To investigate whether the safety culture of a hospital unit is associated with the ability to improve.

Qualitative investigation of safety culture on hospital units following a before-and-after trial on hand hygiene.

VU University Medical Center, a tertiary-care hospital in the Netherlands.

With support from hospital management, we implemented a hospital-wide program to improve compliance. Over 2 years, compliance was measured through direct observation, twice before, and 4 times after interventions. We analyzed changes in compliance from baseline, and selected units to evaluate safety culture using a positive deviance approach: the hospital unit with the highest hand hygiene compliance and 2 units that showed significant improvement (21% and 16%, respectively) were selected as high performing. Another 2 units showed no improvement and were selected as low performing. A blinded, independent observer conducted interviews with unit management, physicians, and nurses, based on the Hospital Survey on Patient Safety Culture. Safety culture was categorized as pathological (lowest level), reactive, bureaucratic, proactive, or generative (highest level).

Overall, 3 units showed a proactive or generative safety culture and 2 units had bureaucratic or pathological safety cultures. When comparing compliance and interview results, high-performing units showed high levels of safety culture, while low-performing units showed low levels of safety culture.

Safety culture is associated with the ability to improve hand hygiene. Interventions may not be effective when applied in units with low levels of safety culture. Although additional research is needed to corroborate our findings, the safety culture on a unit can benefit from enhancement strategies such as team-building exercises. Strengthening the safety culture before implementing interventions could aid improvement and prevent nonproductive interventions.

Infect Control Hosp Epidemiol 2017;38:1277–1283

Estimating the risk of a complicated course of Clostridium difficile infection (CDI) might help doctors guide treatment. We aimed to validate 3 published prediction models: Hensgens (2014), Na (2015), and Welfare (2011).

The validation cohort comprised 148 patients diagnosed with CDI between May 2013 and March 2014. During this period, 70 endemic cases of CDI occurred as well as 78 cases of CDI related to an outbreak of C. difficile ribotype 027. Model calibration and discrimination were assessed for the 3 prediction rules.

A complicated course (ie, death, colectomy, or ICU admission due to CDI) was observed in 31 patients (21%), and 23 patients (16%) died within 30 days of CDI diagnosis. The performance of all 3 prediction models was poor when applied to the total validation cohort with an estimated area under the curve (AUC) of 0.68 for the Hensgens model, 0.54 for the Na model, and 0.61 for the Welfare model. For those patients diagnosed with CDI due to non-outbreak strains, the prediction model developed by Hensgens performed the best, with an AUC of 0.78.

All 3 prediction models performed poorly when using our total cohort, which included CDI cases from an outbreak as well as endemic cases. The prediction model of Hensgens performed relatively well for patients diagnosed with CDI due to non-outbreak strains, and this model may be useful in endemic settings.

Infect Control Hosp Epidemiol 2017;38:897–905

To develop prognostic models for improved risk adjustment in surgical site infection surveillance for 5 surgical procedures and to compare these models with the National Nosocomial Infection Surveillance system (NNIS) risk index.

In a multicenter cohort study, prospective assessment of surgical site infection and risk factors was performed from 1996 to 2000. In addition, risk factors abstracted from patient files, available in a national medical register, were used. The c-index was used to measure the ability of procedure-specific logistic regression models to predict surgical site infection and to compare these models with models based on the NNIS risk index. A c-index of 0.5 indicates no predictive power, and 1.0 indicates perfect predictive power.

Sixty-two acute care hospitals in the Dutch national surveillance network for nosocomial infections.

Patients who underwent 1 of 5 procedures for which the predictive ability of the NNIS risk index was moderate: reconstruction of the aorta (n = 875), femoropopliteal or femorotibial bypass (n = 641), colectomy (n = 1,142), primarytotal hip prosthesis (n = 13,770), and cesarean section (n = 2,962).

The predictive power of the new model versus the NNIS index was 0.75 versus 0.62 for reconstruction of the aorta (P< .01), 0.78 versus 0.58 for femoropopliteal or femorotibial bypass (P< .001), 0.69 versus 0.62 for colectomy (P< .001), 0.64 versus 0.56 for primary total hip prosthesis arthroplasty (P< .001), and 0.70 versus 0.54 for cesarean section (P< .001).

