Reducing Carbapenem-Resistant Enterobacteriaceae Using the Targeted Solution Tool: A Quality Improvement Project : Journal of Nursing Care Quality

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Reducing Carbapenem-Resistant Enterobacteriaceae Using the Targeted Solution Tool

A Quality Improvement Project

Ragonese, Barbara MA; Mularoni, Alessandra MD; Valeri, Andrea BSN, RN; Campanella, Maria BSN, RN; Corso, Brigida RN; Fazzina, Maria Luisa BA; Barone, Maria Angela BSN, RN; Arena, Giuseppe BSN, RN; Lombardo, Rosario BSN, RN; Luca, Angelo MD

Author Information
doi: 10.1097/NCQ.0000000000000651


The US Centers for Disease Control and Prevention (CDC)1 estimates that on any given day, 1 in 31 hospitalized patients will acquire a health care–associated infection (HAI) while being treated in a medical facility. A previous prevalence study that included 231 459 patients across 947 hospitals concluded that 19.5% of patients in intensive care units had at least one HAI.2 These HAIs can have devastating effects on the physical, mental, emotional, and financial health of patients, with added expenses to the health care system.1 In addition, the CDC1 estimates that about half of the hospitalized patients receive an antimicrobial medication, increasing the risk of developing antimicrobial resistance. In all European countries, the global rise of infections with bacteria resistant to carbapenems, or carbapenem-resistant Enterobacteriaceae (CRE), represents a threat to patient safety. Data from the European Antimicrobial Resistance Surveillance Network (EARS-Net) show that Italy is among the countries reporting the highest prevalence of CRE worldwide, being acquired in 34% of hospitalized patients.3

These increasingly prevalent pathogens worldwide cause infections that are associated with high morbidity and mortality, for which very limited treatment options are available.4 For this reason, correct implementation of preventive measures is crucial to prevent CRE infections. Contaminated health care workers' (HCW) hands are the most common cause of transmission of health care–associated pathogens in most settings.5 However, despite hand hygiene's (HH) role in preventing HAIs is evident, low compliance among HCWs is reported.6,7

There are many factors that influence HH compliance. Studies have shown that physicians, nursing assistants, and males have lower compliance with HH.8,9 Other studies have shown that common reasons for noncompliance with HH include lack of availability and accessibility to HH dispensers, and that HH agents cause irritation and dryness to HCWs' skin.9,10

Improvement strategies that have been reported to be effective in increasing HH compliance are education, reminders in the workplace, routine observations, and feedback.11,12 As reported in a systematic review, education is a crucial component of HH interventions; e-learning materials and simulation have been used in several studies, while others have used lectures or workshops.13 Studies have also included, reminders including material based on the World Health Organization (WHO) guidelines and displayed on posters and flyers.14,15 A common strategy is to use audit with performance feedback delivered to units, organizations, and sometimes to individuals. Verbal as well as written feedback may be given, with several researchers displaying HH audit data in clinical areas.11 What influences HH compliance is a complex interdependence of different factors that might change from one organization to another.16–18 The need for every organization to identify the root cause of problems specific to the local setting's culture and environment has been previously highlighted.19

Hand hygiene and other infection prevention measures are particularly important in the hospital where this project took place, as our geographic area is endemic for CRE. As such, since 2013 our hospital began following the CDC bundle,20 including cohorting patients and staff. We have screened all patients for CRE at hospital admission and hospital day 7 per CDC guidelines.20 The rate of health care–associated (HA) CRE colonization is one metric that is monitored by our organization to evaluate efficacy of our infection prevention and control program.

Trends in HA-CRE colonization rates showed a gradual improvement after bundle implementation; however, rates increased again in 2017 with an average of 17.7% between January and August. We hypothesized that HH was the main contributing factor for HA-CRE colonization, and there was a lack of reliable HH data collection. In fact, until then the HH observations had been randomly performed by known infection control nurses, likely influencing HCWs' behavior. The purpose of this project was to decrease HA-CRE colonization rates through improving HH compliance.


