Multilevel approach to individual and organisational predictors of stress and fatigue among healthcare workers of a university hospital: a longitudinal study.

OBJECTIVE: Healthcare workers (HCWs) are at high risk of experiencing stress and fatigue due to the demands of their work within hospitals. Improving their physical and mental health and, in turn, the quality and safety of care requires considering factors at both individual and organisational/ward levels. Using a multicentre prospective cohort, this study aims to identify the individual and organisational predictors of stress and fatigue of HCWs in several wards from university hospitals. METHODS: Our cohort consists of 695 HCWs from 32 hospital wards drawn at random within four volunteer hospital centres in Paris-area. Three-level longitudinal analyses, accounting for repeated measures (level 1) across participants (level 2) nested within wards (level 3) and adjusted for relevant fixed and time-varying confounders, were performed. RESULTS: At baseline, the sample was composed by 384 registered nurses, 300 auxiliary nurses and 11 midwives. According to the three-level longitudinal models, some predictors were found in common for both stress and fatigue (low social support from supervisors, work overcommitment, sickness presenteeism and number of beds per ward). However, specific predictors for high level of stress (negative life events, low social support from colleagues and breaks frequently cancelled due to work overload) and fatigue (longer commuting duration, frequent use of interim staff in the ward) were also found. CONCLUSION: Our results may help identify at-risk HCWs and wards, where interventions to reduce stress and fatigue should be focused. These interventions could include manager training to favour better staff support and overall safety culture of HCWs.

Time-series modelling for the quantification of seasonality and forecasting antibiotic-resistant episodes: application to carbapenemase-producing Enterobacteriaceae episodes in France over 2010-20.

BACKGROUND: Carbapenemase-producing Enterobacteriaceae (CPE) cause resistant healthcare-associated infections that jeopardize healthcare systems and patient safety worldwide. The number of CPE episodes has been increasing in France since 2009, but the dynamics are still poorly understood. OBJECTIVES: To use time-series modelling to describe the dynamics of CPE episodes from August 2010 to December 2016 and to forecast the evolution of CPE episodes for the 2017-20 period. METHODS: We used time series to analyse CPE episodes from August 2010 to November 2016 reported to the French national surveillance system. The impact of seasonality was quantified using seasonal-to-irregular ratios. Seven time-series models and three ensemble stacking models (average, convex and linear stacking) were assessed and compared with forecast CPE episodes during 2017-20. RESULTS: During 2010-16, 3559 CPE episodes were observed in France. Compared with the average yearly trend, we observed a 30% increase in the number of CPE episodes in the autumn. We noticed a 1 month lagged seasonality of non-imported episodes compared with imported episodes. Average stacking gave the best forecasts and predicted an increase during 2017-20 with a peak up to 345 CPE episodes (95% prediction interval = 124-1158, 80% prediction interval = 171-742) in September 2020. CONCLUSIONS: The observed seasonality of CPE episodes sheds light on potential factors associated with the increased frequency of episodes, which need further investigation. Our model predicts that the number of CPE episodes will continue to rise in the coming years in France, mainly due to local dissemination, associated with bacterial carriage by patients in the community, which is becoming an immediate challenge with regard to outbreak control.

Gradual decline in outpatient antibiotic prescriptions in paediatrics: A data warehouse-based 11-year cohort study.

AIM: To describe trends in antibiotic (AB) prescriptions in children in primary care over 11 years, using a large data warehouse. METHODS: A retrospective cohort study assessed outpatient AB prescriptions 2007-2017, using the Massachusetts Health Disparities Repository. The evolution of paediatric outpatient AB prescriptions was assessed using time-series analyses through annual per cent change (APC) for the population and for children with or without comorbid condition. RESULTS: About 25 000 children were followed in primary care with 31 248 AB prescriptions reported in the data warehouse. The youngest children had more AB prescriptions. Penicillins were prescribed most frequently (46%), then macrolides (28%). One third of children had comorbid conditions, receiving significantly more antibiotics (30.3 vs 21.0 AB/100 child-years, relative risk: 1.43, 95% CI: 1.40, 1.46). Overall AB prescription decreased over the period (APC = -5.34%, 95% CI: -7.10, -3.54), with similar trends for penicillins (APC = -5.49; 95% CI: -8.27, -2.62) and macrolides (APC = -6.46; 95% CI: -8.37, -4.58); antibiotic prescribing declined more in children with comorbid conditions. CONCLUSION: Outpatient AB prescribing decline was gradual and consistent in paediatrics over the period. Prescription differences persisted between age groups, conditions and indication. The availability of routine care data through data warehouse fosters the surveillance automation, providing inexpensive fast tools to design appropriate antimicrobial stewardship.

