Full length article| Volume 93, P175-181, April 01, 2020

# Accelerating reductions in antimicrobial resistance: Evaluating the effectiveness of an intervention program implemented by an infectious disease consultant

Open AccessPublished:January 31, 2020

## Highlights

• A concerted infection control intervention program by an infectious disease consultant was evaluated.
• A quasi-experimental study was conducted to detect accelerated rates of increases in drug susceptibility following the intervention.
• The decreasing rates of resistance for MRSA and drug-resistant P. aeruginosa were accelerated following the intervention.
• The rate of MRSA decrease increased by 50%–150% of its original value.
• The intervention program by an infectious disease consultant successfully reduced the drug-resistant bacterial infections.

## Abstract

### Objectives

Very few infectious disease physicians exist in Japan. A concerted infection control intervention program involving an antimicrobial stewardship team and multiple components was designed and implemented in multiple hospitals from 2010. Here, we aimed to retrospectively evaluate the intervention program’s effectiveness.

### Methods

The frequencies of methicillin resistant Staphylococcus aureus (MRSA) and drug-resistant Pseudomonas aeruginosa were monitored in four acute-care hospitals. The primary goal of the program was to accelerate the speed of decline of such resistance. A quasi-experimental study design was used to detect accelerated rates of increases in drug susceptibility, comparing time before and after the intervention.

### Results

Both MRSA and drug-resistant P. aeruginosa exhibited decreasing trends (p < 0.01 for all four hospitals and all bacterial cultures). Compared with the whole of Japan, the decreasing trends for MRSA and drug-resistant P. aeruginosa in the four hospitals accelerated after the intervention program was established; notably, the rate of MRSA decrease increased by 50%–150% of its original value.

### Conclusions

The intervention program successfully reduced the proportion of drug resistance in the four hospitals. Centering on systematic education, decision-making support, and implementation and oversight by an infectious disease consultant, this program was shown to be effective where specialist physicians are scarce.

