Abstract
Background
The goals of the National Action Plan on Antimicrobial Resistance (AMR) of Japan include “implementing appropriate infection prevention and control” and “appropriate use of antimicrobials,” which are relevant to healthcare facilities. Specifically, linking efforts between existing infection control teams and antimicrobial stewardship programs was suggested to be important. Previous studies reported that human resources, such as full-time equivalents of infection control practitioners, were related to improvements in antimicrobial stewardship.
Methods
We posted questionnaires to all teaching hospitals (n = 1017) regarding hospital countermeasures against AMR and infections. To evaluate changes over time, surveys were conducted twice (1st survey: Nov 2016, 2nd survey: Feb 2018). A latent transition analysis (LTA) was performed to identify latent statuses, which refer to underlying subgroups of hospitals, and effects of the number of members in infection control teams per bed on being in the better statuses.
Results
The number of valid responses was 678 (response rate, 66.7%) for the 1st survey and 559 (55.0%) for the 2nd survey. More than 99% of participating hospitals had infection control teams, with differences in activity among hospitals. Roughly 70% had their own intervention criteria for antibiotics therapies, whereas only about 60 and 50% had criteria established for the use of anti-methicillin-resistant Staphylococcus aureus antibiotics and broad-spectrum antibiotics, respectively. Only 50 and 40% of hospitals conducted surveillance of catheter-associated urinary tract infections and ventilator-associated pneumonia, respectively. Less than 50% of hospitals used maximal barrier precautions for central line catheter insertion.
The LTA identified five latent statuses. The membership probability of the most favorable status in the 2nd study period was slightly increased from the 1st study period (23.6 to 25.3%). However, the increase in the least favorable status was higher (26.3 to 31.8%). Results of the LTA did not support a relationship between increasing the number of infection control practitioners per bed, which is reportedly related to improvements in antimicrobial stewardship, and being in more favorable latent statuses.
Conclusions
Our results suggest the need for more comprehensive antimicrobial stewardship programs and increased surveillance activities for healthcare-associated infections to improve antimicrobial stewardship and infection control in hospitals.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12879-021-05921-2.
Keywords: Antimicrobial resistance, Antimicrobial stewardship, Healthcare-associated infection, Infection control, Surveillance
Introduction
The World Health Assembly adopted the Global Action Plan on Antimicrobial Resistance (AMR) in May 2015 [1]. In Japan, the National Action Plan on Antimicrobial Resistance was adopted in April 2016 and included two goals [2], “implementing appropriate infection prevention and control” and “appropriate use of antimicrobials.” These goals are of particular relevance to healthcare facilities in terms of preventing the spread of antimicrobial-resistant organisms. Specifically, at the field level, linking efforts between existing infection control team (ICT) and antimicrobial stewardship (AMS) programs was suggested to be important [2].
Previous studies reported that human resources (expressed as full-time equivalents (FTEs) of infection control practitioners) and FTE-to-bed ratios were related to improvements in AMS [3–5]. However, the definition of improvement varied from study to study. For example, one study used an increase in the number of implemented AMS programs [3] to evaluate the performance of AMS, while another study examined the effectiveness of each program [4].
The purpose of the present study was two-fold: to report the results of nationwide multicenter questionnaire surveys on countermeasures against AMR and infections in Japanese teaching hospitals, and to identify latent statuses, which might imply underlying subgroups of hospitals with similar achievement levels of AMS, and examine the effects of FTE-to-bed ratios of ICT members on the latent statuses.
Methods
We posted questionnaires to all teaching hospitals in Japan (n = 1017 as of 2015). To examine changes over a period of roughly 1 year, surveys were conducted twice in November 2016 and February 2018 (see the English translation of the questionnaires in Additional file 1). No intervention was provided by our study team between the two surveys. The contents of the questionnaire included basic information, such as the number of beds (1st survey only), questions divided into sections 1 to 12 for countermeasures against AMR based from a previous study [6] and a guide published by the Japanese Ministry of Health, Labour and Welfare [7], and section 13 for results of bacterial cultures, as follows: 1. Organizational structure for nosocomial infection control; 2. Activities of ICT; 3. Preventive measures by the route of infections; 4. Maintenance of medical equipment; 5. Standard precautions; 6. Ward; 7. Intensive care unit (ICU); 8. Operating room; 9. Prevention of postoperative infections; 10. Management of food hygiene in hospitals; 11. Management of medical waste; 12. Cleaning, disinfection, and sterilization of instruments; and 13. Antimicrobial-resistant organisms. The questions were answered (1) numerically (e.g., number of physicians) or by choosing (2) either “yes” or “no” or (3) one among three to five options in order (e.g., “in approximately 100%/80%/50%/20%/0% of relevant cases”).
We analyzed valid responses, which included hospital information to link the 1st and 2nd surveys. We excluded duplicate responses to the same survey by the same hospital. Answers to questions in sections 1 to 12 are presented as medians and interquartile ranges, calculated after excluding missing values. For single-choice questions, we presented the proportions of “yes” or the most favorable option (e.g., “approximately 100% of relevant cases”). For these types of questions, we created a “missing” category. Student’s t-tests or Satterthwaite tests were used for continuous variables, and Cochran-Mantel-Haenszel tests for categorical variables, to compare results from the 1st and 2nd surveys.
The answers to questions in section 13 were the results of surveillance in 2015 for the 1st survey and 2016 for the 2nd survey, which were 1 year before each survey. We calculated the proportions of isolated microorganisms and antimicrobial-resistant organisms for each hospital that responded to both surveys. Wilcoxon signed-rank tests were used, assuming that the results from the 1st and 2nd surveys regarding section 13 were paired data.
To study the achievement level for AMS programs of hospitals, we performed a latent transition analysis (LTA), which is a longitudinal extension of latent class analysis [8]. Latent class analysis identifies underlying subgroups in a population, but the characteristics of these underlying subgroups are hard to observe directly; these are indicated by several observed variables [8]. While latent class analysis identifies underlying (unobservable) subgroups within a population as “classes,” LTA refers to the subgroups as “statuses” to reflect the fact that membership in the subgroups can change over time [8]. In this study, we performed LTA using data from hospitals that responded to both surveys, and time periods 1 and 2 for LTA were defined as those of 1st and 2nd surveys, respectively. Questions for which the proportion of the most favorable answer was less than 80% in the 2nd survey were used to classify hospitals into subgroups, latent statuses, with similar sets of answers to these questions. We excluded questions regarding handwashing sinks in ICUs, for which the proportion of the most favorable answer was less than 80%, given the lack of established guidelines. We also reduced the multiple categories in each question to two (most favorable/others) to improve the precision of estimates [9]. FTEs of ICT members were selected as a covariate that might affect the membership probabilities for time period 1. We determined the number of statuses by considering interpretability and fit statistics, and presented the fit statistics, status membership probabilities, transition probabilities, item-response probabilities, and estimated odds ratios for covariates. The domains, which consisted of several questions, were determined empirically according to the LTA results.
SAS® software version 9.4 (SAS Institute Inc., Cary, NC, USA) was used for all analyses, and PROC LTA (version 1.3.2) was used for the LTA [10]. A two-tailed significance level of 0.05 was used for all tests.
