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Covert Observation of Hand Hygiene
Hand hygiene (HH) is believed to be one of the single most important interventions to prevent healthcare‐associated infection, yet physicians are notorious for their poor compliance.[1, 2, 3] At our 800‐bed acute care academic hospital, we implemented a multifaceted HH program[4] in 2007, which was associated with improved HH compliance rates from 43% to 87%. Despite this improvement, HH compliance among physicians remained suboptimal, with rates below 60% in some patient areas. A targeted campaign focused on recruitment of physician champions, resulted in some improvement, but physician compliance has consistently remained below performance of nurses (70%75% for physicians vs 85%90% for nurses).
Our experience parallels the results seen in multinational surveys demonstrating consistently lower physician HH compliance.[5] Given the multiple improvement efforts directed at physicians and the apparent ceiling observed in HH performance, we wanted to confirm whether physicians are truly recalcitrant to cleaning their hands, or whether lower compliance among physicians reflected a differential in the Hawthorne effect inherent to direct observation methods. Specifically, we wondered if nurses tend to recognize auditors more readily than physicians and therefore show higher apparent HH compliance when auditors are present. We also wanted to verify whether the behavior of attending physicians influenced compliance of their physician trainees. To test these hypotheses, we trained 2 clinical observers to covertly measure HH compliance of nurses and physicians on 3 different clinical services.
METHODS
Between May 27, 2015 and July 31, 2015, 2 student observers joined clinical rotations on physician and nursing teams, respectively. Healthcare teams were unaware that the student observers were measuring HH compliance during their clinical rotation. Students rotated in the emergency department, general medical and surgical wards for no more than 1 week at a time to increase exposure to different providers and minimize risk of exposing the covert observation.
Prior to the study period, the students underwent training and validation with a hospital HH auditor at another clinical setting offsite to avoid any recognition of these students by healthcare providers as observers of HH at the main hospital. Training with the auditors occurred until interobserver agreement between all HH opportunities reached 100% agreement for 2 consecutive observation days.
During their rotations, students covertly recorded HH compliance based on moments of hand hygiene[4] and also noted location, presence, and compliance of the attending physician, team size during patient encounter, and isolation requirements. Both students measured HH compliance of nurses and physicians around them. Although students spent the majority of their time with their assigned physician or nurse teams, they did not limit their observations to these individuals only, but recorded compliance of any nurse or physician on the ward as long as they were within sight during an HH opportunity. To limit clustering of observations of the same healthcare worker, up to a maximum of 2 observations per healthcare worker per day was recorded.
We compared covertly measured HH compliance with data from overt observation by hospital auditors during the same time period. Differences in proportion of HH compliance were compared with hospital audits during the same period with a 2 test. Difference between differences in overtly and covertly measured HH compliance for nurses and physicians was compared using Breslow day test.
The study was approved by the hospital's research ethics board. Although deception was used in this study,[2, 6] all data were collected for quality improvement purposes, and the aggregate results were disclosed to hospital staff following the study.
RESULTS
Covertly observed HH compliance was 50.0% (799/1597) compared with 83.7% (2769/3309) recorded by hospital auditors during the same time period (P < 0.0002) (Table 1). There was no significant difference in the compliance measured by each student (50.1%, 473/928 vs 48.7%, 326/669) (P = 0.3), and their results were combined for the rest of the analysis. Compliance before contact with the patient or patient environment was 43.1% (344/798), 74.3% (26/35) before clean/aseptic procedures, 34.8% (8/23) after potential body fluid exposure, and 56.8% (483/851) after contact with the patient or patient environment. Healthcare providers examining patients with isolation precautions were found to have a HH compliance of 74.8% (101/135) compared to 47.0% (385/820) when isolation precautions were not required (P < 0.0002).
Covert Observers, Compliance (95% CI) | Hospital Auditors, Compliance (95% CI) | Difference | |
---|---|---|---|
| |||
Overall hand hygiene compliance | 50.0% (47.6‐52.5) | 83.7% (82.4‐84.9) | 33.7% |
Service | |||
Medicine | 58.9% (55.3‐62.5) | 85.0% (82.7‐87.3) | 26.1% |
Surgery | 45.7% (41.6‐49.8) | 91.0% (87.5‐93.7) | 45.3% |
Emergency | 43.9% (38.9‐49.9) | 73.8% (68.9‐78.2) | 29.9% |
Nurses | 45.1% (41.5‐48.7) | 85.8% (83.3‐87.9) | 40.7% |
Physicians | |||
Overall compliance | 54.2% (50.9‐57.1) | 73.2% (67.3‐78.4) | 19.0% |
Trainee compliance* | 79.5% (73.6‐84.3) | ||
Trainee compliance | 18.9% (13.3‐26.1) |
Hospital auditor data showed that surgery and medicine had similarly high rates of compliance (91.0% and 85.0%, respectively), whereas the emergency department had a notably lower rate of 73.8%. Covert observation confirmed a lower rate in the emergency department (43.9%), but showed a higher compliance on general medicine than on surgery (58.9% vs 45.7%; P = 0.02). The difference in physician compliance between hospital auditors and covert observers was 19.0% (73.2%, 175/239 vs. 54.2%, 469/865); for nurses this difference was much higher at 40.7% (85.8%, 754/879 vs. 45.1%, 330/732) (P < 0.0001) (Table 1).
In terms of physician compliance, primary teams tended to have lower HH compliance of 50.4% (323/641) compared with consulting services at 57.0% (158/277) (P = 0.06). Team rounds of 3 members were associated with higher compliance compared with encounters involving <3 members (62.1%, 282/454 vs. 42.0%, 128/308) (P < 0.0002). Presence of attending physician did not affect trainee HH compliance (55.5%, 201/362 when attending present vs. 56.8%, 133/234 when attending absent; P = 0.79). However, trainee HH compliance improved markedly when attending staff cleaned their hands and decreased markedly when they did not (79.5%, 174/219 vs. 18.9%, 27/143; P < 0.0002).
DISCUSSION
We introduced covert HH observers at our hospital to determine whether differences in Hawthorne effect accounted for measured disparity between physician HH compliance, and to gain further insights into the barriers and enablers of physician HH compliance. We discovered that performance differences between physicians and nurses decreased when neither group was aware that HH was being measured, suggesting that healthcare professions are differentially affected by the Hawthorne effect. This difference may be explained by the continuity of nurses on the ward that makes them more aware of visitors like HH auditors,[7] compared with physicians who rotate periodically on the ward.
Although hospital auditors play a central role in HH education through in‐the‐moment feedback, use of these data to benchmark performance can lead to inappropriate inferences about HH compliance. Prior studies using automated HH surveillance have suggested that the magnitude of the Hawthorne effect varies based on baseline HH rates,[8] whereas our study suggests a differential Hawthorne effect between professions and clinical services. If we relied only on auditor data, we would have continued to believe that only physicians in our organization had poor HH compliance, and we would not be aware of the global nature of the HH problem.
Our results are similar to that of Pan et al., who used covert medical students to measure HH and found compliance of 44.1% compared with 94.1% by unit auditors.[2] Because their study involved an active feedback intervention, the differential in Hawthorne effect between professions could not be reliably assessed. However, they observed a progressive increase in nurse HH compliance using covert observation methods, suggesting improvement in HH performance independent of observer bias.[7]
Covert observation in our study also provided important insights regarding barriers and enablers of HH compliance. Self‐preservation behaviors were common among both nurses and physicians, as HH compliance was consistently higher after patient contact compared to before or when seeing patients who required additional precautions. This finding confirms that the perceived risk of transmission seems to be a powerful motivating factor for HH.[9] Larger groups of trainees were more likely to clean their hands, likely due to peer effects.[10] The strong impact of role modeling on HH was also noted as previously suggested in the literature,[3, 6] but our study captures the magnitude of this effect. Whether or not the attending physician cleaned their hands during rounds either positively or negatively influenced HH compliance of the rest of the physician team (80% when compliant vs 20% when noncompliant).
