Objective There is an abundance of health-related information online, and millions of consumers search for such information. Spell checking is of crucial importance in returning pertinent results, so we propose a technique for increasing the effectiveness of spell-checking tools used for health-related information retrieval.

Design A sample of incorrectly-spelled medical terms was submitted to two different spell checking tool, and the resulting suggestions, derived under two different dictionary configurations, were re-sorted according to how frequently each term appeared in log data from a medical search engine.

Measurements Univariable analysis was carried out to assess the effect of each factor (spell checking tool, dictionary type, re-sort or no re-sort) on the probability of success. The factors that were statistically significant in the univariable analysis were then used in multivariable analysis to evaluate the independent effect of each of the factors.

Results The re-sorted suggestions proved to be significantly more accurate than the original list returned by the spell-checking tool. The odds of finding the correct suggestion in the number one rank were increased by 63% after re-sorting using our method. This effect was independent of both the dictionary and the spell checking tool that were used.

Conclusion Using knowledge about the frequency of a given word's occurrence in the medical domain can significantly improve spelling correction for medical queries.