Results
Among 1017 teaching hospitals, 683 and 563 hospitals responded to the 1st and 2nd surveys, respectively. The numbers of valid responses were 678 for the 1st survey (response rate: 66.7%) and 559 for the 2nd survey (response rate: 55.0%) after excluding duplicated responses and those with missing hospital information. The number of hospitals that responded to both surveys was 437 (response rate: 43.0%).
The mean number of hospital beds was 434 (median, 389: 675 responses). Table 1 presents the results of the two surveys for all hospitals with valid responses and hospitals that responded to both surveys (see Tables S1 and S2 in Additional file 2 for more details). More than 99% of hospitals reported having active ICTs, with a median of 10 to 11 ICT members. Both crude numbers and FTEs of ICT members did not differ significantly between the 1st and 2nd surveys.
Table 1.
Results of the 1st and 2nd questionnaire surveys
| All hospitals with valid responses | Hospitals that responded to both surveys | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Question | 1st survey (n = 678) |
2nd survey (n = 559) |
P* | 1st survey (n = 437) |
2nd survey (n = 437) |
P* | ||||
| Number of staff | ||||||||||
| Physician (full-time) | 75 | (47–128) | 80 | (48.5–137.5) | 0.237 | 80 | (50–140) | 81 | (50–137) | 0.805 |
| Nurse (full-time) | 336 | (235–528.5) | 360 | (251–561) | 0.066 | 368 | (246–543) | 371 | (251–561) | 0.629 |
| Laboratory technologist (full-time) | 23 | (16–34) | 24 | (17–36) | 0.107 | 24 | (17–36.5) | 24.5 | (17–37) | 0.819 |
| Pharmacist (full-time) | 19 | (13–28) | 20 | (14–30) | 0.066 | 19 | (14–28) | 20 | (14–30) | 0.360 |
| Dietitian | 5 | (4–8) | 5 | (4–8) | 0.097 | 5 | (4–8) | 6 | (4–8) | 0.370 |
| Administrative staff | 52 | (32–86) | 53.5 | (32–87) | 0.611 | 56 | (33–87) | 56 | (33–89) | 0.718 |
| Registered ICD (MD or PhD) | 2 | (1–4) | 3 | (2–4) | 0.139 | 3 | (2–4) | 3 | (2–4) | 0.322 |
| We have an active ICT. | 674 | (99.4%) | 557 | (99.6%) | 0.843 | 436 | (99.8%) | 435 | (99.5%) | 0.607 |
| Number of ICT member, crude | 10 | (8–16) | 11 | (7–16) | 0.103 | 11 | (8–17) | 11 | (7–17) | 0.530 |
| Physician | 2.5 | (2–4) | 3 | (2–4) | 0.153 | 3 | (2–4) | 3 | (2–4) | 0.576 |
| Nurse | 2 | (2–4) | 2 | (2–4) | 0.488 | 2 | (2–4) | 2 | (2–4) | 0.757 |
| Pharmacist | 2 | (1–2) | 2 | (1–2) | 0.255 | 2 | (1–2) | 2 | (1–2) | 0.242 |
| Laboratory technologist | 2 | (1–2) | 2 | (1–2) | 0.230 | 2 | (1–2) | 2 | (1–2) | 0.709 |
| Dietitian | 0 | (0–0) | 0 | (0–0) | 0.910 | 0 | (0–0) | 0 | (0–0) | 0.948 |
| Administrative staff | 1 | (0–2) | 1 | (0–1) | 0.969 | 1 | (0–2) | 1 | (1–2) | 0.926 |
| Number of ICT member, full-time equivalent | 2.8 | (1.3–4.3) | 2.8 | (1.8–4) | 0.717 | 2.8 | (1.6–4.3) | 2.8 | (1.8–4.1) | 0.920 |
| Physician | 2.5 | (2–4) | 3 | (2–4) | 0.951 | 3 | (2–4) | 3 | (2–4) | 0.830 |
| Nurse | 0.8 | (0.8–1.3) | 0.8 | (0.8–1.3) | 0.675 | 0.8 | (0.8–1.3) | 0.8 | (0.8–1.3) | 0.693 |
| Pharmacist | 0.5 | (0–0.8) | 0.5 | (0–0.8) | 0.725 | 0.5 | (0–0.8) | 0.5 | (0–0.65) | 0.531 |
| Laboratory technologist | 0.5 | (0–0.8) | 0.5 | (0–0.5) | 0.953 | 0.5 | (0–1) | 0.5 | (0–0.8) | 0.931 |
| Dietitian | 0 | (0–0) | 0 | (0–0) | 0.068 | 0 | (0–0) | 0 | (0–0) | 0.067 |
| Administrative staff | 0 | (0–0.5) | 0 | (0–0.5) | 0.839 | 0 | (0–0.5) | 0 | (0–0.5) | 0.524 |
| FTE per 100 beds | 0.7 | (0.4–1.0) | 0.7 | (0.4–1.0) | 0.918 | 0.7 | (0.4–1.0) | 0.7 | (0.4–1.0) | 0.918 |
| We performed bacterial culture, identification, and susceptibility tests basically in our hospital. | 542 | (79.9%) | 466 | (83.4%) | 0.301 | 355 | (81.2%) | 367 | (84.0%) | 0.362 |
| We participate in JANIS programs. | 647 | (95.4%) | 548 | (98.0%) | 0.025 | 426 | (97.5%) | 432 | (98.9%) | 0.219 |
| Clinical laboratory division | 636 | (93.8%) | 536 | (95.9%) | 0.103 | 421 | (96.3%) | 422 | (96.6%) | 0.855 |
| Antimicrobial-resistant bacterial infection division | 311 | (45.9%) | 288 | (51.5%) | 0.048 | 228 | (52.2%) | 235 | (53.8%) | 0.635 |
| Surgical site infection division | 366 | (54.0%) | 324 | (58.0%) | 0.161 | 249 | (57.0%) | 259 | (59.3%) | 0.493 |
| Intensive care unit division | 116 | (17.1%) | 88 | (15.7%) | 0.519 | 80 | (18.3%) | 74 | (16.9%) | 0.595 |
| Neonatal intensive care unit division | 74 | (10.9%) | 64 | (11.4%) | 0.766 | 56 | (12.8%) | 51 | (11.7%) | 0.606 |
| 1. Organizational structure for nosocomial infection control | ||||||||||
| The head of our hospital attends ICC almost every time. | 576 | (85.0%) | 473 | (84.6%) | 0.027 | 379 | (86.7%) | 369 | (84.4%) | 0.018 |
| We have a comprehensive hospital infection control manual that can be used all around our hospital. | 677 | (99.9%) | 559 | (100.0%) | 0.364 | 437 | (100.0%) | 437 | (100.0%) | – |
| We hold a workshop regarding countermeasures against hospital infection more than once a year. | 677 | (99.9%) | 559 | (100.0%) | 0.364 | 437 | (100.0%) | 437 | (100.0%) | – |
| We have tools, such as the intranet and bulletin boards, to inform our staff of hospital infection-related matters. | 671 | (99.0%) | 556 | (99.5%) | 0.397 | 434 | (99.3%) | 436 | (99.8%) | 0.317 |
| 2. Activities of ICT | ||||||||||
| We hold a regular ICT meeting. | 628 | (92.6%) | 534 | (95.5%) | 0.042 | 410 | (93.8%) | 416 | (95.2%) | 0.353 |
| We provide consultation as an activity of the ICT. | 633 | (93.4%) | 516 | (92.3%) | 0.274 | 412 | (94.3%) | 407 | (93.1%) | 0.333 |
| We have an AST (a member can work for both ICT and AST). | 542 | (79.9%) | 373 | (66.7%) | <.001 | 355 | (81.2%) | 305 | (69.8%) | <.001 |
