Impact of National Policies Promoting Appropriate Antibiotic Use on Outpatient Prescriptions and Hospitalizations for Bacterial Complications of Acute Respiratory Infections in Japan: An Interrupted Time-Series Analysis.

Impact of National Policies Promoting Appropriate Antibiotic Use on Outpatient Prescriptions and Hospitalizations for Bacterial Complications of Acute Respiratory Infections in Japan: An Interrupted Time-Series Analysis - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice Open Forum Infect Dis . 2026 May 21;13(5):ofag312. doi: 10.1093/ofid/ofag312 Impact of National Policies Promoting Appropriate Antibiotic Use on Outpatient Prescriptions and Hospitalizations for Bacterial Complications of Acute Respiratory Infections in Japan: An Interrupted Time-Series Analysis Shungo Yamamoto 1, 2, 3, ✉, 2 , Michihiko Goto 4, 5 , Tatsuyoshi Ikenoue 6, 7 , Kazuaki Jindai 8 , Noriaki Kurita 9, 10 Author information Article notes Copyright and License information 1 Department of Transformative Protection to Infectious Disease, Graduate School of Medicine, The University of Osaka, Osaka, Japan 2 Department of Infection Control and Prevention, Graduate School of Medicine, The University of Osaka, Osaka, Japan 3 Center for Infectious Disease Education and Research (CiDER), The University of Osaka, Osaka, Japan 4 Division of Infectious Diseases, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA 5 Center for Access and Delivery Research and Evaluation (CADRE), Iowa City VA Health Care System, Iowa City, Iowa, USA 6 Department of Public Health, Miyazaki University School of Medicine, Miyazaki, Japan 7 Data Science and AI Innovation Research Promotion Center, Shiga University, Shiga, Japan 8 Department of Healthcare Epidemiology, Graduate School of Medicine, Kyoto University, Kyoto, Japan 9 Department of Preventive Medicine, Tokai University School of Medicine, Kanagawa, Japan 10 Department of Innovative Research and Education for Clinicians and Trainees (DiRECT), Fukushima Medical University Hospital, Fukushima, Japan ✉ Correspondence: Shungo Yamamoto, MD, DTM&H, DrPH, Department of Transformative Protection to Infectious Disease, Graduate School of Medicine, The University of Osaka, Osaka, 1-10, Yamadaoka, Suita City, Osaka 565-0871, Japan ( shungo1977@cider.osaka-u.ac.jp ). 2 Potential conflicts of interest. K.J. is CEO at CartaNova Inc. All other authors declare no conflicts of interest. Received 2026 Feb 26; Accepted 2026 May 13; Collection date 2026 May. © The Author(s) 2026. Published by Oxford University Press on behalf of Infectious Diseases Society of America. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com. PMC Copyright notice PMCID: PMC13221640  PMID: 42221371 Abstract Background National policies in Japan have promoted appropriate antibiotic use, but their safety across age groups remains unclear. We examined whether these policies were associated with changes in outpatient antibiotic prescriptions for nonbacterial acute respiratory infections (ARIs) and hospitalizations for bacterial complications of ARIs. Methods We conducted an interrupted time-series analysis using a Japanese administrative claims database from approximately 3 million enrollees in fiscal years 2016–2019. The interventions were publication of outpatient antimicrobial prescribing guidance in June 2017 and implementation of a pediatric financial incentive with package-insert revisions in April 2018. The primary outcome was the weekly hospitalization rate for bacterial infections potentially complicating ARIs. The secondary outcome was the proportion of outpatient antibiotic prescriptions among visits for nonbacterial ARIs. Results There was no evidence of an overall increase in hospitalizations for bacterial complications of ARIs after either intervention. For the secondary outcome, prescribing declined further after Intervention 1 (slope change, −0.06 percentage points/week; 95% confidence interval [CI], −0.12 to −.01). After Intervention 2, there was no significant level change (−0.09 percentage points; 95% CI, −1.55 to 1.37), but the slope increased by 0.07 percentage points/week (95% CI, .03 to .11), indicating attenuation of the downward trend. In age-stratified analyses, hospitalization rates remained stable in most groups, with an increase in those aged 6–18 years after Intervention 2. Conclusions Japan's national policies promoting appropriate antibiotic use were associated with reduced outpatient antibiotic prescribing for nonbacterial ARIs without an overall increase in hospitalizations for bacterial complications of ARIs. Keywords: acute respiratory infections, appropriate antibiotic prescribing, interrupted time-series analysis Japan's national policies promoting appropriate antibiotic use were associated with reduced outpatient antibiotic prescribing for nonbacterial acute respiratory infections, without