Our study has several important limitations. The differential Hawthorne effect seen at our center may not reflect other institutions that have numerous HH auditors or high staff turnover resulting in lower ability to recognize auditors. We cannot exclude the possibility of Hawthorne effect using covert methods that could have affected nurse and physician performance differently, but frequent rotation of the students helped maintain covertness of observations. Finally, due to the nature of the covert student observers, a longer observation time frame could not be sustained.
Our experience using covert HH auditors suggests that traditional HH audits not only overstate HH performance overall, but can lead to inaccurate inferences regarding HH performance due to relative differences in Hawthorne effect. The answer to the question regarding whether physicians clean their hands appears to be that they do just as often as nurses, but that all healthcare workers have tremendous room for improvement. We suggest that future improvement efforts will rely on more accurate HH monitoring systems and strong attending physician leadership to set an example for trainees.
Disclosures
This study was jointly funded by the Centre for Quality Improvement and Patient Safety of the University of Toronto in collaboration with Sunnybrook Health Sciences Centre. All authors report no conflicts of interest relevant to this article.
- World Health Organization. WHO guidelines on hand hygiene in health care. Available at: http://whqlibdoc.who.int/publications/2009/9789241597906_eng.pdf. Accessed April 4th, 2015.
- Compliance of health care workers with hand hygiene practices: independent advantages of overt and covert observers. PLoS One. 2013;8:e53746. , , , et al.
- Understanding practice: factors that influence physician hand hygiene compliance. Infect Control Hosp Epidemiol. 2014;35:1511–1520. , , , et al.
- (JCYH) Just Clean Your Hands. Ontario Agency for Health Promotion and Protection. Available at: http://www.publichealthontario.ca/en/BrowseByTopic/InfectiousDiseases/JustCleanYourHands/Pages/Just‐Clean‐Your‐Hands.aspx. Accessed August 4, 2015.
- Global implementation of WHO's multimodal strategy for improvement of hand hygiene: a quasi‐experimental study. Lancet Infect Dis. 2013;13:843–851. , , , et al.
- Hand hygiene adherence is influenced by the behavior of role models. Pediatr Crit Care Med. 2009;10:360–363. , , , et al.
- Quantification of the Hawthorne effect in hand hygiene compliance monitoring using an electronic monitoring system: a retrospective cohort study. BMJ Qual Saf. 2014;23:974–980. , , , .
- Variability in the Hawthorne effect with regard to hand hygiene performance in high‐ and low‐performing inpatient care units. Infect Control Hosp Epidemiol. 2009;30:222–225. , , , et al.
- Self‐protection as a driver for hand hygiene among healthcare workers. Infect Control. 2009;30:578–580. , , , et al.
- Do peer effects improve hand hygiene adherence among healthcare workers? Infect Control Hosp Epidemiol. 2014;35:1277–1285. , , et al.
Hand hygiene (HH) is believed to be one of the single most important interventions to prevent healthcare‐associated infection, yet physicians are notorious for their poor compliance.[1, 2, 3] At our 800‐bed acute care academic hospital, we implemented a multifaceted HH program[4] in 2007, which was associated with improved HH compliance rates from 43% to 87%. Despite this improvement, HH compliance among physicians remained suboptimal, with rates below 60% in some patient areas. A targeted campaign focused on recruitment of physician champions, resulted in some improvement, but physician compliance has consistently remained below performance of nurses (70%75% for physicians vs 85%90% for nurses).
Our experience parallels the results seen in multinational surveys demonstrating consistently lower physician HH compliance.[5] Given the multiple improvement efforts directed at physicians and the apparent ceiling observed in HH performance, we wanted to confirm whether physicians are truly recalcitrant to cleaning their hands, or whether lower compliance among physicians reflected a differential in the Hawthorne effect inherent to direct observation methods. Specifically, we wondered if nurses tend to recognize auditors more readily than physicians and therefore show higher apparent HH compliance when auditors are present. We also wanted to verify whether the behavior of attending physicians influenced compliance of their physician trainees. To test these hypotheses, we trained 2 clinical observers to covertly measure HH compliance of nurses and physicians on 3 different clinical services.
METHODS
Between May 27, 2015 and July 31, 2015, 2 student observers joined clinical rotations on physician and nursing teams, respectively. Healthcare teams were unaware that the student observers were measuring HH compliance during their clinical rotation. Students rotated in the emergency department, general medical and surgical wards for no more than 1 week at a time to increase exposure to different providers and minimize risk of exposing the covert observation.
Prior to the study period, the students underwent training and validation with a hospital HH auditor at another clinical setting offsite to avoid any recognition of these students by healthcare providers as observers of HH at the main hospital. Training with the auditors occurred until interobserver agreement between all HH opportunities reached 100% agreement for 2 consecutive observation days.
During their rotations, students covertly recorded HH compliance based on moments of hand hygiene[4] and also noted location, presence, and compliance of the attending physician, team size during patient encounter, and isolation requirements. Both students measured HH compliance of nurses and physicians around them. Although students spent the majority of their time with their assigned physician or nurse teams, they did not limit their observations to these individuals only, but recorded compliance of any nurse or physician on the ward as long as they were within sight during an HH opportunity. To limit clustering of observations of the same healthcare worker, up to a maximum of 2 observations per healthcare worker per day was recorded.
We compared covertly measured HH compliance with data from overt observation by hospital auditors during the same time period. Differences in proportion of HH compliance were compared with hospital audits during the same period with a 2 test. Difference between differences in overtly and covertly measured HH compliance for nurses and physicians was compared using Breslow day test.
The study was approved by the hospital's research ethics board. Although deception was used in this study,[2, 6] all data were collected for quality improvement purposes, and the aggregate results were disclosed to hospital staff following the study.
RESULTS
Covertly observed HH compliance was 50.0% (799/1597) compared with 83.7% (2769/3309) recorded by hospital auditors during the same time period (P < 0.0002) (Table 1). There was no significant difference in the compliance measured by each student (50.1%, 473/928 vs 48.7%, 326/669) (P = 0.3), and their results were combined for the rest of the analysis. Compliance before contact with the patient or patient environment was 43.1% (344/798), 74.3% (26/35) before clean/aseptic procedures, 34.8% (8/23) after potential body fluid exposure, and 56.8% (483/851) after contact with the patient or patient environment. Healthcare providers examining patients with isolation precautions were found to have a HH compliance of 74.8% (101/135) compared to 47.0% (385/820) when isolation precautions were not required (P < 0.0002).