| We monitor the uses of antibiotics to assure their propriety. | 652 | (96.2%) | 544 | (97.3%) | 0.476 | 420 | (96.1%) | 431 | (98.6%) | 0.064 |
| We intervene to assure appropriate uses of antibiotics. | 631 | (93.1%) | 527 | (94.3%) | 0.177 | 410 | (93.8%) | 415 | (95.0%) | 0.317 |
| We have established criteria of interventions, such as their administration duration and selection, for patients administered antibiotics. | 466 | (68.7%) | 399 | (71.4%) | 0.589 | 304 | (69.6%) | 310 | (70.9%) | 0.691 |
| We have criteria for the uses of anti-MRSA antibiotics. | 433 | (63.9%) | 361 | (64.6%) | 0.964 | 267 | (61.1%) | 278 | (63.6%) | 0.594 |
| We record the used amount of anti-MRSA antibiotics. | 667 | (98.4%) | 554 | (99.1%) | 0.508 | 432 | (98.9%) | 432 | (98.9%) | 0.788 |
| We have a reporting system (1st survey: “registration system”) for the use of anti-MRSA antibiotics. | 390 | (57.5%) | 542 | (97.0%) | <.001 | 259 | (59.3%) | 425 | (97.3%) | <.001 |
| We have a preauthorization and/or restriction system for the use of anti-MRSA antibiotics. | 321 | (47.3%) | 208 | (37.2%) | <.001 | 206 | (47.1%) | 169 | (38.7%) | 0.035 |
| We have criteria for the uses of broad-spectrum antibiotics such as carbapenems. | 355 | (52.4%) | 287 | (51.3%) | 0.369 | 217 | (49.7%) | 224 | (51.3%) | 0.305 |
| We have a reporting system (1st survey: “registration system”) for the use of broad-spectrum antibiotics. | 391 | (57.7%) | 530 | (94.8%) | <.001 | 251 | (57.4%) | 415 | (95.0%) | <.001 |
| We have a preauthorization and/or restriction system for the use of broad-spectrum antibiotics. | 258 | (38.1%) | 131 | (23.4%) | <.001 | 157 | (35.9%) | 111 | (25.4%) | 0.003 |
| We record the used amount of broad-spectrum antibiotics. | 667 | (98.4%) | 550 | (98.4%) | 0.935 | 429 | (98.2%) | 431 | (98.6%) | 0.777 |
| We have a reference system, such as the intranet of a booklet, for the antibiogram. | 562 | (82.9%) | 482 | (86.2%) | 0.238 | 371 | (84.9%) | 383 | (87.6%) | 0.499 |
| We performed TDM for basically all cases. | 423 | (62.4%) | 362 | (64.8%) | 0.273 | 273 | (62.5%) | 287 | (65.7%) | 0.193 |
| We record the vaccination proportion of employees who are HBsAg-negative. | 581 | (85.7%) | 485 | (86.8%) | 0.415 | 369 | (84.4%) | 378 | (86.5%) | 0.096 |
| We perform IGRAs for employees who are in contact with tuberculosis patients. | 616 | (90.9%) | 503 | (90.0%) | 0.772 | 404 | (92.4%) | 397 | (90.8%) | 0.556 |
| We record employees’ immunization statuses for measles, rubella, chickenpox, and mumps (2nd survey: “for all of measles, rubella, chickenpox, and mumps”). | 572 | (84.4%) | 340 | (60.8%) | <.001 | 371 | (84.9%) | 273 | (62.5%) | <.001 |
| We have a manual and a reporting system of needle punctures and sharp object injuries. | 678 | (100.0%) | 559 | (100.0%) | – | 437 | (100.0%) | 437 | (100.0%) | – |
| Needle puncture and sharp object injuries are reported to a relevant department, such as ICT. | 463 | (68.3%) | 391 | (69.9%) | 0.177 | 301 | (68.9%) | 307 | (70.3%) | 0.408 |
| ICT and/or ICPs check the number of isolated antimicrobial-resistant organisms and other microorganisms that are relevant to infection control on a daily basis | 436 | (64.3%) | 357 | (63.9%) | 0.409 | 281 | (64.3%) | 286 | (65.4%) | 0.110 |
| ICT and/or ICPs record the species and trends of isolated microorganisms on a type-of-sample and a ward-by-ward basis. | 636 | (93.8%) | 530 | (94.8%) | 0.142 | 413 | (94.5%) | 414 | (94.7%) | 0.257 |
| We have a direct and fast reporting system to the doctor-in-charge, such as e-mail and telephone, when microorganisms are isolated from a sample that is supposed to be aseptic (e.g., a blood sample). | 653 | (96.3%) | 550 | (98.4%) | 0.068 | 422 | (96.6%) | 431 | (98.6%) | 0.088 |
| We perform surveillance for surgical site infections. | 510 | (75.2%) | 446 | (79.8%) | 0.038 | 334 | (76.4%) | 355 | (81.2%) | 0.119 |
| We perform surveillance for ventilator-associated pneumonia. | 238 | (35.1%) | 219 | (39.2%) | 0.254 | 162 | (37.1%) | 175 | (40.0%) | 0.422 |
| We perform surveillance for central line-associated bloodstream infections. | 508 | (74.9%) | 440 | (78.7%) | 0.190 | 330 | (75.5%) | 351 | (80.3%) | 0.088 |
| We perform surveillance for catheter-associated urinary tract infections. | 345 | (50.9%) | 310 | (55.5%) | 0.275 | 224 | (51.3%) | 258 | (59.0%) | 0.063 |
| We perform active surveillance cultures. | 334 | (49.3%) | 273 | (48.8%) | 0.905 | 228 | (52.2%) | 219 | (50.1%) | 0.831 |
| We have an established manual for outbreaks. | 637 | (94.0%) | 534 | (95.5%) | 0.370 | 417 | (95.4%) | 419 | (95.9%) | 0.947 |
| 3. Preventive measures by the route of infections | ||||||||||
| We have a manual for the outbreak of tuberculosis. | 675 | (99.6%) | 559 | (100.0%) | 0.290 | 435 | (99.5%) | 437 | (100.0%) | 0.368 |
| We have a manual for the outbreak of measles. | 623 | (91.9%) | 513 | (91.8%) | 0.175 | 398 | (91.1%) | 401 | (91.8%) | 0.222 |
| We have a manual for the outbreak of chickenpox. | 612 | (90.3%) | 502 | (89.8%) | 0.161 | 393 | (89.9%) | 395 | (90.4%) | 0.222 |
| We provide N95 masks at the outpatient emergency department and other outpatient departments. | 664 | (97.9%) | 551 | (98.6%) | 0.648 | 429 | (98.2%) | 432 | (98.9%) | 0.661 |
| We put a surgical mask on patients with suspected airborne infections while transporting. | 677 | (99.9%) | 558 | (99.8%) | 0.361 | 436 | (99.8%) | 436 | (99.8%) | 0.368 |
| Wearing an N95 mask is mandatory while entering the ward of a patient with suspected tuberculosis. | 676 | (99.7%) | 558 | (99.8%) | 0.680 | 436 | (99.8%) | 436 | (99.8%) | 1.000 |
