Hospital Transfer Network Structure as a Risk Factor for Clostridium difficile Infection

Association of hospital centrality in inter-hospital patient-sharing networks with patient mortality and length of stay

OBJECTIVE

The interdependence of hospitals is underappreciated in patient outcomes studies. We used a network science approach to foreground this interdependence. Specifically, within two large state-based interhospital networks, we examined the relationship of a hospital's network position with in-hospital mortality and length of stay.

METHODS

We constructed interhospital network graphs using data from the Healthcare Cost and Utilization Project and the American Hospital Association Annual Survey for Florida (2014) and California (2011). The exposure of interest was hospital centrality, defined as weighted degree (sum of all ties to a given hospital from other hospitals). The outcomes were in-hospital mortality and length of stay with sub-analyses for four acute medical conditions: pneumonia, heart failure, ischemic stroke, myocardial infarction. We compared outcomes for each quartile of hospital centrality relative to the most central quartile (Q4), independent of patient- and hospital-level characteristics, in this retrospective cross-sectional study.

RESULTS

The inpatient cohorts had 1,246,169 patients in Florida and 1,415,728 in California. Compared to Florida's central hospitals which had an overall mortality 1.60%, peripheral hospitals had higher in-hospital mortality (1.97%, adjusted OR (95%CI): Q1 1.61 (1.37, 1.89), p<0.001). Hospitals in the middle quartiles had lower in-hospital mortality compared to central hospitals (%, adjusted OR (95% CI): Q2 1.39%, 0.79 (0.70, 0.89), p<0.001; Q3 1.33%, 0.78 (0.70, 0.87), p<0.001). Peripheral hospitals had longer lengths of stay (adjusted incidence rate ratio (95% CI): Q1 2.47 (2.44, 2.50), p<0.001). These findings were replicated in California, and in patients with heart failure and pneumonia in Florida. These results show a u-shaped distribution of outcomes based on hospital network centrality quartile.

CONCLUSIONS

The position of hospitals within an inter-hospital network is associated with patient outcomes. Specifically, hospitals located in the peripheral or central positions may be most vulnerable to diminished quality outcomes due to the network. Results should be replicated with deeper clinical data.

Regional transmission patterns of carbapenemase-producing Enterobacterales: A healthcare network analysis

OBJECTIVE

Carbapenem-resistant Enterobacterales (CRE) pose a serious public health threat and spread rapidly between healthcare facilities (HCFs) during interfacility patient movement. We examined patterns of transmission of CRE associated with network clustering and positions during patient interfacility transfer.

METHODS

A retrospective cohort study was conducted in the Greater Houston region ofTexas, , and social network analysis was performed by constructing facility-to-facility patient transfer network using CRE surveillance data. The network method (community detection algorithm) was used to detect clustering patterns of CRE in the network. In addition, network measures of centrality and local connectivity (clustering coefficient) were computed for each healthcare facility. Zero-inflated negative binomial regression analysis was applied to test the association between network measures and facility-specific incidence rate of CRE.

RESULTS

A network of 268 healthcare facilities was identified, in which 10 acute-care hospitals (ACHs) alone accounted for 63% of identified CRE cases. Transmission of New Delhi metallo-β-lactamase-producing CRE occurred in 3 clusters, yet all cases were traced to patients who had had medical care abroad. The incidence rate of CRE attributed to ACHs was >4-fold (adjusted rate ratio, 4.5; 95% confidence interval [CI], 3.02-6.72) higher than that of long-term care facilities. Each additional patient shared with another HCF conferred a 3% (95% CI, 2%-4%) increase in the incidence rate of CRE at that HCF.

CONCLUSIONS

The incidence rates of CRE at a given HCF was predicted by the healthcare network metrics. Increased surveillance and selective targeting of high-risk facilities are warranted.

Nosocomial infections during extracorporeal membrane oxygenation

PURPOSE OF THE REVIEW

The aim of this review is to present the latest evidence regarding the prevention, diagnosis and treatment of nosocomial infections during extracorporeal membrane oxygenation (ECMO) support.

RECENT FINDINGS

New descriptive data from the Extracorporeal Life Support Organisation (ELSO) registry and single centre studies have been published. In parallel, there is an increase in the availability of evidence about the diagnostic accuracy of infection markers, yield of routine cultures, effectivity of antibiotic prophylaxis and other preventive measures.