Covert Observers, Compliance (95% CI) | Hospital Auditors, Compliance (95% CI) | Difference | |
---|---|---|---|
| |||
Overall hand hygiene compliance | 50.0% (47.6‐52.5) | 83.7% (82.4‐84.9) | 33.7% |
Service | |||
Medicine | 58.9% (55.3‐62.5) | 85.0% (82.7‐87.3) | 26.1% |
Surgery | 45.7% (41.6‐49.8) | 91.0% (87.5‐93.7) | 45.3% |
Emergency | 43.9% (38.9‐49.9) | 73.8% (68.9‐78.2) | 29.9% |
Nurses | 45.1% (41.5‐48.7) | 85.8% (83.3‐87.9) | 40.7% |
Physicians | |||
Overall compliance | 54.2% (50.9‐57.1) | 73.2% (67.3‐78.4) | 19.0% |
Trainee compliance* | 79.5% (73.6‐84.3) | ||
Trainee compliance | 18.9% (13.3‐26.1) |
Hospital auditor data showed that surgery and medicine had similarly high rates of compliance (91.0% and 85.0%, respectively), whereas the emergency department had a notably lower rate of 73.8%. Covert observation confirmed a lower rate in the emergency department (43.9%), but showed a higher compliance on general medicine than on surgery (58.9% vs 45.7%; P = 0.02). The difference in physician compliance between hospital auditors and covert observers was 19.0% (73.2%, 175/239 vs. 54.2%, 469/865); for nurses this difference was much higher at 40.7% (85.8%, 754/879 vs. 45.1%, 330/732) (P < 0.0001) (Table 1).
In terms of physician compliance, primary teams tended to have lower HH compliance of 50.4% (323/641) compared with consulting services at 57.0% (158/277) (P = 0.06). Team rounds of 3 members were associated with higher compliance compared with encounters involving <3 members (62.1%, 282/454 vs. 42.0%, 128/308) (P < 0.0002). Presence of attending physician did not affect trainee HH compliance (55.5%, 201/362 when attending present vs. 56.8%, 133/234 when attending absent; P = 0.79). However, trainee HH compliance improved markedly when attending staff cleaned their hands and decreased markedly when they did not (79.5%, 174/219 vs. 18.9%, 27/143; P < 0.0002).
DISCUSSION
We introduced covert HH observers at our hospital to determine whether differences in Hawthorne effect accounted for measured disparity between physician HH compliance, and to gain further insights into the barriers and enablers of physician HH compliance. We discovered that performance differences between physicians and nurses decreased when neither group was aware that HH was being measured, suggesting that healthcare professions are differentially affected by the Hawthorne effect. This difference may be explained by the continuity of nurses on the ward that makes them more aware of visitors like HH auditors,[7] compared with physicians who rotate periodically on the ward.
Although hospital auditors play a central role in HH education through in‐the‐moment feedback, use of these data to benchmark performance can lead to inappropriate inferences about HH compliance. Prior studies using automated HH surveillance have suggested that the magnitude of the Hawthorne effect varies based on baseline HH rates,[8] whereas our study suggests a differential Hawthorne effect between professions and clinical services. If we relied only on auditor data, we would have continued to believe that only physicians in our organization had poor HH compliance, and we would not be aware of the global nature of the HH problem.
Our results are similar to that of Pan et al., who used covert medical students to measure HH and found compliance of 44.1% compared with 94.1% by unit auditors.[2] Because their study involved an active feedback intervention, the differential in Hawthorne effect between professions could not be reliably assessed. However, they observed a progressive increase in nurse HH compliance using covert observation methods, suggesting improvement in HH performance independent of observer bias.[7]
Covert observation in our study also provided important insights regarding barriers and enablers of HH compliance. Self‐preservation behaviors were common among both nurses and physicians, as HH compliance was consistently higher after patient contact compared to before or when seeing patients who required additional precautions. This finding confirms that the perceived risk of transmission seems to be a powerful motivating factor for HH.[9] Larger groups of trainees were more likely to clean their hands, likely due to peer effects.[10] The strong impact of role modeling on HH was also noted as previously suggested in the literature,[3, 6] but our study captures the magnitude of this effect. Whether or not the attending physician cleaned their hands during rounds either positively or negatively influenced HH compliance of the rest of the physician team (80% when compliant vs 20% when noncompliant).
Our study has several important limitations. The differential Hawthorne effect seen at our center may not reflect other institutions that have numerous HH auditors or high staff turnover resulting in lower ability to recognize auditors. We cannot exclude the possibility of Hawthorne effect using covert methods that could have affected nurse and physician performance differently, but frequent rotation of the students helped maintain covertness of observations. Finally, due to the nature of the covert student observers, a longer observation time frame could not be sustained.
Our experience using covert HH auditors suggests that traditional HH audits not only overstate HH performance overall, but can lead to inaccurate inferences regarding HH performance due to relative differences in Hawthorne effect. The answer to the question regarding whether physicians clean their hands appears to be that they do just as often as nurses, but that all healthcare workers have tremendous room for improvement. We suggest that future improvement efforts will rely on more accurate HH monitoring systems and strong attending physician leadership to set an example for trainees.
Disclosures
This study was jointly funded by the Centre for Quality Improvement and Patient Safety of the University of Toronto in collaboration with Sunnybrook Health Sciences Centre. All authors report no conflicts of interest relevant to this article.
Hand hygiene (HH) is believed to be one of the single most important interventions to prevent healthcare‐associated infection, yet physicians are notorious for their poor compliance.[1, 2, 3] At our 800‐bed acute care academic hospital, we implemented a multifaceted HH program[4] in 2007, which was associated with improved HH compliance rates from 43% to 87%. Despite this improvement, HH compliance among physicians remained suboptimal, with rates below 60% in some patient areas. A targeted campaign focused on recruitment of physician champions, resulted in some improvement, but physician compliance has consistently remained below performance of nurses (70%75% for physicians vs 85%90% for nurses).
Our experience parallels the results seen in multinational surveys demonstrating consistently lower physician HH compliance.[5] Given the multiple improvement efforts directed at physicians and the apparent ceiling observed in HH performance, we wanted to confirm whether physicians are truly recalcitrant to cleaning their hands, or whether lower compliance among physicians reflected a differential in the Hawthorne effect inherent to direct observation methods. Specifically, we wondered if nurses tend to recognize auditors more readily than physicians and therefore show higher apparent HH compliance when auditors are present. We also wanted to verify whether the behavior of attending physicians influenced compliance of their physician trainees. To test these hypotheses, we trained 2 clinical observers to covertly measure HH compliance of nurses and physicians on 3 different clinical services.
METHODS
Between May 27, 2015 and July 31, 2015, 2 student observers joined clinical rotations on physician and nursing teams, respectively. Healthcare teams were unaware that the student observers were measuring HH compliance during their clinical rotation. Students rotated in the emergency department, general medical and surgical wards for no more than 1 week at a time to increase exposure to different providers and minimize risk of exposing the covert observation.
Prior to the study period, the students underwent training and validation with a hospital HH auditor at another clinical setting offsite to avoid any recognition of these students by healthcare providers as observers of HH at the main hospital. Training with the auditors occurred until interobserver agreement between all HH opportunities reached 100% agreement for 2 consecutive observation days.
During their rotations, students covertly recorded HH compliance based on moments of hand hygiene[4] and also noted location, presence, and compliance of the attending physician, team size during patient encounter, and isolation requirements. Both students measured HH compliance of nurses and physicians around them. Although students spent the majority of their time with their assigned physician or nurse teams, they did not limit their observations to these individuals only, but recorded compliance of any nurse or physician on the ward as long as they were within sight during an HH opportunity. To limit clustering of observations of the same healthcare worker, up to a maximum of 2 observations per healthcare worker per day was recorded.
We compared covertly measured HH compliance with data from overt observation by hospital auditors during the same time period. Differences in proportion of HH compliance were compared with hospital audits during the same period with a 2 test. Difference between differences in overtly and covertly measured HH compliance for nurses and physicians was compared using Breslow day test.