| We have a manual for the outbreak of influenza. | 674 | (99.4%) | 555 | (99.3%) | 0.736 | 435 | (99.5%) | 435 | (99.5%) | 1.000 |
| Wearing a surgical mask while entering the ward of a patient with a droplet infection is instructed by a manual. | 671 | (99.0%) | 558 | (99.8%) | 0.152 | 432 | (98.9%) | 437 | (100.0%) | 0.081 |
| We provide surgical masks in the wards of patients with droplet infections. | 589 | (86.9%) | 486 | (86.9%) | 0.716 | 374 | (85.6%) | 380 | (87.0%) | 0.336 |
| We have a manual for cases in which MRSA is isolated from a patient. | 667 | (98.4%) | 551 | (98.6%) | 0.661 | 429 | (98.2%) | 433 | (99.1%) | 0.400 |
| Wearing disposable gloves and a gown is mandatory while entering the ward of a patient with suspected contagious diseases. | 618 | (91.2%) | 508 | (90.9%) | 0.966 | 399 | (91.3%) | 401 | (91.8%) | 0.793 |
| We provide alcohol-based hand sanitizers in all wards except for some special wards, such as the psychiatric ward. | 657 | (96.9%) | 546 | (97.7%) | 0.525 | 427 | (97.7%) | 428 | (97.9%) | 0.607 |
| We provide alcohol-based hand sanitizers in all outpatient departments. | 624 | (92.0%) | 529 | (94.6%) | 0.151 | 404 | (92.4%) | 415 | (95.0%) | 0.224 |
| 4. Maintenance of medical equipment | ||||||||||
| We adopt closed urine drainage systems. | 644 | (95.0%) | 544 | (97.3%) | 0.112 | 419 | (95.9%) | 426 | (97.5%) | 0.412 |
| We do not change catheters without blockages or infections regularly. | 512 | (75.5%) | 418 | (74.8%) | 0.619 | 322 | (73.7%) | 323 | (73.9%) | 0.904 |
| We have a manual for the maintenance of ventilators. | 583 | (86.0%) | 499 | (89.3%) | 0.221 | 376 | (86.0%) | 388 | (88.8%) | 0.424 |
| We adopt closed tracheal suction systems. | 568 | (83.8%) | 476 | (85.2%) | 0.799 | 382 | (87.4%) | 381 | (87.2%) | 0.931 |
| We use sterile water for humidifiers. | 658 | (97.1%) | 544 | (97.3%) | 0.120 | 428 | (97.9%) | 426 | (97.5%) | 0.311 |
| We perform regular oral cleansing for intubated patients in approximately 100% of relevant cases. | 524 | (77.3%) | 425 | (76.0%) | 0.225 | 340 | (77.8%) | 333 | (76.2%) | 0.226 |
| We have a manual for the maintenance of central line catheters. | 654 | (96.5%) | 542 | (97.0%) | 0.108 | 418 | (95.7%) | 425 | (97.3%) | 0.294 |
| We insert central line catheters under maximal barrier precautions in approximately 100% of relevant cases. | 254 | (37.5%) | 210 | (37.6%) | 0.086 | 163 | (37.3%) | 167 | (38.2%) | 0.150 |
| We prepare intravenous hyperalimentation admixtures on clean benches in approximately 100% of relevant cases. | 277 | (40.9%) | 225 | (40.3%) | 0.415 | 182 | (41.6%) | 175 | (40.0%) | 0.335 |
| We use transparent dressings on the sites of catheter insertion to make them easy to inspect visually in approximately 100% of relevant cases. | 563 | (83.0%) | 486 | (86.9%) | 0.224 | 357 | (81.7%) | 380 | (87.0%) | 0.112 |
| 5. Standard precautions | ||||||||||
| We instruct new employees in hand hygiene by practical training sessions for all professions. | 361 | (53.2%) | 290 | (51.9%) | 0.955 | 229 | (52.4%) | 222 | (50.8%) | 0.700 |
| We evaluate the implementation of hand hygiene instructions of all wards at least once a year. | 603 | (88.9%) | 523 | (93.6%) | 0.018 | 389 | (89.0%) | 411 | (94.1%) | 0.028 |
| We instruct new employees of all professions how to put on and remove PPE. | 532 | (78.5%) | 426 | (76.2%) | 0.638 | 347 | (79.4%) | 330 | (75.5%) | 0.255 |
| We instruct all employees in PPE by practical training sessions every year. | 135 | (19.9%) | 107 | (19.1%) | 0.281 | 85 | (19.5%) | 80 | (18.3%) | 0.126 |
| 6. Wards | ||||||||||
| We provide hand sanitizers at the entrance of all wards. | 656 | (96.8%) | 544 | (97.3%) | 0.407 | 426 | (97.5%) | 426 | (97.5%) | 0.593 |
| All medical devices (e.g., thermometers, stethoscopes) of single isolation rooms are patient-dedicated. | 653 | (96.3%) | 529 | (94.6%) | 0.152 | 423 | (96.8%) | 414 | (94.7%) | 0.174 |
| We check expiry dates of sterilized medical devices daily. | 638 | (94.1%) | 528 | (94.5%) | 0.949 | 415 | (95.0%) | 416 | (95.2%) | 0.987 |
| We check expiry dates of unused medications. | 664 | (97.9%) | 551 | (98.6%) | 0.516 | 429 | (98.2%) | 430 | (98.4%) | 0.741 |
| We have established guides for the expiry dates of opened medications. | 649 | (95.7%) | 542 | (97.0%) | 0.285 | 421 | (96.3%) | 422 | (96.6%) | 0.514 |
| All wards have at least one infection control link nurse. | 669 | (98.7%) | 547 | (97.9%) | 0.535 | 432 | (98.9%) | 429 | (98.2%) | 0.571 |
| 7. ICU | ||||||||||
| Medical professions do not change their shoes while entering ICU. | 548 | (80.8%) | 425 | (76.0%) | 0.123 | 363 | (83.1%) | 335 | (76.7%) | 0.037 |
| Medical professions are not recommended to wear gowns while entering ICU. | 548 | (80.8%) | 425 | (76.0%) | 0.116 | 361 | (82.6%) | 337 | (77.1%) | 0.128 |
| We have handwashing sinks at the entrance of ICU. | 397 | (58.6%) | 320 | (57.2%) | 0.085 | 259 | (59.3%) | 248 | (56.8%) | 0.107 |
| We provide hand sanitizers at the entrance of ICU. | 549 | (81.0%) | 426 | (76.2%) | 0.114 | 362 | (82.8%) | 338 | (77.3%) | 0.095 |
| We advise the patients’ families to use hand sanitizers or wash hands before and after entering ICU. | 545 | (80.4%) | 428 | (76.6%) | 0.016 | 362 | (82.8%) | 339 | (77.6%) | 0.066 |
| 8. Operating room | ||||||||||
| We do not change stretchers while entering operating rooms. | 518 | (76.4%) | 449 | (80.3%) | 0.046 | 334 | (76.4%) | 352 | (80.5%) | 0.211 |
| Medical professions do not change their shoes while entering operating rooms. | 395 | (58.3%) | 356 | (63.7%) | 0.102 | 263 | (60.2%) | 285 | (65.2%) | 0.299 |