SUMMARY

ECMO is a rescue therapy for severe hemodynamic or respiratory failure. Nosocomial infections on ECMO support are frequent (infection rate ranging between 20.5% to more than 50% of ECMO runs) and have impact in survival, with reported increases in the risk of death up to 63% in infected patients. However, diagnosis and treatment are challenging, as the unique relationship between patient and circuit may act as a confounder for infection and exacerbate the variability of antibiotic pharmacokinetics in critical illness. Clinical practice regarding antibiotic treatment and infection prevention is not yet supported by high-quality evidence.

A Systematic Review of Antibiotic Resistance Trends and Treatment Options for Hospital-Acquired Multidrug-Resistant Infections

Antimicrobial resistance is a major public health challenge described by the World Health Organization as one of the top 10 public health challenges worldwide. Drug-resistant microbes contribute significantly to morbidity and mortality in the hospital, especially in the critical care unit. The primary etiology of increasing antibiotic resistance is inappropriate and excessive use of antibiotics. The alarming rise of drug-resistant microbes worldwide threatens to erode our ability to treat infections with our current armamentarium of antibiotics. Unfortunately, the pace of development of new antibiotics by the pharmaceutical industry has not kept up with rising resistance to expand our options to treat microbial infections. The costs of antibiotic resistance include death and disability, extended hospital stays due to prolonged sickness, need for expensive therapies, rising healthcare expenditure, reduced productivity from time out of the workforce, and rising penury. This review sums up the common mechanisms, trends, and treatment options for hospital-acquired multidrug-resistant microbes.

A review of epidemiological models of Clostridioides difficile transmission and control (2009-2021)

Clostridioides difficile is the leading cause of infectious diarrhea and one of the most common healthcare-acquired infections worldwide. We performed a systematic search and a bibliometric analysis of mathematical and computational models for Clostridioides difficile transmission. We identified 33 publications from 2009 to 2021. Models have underscored the importance of asymptomatic colonized patients in maintaining transmission in health-care settings. Infection control, antimicrobial stewardship, active testing, and vaccination have often been evaluated in models. Despite active testing and vaccination being not currently implemented, they are the most commonly evaluated interventions. Some aspects of C. difficile transmission, such community transmission and interventions in health-care settings other than in acute-care hospitals, remained less evaluated through modeling.

Review of social networks of professionals in healthcare settings-where are we and what else is needed?

Background

Social Network Analysis (SNA) demonstrates great potential in exploring health professional relationships and improving care delivery, but there is no comprehensive overview of its utilization in healthcare settings. This review aims to provide an overview of the current state of knowledge regarding the use of SNA in understanding health professional relationships in different countries.

Methods

We conducted an umbrella review by searching eight academic databases and grey literature up to April 30, 2021, enhanced by citation searches. We completed study selection, data extraction and quality assessment using predetermined criteria. The information abstracted from the reviews was synthesized quantitatively, qualitatively and narratively.

Results

Thirteen reviews were included in this review, yielding 330 empirical studies. The degree of overlaps of empirical studies across included reviews was low (4.3 %), indicating a high diversity of included reviews and the necessity of this umbrella review. Evidence from low- and middle-income countries (LMIC), particularly Asian countries, was limited. The earliest review was published in 2010 and the latest in 2019. Six reviews focused on the construction or description of professional networks and seven reviews reported factors or influences of professional networks. We synthesized existing literature on social networks of health care professionals in the light of (i) theoretical frameworks, (ii) study design and data collection, (iii) network nodes, measures and analysis, and (iv) factors of professional networks and related outcomes. From the perspective of methodology, evidence lies mainly in cross-sectional study design and electronic data, especially administrative data showing “patient-sharing” relationships, which has become the dominant data collection method. The results about the impact of health professional networks on health-related consequences were often contradicting and not truly comparable.

Conclusions

Methodological limitations, inconsistent findings, and lack of evidence from LMIC imply an urgent need for further investigations. The potential for broader utilization of SNA among providers remains largely untapped and the findings of this review may contain important value for building optimal healthcare delivery networks.

PROSPERO registration number

The protocol was published and registered with PROSPERO, the International Prospective Register of Systematic Reviews (CRD42020205996).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12992-021-00772-7.

The Effect of Interdependences of Referral Behaviors on the Quality of Ambulatory Care: Evidence from Taiwan

Purpose

The purpose of this study is to investigate the effect of interdependences of healthcare providers’ referral behaviors on the quality of ambulatory care. The significance of this study is to address the concern regarding the low quality of ambulatory care due to the lack of a compulsory referral system under Taiwan’s National Health Insurance system.