The study was approved by the hospital's research ethics board. Although deception was used in this study,[2, 6] all data were collected for quality improvement purposes, and the aggregate results were disclosed to hospital staff following the study.
RESULTS
Covertly observed HH compliance was 50.0% (799/1597) compared with 83.7% (2769/3309) recorded by hospital auditors during the same time period (P < 0.0002) (Table 1). There was no significant difference in the compliance measured by each student (50.1%, 473/928 vs 48.7%, 326/669) (P = 0.3), and their results were combined for the rest of the analysis. Compliance before contact with the patient or patient environment was 43.1% (344/798), 74.3% (26/35) before clean/aseptic procedures, 34.8% (8/23) after potential body fluid exposure, and 56.8% (483/851) after contact with the patient or patient environment. Healthcare providers examining patients with isolation precautions were found to have a HH compliance of 74.8% (101/135) compared to 47.0% (385/820) when isolation precautions were not required (P < 0.0002).
Covert Observers, Compliance (95% CI) | Hospital Auditors, Compliance (95% CI) | Difference | |
---|---|---|---|
| |||
Overall hand hygiene compliance | 50.0% (47.6‐52.5) | 83.7% (82.4‐84.9) | 33.7% |
Service | |||
Medicine | 58.9% (55.3‐62.5) | 85.0% (82.7‐87.3) | 26.1% |
Surgery | 45.7% (41.6‐49.8) | 91.0% (87.5‐93.7) | 45.3% |
Emergency | 43.9% (38.9‐49.9) | 73.8% (68.9‐78.2) | 29.9% |
Nurses | 45.1% (41.5‐48.7) | 85.8% (83.3‐87.9) | 40.7% |
Physicians | |||
Overall compliance | 54.2% (50.9‐57.1) | 73.2% (67.3‐78.4) | 19.0% |
Trainee compliance* | 79.5% (73.6‐84.3) | ||
Trainee compliance | 18.9% (13.3‐26.1) |
Hospital auditor data showed that surgery and medicine had similarly high rates of compliance (91.0% and 85.0%, respectively), whereas the emergency department had a notably lower rate of 73.8%. Covert observation confirmed a lower rate in the emergency department (43.9%), but showed a higher compliance on general medicine than on surgery (58.9% vs 45.7%; P = 0.02). The difference in physician compliance between hospital auditors and covert observers was 19.0% (73.2%, 175/239 vs. 54.2%, 469/865); for nurses this difference was much higher at 40.7% (85.8%, 754/879 vs. 45.1%, 330/732) (P < 0.0001) (Table 1).
In terms of physician compliance, primary teams tended to have lower HH compliance of 50.4% (323/641) compared with consulting services at 57.0% (158/277) (P = 0.06). Team rounds of 3 members were associated with higher compliance compared with encounters involving <3 members (62.1%, 282/454 vs. 42.0%, 128/308) (P < 0.0002). Presence of attending physician did not affect trainee HH compliance (55.5%, 201/362 when attending present vs. 56.8%, 133/234 when attending absent; P = 0.79). However, trainee HH compliance improved markedly when attending staff cleaned their hands and decreased markedly when they did not (79.5%, 174/219 vs. 18.9%, 27/143; P < 0.0002).
DISCUSSION
We introduced covert HH observers at our hospital to determine whether differences in Hawthorne effect accounted for measured disparity between physician HH compliance, and to gain further insights into the barriers and enablers of physician HH compliance. We discovered that performance differences between physicians and nurses decreased when neither group was aware that HH was being measured, suggesting that healthcare professions are differentially affected by the Hawthorne effect. This difference may be explained by the continuity of nurses on the ward that makes them more aware of visitors like HH auditors,[7] compared with physicians who rotate periodically on the ward.
Although hospital auditors play a central role in HH education through in‐the‐moment feedback, use of these data to benchmark performance can lead to inappropriate inferences about HH compliance. Prior studies using automated HH surveillance have suggested that the magnitude of the Hawthorne effect varies based on baseline HH rates,[8] whereas our study suggests a differential Hawthorne effect between professions and clinical services. If we relied only on auditor data, we would have continued to believe that only physicians in our organization had poor HH compliance, and we would not be aware of the global nature of the HH problem.
Our results are similar to that of Pan et al., who used covert medical students to measure HH and found compliance of 44.1% compared with 94.1% by unit auditors.[2] Because their study involved an active feedback intervention, the differential in Hawthorne effect between professions could not be reliably assessed. However, they observed a progressive increase in nurse HH compliance using covert observation methods, suggesting improvement in HH performance independent of observer bias.[7]
Covert observation in our study also provided important insights regarding barriers and enablers of HH compliance. Self‐preservation behaviors were common among both nurses and physicians, as HH compliance was consistently higher after patient contact compared to before or when seeing patients who required additional precautions. This finding confirms that the perceived risk of transmission seems to be a powerful motivating factor for HH.[9] Larger groups of trainees were more likely to clean their hands, likely due to peer effects.[10] The strong impact of role modeling on HH was also noted as previously suggested in the literature,[3, 6] but our study captures the magnitude of this effect. Whether or not the attending physician cleaned their hands during rounds either positively or negatively influenced HH compliance of the rest of the physician team (80% when compliant vs 20% when noncompliant).
Our study has several important limitations. The differential Hawthorne effect seen at our center may not reflect other institutions that have numerous HH auditors or high staff turnover resulting in lower ability to recognize auditors. We cannot exclude the possibility of Hawthorne effect using covert methods that could have affected nurse and physician performance differently, but frequent rotation of the students helped maintain covertness of observations. Finally, due to the nature of the covert student observers, a longer observation time frame could not be sustained.
Our experience using covert HH auditors suggests that traditional HH audits not only overstate HH performance overall, but can lead to inaccurate inferences regarding HH performance due to relative differences in Hawthorne effect. The answer to the question regarding whether physicians clean their hands appears to be that they do just as often as nurses, but that all healthcare workers have tremendous room for improvement. We suggest that future improvement efforts will rely on more accurate HH monitoring systems and strong attending physician leadership to set an example for trainees.
Disclosures
This study was jointly funded by the Centre for Quality Improvement and Patient Safety of the University of Toronto in collaboration with Sunnybrook Health Sciences Centre. All authors report no conflicts of interest relevant to this article.
- World Health Organization. WHO guidelines on hand hygiene in health care. Available at: http://whqlibdoc.who.int/publications/2009/9789241597906_eng.pdf. Accessed April 4th, 2015.
- Compliance of health care workers with hand hygiene practices: independent advantages of overt and covert observers. PLoS One. 2013;8:e53746. , , , et al.
- Understanding practice: factors that influence physician hand hygiene compliance. Infect Control Hosp Epidemiol. 2014;35:1511–1520. , , , et al.
- (JCYH) Just Clean Your Hands. Ontario Agency for Health Promotion and Protection. Available at: http://www.publichealthontario.ca/en/BrowseByTopic/InfectiousDiseases/JustCleanYourHands/Pages/Just‐Clean‐Your‐Hands.aspx. Accessed August 4, 2015.
- Global implementation of WHO's multimodal strategy for improvement of hand hygiene: a quasi‐experimental study. Lancet Infect Dis. 2013;13:843–851. , , , et al.
- Hand hygiene adherence is influenced by the behavior of role models. Pediatr Crit Care Med. 2009;10:360–363. , , , et al.
- Quantification of the Hawthorne effect in hand hygiene compliance monitoring using an electronic monitoring system: a retrospective cohort study. BMJ Qual Saf. 2014;23:974–980. , , , .