| We do not provide sticky mats at the entrance of operation rooms. | 670 | (98.8%) | 552 | (98.7%) | 0.734 | 434 | (99.3%) | 432 | (98.9%) | 0.715 |
| We have established standards of surgical hand preparation. | 579 | (85.4%) | 492 | (88.0%) | 0.331 | 375 | (85.8%) | 381 | (87.2%) | 0.553 |
| We do not recommend the use of a brush for surgical hand preparation. | 641 | (94.5%) | 534 | (95.5%) | 0.424 | 419 | (95.9%) | 420 | (96.1%) | 0.867 |
| 9. Prevention of postoperative infections | ||||||||||
| We use electric clippers or depilatory creams for patients who need to remove their hair before surgery in all departments. | 651 | (96.0%) | 532 | (95.2%) | 0.572 | 420 | (96.1%) | 418 | (95.7%) | 0.271 |
| We advise patients who can take a shower to take a shower on the night before or the morning of the day of surgery. | 638 | (94.1%) | 526 | (94.1%) | 0.865 | 410 | (93.8%) | 410 | (93.8%) | 0.478 |
| We recommend the administration of prophylactic antibiotics 30 min to 1 h before the incision. | 640 | (94.4%) | 522 | (93.4%) | 0.582 | 421 | (96.3%) | 406 | (92.9%) | 0.710 |
| We have manuals to establish the duration of prophylactic antibiotics administration in all departments. | 304 | (44.8%) | 266 | (47.6%) | 0.532 | 188 | (43.0%) | 214 | (49.0%) | 0.230 |
| 10. Management of food hygiene in hospitals | ||||||||||
| We adopt dry kitchen systems for hospital meals. | 508 | (74.9%) | 453 | (81.0%) | 0.005 | 330 | (75.5%) | 356 | (81.5%) | 0.040 |
| 11. Management of medical waste | ||||||||||
| We distinguish infectious waste from other waste and store it in a place inaccessible to non-authorized people. | 667 | (98.4%) | 546 | (97.7%) | 0.667 | 428 | (97.9%) | 427 | (97.7%) | 0.607 |
| 12. Cleaning, disinfection, and sterilization of instruments | ||||||||||
| We do not pre-clean or pre-disinfect medical devices in wards. | 549 | (81.0%) | 463 | (82.8%) | 0.526 | 355 | (81.2%) | 368 | (84.2%) | 0.501 |
| We clean and disinfect endoscopes in accordance with the manuals or check them regularly. | 582 | (85.8%) | 472 | (84.4%) | 0.498 | 375 | (85.8%) | 372 | (85.1%) | 0.885 |
ICD Infection control doctor, MD Medical doctor, PhD Doctor of philosophy, ICT Infection control team, JANIS Japan Nosocomial Infections Surveillance, ICC Infection control committee, AST Antimicrobial stewardship team, MRSA Methicillin-resistant Staphylococcus aureus, TDM Therapeutic drug monitoring, HBsAg Hepatitis B surface antigen, IGRA Interferon-gamma release assay, ICP Infection control practitioner, PPE Personal protective equipment, ICU Intensive care unit
Values are presented as medians (interquartile range) for numeric variables and numbers (%) for categorical variables
Questions in bold indicate that the proportion of the most favorable answer was < 80%
*Student’s t-test or Satterthwaite test as appropriate for continuous variables; Cochran-Mantel-Haenszel test for categorical variables
P values in bold indicate P < .05
More than 90% of hospitals had weekly ICT meetings, although proportions of specific activities differed from hospital to hospital (section 2): 79.9% (1st survey) and 66.7% (2nd survey) of hospitals had an antimicrobial stewardship team. More than 90% of hospitals indicated that they monitored and intervened to assure appropriate use of antibiotics, but only 70% had established intervention criteria. The proportions of hospitals with intervention criteria for patients administered anti-methicillin-resistant Staphylococcus aureus (MRSA) antibiotics and carbapenems were approximately 60 and 50%, respectively. The proportions of hospitals that performed surveillance varied by the types of infections: catheter-associated urinary tract infections and ventilator-associated pneumonia were monitored less frequently compared to surgical site infections and central line-associated bloodstream infections.
With regard to the maintenance of medical equipment (section 4), less than 50% of hospitals indicated that they used maximal barrier precautions for central line catheter insertion and prepared intravenous hyperalimentation admixtures on clean benches.
For standard precautions (section 5), approximately 50% of hospitals held practical hand hygiene training sessions for new employees regardless of professions; the remaining hospitals trained new employees of selected professions only. Training regarding personal protective equipment for all new employees was held in about 80% of hospitals, although less than 20% of hospitals held these training sessions every year.
Regarding the ICU (section 7), the proportion of hospitals that answered “yes” to “We have handwashing sinks at the entrance of ICU” was lower than the other questions in this section. Roughly 60% of hospitals had handwashing sinks at the ICU entrance, whereas approximately 80% of hospitals answered “yes” for other questions.
Less than 70% of hospitals responded that their staff members do not change their shoes when entering the operating room, and less than 50% had manuals regarding the duration of prophylactic antibiotics available in all departments (section 8). The proportion was lower than 80% even when hospitals that had manuals in selected departments were included (Tables S1 and S2 in Additional file 2).
Table 2 presents the proportions of isolated microorganisms and antimicrobial-resistant microorganisms. Among antimicrobial-resistant microorganisms, only the proportion of those belonging to the family Enterobacteriaceae decreased in 2016 compared with 2015. The proportions of antimicrobial-resistant Streptococcus pneumoniae and Escherichia coli increased during this period.
Table 2.