Mortality review as a tool to assess the contribution of healthcare-associated infections to death: results of a multicentre validity and reproducibility study, 11 European Union countries, 2017 to 2018.

IntroductionThe contribution of healthcare-associated infections (HAI) to mortality can be estimated using statistical methods, but mortality review (MR) is better suited for routine use in clinical settings. The European Centre for Disease Prevention and Control recently introduced MR into its HAI surveillance.AimWe evaluate validity and reproducibility of three MR measures.MethodsThe on-site investigator, usually an infection prevention and control doctor, and the clinician in charge of the patient independently reviewed records of deceased patients with bloodstream infection (BSI), pneumonia, Clostridioides difficile infection (CDI) or surgical site infection (SSI), and assessed the contribution to death using 3CAT: definitely/possibly/no contribution to death; WHOCAT: sole cause/part of causal sequence but not sufficient on its own/contributory cause but unrelated to condition causing death/no contribution, based on the World Health Organization's death certificate; QUANT: Likert scale: 0 (no contribution) to 10 (definitely cause of death). Inter-rater reliability was assessed with weighted kappa (wk) and intra-cluster correlation coefficient (ICC). Reviewers rated the fit of the measures.ResultsFrom 2017 to 2018, 24 hospitals (11 countries) recorded 291 cases: 87 BSI, 113 pneumonia , 71 CDI and 20 SSI. The inter-rater reliability was: 3CAT wk 0.68 (95% confidence interval (CI): 0.61-0.75); WHOCAT wk 0.65 (95% CI: 0.58-0.73); QUANT ICC 0.76 (95% CI: 0.71-0.81). Inter-rater reliability ranged from 0.72 for pneumonia to 0.52 for CDI. All three measures fitted 'reasonably' or 'well' in > 88%.ConclusionFeasibility, validity and reproducibility of these MR measures was acceptable for use in HAI surveillance.

Epidemiology of Clostridioides difficile infections, France, 2010 to 2017.

BackgroundClostridioides difficile is a leading cause of healthcare-associated diarrhoea in middle and high-income countries. Up to 2018, there has been no systematic, annual surveillance for C. difficile infections (CDI) in France.AimsTo provide an updated overview of the epidemiology of CDI in France between 2010 and 2017 based on five different data sources.MethodsThis is a descriptive study of retrospective surveillance and alerts data. Incidence of CDI cases was estimated through the CDI incidence survey (2016) and data from the French National Uniform Hospital Discharge Database (PMSI; 2010-16). Testing frequency for CDI was estimated through the CDI incidence survey and point prevalence studies on healthcare-associated infections (HAI; 2012 and 2017). The national early warning response system for HAI (HAI-EWRS, 2012-17) and National Reference Laboratory data (2012-17) were used to follow the number of severe CDI cases and/or outbreaks.ResultsIn 2016, CDI incidence in acute care was 3.6 cases per 10,000 patient days (PD). There was a statistically significant increase in CDI incidence between 2010 and 2016 (+ 14% annually) and testing frequency was 47.4 per 10,000 PD. The number of CDI HAI-EWRS notifications decreased between 2015 and 2017 with only a few large outbreaks reported.ConclusionThe CDI incidence estimate increased from 2010, but remained below the European average of 7 per 10,000 PD in 2014; there were fewer severe cases or clusters reported in France. The consistency between PMSI and laboratory-based estimated CDI incidence could allow for more routine monitoring of CDI incidence.