an overall increase in hospitalizations for bacterial infections potentially complicating acute respiratory infections. Antimicrobial resistance (AMR) has evolved into a systemic threat that undermines modern medicine. The diminishing effectiveness of antibiotics jeopardizes not only infectious disease control but also the safety of surgery, chemotherapy, and intensive care [ 1 ]. Recognizing this escalating crisis, many governments, including Japan, have adopted policies to facilitate and incentivize antimicrobial stewardship and to reduce unnecessary antimicrobial use [ 2 ]. In April 2016, Japan launched the National Action Plan on AMR, which established a national framework for promoting appropriate antibiotic use and strengthening antimicrobial stewardship [ 2 ]. As part of this policy agenda, the Ministry of Health, Labour and Welfare (MHLW) of Japan published the guidance for appropriate antimicrobial prescribing in outpatient settings (1st edition; hereafter referred to as the MHLW prescribing guidance) in June 2017. The guidance discouraged antibiotic prescribing for self-limiting conditions, such as acute respiratory infections (ARIs) and acute diarrhea [ 3 ]. In April 2018, the MHLW introduced a financial incentive system, a reimbursement program specifically applied to outpatient visits for children under 3 years of age. This incentive rewarded pediatricians for refraining from prescribing antibiotics when not clinically indicated, thereby establishing a direct financial incentive to promote judicious antibiotic use [ 2 ]. Concurrently, the MHLW mandated revisions to the package inserts of antibiotics indicated for pharyngitis/laryngitis, tonsillitis, acute bronchitis, infectious enteritis, and sinusitis, instructing clinicians to refer to national guidelines before prescribing [ 4 ]. Empirical evidence validates the impact of these coordinated interventions. Sato et al demonstrated a marked decline in pediatric antibiotic prescriptions following the 2017 publication of the guidance [ 5 ]. Okubo et al showed that the reimbursement incentive both accelerated reductions in inappropriate prescriptions and maintained its effectiveness over multiple years [ 6 , 7 ]. Jindai et al reported a nationwide decrease in oral antibiotic use across all age groups after the combined implementation of financial and educational measures [ 8 ]. Collectively, these findings indicate that top–down, multilayered policies can successfully reshape prescribing behavior in Japan's healthcare system. However, the potential unintended consequences of reduced antibiotic use remain controversial. Some European reports described small increases in pneumonia and peritonsillar abscess following antimicrobial stewardship efforts [ 9 , 10 ]. In Japan, pediatric studies have not detected increases in hospitalizations or after-hours consultations after the introduction of incentives [ 6 ]. Whether this favorable safety profile extends to adults and older adults has not been established. Given the consistent decline in oral antibiotic consumption across all age strata [ 8 ], Japan's experience in implementing nationwide guidance and financial incentives can provide insights into whether these nationwide policy interventions could lead to unintended consequences, such as increases in bacterial infections. This study addresses this question by analyzing a large, commercially available administrative claims database (DeSC) encompassing fiscal years 2016–2019 [ 11 ]. Using an interrupted time-series design, we quantified the relationships among policy interventions, antibiotic prescribing patterns, and hospitalizations for bacterial infections. The objective of this analysis was to clarify whether bacterial infection-related hospitalizations increased at the national level concomitant with reduced antibiotic exposure. METHODS Study Design, Data Source, and Study Population We conducted an interrupted time-series analysis (ITSA) using data from the DeSC administrative claims database (DeSC Inc., Tokyo, Japan). This database includes anonymized medical and pharmacy claims for approximately 3 million individuals enrolled in multiple public health insurance schemes in Japan. The age and sex distributions are broadly comparable to national population estimates, although adults aged 65–74 years are relatively overrepresented [ 11 ]. The DeSC dataset contains patient demographics, diagnoses coded using the International Classification of Diseases, 10th Revision (ICD-10), prescriptions, procedures, and hospital admissions. Because all data were fully deidentified, the study was exempt from review by the Institutional Ethics Committee. The study population consisted of individuals enrolled in the DeSC database in fiscal year 2016 (baseline enrollees) and their dependents. As the DeSC database expanded over time, changes in population structure