## Introduction

The spread of drug-resistant bacteria is considered a global public health problem. According to the World Health Organization (
• World Health Organization
WHO’s first global report on antibiotic resistance reveals serious, worldwide threat to public health.
), it is anticipated that around 10 million people could die from infections with drug-resistant bacteria by 2050. In Japan, in addition to drug-resistant Gram-positive cocci such as methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci, healthcare-associated infections caused by drug-resistant Gram-negative bacilli, including multidrug-resistant Pseudomonas aeruginosa (MDRP) and multidrug-resistant Acinetobacter still remain major problems in medical institutions (
• Ministry of Health, Labor and Welfare
National action plan on antimicrobial resistance (AMR) 2016-2020.
,
• Muraki Y.
• Kitamura M.
• Maeda Y.
• Kitahara T.
• Mori T.
• Ikeue H.
• et al.
Nationwide surveillance of antimicrobial consumption and resistance to Pseudomonas aeruginosa isolates at 203 Japanese hospitals in 2010.
). Japan aims to reduce antibiotics use by 2020 as part of its countermeasures against antimicrobial resistance, and also aims to meet pre-set targets for reducing MRSA and carbapenem-resistant P. aeruginosa in the general population (
• Ministry of Health, Labor and Welfare
National action plan on antimicrobial resistance (AMR) 2016-2020.
).
The time-dependent epidemiological dynamics of drug-resistant bacteria have been monitored by the Japan Nosocomial Infection Surveillance system (JANIS) (
• Ministry of Health, Labor and Welfare
Japan nosocomial infections surveillance, ministry of health, labour and welfare.
). Assisting its sustainability, national insurance has started to financially cover the medical treatment costs of infection control since 1996, and the government has expanded its coverage since 2012 (
• Ministry of Health, Labor and Welfare
National action plan on antimicrobial resistance (AMR) 2016-2020.
) and intensified its associated interventions across the country. As a result, MRSA and drug-resistant P. aeruginosa percentages have gradually slowed down across the whole country (Figure 1) with an obvious decreasing trend.
In Japan, it is recommended that a few infectious disease specialists should work on a full-time basis at medical institutions with over 300 beds (
• The Japanese Association for Infectious Diseases
On the desired expertise and required number of infectious disease physicians.
). However, there are few infectious disease specialists to act as the central players for properly directing the use of antimicrobial agents. As of 2019, there are approximately 1,500 facilities with at least 300 beds (indicating that a total of 3000–4000 infectious disease specialists are required (
• The Japanese Association for Infectious Diseases
On the desired expertise and required number of infectious disease physicians.
), while the number of accredited persons is 1491 (1.2 per 100,000/ population)). Even with specialist qualifications, only about a half of the accredited physicians are considered to be actively serving as infectious disease doctors (less than 0.6 per 100,000 persons) (
• Gomi H.
Current status of clinical infectious diseases education: what is needed for effective education in infectious diseases in a global era?.
). In the United States, there were 9102 people (2.8 per 100,000/ population) who were qualified infectious disease specialists in 2018 (
• American Board of Internal Medicine
Number of candidates certified.
). Very few clinical infectious disease specialists have been engaged in promoting the proper use of antibiotics to reduce drug-resistant bacterial numbers in Japan.
Given the resource-limited situation in Japan, the first author of this study has acted as an infectious disease physician while working in multiple hospitals as a consultant and directing countermeasures against the spread of drug-resistant bacteria in geographic areas where there are scarce numbers of infectious disease specialists. As an intervention approach, a concerted program (dictated as a bundle approach), which included delivering expert clinical infectious disease education, case consultation, and support of the antimicrobial stewardship team (AST), was adopted. Usually, three to five bundles are combined, making the plan an attractive and effective tool for reducing healthcare-associated infections. One of the key representative studies on such a bundle is the so-called “Keystone Project” in which a reduction in catheter-related bloodstream infections was achieved (
• Pronovost P.
• Needham D.
• Berenholtz S.
• Sinopoli D.
• Chu H.
• Cosgrove S.
• et al.
An intervention to decrease catheter-related bloodstream infections in the ICU.
). Other published studies have applied similar bundle approaches to reducing surgical-site infections (
• Haynes A.B.
• Weiser T.G.
• Berry W.R.
• Lipsitz S.R.
• Breizat A.H.
• Dellinger E.P.
• et al.
A surgical safety checklist to reduce morbidity and mortality in a global population.
), where checklists were employed to assess compliance with each preventive component (
• Haynes A.B.
• Weiser T.G.
• Berry W.R.
• Lipsitz S.R.
• Breizat A.H.
• Dellinger E.P.
• et al.
A surgical safety checklist to reduce morbidity and mortality in a global population.
,
• Gawande A.
The checklist manifesto: how to get things right.
). Moreover, a multi-faceted program with similarity to the bundle approach successfully reduced catheter-related urinary tract infections in the USA (
• Saint S.
• Greene M.T.
• Krein S.L.
• Rogers M.A.
• Ratz D.
• Fowler K.E.
• et al.
A program to prevent catheter-associated urinary tract infection in acute care.
). In addition to the technical aspects of reducing drug-resistant bacteria, the role of behavioral and cultural changes (e.g. precautionary social adaptation factors) in improving the overall quality of medical services and antimicrobial resistance has also been discussed (
• Saint S.
• Howell J.D.
• Krein S.L.
Implementation science: how to jump-start infection prevention.
).
Although the Japanese intervention was not originally accompanied by research, a retrospective observational study assisted by quasi-experimental design could help to elucidate the causal impact of the program on the reduction of drug-resistant bacteria. Therefore, the aim of the present study was to evaluate the risk of drug-resistant bacteria in multiple consulted hospitals via the original programmed approaches.