Isolation proportions of microorganisms and antimicrobial-resistant microorganisms
| Number of hospitals | 1st survey (2015) | 2nd survey (2016) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Microorganism | Mean | ±SD | Median | (IQR) | Mean | ±SD | Median | (IQR) | P* | |
| Staphylococcus aureus | 378 | 14.4% | ±7.7% | 13.2% | (9.6–17.3%) | 15.0% | ±7.4% | 14.2% | (9.7–19.0%) | 0.046 |
| Methicillin-resistant | 378 | 37.8% | ±14.3% | 34.9% | (28.6–43.9%) | 37.9% | ±13.3% | 35.8% | (28.6–44.7%) | 0.342 |
| Methicillin-resistant, in a blood sample | 378 | 6.0% | ±4.3% | 5.1% | (3.2–8.1%) | 6.8% | ±4.9% | 6.2% | (3.9–8.8%) | 0.002 |
| Streptococcus pneumoniae | 296 | 2.1% | ±2.3% | 1.5% | (0.8–2.7%) | 1.9% | ±2.7% | 1.2% | (0.7–2.1%) | <.001 |
| Penicillin-resistant | 296 | 22.6% | ±21.9% | 18.9% | (0.3–40.4%) | 29.1% | ±20.8% | 33.3% | (5.5–45.5%) | <.001 |
| Escherichia coli | 298 | 12.8% | ±7.3% | 11.8% | (8.3–15.7%) | 12.6% | ±5.9% | 11.6% | (9.0–15.4%) | 0.181 |
| Fluoroquinolone-resistant | 298 | 27.2% | ±11.0% | 27.8% | (19.7–34.4%) | 29.4% | ±10.6% | 30.0% | (22.0–36.4%) | <.001 |
| Pseudomonas aeruginosa | 299 | 4.7% | ±3.3% | 4.1% | (2.7–5.8%) | 5.2% | ±2.9% | 4.8% | (3.4–6.4%) | <.001 |
| Carbapenem-resistant | 299 | 10.8% | ±7.2% | 9.8% | (6.0–14.8%) | 10.8% | ±7.1% | 10.0% | (5.1–15.6%) | 0.843 |
| Enterobacteriaceae | 279 | 22.5% | ±10.9% | 21.2% | (15.2–28.0%) | 18.6% | ±9.3% | 17.2% | (13.2–22.9%) | <.001 |
| Carbapenem-resistant | 279 | 1.0% | ±1.5% | 0.5% | (0.1–1.4%) | 0.9% | ±1.7% | 0.2% | (0.0–0.9%) | 0.001 |
SD Standard deviation, IQR Interquartile range
*Wilcoxon signed-rank test
P values in bold indicate P < .05
Tables 3, 4, 5, 6, 7, and Table S3 and Figure S1 in Additional file 2 show the results of the LTA. Five statutes, from the most favorable (status 1) to the least favorable (status 5), were identified (Table 3). Latent status 4 showed the highest status membership probabilities for both time periods (Table 4). As for transition probabilities, members of statuses 1, 2, 4, and 5 were stable in their status membership (Table 5). On the other hand, members of status 3 showed the lowest probability of remaining in the same status (42.7%, Table 5), with 32.7% moving to status 5 and 14.8% moving to status 4 (Table 5). We assigned five domains according to the item-response probabilities for each question (Tables 3, 6 and Figure S1 in Additional file 2): “antimicrobial stewardship” (domain 1); “surveillance” (domain 2); “medical and hospital equipment” (domain 3); “ICT activities regarding vaccinations and education of employees” (domain 4); and “acknowledgment of updating relevant guidelines” (domain 5). Compared to status 1, status 2 showed lower probabilities of having criteria for anti-MRSA antibiotic use and broad-spectrum antibiotic use, whereas status 3 had lower probabilities of performing surveillance. Status 4 had only one domain (i.e., domain 3) with higher probabilities for questions in it. Status 5 had no domain that showed higher probabilities compared to other statuses. In the analysis using the number of ICT members (FTE per 100 beds) as a covariate, the odds ratio of status 3 versus status 5 was 1.32, whereas odds ratios were 0.55 and 0.61 for statuses 1 and 2 versus status 5, respectively (p = 0.027, Table 7).
Table 3.
Item-response probabilities for each question by identified latent statuses
| Domain | Question | Latent status | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| Antimicrobial stewardship | We have an antimicrobial stewardship team (a member can work for both an infection control team and an antimicrobial stewardship team). | 0.853 | 0.828 | 0.934 | 0.742 | 0.743 |
| We have established criteria of interventions, such as their administration duration and selection, for patients administered antibiotics. | 0.819 | 0.729 | 0.821 | 0.653 | 0.563 | |
| We have criteria for the uses of anti-MRSA antibiotics. | 1 | 0 | 1 | 0.595 | 0.487 | |
| We have a preauthorization and/or restriction system for the use of anti-MRSA antibiotics. | 0.525 | 0.505 | 1 | 0.176 | 0.169 | |
| We have criteria for the uses of broad-spectrum antibiotics such as carbapenems. | 0.847 | 0.187 | 0.856 | 0.385 | 0.304 | |
| We have a preauthorization and/or restriction system for the use of broad-spectrum antibiotics. | 0.365 | 0.348 | 0.947 | 0.072 | 0.065 | |
| We performed therapeutic drug monitoring for basically all cases. | 0.800 | 0.723 | 0.607 | 0.593 | 0.506 | |
| We have manuals to establish the duration of prophylactic antibiotics administration in all departments. | 0.603 | 0.621 | 0.513 | 0.426 | 0.324 | |
| Surveillance | We perform surveillance for ventilator-associated pneumonia. | 0.819 | 0.780 | 0.164 | 0.114 | 0.037 |
| We perform surveillance for catheter-associated urinary tract infections. | 0.874 | 0.710 | 0.261 | 0.450 | 0.375 | |
| We perform active surveillance cultures. | 0.798 | 0.738 | 0.315 | 0.402 | 0.298 | |
| Medical and hospital equipment | We perform regular oral cleansing for intubated patients in approximately 100% of relevant cases. | 0.816 | 0.808 | 0.749 | 0.801 | 0.712 |
| We insert central line catheters under maximal barrier precautions in approximately 100% of relevant cases. | 0.374 | 0.358 | 0.416 | 1 | 0.000 | |
| We prepare intravenous hyperalimentation admixtures on clean benches in approximately 100% of relevant cases. | 0.400 | 0.393 | 0.496 | 0.521 | 0.340 | |
| We have handwashing sinks at the entrance of an intensive care unit. | 0.673 | 0.687 | 0.476 | 0.502 | 0.533 | |
| Infection control team activities regarding vaccinations and education of employees | Needle puncture and sharp object injuries are reported to a relevant department, such as an infection control team. | 0.735 | 0.580 | 0.756 | 0.805 | 0.644 |
| We instruct new employees in hand hygiene by practical training for all professions. | 0.493 | 0.423 | 0.593 | 0.460 | 0.571 | |
| We instruct new employees of all professions how to put on and remove personal protective equipment. | 0.762 | 0.745 | 0.818 | 0.774 | 0.769 | |
| We instruct all employees in personal protective equipment by practical training every year. | 0.198 | 0.125 | 0.242 | 0.146 | 0.202 | |
| Acknowledgment of updating relevant guidelines | We do not change catheters without blockages or infections regularly. | 0.892 | 0.786 | 0.657 | 0.666 | 0.657 |
| Medical professions do not change their shoes while entering operating rooms. | 0.764 | 0.713 | 0.509 | 0.532 | 0.509 | |
Values in bold indicate that the probability was above the mean of each question (i.e., each row)
Table 4.
Status membership probabilities for the 1st and 2nd time periods
| Time | Latent status | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1 | 0.236 | 0.171 | 0.180 | 0.149 | 0.263 |
| 2 | 0.253 | 0.171 | 0.088 | 0.170 | 0.318 |
Table 5.
Transition probabilities of each status from the 1st to 2nd time periods
| Status, time 2 | ||||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| Status, time 1 | 1 | 0.996 | 0 | 0 | 0.004 | 0 |
| 2 | 0 | 1 | 0 | 0 | 0 | |
| 3 | 0.099 | 0 | 0.427 | 0.148 | 0.327 | |
| 4 | 0 | 0 | 0.040 | 0.961 | 0 | |
| 5 | 0 | 0 | 0.015 | 0 | 0.985 | |
Table 6.
Characteristics of each latent status
| Latent status | |||||
|---|---|---|---|---|---|
| Domain, number of questions in each domain | 1 | 2 | 3 | 4 | 5 |
| Antimicrobial stewardship, 8 | ✓ | ✓ | ✓ | ✗ | ✗ |
| Surveillance, 3 | ✓ | ✓ | ✗ | ✗ | ✗ |
| Medical and hospital equipment, 4 | ✗ | ✓ | ✗ | ||
| Infection control team activities regarding vaccinations and education of employees, 4 | ✗ | ✓ | |||
| Acknowledgment of updating relevant guidelines, 2 | ✓ | ✓ | ✗ | ✗ | ✗ |
✓, the number of questions for which the probability (shown in Table 3) was above the mean of probabilities for five domains for each question (the mean value of each row in Table 3) was higher than half of the number of questions in each domain; ✗, the number of questions for which the probability (shown in Table 3) was above the mean of probabilities for five domains for each question (the mean value of each row in Table 3) was lower than a half of the number of questions in each domain. For example, latent status 2 had 7 questions of which probabilities were higher than the mean probability of corresponding questions in the first domain “antimicrobial stewardship.” These 7 probabilities were written in bold. The number of these bold ones was 5, which was more than half of the number of questions in the domain “antimicrobial stewardship,” 8, then status 3 was assigned to “✓ “for the first domain
Table 7.