The project was conducted in a 107-bed multiorgan transplant center in Palermo, located in the south of Italy. The hospital has more than 850 full-time employees and cares for about 2800 patients with more than 200 transplants performed per year. All solid organ transplant programs are active for adult patients; liver, kidney, and lung transplants are also performed on pediatric patients. The hospital also cares for patients who do not need transplants, but may be suffering from serious pathologies that can lead to terminal organ failure. The hospital has been accredited by the Joint Commission International (JCI) since 2009 and is committed to ensuring high standards of quality and patient safety. For this project, our organization aimed to comply with the International Patient Safety Goal number 5 (IPSG.5), which requires hospitals to adopt and implement evidence-based HH guidelines to reduce the risk of HAIs.21

From January to August 2017, the hospital's HA-CRE rate increased to 17.7%, compared with an average rate of 5.1% in 2016 and 5.3% in 2015. Our organization decided to participate in the Targeted Solution Tool (TST) for HH as a strategy to contain the spread of HA-CRE colonization. The TST was developed by the Joint Commission Center for Transforming Health Care to support accredited organizations to solve challenging issues for patient safety.22 The quality department promoted the project in conjunction with infection control, nursing leadership, and the nursing education department. A certified Lean Six Sigma Green Belt from the quality department coordinated the project development and the hospital chief executive officer (CEO) supported the project through all phases of development. Since the project supported compliance with existing policy and procedures regarding HH, the institutional review board's approval was not deemed necessary. All hospital units were involved in the project; no control unit was selected in this pre/postintervention project.

Targeted Solution Tool

The Joint Commission Center for Transforming Healthcare's Web-Based TST for improving HH guides health care organizations through a step-by-step improvement process based on the 5 stages of a Six Sigma Project: Define, Measure, Analyze, Improve, and Control (DMAIC).23 The tool enables the hospital to identify the actual level of compliance with HH through accurate measurement, and improve HH compliance by acting on systematic and sustainable changes to processes, for which efficacy has been previously demonstrated.19,24 Several resources are available to users, including training materials for data collectors, an HH observation form, a platform for real-time data analysis, and a set of implementation guides on the targeted solutions addressing the contributing factors identified within the organization. The data collection process focused not only on recording observed HH compliance but also on identifying contributing factors and barriers to optimal HH. Barriers may be related to the infrastructure, the way daily activities are routinely performed, and also HCWs' knowledge and/or organizational specific cultural factors.

To overcome the bias associated with the Hawthorne effect25 generated when HCWs are aware of being observed, the TST methodology requires the organization to engage unknown observers in training to collect reliable data on observed HH compliance.9,26 The tool also provides an observation form; for our project, this was translated into Italian. The form allowed the observer to record which HCW was observed, the type of HH moment (eg, HH performed upon entry into a patient's room or upon exit of a patient's room), and also the observable contributing factors to noncompliance.

The hand hygiene improvement project

This quality improvement (QI) project used a pre-/postintervention design to improve HH compliance by embracing the Six Sigma DMAIC approach from September 2017 to December 2020. The Control phase was divided into “Control 1” and “Control 2” as the project was interrupted due to the COVID-19 pandemic in February 2020, and relaunched again in May 2020; see the Supplemental Digital Content Table (available at: for an overview of the project phases. For purposes of reporting results, data have been classified as Baseline, Improve, Control 1, and Control 2 data. Activities conducted in each stage of the project based on the DMAIC framework are described in the next paragraphs.


During this phase of the project, a review of material and resources was performed and the HH project was launched. The team recruited 18 newly hired nurses to serve in the role of unknown observers. They were trained in how to perform unknown (blinded) observations by the nursing education department using TST classroom education materials. A competency test developed by the JCI was administered to the 18 observers. The competency test assessed the observer's accuracy in HH observations from 16 scenarios using the HH data collection form. All 18 observers completed the test with a score of 90% or higher.


A total of 717 blind observations were recorded by unknown observers and recorded in the TST web-based application between November to December 2017 (baseline data). Following blind observations, the education department, in collaboration with the infection control team, provided Just in Time (JIT) coaching observations. The purpose of JIT coaching observations was to provide direct feedback to HCWs when HH was not correctly performed, and to identify nonobservable contributing factors to noncompliance (eg, distraction, skin irritation perception, and knowledge). A total of 233 non-blinded JIT observations were made during this phase, and were not included in HH compliance rate measurements.


In the Analyze phase, data collected enabled us to determine the baseline HH compliance rate. The main factors that contributed to low HH compliance were identified and evaluated through a Pareto chart (Figure 1). The factors that had the most significant impact on HH compliance were patients being in isolation areas (33.3%), hands being full of supplies (23%), and frequent entry and exit of the patient's room (11%). These factors provided guidance on where to focus improvement strategies, which were addressed as recommended by the TST implementation guide. Also, run charts were used to understand trends in HH compliance, evaluating physicians, nurses, and other clinical staff performance.

Figure 1.:
Pareto chart of factors contributing to hand hygiene noncompliance (baseline phase).