## Methods

### Overview of the intervention program

The present study rests on retrospectively evaluating the existing intervention program that was adopted as part of the first author’s consultation work at four different hospitals (Appendix Table 1). All hospitals were within commutable distance by car or local aircraft from the office of the first author in Sapporo city, the capital city of the northern most Japanese prefecture, Hokkaido. The hospitals were engaged in acute care service and contributed to the maintenance of community medical care. The hospitals are numbered as follows: hospitals 1–3 undertook the program from 2014 to 2017, whereas hospital 4 received the consultation service from 2010 to 2013. All four hospitals possess independent laboratories for microbiological examination, and three of the four (except for hospital 4) are designated teaching hospitals in Japan.
The evidence-based intervention programs were designed along the lines of published studies (
• Resar R.
• Pronovost P.
• Simmonds T.
• Rainey T.
• Nolan T.
Using a bundle approach to improve ventilator care processes and reduce ventilator-associated pneumonia.
,
• Resar R.
• Griffin F.A.
• Nolan T.W.
Using care bundles to improve health care quality. IHI innovation series white paper.
,
• Pronovost P.
• Needham D.
• Berenholtz S.
• Sinopoli D.
• Chu H.
• Cosgrove S.
• et al.
An intervention to decrease catheter-related bloodstream infections in the ICU.
,
• Haynes A.B.
• Weiser T.G.
• Berry W.R.
• Lipsitz S.R.
• Breizat A.H.
• Dellinger E.P.
• et al.
A surgical safety checklist to reduce morbidity and mortality in a global population.
,
• Gawande A.
The checklist manifesto: how to get things right.
,
• Saint S.
• Greene M.T.
• Krein S.L.
• Rogers M.A.
• Ratz D.
• Fowler K.E.
• et al.
A program to prevent catheter-associated urinary tract infection in acute care.
,
• Saint S.
• Howell J.D.
• Krein S.L.
Implementation science: how to jump-start infection prevention.
), including how the antimicrobial stewardship team, the infection control team, and the regular meetings among team members were organized (Appendix Table 2). As an important component of the program, it is well known that continuously studying clinical infectious diseases is an effective way to ensure the proper use of antibiotics (
• Roque F.
• Herdeiro M.T.
• Soares S.
• Teixeira Rodrigues A.
• Breitenfeld L.
• Figueiras A.
Educational interventions to improve prescription and dispensing of antibiotics: a systematic review.
,
• Kozman D.
• Schuttner L.
• Chunda L.
• Tymchuk C.
Educational intervention to improve antibiotic knowledge at Kamuzu Central Hospital, Malawi.
,
• Barlam T.F.
• Cosgrove S.E.
• Abbo L.M.
• MacDougall C.
• Schuetz A.N.
• Septimus E.J.
• et al.
Implementing an antibiotic stewardship program: guidelines by the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America.
) and we developed and implemented a series of nearly 50 lectures offered on a weekly basis. Consultations by infectious disease physicians are known to reduce mortality from S. aureus-related bacteremia and fatalities from antimicrobial-resistant bacteria (
• Burnham J.P.
• Olsen M.A.
• Stwalley D.
• Kwon J.H.
• Babcock H.M.
• Kollef M.H.
Infectious diseases consultation reduces 30-day and 1-year all-cause mortality for multidrug-resistant organism infections.
,
• Bai A.D.
• Showler A.
• Burry L.
• Steinberg M.
• Ricciuto D.R.
• Fernandes T.
• et al.
Impact of infectious disease consultation on quality of care, mortality, and length of stay in Staphylococcus aureus bacteremia: results from a large multicenter cohort study.
,
• Waters C.D.
• Caraccio J.
Rate of positive cultures necessitating definitive treatment in patients receiving empiric vancomycin therapy.
), including one that integrated AST and infectious disease consultation (
• Musgrove M.A.
• Kenney R.M.
• Kendall R.E.
• Peters M.
• Tibbetts R.
• Samuel L.
• et al.
Microbiology comment nudge improves pneumonia prescribing.
). Accordingly, we offered infectious disease consultations for acute care and hospitalized patients. Moreover, quick and accurate reporting of microbial test results is essential for ensuring that antibiotics are used appropriately, and antibiograms are useful in this respect (
• Bruins M.J.
• Ruijs G.J.H.M.
• Wolfhagen M.J.
• Bloembergen P.
• Aarts J.E.
• et al.
Does electronic clinical microbiology results reporting influence medical decision making: a pre- and post-interview study of medical specialists.
,
• Cunney R.J.
• Smyth E.G.
The impact of laboratory reporting practice on antibiotic utilisation.
,
• Gannon C.K.
Responsible reporting in microbiology. Improving quality of care through better communication.
,
• Forsblom E.
• Ruotsalainen E.
• Ollgren J.
• Järvinen A.
Telephone consultation cannot replace bedside infectious disease consultation in the management of Staphylococcus aureus bacteremia.
,
• Roe N.
• Wang M.
• Wisniewski S.J.
• Douce R.
How automatic notification of infectious disease specialists impacted the management of Staphylococcus aureus bacteremia in a community hospital setting.
); thus, we supported development of antibiograms. Moreover, because the geographic area in this report lacks a substantial number of expert infectious disease physicians, we aggressively promoted the use of a regular emailing system from healthcare workers to the physician consultant for reporting purposes, as well as the use of telephone-based consultations (
• Forsblom E.
• Ruotsalainen E.
• Ollgren J.
• Järvinen A.
Telephone consultation cannot replace bedside infectious disease consultation in the management of Staphylococcus aureus bacteremia.
,
• Roe N.
• Wang M.
• Wisniewski S.J.
• Douce R.
How automatic notification of infectious disease specialists impacted the management of Staphylococcus aureus bacteremia in a community hospital setting.
). The five primary components and three additional subcomponents used in the program are summarized in Appendix Table 2.

