctors and researchers, epidemiologists, local healthcare providers, nurses, and healthcare managers [17,18]. Visual communication at meetings through sharing of data on large displays is a marked characteristic of multidisciplinary medical teamwork [16].…”

“…While support for map-based interaction exists, and is often integrated with data collection and epidemiological modelling [22,17], collaboration support in these systems is mostly restricted to asynchronous interaction or individual data presentation. The nu-case system [17], for instance, introduced a unified platform to support data collection by epidemiologists and local fieldworkers working in remote regions.…”

“…The nu-case system [17], for instance, introduced a unified platform to support data collection by epidemiologists and local fieldworkers working in remote regions. It included data aggregation functionality, and a visualization interface for mobile devices, through which users can view and analyse the compiled information on their individual mobile (e.g.…”

Designing a serious game for community-based disease prevention in the Amazon

“…The activities of this group include: (a) identification of the main factors involved with the hyperendemicity of American Cutaneous Leishmaniasis (ACL) in Acre-Brazil through a ten-year retrospective multivariate statistical analysis; (b) use of qualitative field-based ethnographic work to validate transmission factors in the Brazilian municipality of Assis BrasilAcre, at the Madre de Peru-Brazil-Bolivia borders; (c) ongoing research on the regional migration patterns (international and national, in Brazil and Peru) and public policies related to the (re)emergence of Leishmaniases; (d) comprehensive ongoing research aimed at developing an Early Warning System for Bartonellosis and Leishmaniases at the tri-national region, drawing from the OneHealth paradigm and including Climate Change variables; (e) ongoing development of a computer-based tele-health system for handheld mobile devices, including applications for epidemiological surveillance data-sharing, GIS visualization of disease cases, and remote diagnosis support for Bartonellosis and Leishmaniases [7].…”

Readability of a background map layer under a semi-transparent foreground layer

“…This is particularly relevant to the area of disease surveillance, where geographical patterns of disease spread need to be explored by manipulating and selecting a large range of recorded disease data attributes. To make this possible, we have developed a prototype system for mobile devices (tablets in particular) which is intended to be used in the field by healthcare professionals and epidemiologists for data collection, and to support the work of epidemiologists in monitoring the spread of diseases [14].…”