[Skip to Navigation]
Sign In
Figure.  Segmented Linear Regression of the Rate of Antibiotic Prescriptions and Predicted Rate of Antibiotic Prescriptions With ARIMA Model
Segmented Linear Regression of the Rate of Antibiotic Prescriptions and Predicted Rate of Antibiotic Prescriptions With ARIMA Model

A, Segmented linear regression is shown. B, Autoregressive integrated moving average (ARIMA) model: (p, d, q) = (2, 0, 0); seasonal components, (p, d, q, s) = (1, 0, 0, 12). Vertical line indicates February 2006; dots, observed rates; solid line and curve, predicted rates; dashed line (A), trend of rates; dotted curves (B), 95% CIs of predicted rates.

Table.  Comparison of Antibiotic Prescription Rates for URTIs by Intervention
Comparison of Antibiotic Prescription Rates for URTIs by Intervention
1.
Kenealy  T, Arroll  B.  Antibiotics for the common cold and acute purulent rhinitis.  Cochrane Database Syst Rev. 2013;6:CD000247.PubMedGoogle Scholar
2.
Ranji  SR, Steinman  MA, Shojania  KG,  et al.  Closing the Quality Gap: A Critical Analysis of Quality Improvement Strategies.Vol 4. Rockville, MD: Agency for Healthcare Research and Quality; 2006.
3.
Cho  W, Lee  S, Kang  HY, Kang  M.  Setting national priorities for quality assessment of health care services in Korea.  Int J Qual Health Care. 2005;17(2):157-165.PubMedGoogle ScholarCrossref
4.
Werner  RM, Asch  DA.  The unintended consequences of publicly reporting quality information.  JAMA. 2005;293(10):1239-1244.PubMedGoogle ScholarCrossref
5.
Joong Ang Economy Research Institute.  A survey report of perception of disclosure of antibiotic prescription rate for acute upper respiratory infection [in Korean].http://www.mw.go.kr/front_new/al/sal0301vw.jsp?PAR_MENU_ID=04&MENU_ID=0403&CONT_SEQ=40112. Accessed December 11, 2013.
6.
Mangione-Smith  R, Elliott  MN, McDonald  L, McGlynn  EA.  An observational study of antibiotic prescribing behavior and the Hawthorne effect.  Health Serv Res. 2002;37(6):1603-1623.PubMedGoogle ScholarCrossref
1 Comment for this article
EXPAND ALL
potential confounders to be discussed
Young Min Kim | The Catholic University of Korea, Seoul St.Mary's Hospital
This article showed changes in antibiotic prescription rate after the disclosure by HIRA, and concluded that the changes were effectively induced by the disclosure. I'd like to point out potential confounders such as upcoding and retrenchment issues. During the research period, HIRA's program included not only public campaign but augmentation of cutting reimbursements to provider, which might also motivate physicians to \"up-code\" the diagnosis (such as bronchitis) for the claim, when antibiotic treatment is considered needed. Because this article depends on the claim data of HIRA in terms of diagnosis of URTI, this potential issues might as well be discussed.Because the upcoding and retrenchment issues are largely anecdotal (partly for limited data availability), it is arguable if these issues are sufficiently evidenced. But it seems rational to assume that the HIRA's strong program could shifted the coding pattern itself and discouraged physician from antibiotic prescription, as well to argue that the disclosure might influence physicians by observer effect.Additionally, It is true that medical services are provided mostly by private providers in South Korea. However, as this article indicates in the introduction, all of the providers-both public and private- are bound by mandatory and universal contract (not just coverage) to the National Health Insurance, which makes no providers authentically \"private\". The description \"private providers who might be motivated to maintain a good reputation for economic reasons.\" in the discussion of this article, accordingly, seems somewhat controversial.
CONFLICT OF INTEREST: None Reported
READ MORE
Research Letter
Health Care Reform
March 2015

Effect of Public Disclosure on Antibiotic Prescription Rate for Upper Respiratory Tract Infections

Author Affiliations
  • 1Health Promotion Center, Department of Family Medicine, Seoul National University Hospital, Seoul, Korea
  • 2Department of Social and Preventive Medicine, Inha University School of Medicine, Incheon, Korea
  • 3Department of Health Sciences and Technology, Samsung Advanced Institute of Health Science and Technology, Sungkyunkwan University, Seoul, Korea
  • 4Health Insurance Review & Assessment Service, Seoul, Korea
JAMA Intern Med. 2015;175(3):445-447. doi:10.1001/jamainternmed.2014.6569

Although antibiotics are not required for treating uncomplicated upper respiratory tract infection (URTI),1 which is mostly viral, they are often prescribed, fueling antibiotic resistance and loss of protective flora. Accordingly, many studies worldwide have tried to decrease inappropriate antibiotic prescribing behavior.2

In South Korea, where the National Health Insurance provides universal coverage, the Health Insurance Review & Assessment Service (HIRA) oversees claims reviews, quality assessment, and benefits and coverage standards. Since 2001, HIRA has used claims data to assess the appropriateness of care based on various quality indicators, including the antibiotic prescription rate for URTIs,3 and has used them for monitoring and giving feedback to physicians. Because it is a prerequisite that the public perceive low antibiotic prescription rates as good quality of care, starting in February 2006, HIRA began warning the public of the potential harms of antibiotic overuse through television and radio campaigns. In addition, HIRA has disclosed physicians’ antibiotic prescription rates to the general public via its website.