### Program implementations

The primary goal of the program was to accelerate the speed of decline in the frequency of drug-resistant S. aureus and P. aeruginosa in the general population of Japan. These organisms were selected because MRSA and carbapenem-resistant P. aeruginosa are on the list of target goals for reducing antimicrobial-resistant bacteria in Japan (
• Ministry of Health, Labor and Welfare
National action plan on antimicrobial resistance (AMR) 2016-2020.
). Moreover, they are the most frequently acquired bacteria in healthcare settings that can be strongly influenced by having medical experts present in these settings. Each hospital undertook all components of the program, but their interventions were flexibly designed according to the local situation. In addition to the systematically designed subprograms, positive blood cultures were reported by email, clinical consultations on such cases were conducted, and equally importantly, the self-learning process for a specific infectious disease (e.g., a disease that was causing outbreaks in hospitals) was supported among the infection control team and others. Except for hospital 4, which did not possess an electronic medical records system and thus could not write the medical record using fixed-form sentences, all four hospitals pursued the recommended five-action program.
Regular continuous education opportunities were adopted in each hospital. Both systematic (unidirectional) lectures and small group discussion sessions were held. Such sessions were regularly scheduled each month. With a strong stress on the appropriate use of antibiotics, about 50 lectures were designed and delivered, each lasting from 60 to 90 min with an active learning format as well as lecture-style sessions (Appendix Table 3). The primary audiences included physicians, clinical residents, pharmacists, nurses, and laboratory technicians.

### Outcomes and data collection

Our primary outcome was to observe the antibiotic susceptibility rates for S. aureus and P. aeruginosa. Susceptibility data were collected from each hospital before and during the intervention period (i.e., 2009–13 and 2014–17) for hospitals 1–3, and 2006–9 and 2010–13 for hospital 4. As a control group, we also extracted the corresponding data from JANIS, which covers identical data from the whole of Japan. With our 4 hospitals and JANIS alike, the susceptibility data were recorded as the sum of all relevant test results from both outpatient and inpatient services regardless of characteristics such as infection status, colonization status, or carrier status, and irrespective of the clinical site of infection. Our expectations were that the effect of our intervention program would be reflected as an accelerated increase in the antibiotic susceptibility rate. Thus, compared with JANIS and prior to any interventions in the four hospitals, we hypothesized that any susceptibility rate increases would also accelerate during the intervention period.