associated with database expansion could influence outcome trends independent of policy changes. To address this issue, we defined a fixed baseline cohort of fiscal year 2016 enrollees who formed a closed cohort during follow-up. Dependents of these baseline enrollees, primarily spouses and children, including children newly born and recorded during follow-up, were allowed to enter the study population over time. This design was intended to preserve representation of younger age groups while limiting additional heterogeneity in healthcare utilization patterns by restricting new entrants to dependents of baseline enrollees. We constructed weekly time-series for each predefined outcome, aggregated across the study population. The observation period spanned fiscal years 2016 through 2019 (April 2016–March 2020), providing sufficient baseline and postintervention data for the ITSA. Interventions Two national interventions were implemented during the observational period to promote appropriate antibiotic use. The first was the publication of the MHLW prescribing guidance in June 2017, which discouraged antibiotic prescribing for self-limiting illnesses, such as ARIs and acute diarrhea [ 3 ]. The guidance provides evidence-based outpatient recommendations for common conditions in which antimicrobials are often prescribed unnecessarily despite limited indications for antibiotic therapy. It includes syndrome-based clinical algorithms, checklists, and educational materials for patients and families that support symptomatic management, appropriate follow-up, and avoidance of antibiotics for viral illnesses, such as acute upper respiratory infections. The second intervention, implemented on 1 April 2018, was a pediatric financial incentive for appropriate antibiotic use. In this program, eligible pediatric outpatient facilities could claim an additional reward of 800 Japanese Yen (approximately US$7) per patient per month when clinicians refrained from prescribing antibiotics and provided caregiver guidance for children younger than 3 years of age diagnosed with ARI, acute otitis media, acute sinusitis, or acute diarrhea [ 7 ]. Simultaneously, the MHLW directed revisions to the package inserts for oral antibiotics indicated for pharyngitis/laryngitis, tonsillitis, acute bronchitis, infectious enteritis, and sinusitis, instructing prescribers to consult the MHLW prescribing guidance before use [ 4 ]. Outcome Measures The primary outcome was the weekly hospital admission rate for bacterial infections potentially complicating ARIs, expressed per 100 000 person-weeks. To capture new admissions for acute bacterial infections, we required the diagnosis start date to coincide with the hospitalization date. The ICD-10 code set was adapted from previous studies and expanded to include pneumonia diagnoses relevant to severe bacterial outcomes ( Supplementary Table 1 ). The exact rate calculation and interrupted time-series model specifications are provided in Supplementary Methods 1 . The secondary outcome was the weekly proportion of outpatient oral antibiotic prescriptions among visits for nonbacterial ARIs. ARI visit diagnoses were classified using a previously published consensus-based claims classification that distinguishes diagnosis categories in which antibiotic use is considered appropriate (eg, specific streptococcal pharyngitis/tonsillitis) from those for which it is not (eg, common cold and viral pharyngitis), based on combinations of ICD-10 codes and specific Japanese claims diagnosis codes ( Supplementary Table 2 ) [ 12 ]. In this framework, appropriateness was defined at the diagnosis-code level for use in administrative claims analyses and should be interpreted as indicating that antibiotic use cannot be considered inappropriate at the claims level, rather than that antibiotic therapy is definitively indicated for every individual episode. For the secondary outcome, nonbacterial ARIs were defined as antibiotic-inappropriate ARI visits. The denominator was the number of outpatient visits for nonbacterial ARIs each week, and the numerator was the number of visits in which an oral systemic antibacterial agent was prescribed on the same day ( Supplementary Table 3 ). Visits for patients who were hospitalized on the same calendar day were excluded from both the denominator and numerator ( Supplementary eMethods 2 ). To benchmark policy-unrelated trends, urinary tract infection (UTI), which was not targeted by the specific interventions evaluated in this study, was used as a nonequivalent dependent variable (NEDV) for both analyses [ 13 ]. For the hospitalization analysis, we calculated the weekly UTI admission rate per 100 000 person-weeks. For the prescribing analysis, we calculated the weekly proportion of oral antibiotic prescriptions during outpatient UTI visits. UTI-related codes for both measures are listed in