- Variability in the Hawthorne effect with regard to hand hygiene performance in high‐ and low‐performing inpatient care units. Infect Control Hosp Epidemiol. 2009;30:222–225. , , , et al.
- Self‐protection as a driver for hand hygiene among healthcare workers. Infect Control. 2009;30:578–580. , , , et al.
- Do peer effects improve hand hygiene adherence among healthcare workers? Infect Control Hosp Epidemiol. 2014;35:1277–1285. , , et al.
- World Health Organization. WHO guidelines on hand hygiene in health care. Available at: http://whqlibdoc.who.int/publications/2009/9789241597906_eng.pdf. Accessed April 4th, 2015.
- Compliance of health care workers with hand hygiene practices: independent advantages of overt and covert observers. PLoS One. 2013;8:e53746. , , , et al.
- Understanding practice: factors that influence physician hand hygiene compliance. Infect Control Hosp Epidemiol. 2014;35:1511–1520. , , , et al.
- (JCYH) Just Clean Your Hands. Ontario Agency for Health Promotion and Protection. Available at: http://www.publichealthontario.ca/en/BrowseByTopic/InfectiousDiseases/JustCleanYourHands/Pages/Just‐Clean‐Your‐Hands.aspx. Accessed August 4, 2015.
- Global implementation of WHO's multimodal strategy for improvement of hand hygiene: a quasi‐experimental study. Lancet Infect Dis. 2013;13:843–851. , , , et al.
- Hand hygiene adherence is influenced by the behavior of role models. Pediatr Crit Care Med. 2009;10:360–363. , , , et al.
- Quantification of the Hawthorne effect in hand hygiene compliance monitoring using an electronic monitoring system: a retrospective cohort study. BMJ Qual Saf. 2014;23:974–980. , , , .
- Variability in the Hawthorne effect with regard to hand hygiene performance in high‐ and low‐performing inpatient care units. Infect Control Hosp Epidemiol. 2009;30:222–225. , , , et al.
- Self‐protection as a driver for hand hygiene among healthcare workers. Infect Control. 2009;30:578–580. , , , et al.
- Do peer effects improve hand hygiene adherence among healthcare workers? Infect Control Hosp Epidemiol. 2014;35:1277–1285. , , et al.
Catheter Use Among Teaching Hospitals
Urinary catheter use can be associated with urinary tract infections, delirium, trauma, and immobility.[1] Evidence‐based strategies to reduce inappropriate use are available[2]; however, their application across centers is variable.[3] We aimed to characterize the prevalence and indication for catheters among Canadian teaching hospitals with and without catheter reduction programs.
METHODS
Twelve of 17 postgraduate internal medicine training program directors agreed to participate, and 9 Canadian teaching hospitals enrolled in this prevalence study of urinary catheter use among medical inpatients. Data collection used a standardized form and took place over 5 consecutive weekdays during August 2015. Each site anonymously collected the total number of catheters, total number of inpatient‐days, and indications for use from either the bedside nurse or physician. Appropriate clinical indications were based on the 2009 guidelines from the Healthcare Infection Control Practice Advisory Committee.[4] Potentially inappropriate indications included urine output measurement in noncritically ill patients, and other or unknown indications.[4, 5] A catheter reduction program was defined as the presence of a structured system to monitor and reduce use via: nurse‐directed catheter removal, audit‐feedback of use to providers, physician reminders, and/or automatic stop orders.
The primary outcome was the number of catheter days per 100 inpatient‐days. We used generalized estimating equations to adjust the 95% confidence interval (CI) and P value to account for hospital‐level clustering of the responses. The P values are from a 2‐tailed Wald test against the true log scale parameter being equal to zero. The analysis was performed using R version 3.0.2 using the geepack package (Free Software Foundation, Boston, MA).
The McGill University Health Centre Research Ethics Board approved this study with concomitant authorization at participating sites.
RESULTS
The characteristics of participating hospitals are displayed in Table 1. Those with active catheter reduction programs reported established systems for monitoring catheter placement, duration, and catheter‐associated urinary tract infections. More than half of the hospitals lacked a catheter reduction program. Overall, catheters were present on 13.6% of patient‐days (range, 2.3%32.4%). Centers without reduction programs reported higher rates of catheter use both overall and for potentially inappropriate indications. After adjustment for clustering, those with a formal intervention had 8.8 fewer catheter days per 100 patient‐days as compared to those without (9.8 [95% CI: 6.0‐15.6] vs 18.6 [95% CI: 13.0‐26.1], P = 0.03). This meant that the odds of a urinary catheter being present were 2 times (95% CI: 1.0‐3.4) greater in hospitals without reduction programs. Differences in appropriate catheter use did not reach statistical significance.
Characteristic | Hospital | Overall, n (%)* | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
A | B | C | D | E | F | G | H | I | ||
| ||||||||||
Total beds, n | 442 | 533 | 824 | 505 | 272 | 925 | 650 | 777 | 446 | 5,374 |
Has system in place to monitor urinary catheter placement | Yes | Yes | Yes | Yes | No | No | No | No | No | N/A |
Has system in place to monitor duration and/or discontinuation of urinary catheters | Yes | Yes | Yes | No | No | No | No | No | No | N/A |
Has a system in place for monitoring catheter associated urinary tract infection rates | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No | No | N/A |
Presence of a UC reduction program | Active | Active | Active | Active | No | No | No | No | No | N/A |
Duration of UC reduction program, y | 1 | 2 | 1 | 1 | N/A | N/A | N/A | N/A | N/A | N/A |
Total patient‐days | 425 | 455 | 527 | 405 | 87 | 311 | 285 | 394 | 253 | 3142 |
Total UC days | 27 | 32 | 42 | 77 | 2 | 36 | 48 | 80 | 82 | 426 |
UC rate per 100 patient‐days | 6.4 | 7.0 | 8.0 | 19.0 | 2.3 | 11.6 | 16.8 | 20.3 | 32.4 | 13.6 |
Reported historical UC rate per 100 patient‐days∥ | 12.0 | 16.5 | 18.8 | N/A | N/A | N/A | N/A | N/A | N/A | N/A |
Potentially appropriate indications, n (%) | 19 (70) | 25 (78) | 30 (71) | 36 (47) | 0 | 33 (92) | 27 (56) | 32 (40) | 59 (72) | 261 (61) |
Obstruction | 5 (19) | 11 (34) | 19 (45) | 7 (9) | 0 | 1 (3) | 10 (21) | 20 (25) | 2 (2) | 75 (17.6) |
Retention | 10 (37) | 9 (28) | 7 (17) | 21 (27) | 0 | 22 (61) | 9 (19) | 11 (14) | 23 (28) | 112 (26.3) |
Palliative | 4 (15) | 0 | 4 (10) | 8 (10) | 0 | 10 (28) | 5 (10) | 1 (1) | 16 (20) | 93 (21.8) |
Sacral ulcer | 0 | 5 (16) | 0 | 0 | 0 | 0 | 3 (6) | 0 | 18 (22) | 26 (6.1) |
Potentially inappropriate indications, n (%) | 8 (30) | 8 (25) | 12 (28) | 50 (65) | 2 (100) | 3 (8) | 21 (44) | 70 (88) | 16 (20) | 190 (45) |
Urine output | 2 (7) | 0 | 1 (2) | 22 (14) | 2 (100) | 3 (8) | 11 (23) | 50 (35) | 8 (10) | 96 (22.5) |
Other | 6 (22) | 8 (25) | 10 (24) | 26 (32) | 0 | 0 | 5 (10) | 13 (16) | 0 | 68 (16.0) |
Unknown | 0 | 0 | 1 (2) | 2 (3) | 0 | 0 | 5 (10) | 7 (9) | 8 (10) | 23 (5.3) |
DISCUSSION
Despite the availability of consensus guidelines for appropriate use and the efforts of movements like Choosing Wisely, many Canadian teaching hospitals have not yet established a urinary catheter reduction program for medical inpatients. Our findings are similar to 2 non‐Canadian studies, which demonstrated that fewer than half of hospitals had implemented control measures.[4, 6] In contrast to those other studies, our study demonstrated that hospitals that employed control measures had reduced rates of catheter use suggesting that systematic, structured efforts are necessary to improve practice.[7, 8]
Ours is the first nation‐wide study in Canada to report urinary catheter rates and the effect of associated reduction programs. Data from the National Healthcare Safety Network suggest our Canadian estimates of urinary catheter rates in medical inpatients are similar to those of the United States (13.6 vs 14.8 catheter days per 100 inpatient‐days, respectively, for general medical inpatients).[9, 10]
Several limitations of this study warrant discussion. First, we sampled only academic institutions at 1 time point, which may not represent annualized rates or rates in community hospitals. However, our findings are similar to those reported in previous studies.[10] Second, our method of consecutive daily audits may have caused individuals to change their behavior knowing that they were being observed, resulting in lower catheter utilization than would have been otherwise present and biasing our estimates of catheter overuse downward. Third, we collected point prevalence data, limiting our ability to make inferences on causality. The key factor(s) contributing to observed differences between hospitals remains unknown. However, pre‐post intervention data available for 3 hospitals suggest that improvements followed active catheter reduction efforts.[7, 8] Fourth, we were unable to obtain outcome data such as catheter‐associated urinary tract infection, delirium, or fall rates. However, catheter reduction is widely recognized as an important first step to reducing preventable harm for hospital patients.
