English

Predicting Healthcare Provider Engagement in SMS Campaigns

Physics and Society 2025-11-25 v1 Artificial Intelligence Computers and Society Machine Learning Machine Learning

Abstract

As digital communication grows in importance when connecting with healthcare providers, traditional behavioral and content message features are imbued with renewed significance. If one is to meaningfully connect with them, it is crucial to understand what drives them to engage and respond. In this study, the authors analyzed several million text messages sent through the Impiricus platform to learn which factors influenced whether or not a doctor clicked on a link in a message. Several key insights came to light through the use of logistic regression, random forest, and neural network models, the details of which the authors discuss in this paper.

Keywords

Cite

@article{arxiv.2511.17658,
  title  = {Predicting Healthcare Provider Engagement in SMS Campaigns},
  author = {Daanish Aleem Qureshi and Rafay Chaudhary and Kok Seng Tan and Or Maoz and Scott Burian and Michael Gelber and Phillip Hoon Kang and Alan George Labouseur},
  journal= {arXiv preprint arXiv:2511.17658},
  year   = {2025}
}