Supplementary Table 4 [ 14 ]. UTI was used in parallel analyses and visual comparison rather than as a comparator in a formal controlled interrupted time-series model, because respiratory infections and UTIs were not expected to share the same seasonal and temporal patterns. Statistical Analysis We used ITSA to evaluate policy effects [ 15 ]. For both the primary and secondary outcomes, we modeled a slope change after Intervention 1 (guideline publication) and both level and slope changes after Intervention 2 (pediatric incentive and package-insert revision). Because dissemination of the guidance to frontline clinicians required time, and survey data from September 2020 in 3000 randomly selected community-based medical clinics suggested delayed uptake, Intervention 1 was modeled as a change in trend without an immediate level change [ 16 ]. We fitted segmented regressions that included a continuous time variable (weeks), indicators for each intervention, and time-by-intervention interaction terms to estimate postintervention shifts in level and slope. We assessed first-order autocorrelation using the Durbin–Watson statistic and the estimated AR(1) parameter (rho). To account for serial correlation, we fitted Prais–Winsten AR(1) regression with robust inference [ 17 ] and controlled seasonality by including Fourier terms [ 18 ]. We conducted analyses overall and within predefined age strata (<3, 3–5, 6–18, 19–64, and ≥65 years). We performed 2 post hoc exploratory analyses to aid the interpretation of the main findings. First, we assessed whether antibiotic prescribing increased for diagnoses in which antibiotic therapy is considered appropriate to evaluate whether reductions in inappropriate prescribing could be explained by diagnostic upcoding from nonbacterial ARIs to antibiotic-appropriate conditions ( Supplementary Table 2 ). Second, after observing an age-specific increase in hospital admissions for bacterial infections in the primary analysis, we examined the diagnostic categories contributing to this change. Hospital admissions were decomposed into prespecified diagnostic categories, and segmented regression models were reestimated for each category. Two-sided P -values <.05 were considered statistically significant. All analyses were performed using Stata, version 17.0 (StataCorp, College Station, Texas, USA). RESULTS Study Population The baseline study population included 3 888 149 unique registrants in fiscal year 2016, representing approximately 3% of Japan's population ( Table 1 ). During follow-up, the population size decreased, and the age distribution shifted toward older adults. The proportion of individuals aged ≥65 years increased from 42.0% in fiscal year 2016% to 50.3% in fiscal year 2019. Table 1. Unique Registrants by Fiscal Year Fiscal Year 2016 2017 2018 2019 Total unique registrants, no. 3 888 149 3 550 665 3 308 214 3 105 799 Female, no. (%) 2 020 266 (52.0) 1 848 318 (52.1) 1 732 102 (52.4) 1 633 242 (52.6) Age category, no. (%) … … … … <3 53 323 (1.4) 42 212 (1.2) 34 642 (1.0) 29 556 (1.0) 3–5 61 448 (1.6) 51 835 (1.5) 45 280 (1.4) 38 779 (1.2) 6–18 306 517 (7.9) 271 187 (7.6) 246 297 (7.4) 225 719 (7.3) 19–64 1 834 315 (47.2) 1 562 356 (44.0) 1 385 244 (41.9) 1 247 994 (40.2) ≥65 1 632 546 (42.0) 1 623 075 (45.7) 1 596 751 (48.3) 1 563 751 (50.3) Open in a new tab Fiscal year in Japan = April 1–March 31. “Unique” denotes deduplicated individuals by ID within each fiscal year (the same person may appear in multiple years). Percentages are column percentages; due to rounding, they may not sum to 100%. Primary Outcome: Hospitalizations for Bacterial Infections In the overall study population, segmented regression estimates showed no evidence of an increase in hospitalization rates for bacterial infections potentially complicating ARIs after either intervention. The slope change after Intervention 1 was not significant (−0.05 per 100 000 person-weeks per week; 95% CI, −.14 to .04; P = .31). After Intervention 2, neither the level change (1.17 per 100 000 person-weeks; 95% CI, −1.23 to 3.56; P = .34) nor the slope change (−0.01 per 100 000 person-weeks per week; 95% CI, −.07 to .05; P = .70) was significant ( Table 2 and Figure 1 ). The estimated AR(1) parameter was small (rho = −0.13), and the Durbin–Watson statistic after transformation was close to 2 (2.01), indicating minimal residual first-order autocorrelation. In age-stratified analyses, hospitalization rates remained stable across age groups, except for an increase in the 6–18-year-old group after Intervention 2. UTI admissions exhibited time-varying changes during the study period ( Supplementary Table 5 and Figure 1 ). Table 2. Hospitalization Rates for Bacterial Infections Potentially Complicating Acute Respiratory Infections (Weekly Admissions/100 000) Interrupted Time-Series Segmented Regression Coefficients—estimates (95% CI), P -values Postintervention Weekly Slope (95% CI, P -value) Baseline trend Postintervention 1 trend change Postintervention 2 level change Postintervention 2 trend change Constant Postintervention 1 Postintervention 2 Age category β 1 β 2 β 3 β 4 β 0 β 1 + β 2 β 1 + β 2 + β 4 All 0.05 (0.01, 0.09), 0.02 −0.05 (−0.14, 0.04), 0.31 1.17 (−1.23, 3.56), 0.34 −0.01 (−0.07, 0.05), 0.70 27.0 (25.4, 28.6), <0.001 0.00 (−0.06, 0.06), 0.90 −0.01 (−0.03, 0.01), 0.48 <3 −0.08 (−0.19, 0.02), 0.13 0.11 (−0.13, 0.34), 0.37 −1.99 (−8.38, 4.40), 0.54 −0.08 (−0.24, 0.09), 0.35 30.8 (26.6, 35.0), <0.001 0.02 (−0.13, 0.18), 0.77 −0.05 (−0.11, 0.01), 0.08 3–5 −0.14 (−0.20, −0.08), <0.001 0.13 (−0.00, 0.26), 0.05 2.56 (−0.99, 6.12), 0.16 −0.03 (−0.12, 0.06), 0.45 19.4 (17.0, 21.7), <0.001 −0.01 (−0.10, 0.07), 0.75 −0.05 (−0.08, −0.01), 0.005 6–18 −0.04 (−0.06, −0.02), 0.001 −0.02 (−0.07, 0.03), 0.37 1.76 (0.49, 3.03), 0.01 0.05 (0.02, 0.08), 0.004 5.71 (4.84, 6.58), <0.001 −0.06 (−0.09, −0.03), <0.001 −0.01 (−0.02, 0.00), 0.12 19–64 −0.00 (−0.01, 0.01), 0.68 −0.01 (−0.02, 0.01), 0.52 0.08 (−0.38, 0.54), 0.72 0.01 (−0.00, 0.02), 0.15 4.25 (3.95, 4.55), <0.001 −0.01 (−0.02, 0.00), 0.22 0.00 (−0.00, 0.01), 0.47 ≥65 0.05 (−0.03, 0.14), 0.22 −0.10 (−0.28, 0.08), 0.28 2.11 (−2.79, 7.02), 0.40 −0.01 (−0.14, 0.12), 0.86 58.8 (55.5, 62.1), <0.001 −0.05 (−0.17, 0.07), 0.44 −0.06 (−0.11, −0.01), 0.01 Open in a new tab ARI, acute respiratory infection. β 1 , β 2 , β 4 : per 100 000 per week; β 3 , β 0 : per 100 000. Figure 1. Open in a new tab Weekly hospitalizations for bacterial infections potentially complicating acute respiratory infections and urinary tract infections, by age group. Observed (points) and model-predicted (lines) weekly admissions per 100 000 person-weeks are shown for bacterial infection potentially complicating acute respiratory infections (filled circles, solid line) and urinary tract infections (open circles, dashed line) from fiscal year 2016 to 2019 (April 2016–March 2020). Vertical dashed lines indicate the June 2017 stewardship guideline publication (Intervention 1) and the April 2018 pediatric incentive with package-insert revisions (Intervention 2). Abbreviations: BI, bacterial infections potentially complicating acute respiratory infections; UTI, urinary tract infection. Secondary Outcome: Antibiotic Prescribing for Nonbacterial ARIs Segmented regression estimates showed that the weekly proportion of oral antibiotic prescriptions among outpatient visits for nonbacterial ARIs declined after Intervention 1, with a significant slope change of −0.06 percentage points per week (95% CI, −.12 to −.01; P = .03). After Intervention 2, there was no significant level change (−0.09 percentage points; 95% CI, −1.55 to 1.37; P = .91), whereas the slope change was 0.07 percentage points per week (95% CI, .03 to .11; P = .001), indicating attenuation of the downward trend ( Table 3 and Figure 2 ). Model-based estimates suggested that the predicted prescribing proportion decreased from approximately 52% at baseline to about 40% by the end of follow-up. In age-stratified analyses, the decline after Intervention 1 was evident in the 3–5−, 6–18−, and 19–64-year groups, whereas the group aged ≥65 years did not show a clear change. Among children aged <3 years, an immediate decrease was observed after Intervention 2. In contrast, the downward trend attenuated after Intervention 2 in those aged 3–64 years for nonbacterial ARIs. The weekly proportion of oral antibiotic prescriptions among UTI visits showed an increasing trend after Intervention 2 ( Supplementary Table 6 and Figure 2 ). Table 3. Weekly Proportion of Antibiotic Prescriptions for Nonbacterial Acute Respiratory Infections (Percentage Points) Interrupted Time-Series Segmented Regression Coefficients—estimates (95% CI), P -values Postintervention Weekly Slope (95% CI, P -value) Baseline trend Postintervention 1 trend change Postintervention 2 level change Postintervention 2 trend change Constant Postintervention 1 Postintervention 2 Age category β 1 β 2 β 3 β 4 β 0 β 1 + β 2 β 1 + β 2 + β 4 All −0.05 (−0.08, −0.03), <0.001 −0.06 (−0.12, −0.01), 0.03 −0.09 (−1.55, 1.37), 0.91 0.07 (0.03, 0.11), 0.001 51.8 (50.8, 52.8), <0.001 −0.11 (−0.15, −0.08), <0.001 −0.05 (−0.06, −0.03), <0.001 <3 −0.07 (−0.09, −0.05), <0.001 −0.02 (−0.07, 0.02), 0.30 −2.51 (−3.70, −1.31), <0.001 0.06 (0.03, 0.10), <0.001 37.1 (36.3, 37.9), <0.001 −0.10 (−0.13, −0.07), <0.001 −0.03 (−0.04, −0.02), <0.001 3–5 −0.10 (−0.12, −0.07), <0.001 −0.06 (−0.12, −0.01), 0.03 −1.19 (−2.66, 0.28), 0.11 0.11 (0.07, 0.15), <0.001 50.9 (49.9, 51.9), <0.001 −0.16 (−0.19, −0.12), <0.001 −0.05 (−0.06, −0.04), <0.001 6–18 −0.07 (−0.11, −0.02), 0.003 −0.11 (−0.21, −0.02), 0.02 0.52 (−1.88, 2.92), 0.67 0.13 (0.06, 0.19), <0.001 57.9 (56.1, 59.6), <0.001 −0.18 (−0.24, −0.12), <0.001 −0.05 (−0.08, −0.03), <0.001 19–64 −0.04 (−0.07, −0.00), 0.03 −0.10 (−0.17, −0.03), 0.004 1.00 (−0.77, 2.77), 0.27 0.09 (0.04, 0.14), <0.001 60.4 (59.1, 61.7), <0.001 −0.14 (−0.18, −0.09), <0.001 −0.05 (−0.06, −0.03), <0.001 ≥65 −0.03 (−0.07, 0.00), 0.08 −0.04 (−0.12, 0.04), 0.31 −0.26 (−2.23, 1.70), 0.79 0.03 (−0.03, 0.09), 0.28 45.4 (43.9, 46.9), <0.001 −0.08 (−0.13, −0.02), 0.005 −0.04 (−0.07, −0.02), <0.001 Open in a new tab β 1 , β 2 , β 4 : percentage points per week; β 3 , β 0 : percentage points. Figure 2. Open in a new tab Weekly proportion of outpatient antibiotic prescriptions among visits for nonbacterial acute respiratory infections and urinary tract infections, by age group. Observed (points) and model-predicted (lines) weekly proportions are shown for nonbacterial acute respiratory infections (filled circles, solid line) and urinary tract infections (open circles, dashed line) from fiscal year 2016 to 2019 (April 2016–March 2020). Vertical dashed lines indicate the June 2017 stewardship guideline publication (Intervention 1) and the April 2018 pediatric incentive with package-insert revisions (Intervention 2). Abbreviations: NBARI, nonbacterial acute respiratory infections; UTI, urinary tract infection. Additional Analyses In additional analyses conducted to aid interpretation, we examined trends in antibiotic prescriptions for antibiotic-appropriate diagnoses and decomposing hospitalizations for bacterial infections by diagnostic category. The number of prescriptions for these diagnoses did not increase during the study period and showed an overall downward trend ( Supplementary Table 7 and Supplementary Figure 1 ). We also examined diagnostic categories contributing to the age-specific increase in hospitalizations for bacterial infections observed among individuals aged 6–18 years after Intervention 2. This increase was driven by pneumonia-related admissions, particularly those coded as Mycoplasma pneumoniae , rather than a broad increase across bacterial infection categories ( Supplementary Tables 8 and 9 and Supplementary Figure 2 ). DISCUSSION This ITSA using a large administrative claims database evaluated the association between Japan's national antimicrobial stewardship policies, hospitalizations for bacterial infections, and outpatient antibiotic prescribing for nonbacterial ARIs. Overall, we found no increase in hospitalizations for bacterial infections after either intervention. Antibiotic prescribing for nonbacterial ARIs declined after the first intervention; however, the overall downward trend attenuated after the second intervention. An increase in bacterial infection hospitalizations was observed only among individuals aged 6–18 years after the second intervention. Antibiotic prescribing for nonbacterial ARIs was already declining before Intervention 1. This indicates that the observed effects of the national guidance were superimposed on an existing secular decline rather than initiating a new prescribing trajectory. Awareness of appropriate antibiotic use may already have been increasing in Japan, potentially in relation to the national AMR Action Plan introduced in 2016. Nevertheless, the policy interventions evaluated in this study were the publication of the prescribing guidance and the subsequent pediatric financial incentive. Accordingly, the ITSA was designed to assess whether these interventions changed the slope of an already declining trend. The postintervention 2 increase observed among adolescents warrants careful interpretation. Diagnostic decomposition analyses indicated that this increase was driven by pneumonia-related admissions; particularly those attributed to M. pneumoniae , and included both immediate and sustained components. Importantly, antibiotic prescribing in this age group did not decline after Intervention 2. Given the pediatric focus of the policy, the increase observed among adolescents is more consistent with contemporaneous epidemiological dynamics than with reduced antibiotic exposure attributable to the national policies. This interpretation is further supported by Japan's national sentinel surveillance data. Publicly available Infectious Diseases Weekly Report data from the Japan Institute for Health Security for M. pneumoniae showed a broadly similar epidemic curve during the study period ( Supplementary Figure 2 ) [ 19 ]. One plausible contributor to the attenuation of the overall decline in antibiotic prescribing after Intervention 2 is population aging within the closed cohort of baseline enrollees. Findings from subgroup analyses and the NEDV comparator support this interpretation. Although Intervention 2 primarily targeted children aged <3 years, prescribing for nonbacterial ARIs shifted upward after the intervention, not only in this target group but also across most nontarget age groups, particularly among individuals aged 3–64 years. This pattern suggests that the observed