All potential contributing factors identified during the Analyze phase were taken into consideration and brainstorming sessions were held with relevant hospital stakeholders. The following strategies were suggested by the TST implementation guide and were implemented to overcome the potential contributing factors of low HH compliance among the HCWs in our hospital. For patients being in an isolation area, (1) instructions for creating a standard process for donning and doffing personal protective equipment (PPE) were developed, and (2) glove dispensers were relocated based on recommendation from the TST implementation guide for the best placement in the clinical area to maximize their use. For hands being full of supplies, (1) education was provided on the need to place supplies on the shelf in front of the patient's room and perform HH before entering the room, and (2) all hand sanitizer dispenser locations were reviewed and standardized, providing HH product at the right time and the right place. Dispensers were positioned at the entrance to the unit and inside each room.

For the other contributing factors detected, the following interventions were put into place: (1) an extensive communication campaign was launched using screensavers, leaflets, posters, and emails to remind HCWs of the importance of HH, (2) the internal policy on glove use was merged with the HH policy, and the WHO Gloves Pyramid was customized to inform HCWs on appropriate glove use, and (3) an e-learning module on HH best practices to reduce HAIs and on correct glove use was introduced as a mandatory course for HCWs. After implementing these interventions, a total of 856 blind observations were conducted from June to August 2018 to assess the HH compliance rate. As part of the Improve phase, we trained additional nurses as unknown observers using the TST education material.

Control 1

The Control 1 phase was initiated to sustain the improvements. From February 2019 through February 2020, 1303 blind observations were performed. These data showed that HH compliance and HA-CRE colonization rates improved and were sustained. Data were reviewed within the quality steering committee, which met quarterly to evaluate and discuss improvement strategies. Blind observations stopped during the onset of the COVID-19 pandemic (March to May 2020).

Control 2

The project was relaunched in May 2020 until December 2020, with more blind observers trained, including other professional groups. The number of observations increased to 7939 over the 6-month period. On-the-job training was performed and data were reviewed during monthly leadership meetings. In this phase all of the interventions implemented during the Improve phase were standardized, and data showed a further increased HH compliance rate and a reduction of CRE acquisition (Figure 2).

Figure 2.:
Hand hygiene compliance rates and HA-CRE colonization rates in the 4 project phases. HA-CRE indicates health care–associated carbapenem-resistant Enterobacteriaceae.

Statistical analysis

Comparisons of discrete variables between the Baseline and Improve phases, and between the Control 1 and 2 phases, were done with the z test for proportions (Statistical Software is SPCXL 2010). A P value ≤ .05 was considered statistically significant. The results were expressed as absolute values and percentages.


During the 38-month project period, 10 815 observations were conducted by unknown observers. Nurses showed significant increases in HH rates between the Baseline and Improve phases (54.9% −81.3%, P = .0001) and between Control 1 and Control 2 (78.4%-83.7%, P = .001). Physicians saw an increase in HH from Baseline and Improve (50.5%-56.4%); however, this was not significant (P = .367). Physicians did have a significant increase from the Control 1 to Control 2 phases (64.4%-79.8%, P = .0001). Other clinical (technicians, health care assistants) and nonclinical staff significantly improved from the Baseline to Improve phases (P = .0001), yet non significant improvements were observed from Control 1 to Control 2 (Table).

Table. - Comparison of Hand Hygiene Compliance
Baseline n (%) Improve n (%) P Value Control 1 n (%) Control 2 n (%) P Value
Nurse 234/426 (54.9) 326/399 (81.3) .000 485/618 (78.4) 2920/3530 (83.7) .001
Physician 53/105 (50.5) 81/144 (56.4) .367 179/278 (64.4) 1505/1896 (79.8) .000
Other clinical roles 65/166 (39.1) 240/295 (81.2) .000 309/391 (78.8) 2028/2457 (83.6) .092
Other nonclinical roles 0/20 (0.0) 12/18 (66.6) .000 9/16 (57.1) 34/56 (60.7) .748
Clinical unit/area
ICU 120/214 (56.1) 180/242 (74.0) .000 385/490 (78.5) 1630/1941 (83.4) .011
Cardio unit 100/242 (41.3) 92/113 (81.2) .000 372/500 (74.4) 1660/1980 (83.1) .000
Abdominal unit 71/144 (49.3) 171/213 (79.9) .000 193/270 (71.4) 954/1131 (83.7) .000
Other hospital units 61/117 (52.1) 216/288 (75.0) .000 32/43 (74.4) 2243/2887 (77.6) .061
Type of audit
Entering patient's room 169/418 (38.0) 348/463 (75.4) .000 471/660 (71.4) 3515/4379 (80.5) .000
Exiting patient's room 183/299 (60.0) 311/393 (78.3) .000 511/643 (79.1) 2972/3560 (83.3) .008
Overall HH compliance 352/717 (49) 659/856 (76.9) .000 982/1303 (75.3) 6487/7939 (81.9) .000
Abbreviations: HH, hand hygiene; ICU, intensive care unit.