We suggest that the broader uptake of structured models of care that promote early discontinuation of urinary catheters on medical wards is needed to improve their appropriateness. Fortunately, it appears as though a variety of models are effective. Therefore, when it comes to adopting Choosing Wisely's less is more philosophy toward urinary catheter utilization, we suggest that less time be allowed to pass before more proven and structured interventions are universally implemented.
Acknowledgements
The authors are indebted to John Matelski, MSc, for statistical analyses.
Disclosures: The Canadian Society of Internal Medicine and its Choosing Wisely Canada Subcommittee supported this work. The authors report no conflicts of interest.
- Diagnosis, prevention, and treatment of catheter‐associated urinary tract infection in adults: 2009 international clinical practice guidelines from the Infectious Diseases Society of America. Clin Infect Dis. 2010;50(5):625–663. , , , et al.
- Strategies to prevent catheter‐associated urinary tract infections in acute care hospitals: 2014 update. Infect Control Hosp Epidemiol. 2014;35(5):464–479. , , , et al.
- Preventing catheter‐associated urinary tract infection in the United States: a national comparative study. JAMA Intern Med. 2013;173(10):874–879. , , , et al.
- 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. , , , et al,
- Are physicians aware of which of their patients have indwelling urinary catheters? Am J Med. 2000;109(6):476–480. , , , et al.
- Adoption of policies to prevent catheter‐associated urinary tract infections in United States intensive care units. Am J Infect Control. 2012;40(8):705–710. , , , et al.
- Medical directive for urinary catheter removal by nurses on general medical wards. JAMA Intern Med. 2016;176(1):113–115. , , , et al.
- Novel low‐resource intervention reduces urinary catheter use and associated urinary tract infections: role of outcome measure bias? Am J Infect Control. 2015;43(4):348–353. , , , et al.
- National Healthcare Safety Network report, data summary for 2013, Device-associated Module. Am J Infect Control. 2015;43(3):206–221. , , , et al.
- Regional variation in urinary catheter use and catheter‐associated urinary tract infection: results from a national collaborative. Infect Control Hosp Epidemiol. 2014;35(suppl 3):S99–S106. , , , et al.
Urinary catheter use can be associated with urinary tract infections, delirium, trauma, and immobility.[1] Evidence‐based strategies to reduce inappropriate use are available[2]; however, their application across centers is variable.[3] We aimed to characterize the prevalence and indication for catheters among Canadian teaching hospitals with and without catheter reduction programs.
METHODS
Twelve of 17 postgraduate internal medicine training program directors agreed to participate, and 9 Canadian teaching hospitals enrolled in this prevalence study of urinary catheter use among medical inpatients. Data collection used a standardized form and took place over 5 consecutive weekdays during August 2015. Each site anonymously collected the total number of catheters, total number of inpatient‐days, and indications for use from either the bedside nurse or physician. Appropriate clinical indications were based on the 2009 guidelines from the Healthcare Infection Control Practice Advisory Committee.[4] Potentially inappropriate indications included urine output measurement in noncritically ill patients, and other or unknown indications.[4, 5] A catheter reduction program was defined as the presence of a structured system to monitor and reduce use via: nurse‐directed catheter removal, audit‐feedback of use to providers, physician reminders, and/or automatic stop orders.
The primary outcome was the number of catheter days per 100 inpatient‐days. We used generalized estimating equations to adjust the 95% confidence interval (CI) and P value to account for hospital‐level clustering of the responses. The P values are from a 2‐tailed Wald test against the true log scale parameter being equal to zero. The analysis was performed using R version 3.0.2 using the geepack package (Free Software Foundation, Boston, MA).
The McGill University Health Centre Research Ethics Board approved this study with concomitant authorization at participating sites.
RESULTS
The characteristics of participating hospitals are displayed in Table 1. Those with active catheter reduction programs reported established systems for monitoring catheter placement, duration, and catheter‐associated urinary tract infections. More than half of the hospitals lacked a catheter reduction program. Overall, catheters were present on 13.6% of patient‐days (range, 2.3%32.4%). Centers without reduction programs reported higher rates of catheter use both overall and for potentially inappropriate indications. After adjustment for clustering, those with a formal intervention had 8.8 fewer catheter days per 100 patient‐days as compared to those without (9.8 [95% CI: 6.0‐15.6] vs 18.6 [95% CI: 13.0‐26.1], P = 0.03). This meant that the odds of a urinary catheter being present were 2 times (95% CI: 1.0‐3.4) greater in hospitals without reduction programs. Differences in appropriate catheter use did not reach statistical significance.
