txt2MEDLINE provides access to high-quality medical evidence via text-messaging in settings with inadequate Internet access. We optimized the txt2MEDLINE search technique by parsing queries for MeSH (Medical Subject Heading) terms and searching MEDLINE for articles containing these terms in their titles or abstracts. We compared our results to the existing txt2MEDLINE tool by compiling benchmark queries from low-income and low-middle-income countries, and asking doctors and nurses with practice experience in low-resource areas to evaluate them. The median scores on a 5-point Likert scale were 2.9 for the existing txt2MEDLINE vs. 3.8 for the modified version (p=0.015). This reached our predefined criterion for clinical significance, a difference of 0.5 standard deviations. Improving this technology could improve clinical information resources in the world's most medically underserved communities.