A clone of the emergent Streptococcus pyogenes emm89 clade responsible for a large outbreak in a post-surgery oncology unit in France.

An outbreak of nosocomial infections due to Streptococcus pyogenes (Group A Streptococcus; GAS) occurred in a post-surgery oncology unit and concerned more than 60 patients and lasted 20 months despite enhanced infection control and prophylaxis measures. All GAS strains were characterized (emm genotype, toxin gene profile and pulse-field gel electrophoresis subtype). Selected strains were sequenced and phylogenetic relationship established. Capacity to form biofilm and interaction with human pulmonary epithelial cells and macrophages were determined. Twenty-six GAS strains responsible for invasive infections (II) and 57 for non-II or colonization were isolated from patients (n = 66) or healthcare workers (n = 13). Seventy strains shared the same molecular markers and 69 the same PFGE pattern; 56 were sequenced. They all belonged to the emerging emm89 clade 3; all but 1 were clonal. Whole genome sequencing identified 43 genetic profiles with sporadic mutations in regulatory genes and acquired mutations in 2 structural genes. Except for two regulatory gene mutants, all strains tested had the same biofilm formation capacity and displayed similar adherence and invasion of pulmonary epithelial cells and phagocytosis and survival in human macrophages. This large outbreak of GAS infection in a post-surgery oncology unit, a setting that contains highly susceptible patients, arose from a strain of the emergent emm89 clade. No relationship between punctual or acquired mutations, invasive status, and strain phenotypic characteristics was found. Noteworthy, the phenotypic characteristics of this clone account for its emergence and its remarkable capacity to elicit outbreaks.

Spread of hospital-acquired infections: A comparison of healthcare networks.

Hospital-acquired infections (HAIs), including emerging multi-drug resistant organisms, threaten healthcare systems worldwide. Efficient containment measures of HAIs must mobilize the entire healthcare network. Thus, to best understand how to reduce the potential scale of HAI epidemic spread, we explore patient transfer patterns in the French healthcare system. Using an exhaustive database of all hospital discharge summaries in France in 2014, we construct and analyze three patient networks based on the following: transfers of patients with HAI (HAI-specific network); patients with suspected HAI (suspected-HAI network); and all patients (general network). All three networks have heterogeneous patient flow and demonstrate small-world and scale-free characteristics. Patient populations that comprise these networks are also heterogeneous in their movement patterns. Ranking of hospitals by centrality measures and comparing community clustering using community detection algorithms shows that despite the differences in patient population, the HAI-specific and suspected-HAI networks rely on the same underlying structure as that of the general network. As a result, the general network may be more reliable in studying potential spread of HAIs. Finally, we identify transfer patterns at both the French regional and departmental (county) levels that are important in the identification of key hospital centers, patient flow trajectories, and regional clusters that may serve as a basis for novel wide-scale infection control strategies.

[Regulatory science in public health: What are we talking about?] / Science réglementaire en santé publique : de quoi parle-t-on ?

This article sheds light on a concept little known to public health actors in France: regulatory science, used to describe the range of scientific activities used to produce the knowledge mobilized to support, develop or adapt public policy decisions. The objective is to understand how the expression appeared in the mid-1980s and was formalized into a sociological concept by the American writer Sheila Jasanoff in 1990, and has gradually imposed itself in American, Japanese and European regulatory agencies as a new scientific discipline. The article examines the evolution of the concept and the various approaches proposed to define regulatory science. It highlights its hybrid and heterogeneous nature, underlining the different characteristics that the expression covers according to the institution which formulates it (FDA, EMA, PMDA) and the scope of application that it covers. Based on concrete examples of the application of regulatory science practices in three broad areas of health risk, the paper focuses on the role of research in the decision-making process by showing how the emergence of new methods designed to strengthen the regulatory capacities of regulators and the role of academic communities associated with this approach, contribute to the strengthening of public health policies in France and worldwide.

Mathematical models of infection transmission in healthcare settings: recent advances from the use of network structured data.