Data available from hospital information systems can be used to develop models that are better at predicting the risk of surgical site infection than the NNIS risk index. Additional data collection may be indicated for certain procedures–for example, total hip prosthesis arthroplasty.

To determine hospital-related risk factors for surgical-site infection (SSI) following hip arthroplasty.

Prospective, multicenter cohort study based on surveillance data and data collected through a structured telephone interview. With the use of multilevel logistic regression, the independent effect of hospital-related characteristics on SSI was assessed.

Thirty-six acute care hospitals in the Dutch surveillance network for nosocomial infections (PREZIES), from 1996 to 2000.

Thirteen thousand six hundred eighty patients who underwent total or partial hip arthroplasty.

A high annual volume of operations was associated with a reduced risk of SSI (risk-adjusted risk ratio [RR] per 50 extra operations, 0.85; 95% confidence interval [CI95], 0.74–0.97). With each extra full-time–equivalent infection control staff member per 250 beds available for prevention of SSI, the risk for SSI was decreased (RR, 0.48; CI95, 0.16–1.44), although the decrease was not statistically significant. Hospital size, teaching status, university affiliation, and number of surgeons and their years of experience showed no important association with the risk of SSI.

Undergoing surgery in a hospital with a low volume of operations increases a patient's risk of SSI.

The benefit of screening healthcare workers (HCWs) at risk for methicillin-resistant Staphylococcus aureus (MRSA) carriage and furloughing MRSA-positive HCWs to prevent spread to patients is controversial. We evaluated our MRSA program for HCWs between 1992 and 2002.

A university medical center in the Netherlands, where methicillin resistance has been kept below 0.5% of all nosocomial S. aureus infections using active surveillance cultures and isolation of colonized patients.

HCWs caring for MRSA-positive patients or patients in foreign hospitals were screened for MRSA. MRSA-positive HCWs had additional cultures, temporary exclusion from patient-related work, assessment of risk factors for persisting carriage, decolonization therapy with mupirocin intranasally and chlorhexidine baths for skin and hair, and follow-up cultures.

Fifty-nine HCWs were colonized with MRSA. Seven of 840 screened employees contracted MRSA in foreign hospitals; 36 acquired MRSA after contact with MRSA-positive patients despite isolation precautions (attack rate per outbreak varied from less than 1% to 15%). Our hospital experienced 17 MRSA outbreaks, including 13 episodes in which HCWs were involved. HCWs were index cases of at least 4 outbreaks. In 8 outbreaks, HCWs acquired MRSA after caring for MRSA-positive patients despite isolation precautions.

Postexposure screening of HCWs allowed early detection of MRSA carriage and prevention of subsequent transmission to patients. Where the MRSA prevalence is higher, the role of HCWs may be greater. In such settings, an adapted version of our program could help prevent dissemination.

To determine incidence rates of hospital-acquired infections and to develop preventive measures to reduce the risk of hospital-acquired infections.

Prospective surveillance for hospital-acquired infections was performed during a 5-year period in the wards housing general and vascular, thoracic, orthopedic, and general gynecologic and gynecologic-oncologic surgery of the University Medical Center Utrecht, the Netherlands. Data were collected from patients with and without infections, using criteria of the Centers for Disease Control and Prevention.

The infection control team recorded 648 hospital-acquired infections affecting 550 (14%) of 3,845 patients. The incidence density was 17.8 per 1,000 patient-days. Patients with hospital-acquired infections were hospitalized for 19.8 days versus 7.7 days for patients without hospital-acquired infections.

Prolongation of stay among patients with hospital-acquired infections may have resulted in 664 fewer admissions due to unavailable beds. Different specialties were associated with different infection rates at different sites, requiring a tailor-made approach. Interventions were recommended for respiratory tract infections in the thoracic surgery ward and for surgical-site infections in the orthopedic and gynecologic surgery wards.

Surveillance in four surgical wards showed that each had its own prominent infection, risk factors, and indications for specific recommendations. Because prospective surveillance requires extensive resources, we considered a modified approach based on a half-yearly point-prevalence survey of hospital-acquired infections in all wards of our hospital. Such surveillance can be extended with procedure-specific prospective surveillance when indicated.