Background: With the development of internet-assisted medical services, in the outpatient time slot-based online appointment system, patients’ late arrival has a negative impact on the output of medical services. Identifying the characteristics of late-arriving outpatients helps identify intervention strategies and management mechanisms against late arrival.Methods: In this study, the demographic information and appointment-based visit information of 29,337 patients in the Thoracic Surgery Clinic in 2019 were retrieved from the hospital information system of a Class A tertiary hospital in China, covering nine fields. After excluding those with missing information, valid data from 9,378 patients were obtained. The patients who were on time for visits constituted the control group. The SPSS 24.0 software was used to conduct statistical tests and regression analysis of patients with late arrival (P <0.05). Results: Univariate test showed that there were seven characteristics that affected patients’ late arrival, including gender, place of origin, visit type, weekday of visit, booking method, the level of specialist and visit time slot. Multivariate analysis showed a total of six combined characteristics: gender, age, visit type, weekday of visit, booking method and level of specialist. Patients had the highest rate of late arrival on Mondays, reaching 34.6%. Among the morning slots of the day, the rate of late arrivals during 08:30-09:00 was the highest, reaching 78.1%; and among the afternoon slots, the rate of late arrivals during 13:00-13:30 was the highest, reaching 65.7%. The group of late-arriving patients on Mondays were characterised by the time slot of visit, visit type and payment type, while the group of late-arriving patients in the two peak slots were characterised by booking method, payment type, weekday of visit and level of specialist.Conclusion: Patients who arrived later than the booked time slots are characterized by some features, such as being female, showing ‘morning-market’ feature and residing in a short distance. This study discussed the possible interventions for late arrival and the recommended strategies for making appointments based on the above characteristics.