Characterizing the availability of opportunities to residents has been a long-term aim in health care geographic investigation. It is important to measure the degree of inequity in health care accessibility and to identify underserved areas, due to the uneven distribu-tion of health care services. In this study, JavaScript was used to calculate travel time based on Amap, as this can provide a more reli-able data support to measure the health care accessibility in Xi'an communities, China. Based on the overall equity, herein, an attempt was made to quantify the equity of health care accessibility, and to identify health care underserved areas inside the different communit-ies. Results show that the accessibility to low-level health care services is high in the northern areas and low in the southern areas, while the accessibility to high-level and comprehensive health care services shows a clear core-periphery spatial structure. Moreover, the over-all equity of the health care accessibility is relatively low, and the inequity of high-level health care accessibility is further aggravated. Furthermore, the quantified equity of accessibility to high-level and comprehensive health care services in the central urban areas is bet-ter; however low-level health care services are relatively inadequate. There are significant differences among health care underserved areas, in particular, for the worst equity and the lowest accessibility areas (A1) and the worse equity and the lowest accessibility areas (B1) in high-level underserved areas. Notably, the sharing of health care services and the reasonable flow of health technical personnel among different levels of health institutions can make the high-level health care services in the central urban areas have a greater trickle effect on the surrounding areas.