These results indicate encouraging prospects for mHealth technologies in general, and the use of rich media clinical guidelines on cell phones in particular, for the improvement of community health worker performance in developing countries.
There are few tried and tested mobile technology applications to enhance and standardize the quality of health care by frontline rural health providers in low-resource settings. We developed a media-rich, mobile phone-based clinical guidance system for management of fevers, diarrhoeas and respiratory problems by rural health providers. Using a randomized control design, we field tested this application with 16 rural health providers and 128 patients at two rural/tribal sites in Tamil Nadu, Southern India. Protocol compliance for both groups, phone usability, acceptability and patient feedback for the experimental group were evaluated. Linear mixed-model analyses showed statistically significant improvements in protocol compliance in the experimental group. Usability and acceptability among patients and rural health providers were very high. Our results indicate that mobile phone-based, media-rich procedural guidance applications have significant potential for achieving consistently standardized quality of care by diverse frontline rural health providers, with patient acceptance.
Biological signaling networks comprise the chemical processes by which cells detect and respond to changes in their environment. Such networks have been implicated in the regulation of important cellular activities, including cellular reproduction, mobility, and death. Though technological and scientific advances have facilitated the rapid accumulation of information about signaling networks, utilizing these massive information resources has become infeasible except through computational methods and computer-based tools. To date, visualization and simulation tools have received significant emphasis. In this paper, we present a graph-theoretic formalization of biological signaling network models that are in wide but informal use, and formulate two problems on the graph: the Constrained Downstream and Minimum Knockout Problems. Solutions to these problems yield qualitative tools for generating hypotheses about the networks, which can then be experimentally tested in a laboratory setting. Using established graph algorithms, we provide a solution to the Constrained Downstream Problem. We also show that the Minimum Knockout Problem is NP-Hard, propose a heuristic, and assess its performance. In tests on the Epidermal Growth Factor Receptor (EGFR) network, we find that our heuristic reports the correct solution to the problem in seconds. Source code for the implementations of both solutions is available from the authors upon request.
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