changes were driven by cohort-wide influences rather than effects specific to the pediatric incentive [ 13 ]. Consistent with this explanation, the NEDV analysis demonstrated an increase in antibiotic prescribing for UTIs following Intervention 2, despite UTIs not being targeted by the pediatric incentive. As the proportion of older adults increased over time within the baseline enrollment population, population aging may have elevated background demand for clinically appropriate antibiotic use, thereby partially offsetting reductions in antibiotic prescribing for ARIs during follow-up. These findings should be interpreted in the context of historically high antibiotic prescribing for upper respiratory tract infections in Japan. Claims-based studies from the mid-2000s and early 2010s reported that approximately 50%–60% of outpatient visits for upper respiratory tract infections resulted in antibiotic prescriptions, particularly in primary care settings [ 20 , 21 ]. Given that most ARIs are viral and self-limiting these studies indicate a substantial reservoir of unnecessary antibiotic use [ 22 ]. In this context, the reductions observed in the present study are most plausibly interpreted as decreases in low-value prescribing rather than reductions in clinically indicated treatments [ 23 ]. Our findings are also consistent with prior evidence on the safety of efforts to reduce unnecessary antibiotic prescribing. In UK primary care, reductions in antibiotic prescribing were associated with modest increases in pneumonia and peritonsillar abscess, but not in deep or invasive infections, suggesting that reductions in unnecessary prescribing may be achieved with minimal safety tradeoffs [ 9 ]. Swedish primary care data similarly showed only minor increases in peritonsillar abscess [ 10 ]. In China, a nationwide stewardship campaign produced marked reductions in antibiotic use in primary care and incorporated both reward-based mechanisms and punitive administrative measures, including compulsory prescribing restrictions and audit procedures linked to institutional accountability [ 24 ]. In the United States, multimodal stewardship interventions combining clinician education, audit and feedback, peer comparison, and electronic dashboards have improved prescribing quality across large urgent care networks [ 25 ]. In contrast, Japan's approach relies primarily on positive financial incentives without punitive enforcement, and pediatric evaluations of these incentives have demonstrated sustained reductions in antibiotic use without increases in hospitalizations or after-hours visits [ 6 ]. Extending prior pediatric evidence, our findings support the safety of Japan's national policies promoting appropriate antibiotic use, showing reduced outpatient antibiotic prescribing for nonbacterial ARIs without increased hospitalizations for bacterial infections potentially complicating ARIs. STRENGTHS AND LIMITATIONS This study has several strengths. First, we used a large administrative claims database with broad demographic coverage, enabling evaluation of Japan's national policies promoting appropriate antibiotic use across multiple age groups [ 11 ]. Second, the interrupted time-series design with segmented regression leveraged weekly data over several years and incorporated adjustments for seasonality and serial correlation, allowing estimation of both level and slope changes associated with each intervention [ 15 , 17 , 18 ]. Third, we used UTI as an NEDV comparator to benchmark policy-unrelated background trends and aid interpretation of postintervention changes [ 13 ]. Fourth, prescribing trends for antibiotic-appropriate diagnoses did not increase, which is inconsistent with diagnostic upcoding as the primary explanation for reduced prescribing for nonbacterial ARIs. Finally, age-stratified and diagnosis-decomposition analyses improved the interpretability of subgroup findings, including the increase observed among individuals aged 6–18 years. This study also has several limitations. First, claims data lack microbiological confirmation and detailed clinical severity information, making diagnostic misclassification possible. Accordingly, the diagnosis-based appropriateness classification may not fully reflect the need for antibiotics in every individual episode, because some categories classified as appropriate, such as acute sinusitis, may include cases in which antibiotic treatment is not required. Second, because outcomes were assessed using weekly aggregated measures across the study population, the analysis was not designed to link individual ARI episodes with antibiotic exposure and subsequent hospitalization. Accordingly, the findings should be interpreted as signals from aggregated time-series rather than patient-level causal effects. Third, because we relied on administrative claims data, we could not directly