We contribute to the literature on new mobilities by measuring spatial disparities in travel times for accessing essential non-work destinations via ridehailing. We focused on healthcare, restaurants, and grocery destinations in Chicago. Data from Chicago ridehailing providers, which included detailed information about all realized ridehailing trips in Chicago, were used to derive mean travel times by ridehailing for each census tract. Inspired by the gravity-based model, we calculated an inverse travel time index based on cumulative travel times for each census tract where ridehailing trips occurred. To understand the disparities in travel times, we compared the inverse travel time index for ridehailing and transit in the same census tracts. Then, we applied spatial autoregressive regression to examine the effects of various sociodemographic factors. The results suggested that the inverse travel time index was preferable in tracts with a higher household income and a lower percentage of minority populations. Also, disparities in travel times tended to be greater via ridehailing than transit. This study sheds light on disparities related to ridehailing and how we could improve access to essential destinations for underserved and underrepresented populations and communities. Policy implications include subsidizing disadvantaged users who lack reliable transportation options, regulating ridehailing prices, increasing the provision of essential destinations for underserved areas, and maintaining the quality of public transit services.