### Statistical analysis

We examined the time course of the S. aureus and P. aeruginosa susceptibility rates to each antibiotic agent in two steps. In the first step, we examined whether a decreasing trend existed by employing a trend analysis technique. Specifically, we employed the Cochrane-Armitage trend test to detect statistically significant trends in antibiotic sensitivity in the total number of samples. In addition to these samples, we also investigated susceptibility rate trends in the blood culture data.
In the second step, we employed the difference-in-differences (DiD) design approach, a quasi-experimental study design, to detect accelerated increases in antibiotic susceptibility rates. Two different time periods, that is, before and after introducing the abovementioned intervention program, were compared. Before the program, we assumed that the decreasing rate of antibiotic resistance was proportional to that for the whole of Japan, as seen in the JANIS data. However, in introducing the program, we anticipated that the decreasing rate of resistance would be accelerated. We used h = 1,…, 4 to index hospitals and t = 2003,…, 2017 to indicate the year. The term $Yhtk$ represents the outcome (i.e., the rate of susceptibility) against the susceptibility rate from JANIS (k = 1 and k is 0 otherwise) in year t. We used the expected value of the susceptibility rate calculated as
$EYhtk=α0+α1t−t0+βt−tvThkPt+γThk,$
(1)

to predict the susceptibility rate in a hospital and also for JANIS, where α0 and α1 describe the susceptibility rate for JANIS (i.e. the control group) that is assumed to share the same trend in parallel with our subject hospitals prior to the intervention programs, and where t0 is the first year of our analysis (i.e., t0 = 2009 for hospitals 1–3 and 2006 for hospital 4), β is the causal effect of the intervention program, tv is the first year when the program starts to reduce the susceptibility rate (i.e., tv = 2014 for hospitals 1–3 and 2010 for hospital 4) and γ is the group effect on the hospital h. $Thk$ and Pt are dichotomous dummy variables, where $Thk$ = 1 for the four hospitals, 0 is for JANIS and Pt = 1 is for t ≥ tv and 0 otherwise. JANIS data were assumed not to have changed after tv, because time tv was only special for four hospitals. Because the susceptibility rate comes from the binomial sampling process, we used the binomial distribution as the likelihood for describing the expected susceptibility rate as described by equation (1) and performed the maximum-likelihood estimation. The 95% confidence intervals (CI) for the parameters were computed by the profile likelihood method. A p-value less than 0.05 was considered as statistically significant. All statistical data were analyzed using JMP version 14.0.0 statistical software (SAS Institute Inc., Cary, NC, USA).

### Ethical considerations

We retrospectively analyzed the following two different pieces of data: (i) datasets from hospitals under the intervention program and (ii) JANIS data for the whole of Japan. For dataset (i), we retrospectively analyzed the data routinely collected by the hospitals. The numbers of drug-resistant bacteria detected and the corresponding resistance rates were regularly reported and published by each hospital as part of the infection control practice. Similarly, the numbers of drug-resistant bacteria detected in blood cultures and the corresponding resistance rates for S. aureus and P. aeruginosa were reported as annual data by the hospital’s infection control committees. These datasets were fully anonymized in advance of our analysis, and the datasets were reported publicly. For (ii), the similarly collected and publicly available time series data for the susceptibility rates were obtained from the JANIS website (
• Ministry of Health, Labor and Welfare
Japan nosocomial infections surveillance, ministry of health, labour and welfare.
). Again, the datasets used in our study were de-identified and fully anonymized in advance. Accordingly, we did not require patient consent. The Medical Ethics Committee of Hokkaido University Graduate School of Medicine (Japan) reviewed and approved the present study (ID: D19-032).