Odds ratio estimates of covariates
| Covariate | Latent status | P | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| Number of members in an infection control team* | 0.55 | 0.61 | 1.32 | 0.74 | Reference | 0.027 |
* In full-time equivalent per 100 hospital beds
Discussion
We conducted two surveys on AMR and infections in teaching hospitals in Japan, with an interval of approximately 1 year between the surveys. Most hospitals had activities of ICTs, however, actual activities differed among hospitals. The results of LTA suggested that there were five subgroups of hospitals, which were considered indicating similar achievement levels of AMS. The presence of local (i.e. hospital-level) guidelines for using anti-MRSA and broad-spectrum antibiotics, and the range of surveillance activities of each hospital were identified as two major determinants of the membership in each subgroup.
The proportion of hospitals with antimicrobial stewardship teams decreased during the study period. In fiscal year 2018 (after the 2nd survey), a fee for antimicrobial stewardship teams was introduced by the National Fee Schedule. To claim this fee, hospitals must fulfill requirements such as having at least one full-time staff member who is a physician with more than 3 years of experience in infectious disease treatment, a nurse with more than 5 years of experience working in a hospital, or a pharmacist or a laboratory technologist with more than 3 years of experience working in a hospital. Our results suggest that hospitals not fulfilling this requirement might have changed their answers to this question from “having an antimicrobial stewardship team” to “not having an antimicrobial stewardship team.”
The proportion of hospitals with preauthorization and/or restriction systems for the use of anti-MRSA antibiotics and broad-spectrum antibiotics decreased during the study period. Preauthorization and/or prospective audit and feedback interventions by AMS programs are strongly recommended [11]. Although more than 90% of hospitals in our study responded that they carried out monitoring and intervention activities, roughly 70% had established intervention criteria, and less than 40% had preauthorization and/or restriction systems for anti-MRSA antibiotics and broad-spectrum antibiotics. These proportions also decreased throughout the study period. The use of restricted antibiotics lists has been reported to reduce antimicrobial resistance rates and costs [12]. Thus, hospitals should consider introducing preauthorization and/or restriction systems for relevant antibiotics to enhance their AMS programs.
The proportions of hospitals with surveillance for ventilator-associated pneumonia and catheter-associated urinary tract infections increased slightly, but remained under 60%. Given that these infections are considered major healthcare-associated infections along with surgical site infections and central line-associated bloodstream infections, surveillance is recommended [13–15]. The proportion of hospitals performing active surveillance cultures was roughly 65%. However, active surveillance cultures for MRSA and vancomycin-resistant enterococci for all inpatients except for high-risk patients are not recommended [16]. The WHO Guidelines Development Group strongly recommends surveillance cultures for asymptomatic carbapenem-resistant Enterobacteriaceae and surveillance for carbapenem-resistant Acinetobacter baumannii and Pseudomonas aeruginosa despite a very low quality of evidence [17]. Further studies will be needed to determine the targets for active surveillance cultures and their efficacy.
For all questions regarding the ICU, the proportions of hospitals with the most favorable answers were less than 80%. This might be due to the fact that hospitals without an ICU were also included in this study. However, the proportion of hospitals that answered “yes” to the question about handwashing sinks at the ICU entrance was considerably lower (less than 60%) compared to those of hospitals that answered “yes” to the other questions. A Japanese guideline (2002) that recommended hospitals to place handwashing sinks at the ICU entrance [18] was revised to allow for the location to be based on staff accessibility [19]. However, since recent studies have suggested that sinks in the ICU might be a source of infections [20–22], further investigations will be needed on appropriate locations and specifications of sinks in the ICU.
The LTA identified five statuses. There was a slight increase in the most favorable status (status 1) over the course of the study period (23.6 to 25.3%). However, the least favorable status (status 5) also showed an increase (26.3 to 31.8%), which was mainly due to a decrease in status 3 (18.0 to 8.8%). Previous studies have reported that human resources (FTEs of infection control practitioners) and FTE-to-bed ratios were related to improvements in AMS [3–5], defined as an increase in the number of implemented AMS programs [3] or effectiveness of AMS programs [4]. However, improvements in AMS may not correlate with the number of implemented programs, considering that the weight of each program is unlikely to be equal. In fact, the results of the LTA do not support a relationship between increasing the number of FTEs per bed and being in more favorable latent statuses. The odds ratio of status 3 versus status 5 was 1.32, indicating that more infection control practitioners might be required to improve domain 1, “antimicrobial stewardship,” whereas improvement in domains 2, 3, and 5 could not be fully explained by an increase in human resources alone. However, since previous studies, as well as our study, did not account for patient-level variations, further studies will be needed to identify factors associated with AMS other than human resources.
This study had some limitations. First, response rates were 55.0% for all hospitals with valid responses and 43.0% for those that responded to both surveys. There may have been selection bias in these hospitals. Second, hospitals participating in our study may have different profiles of cases and individual risks. To address these issues, we plan to link administrative data and the data of this study for further analyses.
Conclusion
The present nationwide surveys revealed the need for more comprehensive AMS programs; specifically, hospitals should consider introducing preauthorization and/or restriction systems for anti-MRSA antibiotics and broad-spectrum antibiotics. Our results also suggest that surveillance activities for ventilator-associated pneumonia and catheter-associated urinary tract infections need to be increased.
Supplementary Information
Additional file 1. English translation of the questionnaire for the study.
Additional file 2: Supplementary tables and a figure.
Acknowledgements
None.
Abbreviations
- AMR
Antimicrobial resistance
- AMS
Antimicrobial stewardship
- FTE
Full-time equivalent
- ICT
Infection control team
- ICU
Intensive care unit
- LTA
Latent transition analysis
- MRSA
Methicillin-resistant Staphylococcus aureus
Authors’ contributions
Conception/design of the work: JS, SM, NS, SK, MK, MY, YG, DM, KS, NO, YI. Acquisition of data: SM, NS, SK, YI. Interpretation of data: JS, TO, HI, NS, YI. Drafted the work: JS. Revised the work: JS, SM, TO, HI, NS, SK, MK, MY, YG, DM, KS, NO, YI. All authors have approved the manuscript and agree with its submission to the journal.
Funding
This work was supported by Health Labour Sciences Research Grants from the Ministry of Health, Labour and Welfare, Japan [H27-shinkogyosei-shitei-005, H29-shinkogyosei-shitei-005, and 20HA2003 to Y. I.] and JSPS KAKENHI from the Japan Society for the Promotion of Science [JP16H02634 and JP19H01075 to Y. I.]. The funders played no role in the study design, data collection, and analysis, decision to publish, or preparation of the manuscript.
Availability of data and materials
The datasets used and/or analyzed during the current study are de-identified and available from the corresponding author on reasonable request.