We evaluated the effect of such public disclosure using nationally representative data.

Methods

From the National Health Insurance claims data, a random sample of 3% of the adult population was selected (1 162 354 persons who were 20 years or older on December 31, 2002). The claims data of medical services, which include all prescriptions written from January 1, 2003, through December 31, 2010, were used.

From these data, we defined the cases of URTI based on the International Classification of Diseases, Tenth Revision (ICD-10) codes J00 through J06, and the antibiotics according to their Anatomical Therapeutic Chemical classification (J01 category).

To perform segmented regression, we totaled the visits each month and calculated the rate of antibiotic use. We performed segmented linear regression to compare the trend of antibiotic use before and after February 1, 2006. We analyzed the trend using the autoregressive integrated moving average model, which included the seasonal effect. We also compared the rates by intervention at 3 hospital levels: primary clinic, secondary care hospital, and tertiary care hospital. Analyses were conducted using STATA, version 13.1 (StataCorp).

Results

From the predefined cohort, 938 118 persons with URTI (80.7%) had visited a clinic at least once between January 1, 2003, and December 31, 2010. The number of visits was 11 665 529, and 95.7% of the visits were to primary clinics.

The rates of antibiotic prescriptions before and after public disclosure were 58.8% and 53.0%, respectively, and the decrease in rates by intervention were consistent regardless of the hospital level (Table).

Segmented linear regression showed that antibiotic prescription rates abruptly decreased by February 2006, and differences between actual rates and predicted rates persisted until the end of the follow-up period. Autoregressive integrated moving average models showed that all actual rates after the intervention were below the predicted values, and most rates were observed below the lower limits of the 95% CIs (Figure).

Discussion

Our data show that public disclosure was effective in lowering antibiotic use for URTIs. Based on the findings in a previous study4 on the effect of publicly disclosing quality improvement in other clinical areas, 2 primary mechanisms can be suggested: selection of high-quality providers by patients and provider response to report cards. A survey5 in 2007 found that 21.5% of health consumers were aware of the disclosure of antibiotic prescription rates and 40.3% of them had changed their health care provider. The survey also found that 95.0% of physicians were aware, and the abrupt change might be explained by observer effect.6

Our study should be interpreted within the context of South Korea’s medical care, in which medical services are provided mostly by private providers who might be motivated to maintain a good reputation for economic reasons. In addition, the preexisting National Health Insurance database for fee-for-service reimbursement makes individual medical institutions’ antibiotic prescription rate easily available and implementation of the program affordable.

Back to top
Article Information

Corresponding Author: Dong Wook Shin, MD, DrPH, MBA, Health Promotion Center, Department of Family Medicine Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 110-744, Korea (dwshin.snuh@gmail.com).

Published Online: December 15, 2014. doi:10.1001/jamainternmed.2014.6569.

Author Contributions: Drs Shin and Yun had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Yun, Shin, Hwang, B. L. Cho.

Acquisition, analysis, or interpretation of data: Yun, Shin, Hwang, J. Cho, Nam.

Drafting of the manuscript: All authors.

Critical revision of the manuscript for important intellectual content: Yun, Shin, J. Cho, Nam, B. L. Cho.

Statistical analysis: Yun, Hwang.

Obtained funding: B. L. Cho.

Administrative, technical, or material support: Kim.

Study supervision: Shin, J. Cho, Nam, B. L. Cho.

Conflict of Interest Disclosures: Dr Kim reports being affiliated with the Health Insurance Review & Assessment Service, but she did not participate in data collection and analysis. No other disclosures were reported.

Funding/Support: This research was supported by grant 800-20130091 from the Korea Centers for Disease Control and Prevention.

Role of the Funder/Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: Sang Hyuck Kim, MD, Yun Hee Chung, MD, Hyejin Lee, MD, MPH, and Eunmi Ahn, MD, MPH, Health Promotion Center, Department of Family Medicine, Seoul National 11 University Hospital, contributed to the critical revision of the manuscript. They were not financially compensated.

References
1.
Kenealy  T, Arroll  B.  Antibiotics for the common cold and acute purulent rhinitis.  Cochrane Database Syst Rev. 2013;6:CD000247.PubMedGoogle Scholar
2.
Ranji  SR, Steinman  MA, Shojania  KG,  et al.  Closing the Quality Gap: A Critical Analysis of Quality Improvement Strategies.Vol 4. Rockville, MD: Agency for Healthcare Research and Quality; 2006.
3.
Cho  W, Lee  S, Kang  HY, Kang  M.  Setting national priorities for quality assessment of health care services in Korea.  Int J Qual Health Care. 2005;17(2):157-165.PubMedGoogle ScholarCrossref
4.
Werner  RM, Asch  DA.  The unintended consequences of publicly reporting quality information.  JAMA. 2005;293(10):1239-1244.PubMedGoogle ScholarCrossref
5.
Joong Ang Economy Research Institute.  A survey report of perception of disclosure of antibiotic prescription rate for acute upper respiratory infection [in Korean].http://www.mw.go.kr/front_new/al/sal0301vw.jsp?PAR_MENU_ID=04&MENU_ID=0403&CONT_SEQ=40112. Accessed December 11, 2013.
6.
Mangione-Smith  R, Elliott  MN, McDonald  L, McGlynn  EA.  An observational study of antibiotic prescribing behavior and the Hawthorne effect.  Health Serv Res. 2002;37(6):1603-1623.PubMedGoogle ScholarCrossref
×