This study investigates the quality of answers in health-related community-based question answering (HCQA) forums through a two-phase approach. Initially, machine learning was used to assess answer quality, validated against physician ratings. Subsequently, the effect of the first answer's quality on subsequent answers was analyzed using data from Yahoo! Answers Health section. Findings indicate that high-quality first answers positively influence subsequent answers, with a greater impact observed among experienced users and a reduced effect in forums with answer tips. The study proposes creating algorithmic solutions to measure answer quality and adjusting answer order to enhance overall forum quality.