PURPOSE OF REVIEW: Mathematical modeling approaches have brought important contributions to the study of pathogen spread in healthcare settings over the last 20 years. Here, we conduct a comprehensive systematic review of mathematical models of disease transmission in healthcare settings and assess the application of contact and patient transfer network data over time and their impact on our understanding of transmission dynamics of infections. RECENT FINDINGS: Recently, with the increasing availability of data on the structure of interindividual and interinstitution networks, models incorporating this type of information have been proposed, with the aim of providing more realistic predictions of disease transmission in healthcare settings. Models incorporating realistic data on individual or facility networks often remain limited to a few settings and a few pathogens (mostly methicillin-resistant Staphylococcus aureus). SUMMARY: To respond to the objectives of creating improved infection prevention and control measures and better understanding of healthcare-associated infections transmission dynamics, further innovations in data collection and parameter estimation in modeling is required.

Ongoing increasing temporal and geographical trends of the incidence of extended-spectrum beta-lactamase-producing Enterobacteriaceae infections in France, 2009 to 2013.

Extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-E) are a major focus of multidrug-resistant organisms (MRO) surveillance programmes in France. To describe the temporal and geographical trends of these pathogens, we conducted an epidemiological study based on data extracted from the nationwide MRO surveillance network from 2009 to 2013. During this time, the incidence of ESBL-E infections in French hospitals increased by 73%, from 0.35 to 0.60 per 1,000 patient days (PD) (p<0.001) and ESBL-E bacteraemia by 77%, from 0.03 to 0.05 per 1,000 PD (p<0.001). The incidence of ESBL-E infections was higher in intensive-care units (1.62 to 2.44 per 1,000 PD (p<0.001)) than in recovery and long-term care facilities (0.20 to 0.31 per 1,000 PD (p<0.001)). Escherichia coli was the most frequent extended-spectrum beta-lactamase-producing (ESBL) pathogen, representing 59% (26,238/44,425) of all ESBL isolates, followed by Klebsiella pneumoniae (20%; 8,856/44,425) in 2013. The most frequent infection was urinary tract infection, for all species. The incidence of ESBL-E varied by region but showed an upward trend overall. Reinforcement of control measures for halting the spread of such MRO is crucial.

[Teaching quantitative methods in public health: the EHESP experience]. / Enseignement des méthodes quantitatives en santé publique: l'expérience de l'EHESP.

Many scientific disciplines, including epidemiology and biostatistics, are used in the field of public health. These quantitative sciences are fundamental tools necessary for the practice of future professionals. What then should be the minimum quantitative sciences training, common to all future public health professionals? By comparing the teaching models developed in Columbia University and those in the National School of Public Health in France, the authors recognize the need to adapt teaching to the specific competencies required for each profession. They insist that all public health professionals, whatever their future career, should be familiar with quantitative methods in order to ensure that decision-making is based on a reflective and critical use of quantitative analysis.

Comorbidities directly extracted from the hospital database for adjusting SSI risk in the new national semiautomated surveillance system in France: The SPICMI network.

OBJECTIVE: To evaluate the performance of a comorbidity-based risk-adjustment model for surgical-site infection (SSI) reporting and benchmarking using a panel of variables extracted from the hospital discharge database (HDD), including comorbidities, compared to other models that use variables from different data sources. METHODS: The French national surveillance program for SSI (SPICMI) has collected data from voluntary hospitals in the first 6 months of 2020 and 2021, for 16 selected surgery procedures, using a semiautomated algorithm for detection. Four risk-adjustment models were selected with logistic regression analysis, combining the different patterns of variables: National Nosocomial Infections Surveillance System (NNIS) risk-index components, individual operative data, and 6 individual comorbidities according to International Classification of Disease, Tenth Revision (ICD-10) diagnosis: obesity, diabetes, malnutrition, hypertension, cancer, or immunosuppression. Areas under the curve (AUCs) were calculated and compared. RESULTS: Overall, 294 SSI were detected among 11,975 procedures included. All 6 comorbidities were related to SSI in the univariate analysis. The AUC of the selected model including comorbidities (0.675; 95% confidence interval [CI], 0.642-0.707), was significantly higher than the AUC of the model without comorbidities (0.641; 95% CI, 0.609-0.672; P = .016) or the AUC using the NNIS-index components (0.598; 95% CI, 0.564-0.630; P < .001). The HDD-based model AUC (0.659; 95% CI, 0.625-0.692) did not differ significantly from the selected model without comorbidities (P = .23). CONCLUSION: Including HDD-based comorbidities as patient case-mix variables instead of NNIS risk index factors could be an effective approach for risk-adjustment of automated SSI surveillance more widely accessible to hospitals.