Characteristic | Hospital | Overall, n (%)* | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
A | B | C | D | E | F | G | H | I | ||
| ||||||||||
Total beds, n | 442 | 533 | 824 | 505 | 272 | 925 | 650 | 777 | 446 | 5,374 |
Has system in place to monitor urinary catheter placement | Yes | Yes | Yes | Yes | No | No | No | No | No | N/A |
Has system in place to monitor duration and/or discontinuation of urinary catheters | Yes | Yes | Yes | No | No | No | No | No | No | N/A |
Has a system in place for monitoring catheter associated urinary tract infection rates | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No | No | N/A |
Presence of a UC reduction program | Active | Active | Active | Active | No | No | No | No | No | N/A |
Duration of UC reduction program, y | 1 | 2 | 1 | 1 | N/A | N/A | N/A | N/A | N/A | N/A |
Total patient‐days | 425 | 455 | 527 | 405 | 87 | 311 | 285 | 394 | 253 | 3142 |
Total UC days | 27 | 32 | 42 | 77 | 2 | 36 | 48 | 80 | 82 | 426 |
UC rate per 100 patient‐days | 6.4 | 7.0 | 8.0 | 19.0 | 2.3 | 11.6 | 16.8 | 20.3 | 32.4 | 13.6 |
Reported historical UC rate per 100 patient‐days∥ | 12.0 | 16.5 | 18.8 | N/A | N/A | N/A | N/A | N/A | N/A | N/A |
Potentially appropriate indications, n (%) | 19 (70) | 25 (78) | 30 (71) | 36 (47) | 0 | 33 (92) | 27 (56) | 32 (40) | 59 (72) | 261 (61) |
Obstruction | 5 (19) | 11 (34) | 19 (45) | 7 (9) | 0 | 1 (3) | 10 (21) | 20 (25) | 2 (2) | 75 (17.6) |
Retention | 10 (37) | 9 (28) | 7 (17) | 21 (27) | 0 | 22 (61) | 9 (19) | 11 (14) | 23 (28) | 112 (26.3) |
Palliative | 4 (15) | 0 | 4 (10) | 8 (10) | 0 | 10 (28) | 5 (10) | 1 (1) | 16 (20) | 93 (21.8) |
Sacral ulcer | 0 | 5 (16) | 0 | 0 | 0 | 0 | 3 (6) | 0 | 18 (22) | 26 (6.1) |
Potentially inappropriate indications, n (%) | 8 (30) | 8 (25) | 12 (28) | 50 (65) | 2 (100) | 3 (8) | 21 (44) | 70 (88) | 16 (20) | 190 (45) |
Urine output | 2 (7) | 0 | 1 (2) | 22 (14) | 2 (100) | 3 (8) | 11 (23) | 50 (35) | 8 (10) | 96 (22.5) |
Other | 6 (22) | 8 (25) | 10 (24) | 26 (32) | 0 | 0 | 5 (10) | 13 (16) | 0 | 68 (16.0) |
Unknown | 0 | 0 | 1 (2) | 2 (3) | 0 | 0 | 5 (10) | 7 (9) | 8 (10) | 23 (5.3) |
DISCUSSION
Despite the availability of consensus guidelines for appropriate use and the efforts of movements like Choosing Wisely, many Canadian teaching hospitals have not yet established a urinary catheter reduction program for medical inpatients. Our findings are similar to 2 non‐Canadian studies, which demonstrated that fewer than half of hospitals had implemented control measures.[4, 6] In contrast to those other studies, our study demonstrated that hospitals that employed control measures had reduced rates of catheter use suggesting that systematic, structured efforts are necessary to improve practice.[7, 8]
Ours is the first nation‐wide study in Canada to report urinary catheter rates and the effect of associated reduction programs. Data from the National Healthcare Safety Network suggest our Canadian estimates of urinary catheter rates in medical inpatients are similar to those of the United States (13.6 vs 14.8 catheter days per 100 inpatient‐days, respectively, for general medical inpatients).[9, 10]
Several limitations of this study warrant discussion. First, we sampled only academic institutions at 1 time point, which may not represent annualized rates or rates in community hospitals. However, our findings are similar to those reported in previous studies.[10] Second, our method of consecutive daily audits may have caused individuals to change their behavior knowing that they were being observed, resulting in lower catheter utilization than would have been otherwise present and biasing our estimates of catheter overuse downward. Third, we collected point prevalence data, limiting our ability to make inferences on causality. The key factor(s) contributing to observed differences between hospitals remains unknown. However, pre‐post intervention data available for 3 hospitals suggest that improvements followed active catheter reduction efforts.[7, 8] Fourth, we were unable to obtain outcome data such as catheter‐associated urinary tract infection, delirium, or fall rates. However, catheter reduction is widely recognized as an important first step to reducing preventable harm for hospital patients.
We suggest that the broader uptake of structured models of care that promote early discontinuation of urinary catheters on medical wards is needed to improve their appropriateness. Fortunately, it appears as though a variety of models are effective. Therefore, when it comes to adopting Choosing Wisely's less is more philosophy toward urinary catheter utilization, we suggest that less time be allowed to pass before more proven and structured interventions are universally implemented.
Acknowledgements
The authors are indebted to John Matelski, MSc, for statistical analyses.
Disclosures: The Canadian Society of Internal Medicine and its Choosing Wisely Canada Subcommittee supported this work. The authors report no conflicts of interest.
Urinary catheter use can be associated with urinary tract infections, delirium, trauma, and immobility.[1] Evidence‐based strategies to reduce inappropriate use are available[2]; however, their application across centers is variable.[3] We aimed to characterize the prevalence and indication for catheters among Canadian teaching hospitals with and without catheter reduction programs.
METHODS
Twelve of 17 postgraduate internal medicine training program directors agreed to participate, and 9 Canadian teaching hospitals enrolled in this prevalence study of urinary catheter use among medical inpatients. Data collection used a standardized form and took place over 5 consecutive weekdays during August 2015. Each site anonymously collected the total number of catheters, total number of inpatient‐days, and indications for use from either the bedside nurse or physician. Appropriate clinical indications were based on the 2009 guidelines from the Healthcare Infection Control Practice Advisory Committee.[4] Potentially inappropriate indications included urine output measurement in noncritically ill patients, and other or unknown indications.[4, 5] A catheter reduction program was defined as the presence of a structured system to monitor and reduce use via: nurse‐directed catheter removal, audit‐feedback of use to providers, physician reminders, and/or automatic stop orders.
The primary outcome was the number of catheter days per 100 inpatient‐days. We used generalized estimating equations to adjust the 95% confidence interval (CI) and P value to account for hospital‐level clustering of the responses. The P values are from a 2‐tailed Wald test against the true log scale parameter being equal to zero. The analysis was performed using R version 3.0.2 using the geepack package (Free Software Foundation, Boston, MA).
The McGill University Health Centre Research Ethics Board approved this study with concomitant authorization at participating sites.
RESULTS
The characteristics of participating hospitals are displayed in Table 1. Those with active catheter reduction programs reported established systems for monitoring catheter placement, duration, and catheter‐associated urinary tract infections. More than half of the hospitals lacked a catheter reduction program. Overall, catheters were present on 13.6% of patient‐days (range, 2.3%32.4%). Centers without reduction programs reported higher rates of catheter use both overall and for potentially inappropriate indications. After adjustment for clustering, those with a formal intervention had 8.8 fewer catheter days per 100 patient‐days as compared to those without (9.8 [95% CI: 6.0‐15.6] vs 18.6 [95% CI: 13.0‐26.1], P = 0.03). This meant that the odds of a urinary catheter being present were 2 times (95% CI: 1.0‐3.4) greater in hospitals without reduction programs. Differences in appropriate catheter use did not reach statistical significance.
