A mathematical framework of SMS reminder campaigns for pre- and post-diagnosis check-ups using socio-demographics: An in-silco investigation into breast cancer

Abstract

Timely pre- and post-diagnosis check-ups are critical for various diseases, in general, and for cancer , in particular, as these often lead to better outcomes. Several socio-demographic properties have been identified as strongly connected with both clinical dynamics and (indirectly) with different individual check-up behaviors. Unfortunately, existing check-up policies typically consider only the former association explicitly. In this work, we propose a novel computational framework, accompanied by a high-resolution computer simulation, to investigate and optimize socio-demographic-based Short Messaging Service (SMS) reminder campaigns for check-ups. We demonstrate our computational framework using extensive real-world data from the United States (US) population, focusing on breast cancer. Our results indicate that optimizing an SMS reminder campaign based solely on simple socio-demographic features can bring about a statistically significant reduction in mortality rate compared to alternative campaigns. These results indicate SMS reminder campaigns for pre- and post-diagnosis check-ups can be instrumental in improving healthcare outcomes. However, additional research is needed to bring about applicative tools.