Identifying individual and organizational predictors of accidental exposure to blood (AEB) among hospital healthcare workers: A longitudinal study.

BACKGROUND: Accidental exposure to blood (AEB) poses a risk of bloodborne infections for healthcare workers (HCWs) during hospital activities. In this study, we identified individual behavioral and organizational predictors of AEB among HCWs. METHODS: The study was a prospective, 1-year follow-up cohort study conducted in university hospitals in Paris, France. Data were collected from the Stress at Work and Infectious Risk in Patients and Caregivers (STRIPPS) study. Eligible participants included nurses, nursing assistants, midwives, and physicians from 32 randomly selected wards in 4 hospitals. AEB occurrences were reported at baseline, 4 months, 8 months, and 12 months, and descriptive statistical and multilevel risk-factor analyses were performed. RESULTS: The study included 730 HCWs from 32 wards, predominantly nurses (52.6%), nursing assistants (41.1%), physicians (4.8%), and midwives (1.5%). The incidence rate of AEB remained stable across the 4 visits. The multilevel longitudinal analysis identified several significant predictors of AEB occurrence. Individual-level predictors included younger age, occupation as nurses or midwives, irregular work schedule, rotating shifts, and lack of support from supervisors. The use of external nurses was the most significant ward-level predictor associated with AEB occurrence. CONCLUSIONS: AEBs among HCWs are strongly associated with organizational predictors, highlighting the importance of complementing infection control policies with improved staff management and targeted training. This approach can help reduce AEB occurrences and enhance workplace safety for HCWs.

National multidrug-resistant bacteria (MDRB) surveillance in France through the RAISIN network: a 9 year experience.

BACKGROUND: In the mid-1990s, the prevalence rate of multidrug-resistant bacteria (MDRB) in French hospitals was high and control of MDRB spread then became a major priority in the national infection control programme (ICP). METHODS: To evaluate the impact of the ICP, a national coordination of MDRB surveillance was set up in 2002. Data were collected 3 months a year in healthcare facilities (HCFs) on a voluntary basis. All clinical specimens of methicillin-resistant Staphylococcus aureus (MRSA) and extended-spectrum ß-lactamase-producing Enterobacteriaceae (ESBLE) were prospectively included. Incidences per 1000 patient days (PDs) were calculated and trends in incidence from 2003 to 2010 were assessed. RESULTS: Participation in the surveillance increased from 478 HCFs in 2002 to 933 in 2010. In 2010, MRSA incidence was 0.40/1000 PDs: 1.14 in intensive care units (ICUs), 0.48 in acute care facilities (ACFs) and 0.27 in rehabilitation and long-term care facilities (RLTCFs). ESBLE incidence was 0.39/1000 PDs: 1.63 in ICUs, 0.46 in ACFs and 0.23 in RLTCFs. MRSA incidence significantly decreased from 0.72/1000 PDs in 2003 to 0.41/1000 PDs in 2010 (P<10(-3)); in contrast, ESBLE incidence significantly increased from 0.17/1000 PDs to 0.48/1000 PDs (P<10(-3)). The most prevalent ESBLE were Enterobacter aerogenes (34%) and Escherichia coli (25%) in 2003 and E. coli (60%) and Klebsiella pneumoniae (18%) in 2010. CONCLUSION: These results demonstrate the positive impact of the national ICP on MRSA rates. In contrast, ESBLE incidence, especially ESBL-producing E. coli, is increasing dramatically and represents a serious threat for hospitals and for the community that deserves specific control actions.