## Results

Many secondary and tertiary care hospitals including those consulted by the authors (Figure 1A) have implemented interventions associated with insurance coverage of infection control. For this reason, even before starting the authors’ intervention programs, the obvious downward trend has been observed (Figure 1B). The Cochrane-Armitage trend test was performed on the proportion of MRSA identified in this study and the resistance rate of P. aeruginosa to one of four antibiotics (Table 1). The frequency of MRSA decreased over time in all four hospitals. A similar trend was seen for P. aeruginosa (15 significant results out of 16 items in Table 1). Among the severe fraction of cases where blood culturing was required, MRSA was shown to have decreased in three of the four hospitals, but although P. aeruginosa resistance to at least one of four antibiotics also decreased in the three hospitals, in only one hospital was the trend significant.
Table 1Trend in MRSA and the resistance rate to one of four antibiotics in Pseudomonas aeruginosa (rate of change per year).
Antibiotic typeHospital 1Hospital 2Hospital 3Hospital 4
Staphylococcus aureus
All cultures

MRSA
−0.053 (p < 0.01)−0.078 (p < 0.01)−0.052 (p < 0.01)−0.029 (p < 0.01)
Blood cultures

MRSA
−0.059 (p = 0.02)−0.047 (p = 0.04)−0.082 (p = 0.04)−0.044 (p = 0.35)
Pseudomonas aeruginosa
All cultures

Carbapenems
−0.046 (p < 0.01)−0.025 (p < 0.01)−0.035 (p = 0.03)−0.023 (p = 0.06)
All cultures

4th generation cephalosporins
−0.027 (p < 0.01)−0.021 (p < 0.01)−0.055 (p < 0.01)−0.072 (p < 0.01)
All cultures

3rd generation cephalosporins
−0.018 (p < 0.01)−0.018 (p < 0.01)−0.085 (p < 0.01)−0.026 (p = 0.01)
All cultures

Quinolones
−0.034 (p < 0.01)−0.017 (p < 0.01)−0.09 (p < 0.01)−0.038 (p = 0.02)
Blood cultures

Drug-resistant Pseudomonas
−0.058 (p = 0.20)−0.018 (p = 0.34)−0.306 (p = 0.19)-------- (p = 0.23)
Cochrane-Armitage trend test was employed to analyze the percentage of MRSA and antibiotic-resistant P. aeruginosa. The results are classified as non-blood cultures and blood cultures. The rate of change per year and p-value in parenthesis are shown. Drug-resistant Pseudomonas obtained from blood culture samples was defined as resistant to at least one carbapenem, cephalosporin or quinolone. In Hospital 4, the number of resistant P. aeruginosa blood culture submissions was small, making the rate of change not calculable.
Employing DiD as a quasi-experimental study design, we compared the time trend of the proportion of MRSA out of all S. aureus between the intervention hospitals and Japan as a whole, as informed by JANIS (Figure 2). Assuming that the decreasing trend was shared between the four hospitals and Japan in its entirety prior to the intervention program, the DiD model indicates that the decreasing MRSA rate had accelerated since initiating the intervention program. All four hospitals show downward acceleration trends, and three of the four showed significant acceleration with the 95% CIs from the accelerated rate not containing a zero value. For instance, the rate of decrease in hospital 1 prior to the intervention program was 1.42% per year, and this decrease accelerated by an additional 1.50% per year in and after 2014.