Significant improvements in HH compliance were observed in all clinical units/areas between the Baseline and Improve phases (P = .0001). Between the Control 1 and Control 2 phases, 3 units showed significant improvements, including the intensive care unit (78.5%-83.4%, P = .011), cardio unit (74.4%-83.1%, P = .0001), and abdominal unit (71.4%-83.7%, P = .0001). The other hospital units, including the postanesthesia care unit, radiology, and endoscopy, saw improvements between the Control 1 and Control 2 phases; however, these were not significant (74.4%-77.6%, P = .061). Overall HH compliance significantly increased between the Baseline and Improve phases (49%-76.9%, P = .0001) as well as between the Control 1 and Control 2 phases (75.3%-81.9%, P = .0001) (Table).

We also examined HA-CRE colonization rates to assess whether increased HH compliance impacted HA-CRE colonization rate. We found a statistically significant reduction in the incidence of HA-CRE colonization rate at hospital day 7 between the Baseline and Improve phases (24.9%-18.9%, P = .007). There was also a significant reduction in HA-CRE colonization rates from the Improve to Control 1 phases (13.0%, P = .001) and from the Control 1 to Control 2 phases (5.6%, P = .0001) (Figure 2).


By adopting the TST methodology, we were able to increase our HH compliance from 49% at the Baseline phase to 81.9% during the Control 2 phase. Our improvements in HH compliance after using TST are similar to previous findings reported.19,24 A previous study has also shown the effectiveness of the TST in increasing adherence to HH, obtaining results comparable to our.19,24 The TST method allowed us to implement specific interventions based on factors contributing to noncompliance with HH. In this QI project, the largest contributing factors were patients being in an isolation area (33.3%) and HCWs' hands being full of supplies (23%); in a similar study, hands being full of supplies (27.5%) and improper glove use (27.2%) were the main barriers to HH compliance.24 A study conducted by Chassin et al27 demonstrated that each hospital had a different set of key causes of HH noncompliance. Implementing customized interventions, such as a targeted approach, may be more effective and efficient than a one-size-fits-all improvement strategy.27

We observed a decrease in HA-CRE colonization that was related to an increase in HH compliance by HCWs. This correlation was previously demonstrated in a case-control study by Grabowski and colleagues,28 where HH, combined with cohorting strategies, reduced the risk of CRE transmission.28 Additionally, Grabowski and colleagues28 found that patients who acquired CRE during their hospitalization were more likely to have received care from a provider that was caring for another patient with CRE.

Following the Improve and Control 1 phases, overt observations (JIT coaching) were conducted. In line with another recent study,29 the introduction of overt observations is a key factor in keeping the focus on HH and enhancing patient safety. Overt observations facilitated communication between the HH program and HCWs to better understand workflow and educate staff on HH opportunities.29 Birnbach et al30 showed that, even after intensive HH education, medical student HH compliance remained low. The TST methodology enabled us to switch the focus from a staff educational only approach, to improving processes (eg, PPE donning and doffing) and environmental factors (eg, hand sanitizer dispensers at the right place, glove dispenser relocation).

Although we observed a significant decrease in the HA-CRE colonization rates, other HAIs were not evaluated in this project because, as noted in a previous study,31 linking HAIs to HH practices can be challenging. Infection rates are affected by additional factors related to patients (age, comorbidities), organizations (staffing, competencies), and processes (bundle implementation); therefore, it is difficult to separate the influence of improved HH from other factors.31

In our project, the CEO played an important role, approving the project and requesting regular updates on HH compliance rates to be shared with the leadership team. Top-down leadership support involving nursing and medical leaders from each hospital unit is critical to success in improving HH compliance.32


Our project had several limitations. First, it was conducted at a single center and the results may not be generalizable. During the development of the project, we were unable to maintain the same HH observers; however, all the observers underwent the same specific training on TST methodology. The HH compliance data were collected with blind observations in 20 out of 38 months of the project. During some phases of the project, such as the Define phase, no observations were completed. In addition, the JIT coaching overt observations were performed in different phases of the project, and were not included in the HH compliance data collection. During the first months of the COVID-19 pandemic (March to May 2020), no HH observations took place. In addition, in the Improve phase, no data were collected prior to implementing interventions.


This QI project showed that a significant increase in HH was effective in reducing HA-CRE colonization in our hospital. The TST methodology is relatively easy to use and does not require significant extra costs to health care systems. In addition, targeting interventions to specific factors and barriers may be more efficient than a one-size-fits-all best practice, as it permits hospitals to avoid wasting resources on barriers that may not be present.


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compliance; DMAIC; hand hygiene; health care–associated infection; quality improvement

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