Validation of the first computerized indicator for orthopaedic surgical site infections in France: ISO-ORTHO.

BACKGROUND: The French national authority for health (HAS) develops in-hospital indicators for improving quality of care, safety and patient outcome. Since 2017, it has developed a measurement of surgical site infections (SSI) after total hip or knee arthroplasty (TH/KA) by using a computerized indicator, called ISO-ORTHO, based on a hospital discharge database (HDD) algorithm. The aim of the study was to assess the performance of this new indicator . METHODS: The ISO-ORTHO performance was estimated via its positive predictive value (PPV) among adult patients having undergone a TH/KA between January 1st and September 30th 2018, based on the orthopaedic procedure codes. Patients at very high risk of SSI and/or with SSI not related to the in-hospital care were excluded. SSI were detected from the date of admission up to 90 days after the TH/KA using the ISO-ORTHO algorithm, based on 15 combinations of ICD-10 and procedure codes. Its PPV was estimated by a chart review in volunteer healthcare organisations (HCO). RESULTS: Over the study period, 777 HCO including 143,227 TH/KA stays were selected, providing 1,279 SSI according to the ISO-ORTHO indicator. The 90-day SSI rate was 0.89 per 100 TH/KA stays (0.98% for THA and 0.80% for TKA). Among the 448 HCO with at least 1 SSI, 250 HCO participated in reviewing 725 SSI charts; 665 were confirmed, giving a PPV of 90.3% [88.2-92.5%], 89.9% [87.1-92.8%] in THA and 90.9% [87.7-94.2%] in TKA. CONCLUSIONS: The PPV of ISO-ORTHO over 90% confirms its validity for any use according to the HAS method. ISO-ORTHO and detailed information were provided in 2020 to HCO and used for quality assessment and in-hospital risk management.

A computerized indicator for surgical site infection (SSI) assessment after total hip or total knee replacement: The French ISO-ORTHO indicator.

OBJECTIVE: The French National Authority for Health (HAS), with a multidisciplinary working group, developed an indicator 'ISO-ORTHO' to assess surgical site infections (SSIs) after total hip arthroplasty or total knee arthroplasty (THA/TKA) based on the hospital discharge database. We present the ISO-ORTHO indicator designed for SSI automated detection and its relevance for quality improvement and hospital benchmarks. METHODS: The algorithm is based on a combination of International Statistical Classification of Diseases, Tenth Revision (ICD-10) and procedure codes of the hospital stay. The target population was selected among adult patients who had a THA or TKA between January 1, 2017, and September 30, 2017. Patients at very high risk of SSI and/or with SSI not related to hospital care were excluded. We searched databases for SSIs up to 3 months after THA/TKA. The standardized infection ratio (SIR) of observed versus expected SSIs was calculated (logistic regression) and displayed as funnel plot with 2 and 3 standard deviations (SD) after adjustment for 13 factors known to increase SSI risk. RESULTS: In total, 790 hospitals and 139,926 THA/TKA stays were assessed; 1,253 SSI were detected in the 473 included hospitals (incidence, 0.9%: 1.0% for THA, 0.80% for TKA). The SSI rate was significantly higher in males (1.2%), in patients with previous osteo-articular infection (4.4%), and those with cancer (2.3%), obesity, or diabetes. Most hospitals (89.9%) were within 2 SD; however, 12 hospitals were classified as outliers at more than +3 SD (1.6% of facilities), and 59 hospitals (7.9%) were outliers between +2 SD and +3 SD. CONCLUSION: ISO-ORTHO is a relevant indicator for automated surveillance; it can provide hospitals a metric for SSI assessment that may contribute to improving patient outcomes.

Epidemiology of complex bone and joint infections in France using a national registry: The CRIOAc network.

