Factors affecting the rate of antibiotic prescription in dental practices

Hyesung Kim; Myeng Ki Kim; Hyungkil Choi

doi:10.11149/jkaoh.2017.41.1.28

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Kim, Kim, and Choi: Factors affecting the rate of antibiotic prescription in dental practices

Original Article

Journal of Korean Academy of Oral Health 2017; 41(1): 28-35.

Published online: 31 March 2017

DOI: https://doi.org/10.11149/jkaoh.2017.41.1.28

Factors affecting the rate of antibiotic prescription in dental practices

Hyesung Kim¹, Myeng Ki Kim², Hyungkil Choi³

¹Apple Tree Dental Hospital, Goyang, Korea.

²Department of Dental Services Management and Informatics, Graduate School of Dentistry, Seoul National University, Seoul, Korea.

³SMD Solution, Seoul, Korea.

Corresponding Author: Hyungkil Choi. SMD Solution, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea. Tel: +82-2-740-8795, Fax: +82-2-743-7633, niceov@gmail.com

Received 9 January 2017 Revised 26 January 2017 Accepted 26 January 2017

(open-access):

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objectives

Resistance to antibiotics is getting worse every day. Antibiotics are commonly prescribed medicines for the prevention and treatment of bacterial infections in dental clinics. Nationally, we are attempting to reduce the use of antibiotics, but this cannot be easily achieved. As a precedent study, we investigated factors affecting antibiotic prescription in dental clinics.

Methods

We analyzed electronic patient records of S dental hospital located in a big city. A total of 12,711 medical records were analyzed. The type of prescribed antibiotic, the prescription rate, and the number of prescription days were analyzed by chi-square test and t-test. Factors associated with the rate of antibiotic prescription were analyzed using logistic regression by dividing the independent variables into four groups: patient characteristics, dentist characteristics, treatment characteristics, and time characteristics.

Results

The rate of antibiotic prescription was 91.7% for the first implant surgery and 60.0% for minor operations including incision and drainage. The duration of antibiotic prescription differed according to the sex of the dentist and the type of treatment. The logistic regression analysis showed that the rate of antibiotic prescription was higher in male patients, in older patients, and in female dentists, and decreased with increasing age of the dentist. Compared with basic treatment, the odds ratio of first implant surgery was highest at 102.166 times, minor operation at 18.997, and extraction of impacted tooth at 14.429.

Conclusions

This is the first study to analyze the factors affecting prescription rate of antibiotics in dental clinics. We found that the antibiotic prescription rate was significantly different for each dental treatment. It was necessary to analyze the prescription rate of antibiotics according to the type of treatment. The fact that prescribing antibiotics differed according to dentist characteristics indicated that consistent guidelines need to be established and promoted.

Keywords: Antibiotics, Dentist, Duration, Factors, Rate

Figures and Tables

Fig. 1

Conceptual framework for the antibiotics prescription rate; bold letters mean selected variables for the regression analysis.

Fig. 2

Antibiotics prescription rate for each treatment (descending ordered by rate).

Table 1

Factors of cases, antibiotics, patient characteristics and dentist characteristics

Values of Patient Characteristics and Dentist Characteristics are unweighted values by removing multiple cases with same personnel.

Table 2

The difference in days of antibiotics prescription between the factors

^*Statistically significant (P<0.05).

Values are presented as average days±standard deviation.

Table 3

Distribution of the frequency of antibiotics prescription cases according to independent variables

^*Statistically significant (P<0.05).

Values are presented as frequencies (percentage of factor).

Table 4

Logistic regression of antibiotics prescription rate

^*Statistically significant (P<0.05).

Nagelkerke R square=0.398.

Variable(s) removed on step 2: Foreigner, on step 3: Dent_training, on step 4: Month.

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