Table 2 summarizes the estimated decrease and acceleration rates for MRSA and drug-resistant P. aeruginosa at the different hospitals based on the DiD model. Positive acceleration rates indicate that the decreasing trend intensified. For all the resistance types, the rate of decrease before the intervention program was positive; thus, a decreasing trend was evident. The decrease accelerated in the four hospitals. Considering that all expected values were positive, the rate of change was pointing towards the accelerating direction. For instance, regarding the four different antibiotics used for P. aeruginosa infections in the four hospitals, 13 out of 16 items revealed a notable acceleration via the intervention program.
Table 2Estimated rates of decline and acceleration for MRSA and drug-resistant Pseudomonas aeruginosa using the difference-in-differences design model.
Control period (before intervention) [percent decline/year]Intervention period (increment only) [percent decline/year]
AntibioticsHospitalsHospitals
12341234
Staphylococcus aureus
MRSA1.42 (1.40, 1.45)1.42 (1.40, 1.45)1.42 (1.40, 1.45)1.77 (1.72, 1.82)1.50 (1.12, 1.87)2.06 (1.73, 2.38)0.76 (0.18, 1.35)0.74 (−1.59, 0.12)
Pseudomonas aeruginosa
Carbapenems0.55 (0.52, 0.59)0.55 (0.52, 0.59)0.55 (0.52, 0.58)1.09 (1.03, 1.15)2.01 (1.49, 2.52)0.53 (0.05, 1.01)0.18 (−1.13, 0.81)1.04 (−2.37, 0.30)
4th generation cephalosporins1.06 (1.03, 1.09)0.70 (0.67, 0.73)1.09 (1.05, 1.12)0.74 (0.69, 0.80)0.55 (0.07, 1.01)0.74 (0.40, 1.06)1.77 (0.16, 3.31)3.76 (2.30, 5.15)
3rd generation cephalosporins0.57 (0.54, 0.59)0.57 (0.54, 0.59)0.57 (0.54, 0.60)0.39 (0.34, 0.44)0.49 (0.09, 0.87)0.74 (0.35, 1.11)3.53 (2.67, 4.31)1.37 (0.24, 2.45)
Quinolones1.09 (1.06, 1.12)1.09 (1.06, 1.12)1.09 (1.06, 1.12)0.65 (0.59, 0.71)2.19 (1.64, 2.73)0.19 (−0.55, 0.19)1.90 (0.87, 2.90)1.79 (0.08, 3.49)
Acceleration rate for the resistance rate decline, which is considered to have been induced by the intervention program, was estimated employing a quasi-experimental study design. The percentage decrease rate per year is shown. In the absence of the intervention program, the entire country data from the JANIS system was assumed as parallel to the baseline rate of decline in all four hospitals. During the intervention period, the increment in the rate of decline (i.e. accelerated rate of decline) was estimated. Bold indicates significant results. The 95% confidence intervals are shown in parentheses.