OBJECTIVES: In France, a network of reference centers for bone and joint infections (BJI) was created in 2008, focused on the management of complex BJI (previous failure, difficult-to-treat microorganisms, heavy comorbidities or surgical procedures). A national registry was implemented from 2012, collecting decisions advised in periodic multidisciplinary meetings. We present here an epidemiological overview. METHODS: All consecutive adult patients presented from 2014 to 2019 in 23/30 reference centers were included in this cohort. Characteristics of patients, BJI, and medico-surgical management advice were described. RESULTS: 27,483 individual patients were included, corresponding to 28,365 distinct infectious episodes, which 17,328 were complex. Median age was 65 years, with 62% of men, 1/3 patients presented more than 2 comorbidities. Prosthetic joint infections (PJI) represented 42% of all BJIs (11,812 episodes). Staphylococcus aureus, coagulase-negative staphylococci and polymicrobial PJI represented 26%, 25% and 16% respectively. DAIR (debridement, antibiotics and implant retention) was proposed for 3,157 (27%), whereas one-stage and two-stage revision for 3,683 (31%) and 1,764 (15%). An antibiotic treatment was advised in 10,493 episodes (87%), with combination therapy in 88%. CONCLUSION: This national network allows an optimized management of complex BJIs. Its cohort is a unique opportunity to draw up a detailed epidemiological picture and to follow the trends of these infrequent infections.

PRAISE: providing a roadmap for automated infection surveillance in Europe.

INTRODUCTION: Healthcare-associated infections (HAI) are among the most common adverse events of medical care. Surveillance of HAI is a key component of successful infection prevention programmes. Conventional surveillance - manual chart review - is resource intensive and limited by concerns regarding interrater reliability. This has led to the development and use of automated surveillance (AS). Many AS systems are the product of in-house development efforts and heterogeneous in their design and methods. With this roadmap, the PRAISE network aims to provide guidance on how to move AS from the research setting to large-scale implementation, and how to ensure the delivery of surveillance data that are uniform and useful for improvement of quality of care. METHODS: The PRAISE network brings together 30 experts from ten European countries. This roadmap is based on the outcome of two workshops, teleconference meetings and review by an independent panel of international experts. RESULTS: This roadmap focuses on the surveillance of HAI within networks of healthcare facilities for the purpose of comparison, prevention and quality improvement initiatives. The roadmap does the following: discusses the selection of surveillance targets, different organizational and methodologic approaches and their advantages, disadvantages and risks; defines key performance requirements of AS systems and suggestions for their design; provides guidance on successful implementation and maintenance; and discusses areas of future research and training requirements for the infection prevention and related disciplines. The roadmap is supported by accompanying documents regarding the governance and information technology aspects of implementing AS. CONCLUSIONS: Large-scale implementation of AS requires guidance and coordination within and across surveillance networks. Transitions to large-scale AS entail redevelopment of surveillance methods and their interpretation, intensive dialogue with stakeholders and the investment of considerable resources. This roadmap can be used to guide future steps towards implementation, including designing solutions for AS and practical guidance checklists.

Surveillance of surgical-site infections: impact on quality of care and reporting dilemmas.

PURPOSE OF REVIEW: Among a wide range of publications on surgical-site infections (SSIs), many issues are still controversial, especially those concerning their monitoring and feedback. This review focuses on recent advances in surveillance as a tool for improving healthcare quality performance in surgery. RECENT FINDINGS: Recent data were obtained from many reference surveillance systems which tend to demonstrate significant decrease in SSI incidence rates over a several-year period. Most studies emphasize data feedback to surgical team is an important way to improve care quality and surgical performance. Few data demonstrated the relationship between the lack of compliance to control measures and SSI risk, including suboptimal antibiotic prophylaxis, perforated gloves, control of blood glucose, and avoidance of shaving. No clear consensus is achieved yet regarding preoperative systematic screening and decolonization of multidrug-resistant Staphylococcus aureus. There is a good amount of recent data regarding the benchmark approach for ranking surgery wards according to SSI rates. However, methodological issues on SSI indicator for public reporting are still being debated. Pilot studies attempt to demonstrate the usefulness of more cost-effective surveillance systems, especially those based on automated data process. SUMMARY: There are new exciting developments and perspectives in the field of surveillance and control of SSI. More data are needed to better establish the relationship with global care quality.