assess changes in documentation practices or medical record quality after the introduction of the pediatric financial incentive. Fourth, the fixed baseline cohort design reduced temporal confounding related to database expansion, but it also allowed the study population to age during follow-up. Because the ITSA was performed on weekly aggregated outcomes rather than individual-level observations, we could not directly adjust the primary models for age in years. Although we conducted prespecified age-stratified analyses, this approach may not have fully captured progressive aging of the cohort over time, and some residual confounding related to changes in age composition may have remained, particularly after Intervention 2. Fifth, unmeasured time-varying factors may have influenced observed trends. Although we adjusted for seasonality, alternative explanations cannot be excluded. Sixth, the observation period ended before the COVID-19 pandemic, and patterns of respiratory infections and healthcare utilization in later years may differ. Seventh, although the age and sex distributions in the DeSC database are broadly comparable to those of the overall Japanese population, adults aged 65–74 years are more prevalent, which may limit generalizability. CONCLUSION Japan's national policies promoting appropriate antibiotic use were associated with reduced outpatient antibiotic prescribing for nonbacterial ARIs compared with the preintervention period, without evidence of increased hospitalizations for bacterial infections potentially complicating ARIs. These findings support the safety of these policies and highlight the importance of continued monitoring to sustain appropriate antibiotic use. Supplementary Material ofag312_Supplementary_Data ofag312_supplementary_data.docx (642.3KB, docx) Notes Acknowledgments. We thank DeSC Inc. for providing access to anonymized data. This study was conducted as part of “The Nippon Foundation of The University of Osaka Project for Infectious Disease Prevention.” We would like to thank Editage ( www.editage.jp ) for English language editing. Author Contributions. All authors conceived and designed the study. S.Y. managed the database and performed the data analysis. All authors confirmed the validity of the data analysis and interpreted the data. S.Y. drafted the study. All authors critically revised and approved the final version of the manuscript. All authors have read and agreed to the published version of the manuscript. Generative AI and AI-assisted technologies in the writing process . During the preparation of this work, the authors used ChatGPT (GPT-5.2, OpenAI) to enhance readability, proofread the English text, and assist in writing the STATA code. After using this tool, the authors reviewed and edited the content as necessary and take full responsibility for the content of the publication. Data availability statement. The datasets generated and/or analyzed during the current study are not publicly available because of the restrictions imposed by DeSC Healthcare Inc. (Tokyo, Japan; https://desc-hc.co.jp/company ), but are available from the corresponding author upon reasonable request. Financial support. This work was supported by Japan Society for the Promotion of Science (JSPS) KAKENHI (grant number JP23K14710). Contributor Information Shungo Yamamoto, Department of Transformative Protection to Infectious Disease, Graduate School of Medicine, The University of Osaka, Osaka, Japan; Department of Infection Control and Prevention, Graduate School of Medicine, The University of Osaka, Osaka, Japan; Center for Infectious Disease Education and Research (CiDER), The University of Osaka, Osaka, Japan. Michihiko Goto, Division of Infectious Diseases, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA; Center for Access and Delivery Research and Evaluation (CADRE), Iowa City VA Health Care System, Iowa City, Iowa, USA. Tatsuyoshi Ikenoue, Department of Public Health, Miyazaki University School of Medicine, Miyazaki, Japan; Data Science and AI Innovation Research Promotion Center, Shiga University, Shiga, Japan. Kazuaki Jindai, Department of Healthcare Epidemiology, Graduate School of Medicine, Kyoto University, Kyoto, Japan. Noriaki Kurita, Department of Preventive Medicine, Tokai University School of Medicine, Kanagawa, Japan; Department of Innovative Research and Education for Clinicians and Trainees (DiRECT), Fukushima Medical University Hospital, Fukushima, Japan. Supplementary Data Supplementary materials are available at Open Forum Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author. References 1. O'Neill  J. Tackling a global health crisis: initial steps. Available at: https://amr-review.org/sites/default/files/Report-52.15.pdf . Accessed 31, January 2026. 2. Jindai  K, Kusama  Y, Gu  Y, Honda  H, Ohmagari  N. 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