Characteristic | Hospital | Overall, n (%)* | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
A | B | C | D | E | F | G | H | I | ||
| ||||||||||
Total beds, n | 442 | 533 | 824 | 505 | 272 | 925 | 650 | 777 | 446 | 5,374 |
Has system in place to monitor urinary catheter placement | Yes | Yes | Yes | Yes | No | No | No | No | No | N/A |
Has system in place to monitor duration and/or discontinuation of urinary catheters | Yes | Yes | Yes | No | No | No | No | No | No | N/A |
Has a system in place for monitoring catheter associated urinary tract infection rates | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No | No | N/A |
Presence of a UC reduction program | Active | Active | Active | Active | No | No | No | No | No | N/A |
Duration of UC reduction program, y | 1 | 2 | 1 | 1 | N/A | N/A | N/A | N/A | N/A | N/A |
Total patient‐days | 425 | 455 | 527 | 405 | 87 | 311 | 285 | 394 | 253 | 3142 |
Total UC days | 27 | 32 | 42 | 77 | 2 | 36 | 48 | 80 | 82 | 426 |
UC rate per 100 patient‐days | 6.4 | 7.0 | 8.0 | 19.0 | 2.3 | 11.6 | 16.8 | 20.3 | 32.4 | 13.6 |
Reported historical UC rate per 100 patient‐days∥ | 12.0 | 16.5 | 18.8 | N/A | N/A | N/A | N/A | N/A | N/A | N/A |
Potentially appropriate indications, n (%) | 19 (70) | 25 (78) | 30 (71) | 36 (47) | 0 | 33 (92) | 27 (56) | 32 (40) | 59 (72) | 261 (61) |
Obstruction | 5 (19) | 11 (34) | 19 (45) | 7 (9) | 0 | 1 (3) | 10 (21) | 20 (25) | 2 (2) | 75 (17.6) |
Retention | 10 (37) | 9 (28) | 7 (17) | 21 (27) | 0 | 22 (61) | 9 (19) | 11 (14) | 23 (28) | 112 (26.3) |
Palliative | 4 (15) | 0 | 4 (10) | 8 (10) | 0 | 10 (28) | 5 (10) | 1 (1) | 16 (20) | 93 (21.8) |
Sacral ulcer | 0 | 5 (16) | 0 | 0 | 0 | 0 | 3 (6) | 0 | 18 (22) | 26 (6.1) |
Potentially inappropriate indications, n (%) | 8 (30) | 8 (25) | 12 (28) | 50 (65) | 2 (100) | 3 (8) | 21 (44) | 70 (88) | 16 (20) | 190 (45) |
Urine output | 2 (7) | 0 | 1 (2) | 22 (14) | 2 (100) | 3 (8) | 11 (23) | 50 (35) | 8 (10) | 96 (22.5) |
Other | 6 (22) | 8 (25) | 10 (24) | 26 (32) | 0 | 0 | 5 (10) | 13 (16) | 0 | 68 (16.0) |
Unknown | 0 | 0 | 1 (2) | 2 (3) | 0 | 0 | 5 (10) | 7 (9) | 8 (10) | 23 (5.3) |
DISCUSSION
Despite the availability of consensus guidelines for appropriate use and the efforts of movements like Choosing Wisely, many Canadian teaching hospitals have not yet established a urinary catheter reduction program for medical inpatients. Our findings are similar to 2 non‐Canadian studies, which demonstrated that fewer than half of hospitals had implemented control measures.[4, 6] In contrast to those other studies, our study demonstrated that hospitals that employed control measures had reduced rates of catheter use suggesting that systematic, structured efforts are necessary to improve practice.[7, 8]
Ours is the first nation‐wide study in Canada to report urinary catheter rates and the effect of associated reduction programs. Data from the National Healthcare Safety Network suggest our Canadian estimates of urinary catheter rates in medical inpatients are similar to those of the United States (13.6 vs 14.8 catheter days per 100 inpatient‐days, respectively, for general medical inpatients).[9, 10]
Several limitations of this study warrant discussion. First, we sampled only academic institutions at 1 time point, which may not represent annualized rates or rates in community hospitals. However, our findings are similar to those reported in previous studies.[10] Second, our method of consecutive daily audits may have caused individuals to change their behavior knowing that they were being observed, resulting in lower catheter utilization than would have been otherwise present and biasing our estimates of catheter overuse downward. Third, we collected point prevalence data, limiting our ability to make inferences on causality. The key factor(s) contributing to observed differences between hospitals remains unknown. However, pre‐post intervention data available for 3 hospitals suggest that improvements followed active catheter reduction efforts.[7, 8] Fourth, we were unable to obtain outcome data such as catheter‐associated urinary tract infection, delirium, or fall rates. However, catheter reduction is widely recognized as an important first step to reducing preventable harm for hospital patients.
We suggest that the broader uptake of structured models of care that promote early discontinuation of urinary catheters on medical wards is needed to improve their appropriateness. Fortunately, it appears as though a variety of models are effective. Therefore, when it comes to adopting Choosing Wisely's less is more philosophy toward urinary catheter utilization, we suggest that less time be allowed to pass before more proven and structured interventions are universally implemented.
Acknowledgements
The authors are indebted to John Matelski, MSc, for statistical analyses.
Disclosures: The Canadian Society of Internal Medicine and its Choosing Wisely Canada Subcommittee supported this work. The authors report no conflicts of interest.
- Diagnosis, prevention, and treatment of catheter‐associated urinary tract infection in adults: 2009 international clinical practice guidelines from the Infectious Diseases Society of America. Clin Infect Dis. 2010;50(5):625–663. , , , et al.
- Strategies to prevent catheter‐associated urinary tract infections in acute care hospitals: 2014 update. Infect Control Hosp Epidemiol. 2014;35(5):464–479. , , , et al.
- Preventing catheter‐associated urinary tract infection in the United States: a national comparative study. JAMA Intern Med. 2013;173(10):874–879. , , , et al.
- 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. , , , et al,
- Are physicians aware of which of their patients have indwelling urinary catheters? Am J Med. 2000;109(6):476–480. , , , et al.
- Adoption of policies to prevent catheter‐associated urinary tract infections in United States intensive care units. Am J Infect Control. 2012;40(8):705–710. , , , et al.
- Medical directive for urinary catheter removal by nurses on general medical wards. JAMA Intern Med. 2016;176(1):113–115. , , , et al.
- Novel low‐resource intervention reduces urinary catheter use and associated urinary tract infections: role of outcome measure bias? Am J Infect Control. 2015;43(4):348–353. , , , et al.
- National Healthcare Safety Network report, data summary for 2013, Device-associated Module. Am J Infect Control. 2015;43(3):206–221. , , , et al.
- Regional variation in urinary catheter use and catheter‐associated urinary tract infection: results from a national collaborative. Infect Control Hosp Epidemiol. 2014;35(suppl 3):S99–S106. , , , et al.
- Diagnosis, prevention, and treatment of catheter‐associated urinary tract infection in adults: 2009 international clinical practice guidelines from the Infectious Diseases Society of America. Clin Infect Dis. 2010;50(5):625–663. , , , et al.
- Strategies to prevent catheter‐associated urinary tract infections in acute care hospitals: 2014 update. Infect Control Hosp Epidemiol. 2014;35(5):464–479. , , , et al.
- Preventing catheter‐associated urinary tract infection in the United States: a national comparative study. JAMA Intern Med. 2013;173(10):874–879. , , , et al.
- 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. , , , et al,
- Are physicians aware of which of their patients have indwelling urinary catheters? Am J Med. 2000;109(6):476–480. , , , et al.
- Adoption of policies to prevent catheter‐associated urinary tract infections in United States intensive care units. Am J Infect Control. 2012;40(8):705–710. , , , et al.
- Medical directive for urinary catheter removal by nurses on general medical wards. JAMA Intern Med. 2016;176(1):113–115. , , , et al.
- Novel low‐resource intervention reduces urinary catheter use and associated urinary tract infections: role of outcome measure bias? Am J Infect Control. 2015;43(4):348–353. , , , et al.
- National Healthcare Safety Network report, data summary for 2013, Device-associated Module. Am J Infect Control. 2015;43(3):206–221. , , , et al.
- Regional variation in urinary catheter use and catheter‐associated urinary tract infection: results from a national collaborative. Infect Control Hosp Epidemiol. 2014;35(suppl 3):S99–S106. , , , et al.
© 2016 Society of Hospital Medicine