Big data analysis of patients with periodontitis and factors influencing treatment behavior

To study patient-related information and factors altering their decision making in periodontal treatment and treatment behavior via big data analysis of the electronic medical records and to guide better dental care service and improve periodontal treatment.

A retrospective study was performed in patients with periodontitis who visited the Affiliated Stomatological Hospital of Tongji University from 2014 to 2016. Based on the periodontal sequence treatment procedure, the treatment types were divided into six groups and were analyzed using multivariable regression analysis. Chi-square test was performed according to gender and age.

Age, payment method, disease severity, exhibited statistically significant differences regarding their effects on patients’treatment behavior (P < 0.05). Men were more likely to have severe periodontitis than women (male 41.04%; female 31.85%), and use medical insurance more often as payment method (male 86.14%; female 83.74%) (P < 0.05). Compared with the population under 35 years old, moderate and severe periodontitis accounted for a larger proportion (84.58%) in the population over 35 years old. The compliance of the population over 35 years old was poor. Less follow - up reviews were conducted (17.10%) and medical insurance was less often used (49.65%) in this population. The differences were statistically significant (P < 0.05).

Moderate and severe periodontitis accounted for a larger proportion in the population over 35 years old. Patients over 35 years old tend to choose simpler treatments with lower compliance and frequency of revisits. This situation may be related to the lower proportion of medicare use in this population. The awareness and compliance of periodontal treatment protocols in people over 35 years old needs to be improved.