## Discussion

We explored the time-dependent patterns of MRSA and drug-resistant P. aeruginosa in four intervention hospitals in Hokkaido where an infectious disease specialist was engaged in systematic education on clinical infectious diseases and supported the clinical decision-making including interpretation of the microbiological test results for each patient and the appropriate use of antibiotics. Employing a trend test and a quasi-experimental study design, we have shown that (i) both MRSA and drug-resistant P. aeruginosa exhibited decreasing trends in their frequencies over time, (ii) compared with Japan as a whole (the control), the decreasing trends in MRSA and drug-resistant P. aeruginosa in the four hospitals accelerated after the intervention program was implemented, and (iii) the rate of decrease in MRSA increased by 50%–150% of its original value. To the best of our knowledge, this study is the first to demonstrate that the proportion of drug-resistant S. aureus and P. aeruginosa tested in healthcare settings could be successfully reduced by an intervention program instituted by an infectious disease specialist. Of note, blood culture positive MRSA was also reduced by the program.
Importantly, we have shown that an accelerated decrease in the proportion of drug resistant bacteria occurred in the intervention program using the quasi-experimental DiD design. So long as the parallel trend assumption before the intervention is intact, the rates of reduction in MRSA and drug-resistance in P. aeruginosa were determined to have been accelerated. It is remarkable that the aggressive series of intervention programs have contributed to reducing the drug-resistance rate of S. aureus and P. aeruginosa. Although each single item in the intervention program is small and subtle, the programmed structure is known to be effective as a bundle and would act as an independent intervention plan because it was in practice since 2000 (
• Resar R.
• Pronovost P.
• Simmonds T.
• Rainey T.
• Nolan T.
Using a bundle approach to improve ventilator care processes and reduce ventilator-associated pneumonia.
,
• Resar R.
• Griffin F.A.
• Nolan T.W.
Using care bundles to improve health care quality. IHI innovation series white paper.
). Compared with Western countries (e.g. the USA (
• American Board of Internal Medicine
Number of candidates certified.
)), very few such specialists are available who can professionally direct the appropriate use of antibiotics in Japan (
• The Japanese Association for Infectious Diseases
On the desired expertise and required number of infectious disease physicians.
). Because antimicrobial-resistant bacteria are considered a global health threat, the present study indicates how a small number of infectious disease specialists can be effectively used in Japan, especially in human-resource limited settings such as ours in Hokkaido.
The intervention program consisted of two important activities: education and clinical decision making support. The reasoning behind this was that a common understanding of the proper use of antimicrobial drugs and the systematic education and leadership of infectious disease specialists would be essential components of the program. Continued study opportunities ensured that the participants could share best practice and common sense measures for reducing drug-resistant bacterial infections. Of note, because participating staff members had acquired pertinent educational skills through these sessions, they became equipped with the tools required for future leadership roles. In addition to the acquisition of appropriate knowledge about the program, it was a critical necessity for the infectious disease specialist to support decision making so that behavioral changes occurred among the medical experts including physicians, pharmacists and nursing practitioners. In fact, the importance of behavioral and cultural changes in improving medical quality has been emphasized elsewhere (Saint, 2010). For instance, physicians sometimes say “I know about de-escalation, but is it safe to switch to a narrow-spectrum antimicrobial drug?” or “I am not sure if my interpretation of the bacterial culture results is valid.” While it may be ideal for infectious disease specialists to directly respond to all such consultations, this is not achievable where infectious disease experts are scarce. We believe that the intervention program described herein involving periodic visits of the expert should bring about more effective antimicrobial stewardship in population-decreasing countries.
To interpret the time course of drug-resistant bacteria, it is vital to pay attention to other important events. In our case study, the breakpoint for carbapenem was revised in 2014 following CLSI2012 guidelines, and this change coincided with the first year of this intervention (Figure 1). In fact, carbapenem sensitivity in P. aeruginosa was aggravated in 2014 as revealed by the JANIS data. We must emphasize, however, that the revisions covered all of Japan, and our control was JANIS, which substantially reflected the revisions in its own trend.
Three technical limitations require discussion. First, our surveillance of antimicrobial-resistant bacteria encountered a number of technical problems. Notably, the datasets do not separate inpatient from outpatient samples, making it difficult to identify where any selection pressure took place. Moreover, the body part sampled was not classified and multiple samples (e.g. before and after antibiotic treatment) were sometimes taken from the same patient. Thus, we were only able to judge the overall trend in a casual manner. Second, the JANIS data that we used is the largest surveillance dataset in Japan, but it represents the results of sampling; particularly the sampled healthcare facilities representing acute-care hospitals (n = 2261 hospitals participating from January 2019). Third, the DiD design could potentially eliminate confounding factors in interpreting the time trends, but the causal impact may have been better explored using individual-based data rather than time-series data.
In Japan, 2020 has been set as the year to achieve the target goal of controlling antimicrobial-resistant bacteria and specific reduction targets that include MRSA, and carbapenem-resistant P. aeruginosa have been specified. As a method of accelerating the rate of decrease, a regular intervention program by an infectious disease specialist, centered on systematic education and decision-making support can act as a strong option for steadily accelerating a decreasing rate for the proportion of drug-resistant bacteria.

## Potential conflicts of interest

The first author (NK) is the Chief Executive Office of a private medical consultant company, offering services as infectious disease consultant to and receiving remunerations from all four hospitals that were the study subjects and are anonymized.

## Funding

HN received funding support from the Japan Agency for Medical Research and Development ( JP18fk0108050 ), the Japan Science and Technology Agency (JST) CREST program ( JPMJCR1413 ), the Inamori Foundation , and the Japan Society for the Promotion of Science ( JSPS ) KAKENHI ( 17H04701 , 17H05808 , 18H04895 and 19H01074 ). The funders played no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

## Acknowledgement

We thank Sandra Cheesman, PhD, from Edanz Group (www.edanzediting.com/ac) for editing a draft of this manuscript.

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