Ethics approval and consent to participate
This study was conducted in accordance with the Ethical Guidelines for Medical and Health Research Involving Human Subjects of the MHLW, Japan. The Ethics Committee, Graduate School of Medicine, Kyoto University has approved this study (approval number: R0849). The Ethics Committee has also approved that consent is not applicable for the study. Patients’ information was anonymized prior to analysis. No additional permission was needed from each hospital to post the questionnaire.
Consent for publication
Not applicable.
Competing interests
None.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.World Health Organization . Global action plan on antimicrobial resistance. Geneva: World Health Organization; 2015. [DOI] [PubMed] [Google Scholar]
- 2.Government of Japan. National Action Plan on Antimicrobial Resistance (AMR) 2016–2020. Available at: https://www.mhlw.go.jp/file/06-Seisakujouhou-10900000-Kenkoukyoku/0000138942.pdf. Accessed 1 Mar 2020.
- 3.Sekimoto M, Imanaka Y, Kobayashi H, Okubo T, Kizu J, Kobuse H, et al. Japan Council for Quality Health Care, expert group on healthcare-associated infection control and prevention. Factors affecting performance of hospital infection control in Japan. Am J Infect Control. 2009;37(2):136–142. doi: 10.1016/j.ajic.2008.03.005. [DOI] [PubMed] [Google Scholar]
- 4.Doernberg SB, Abbo LM, Burdette SD, Fishman NO, Goodman EL, Kravitz GR, et al. Essential resources and strategies for antibiotic stewardship programs in the acute care setting. Clin Infect Dis. 2018;67(8):1168–1174. doi: 10.1093/cid/ciy255. [DOI] [PubMed] [Google Scholar]
- 5.Maeda M, Muraki Y, Kosaka T, Yamada T, Aoki Y, Kaku M, et al. The first nationwide survey of antimicrobial stewardship programs conducted by the Japanese Society of Chemotherapy. J Infect Chemother. 2019;25(2):83–88. doi: 10.1016/j.jiac.2018.11.001. [DOI] [PubMed] [Google Scholar]
- 6.Kobayashi H, Okubo T, Kizu J, Fujii A, Tomono K, Oie S, et al. Hospital infection control programs in Japan: current practices and activities in 446 teaching hospitals. Japanese J Infect Prev Control. 2006;21(3):200–208. [Google Scholar]
- 7.Ministry of Health, Labour and Welfare. [Nosocomial infection control in healthcare institutions]. Available at: https://www.mhlw.go.jp/web/t_doc?dataId=00tc0640&dataType=1&page. Accessed 1 Mar 2020. (in Japanese).
- 8.Lanza ST, Collins LM. A new SAS procedure for latent transition analysis: transitions in dating and sexual risk behavior. Dev Psychol. 2008;44(2):446–456. doi: 10.1037/0012-1649.44.2.446. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Ryoo JH, Wang C, Swearer SM, Hull M, Shi D. Longitudinal model building using latent transition analysis: an example using school bullying data. Front Psychol. 2018;9:675. doi: 10.3389/fpsyg.2018.00675. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.The Methodology Center, Penn State. PROC LCA & PROC LTA (Version 1.3.2) [Software]. 2015 [cited 2020 March 1]. Available from: http://methodology.psu.edu/downloads/proclcalta/.
- 11.Barlam TF, Cosgrove SE, Abbo LM, MacDougall C, Schuetz AN, Septimus EJ, et al. Implementing an antibiotic stewardship program: guidelines by the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America. Clin Infect Dis. 2016;62(10):e51–e77. doi: 10.1093/cid/ciw118. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Schuts EC, Hulscher MEJL, Mouton JW, Verduin CM, Stuart JWTC, Overdiek HWPM, et al. Current evidence on hospital antimicrobial stewardship objectives: a systematic review and meta-analysis. Lancet Infect Dis. 2016;16(7):847–856. doi: 10.1016/S1473-3099(16)00065-7. [DOI] [PubMed] [Google Scholar]
- 13.Japan Infection Prevention and Control Conference for National and Public University Hospitals . Guidelines for infection control in university hospitals 2018 edition. Tokyo: Jiho; 2018. [Google Scholar]
- 14.Ling ML, Apisarnthanarak A, Jaggi N, Harrington G, Morikane K, Thu le TA, et al. APSIC guide for prevention of central line associated bloodstream infections (CLABSI). Antimicrob Resist Infect Control 2016;5:16. doi: 10.1186/s13756-016-0116-5. [DOI] [PMC free article] [PubMed]
- 15.Gould CV, Umscheid CA, Agarwal RK, Kuntz G. Pegues DA; healthcare infection control practices advisory committee. Guideline for prevention of catheter-associated urinary tract infections 2009. Infect Control Hosp Epidemiol. 2010;31(4):319–326. doi: 10.1086/651091. [DOI] [PubMed] [Google Scholar]
- 16.Weber SG, Huang SS, Oriola S, Huskins WC, Noskin GA, Harriman K, et al. Legislative mandates for use of active surveillance cultures to screen for methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococci: position statement from the joint SHEA and APIC task force. Am J Infect Control. 2007;35(2):73–85. doi: 10.1016/j.ajic.2007.01.001. [DOI] [PubMed] [Google Scholar]
- 17.World Health Organization . Guidelines for the prevention and control of carbapenem-resistant Enterobacteriaceae, Acinetobacter baumannii and Pseudomonas aeruginosa in health care facilities. Geneva: World Health Organization; 2017. [PubMed] [Google Scholar]
- 18.Japanese Society of Intensive Care Medicine. [Guidelines for setting up an intensive care unit, March 2002]. Available at: https://www.jstage.jst.go.jp/article/jsicm1994/9/2/9_2_159/_pdf/-char/ja. Accessed 1 Mar 2020. (in Japanese).
- 19.Japanese National and Public University Hospital Association for Intensive Care Unit, Revision Committee of the Clinical Practice Guidelines for Control of infection in the ICU. Guidelines for Control of infection in the ICU, 2nd edition. Tokyo: Jiho; 2013. in Japanese
- 20.De Geyter D, Blommaert L, Verbraeken N, Sevenois M, Huyghens L, Martini H, et al. The sink as a potential source of transmission of carbapenemase-producing Enterobacteriaceae in the intensive care unit. Antimicrob Resist Infect Control. 2017;6:24. 10.1186/s13756-017-0182-3. [DOI] [PMC free article] [PubMed]
- 21.Hopman J, Tostmann A, Wertheim H, Bos M, Kolwijck E, Akkermans R, et al. Reduced rate of intensive care unit acquired gram-negative bacilli after removal of sinks and introduction of ‘water-free’ patient care. Antimicrob Resist Infect Control. 2017;6:59. 10.1186/s13756-017-0213-0. [DOI] [PMC free article] [PubMed]
- 22.Tran-Dinh A, Neulier C, Amara M, Nebot N, Troché G, Breton N, et al. Impact of intensive care unit relocation and role of tap water on an outbreak of Pseudomonas aeruginosa expressing OprD-mediated resistance to imipenem. J Hosp Infect. 2018;100(3):e105–14. 10.1016/j.jhin.2018.05.016. [DOI] [PubMed]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Additional file 1. English translation of the questionnaire for the study.
Additional file 2: Supplementary tables and a figure.
Data Availability Statement
The datasets used and/or analyzed during the current study are de-identified and available from the corresponding author on reasonable request.