Methods

We applied the dynamic connectedness network analysis to estimate the total connectedness index of the referral behavior network, which was separated into the horizontal and vertical referral behavior components in order to measure the interdependences of horizontal and vertical referral behaviors across hospitals and local clinics, respectively.

Results

Our results suggest that the interdependences of referral behaviors increase the quality of ambulatory care. The harmful effect on the quality of ambulatory care from the interdependences of horizontal referral behaviors within the local clinics sector is more significant than that from the interdependences of horizontal referral behaviors within the hospital sector, and the negative effect on the overall and chronic composite measures of avoidable hospital admissions from the interdependences of vertical behaviors associated with local clinics is more substantial than that from the interdependences of vertical behaviors within the hospital sector.

Conclusion

These results not only highlight the significance of care collaboration between local clinics and hospitals to restrain avoidable hospital admissions of chronic diseases for a better overall quality of ambulatory care, but they also suggest that the surveillance system established for the quality of ambulatory care under the global budget payment scheme for the local clinics sector should target ambulatory care for patients with acute conditions.

Interfacility transfer communication of multidrug-resistant organism colonization or infection status: Practices and barriers in the acute-care setting

OBJECTIVE

To describe interfacility transfer communication (IFTC) methods for notification of multidrug-resistant organism (MDRO) status in a diverse sample of acute-care hospitals.

DESIGN

Cross-sectional survey.

PARTICIPANTS

Hospitals within the Society for Healthcare Epidemiology of America (SHEA) Research Network (SRN).

METHODS

SRN members completed an electronic survey on protocols and methods for IFTC. We assessed differences in IFTC frequency, barriers, and perceived benefit by presence of an IFTC protocol.

RESULTS

Among 136 hospital representatives who were sent the survey, 54 (40%) responded, of whom 72% reported having an IFTC protocol in place. The presence of a protocol did not differ significantly by hospital size, academic affiliation, or international status. Of those with IFTC protocols, 44% reported consistent notification of MDRO status (>75% of the time) to receiving facilities, as opposed to 13% from those with no IFTC protocol (P = .04). Respondents from hospitals with IFTC protocols reported significantly fewer barriers to communication compared to those without (2.8 vs 4.3; P = .03). Overall, however, most respondents (56%) reported a lack of standardization in communication. Presence of an IFTC protocol did not affect whether respondents perceived IFTC protocols as having a significant impact on infection prevention or antimicrobial stewardship.

CONCLUSIONS

Most respondents reported having an IFTC protocol, which was associated with reduced communication barriers at transfer. Standardization of protocols and clarity about expectations for sending and receipt of information related to MDRO status may facilitate IFTC and promote appropriate and timely infection prevention practices.

Interfacility patient sharing and Clostridioides difficile infection incidence in the Ontario hospital system: A 13-year cohort study

OBJECTIVE

Interfacility patient movement plays an important role in the dissemination of antimicrobial-resistant organisms throughout healthcare systems. We evaluated how 3 alternative measures of interfacility patient sharing were associated with C. difficile infection incidence in Ontario acute-care facilities.

DESIGN

The cohort included adult acute-care facility stays of ≥3 days between April 2003 and March 2016. We measured 3 facility-level metrics of patient sharing: general patient importation, incidence-weighted patient importation, and C. difficile case importation. Each of the 3 patient-sharing metrics were examined against the incidence of C. difficile infection in the facility per 1,000 stays, using Poisson regression models.

RESULTS

The analyzed cohort included 6.70 million stays at risk of C. difficile infection across 120 facilities. Over the 13-year period, we included 62,189 new cases of healthcare-associated CDI (incidence, 9.3 per 1,000 stays). After adjustment for facility characteristics, general importation was not strongly associated with C. difficile infection incidence (risk ratio [RR] per doubling, 1.10; 95% confidence interval [CI], 0.97-1.24; proportional change in variance [PCV], -2.0%). Incidence-weighted (RR per doubling, 1.18; 95% CI, 1.06-1.30; PCV, -8.4%) and C. difficile case importation (RR per doubling, 1.43; 95% CI, 1.29-1.58; PCV, -30.1%) were strongly associated with C. difficile infection incidence.

CONCLUSIONS

In this 13-year study of acute-care facilities in Ontario, interfacility variation in C. difficile infection incidence was associated with importation of patients from other high-incidence acute-care facilities or specifically of patients with a recent history of C. difficile infection. Regional infection control strategies should consider the potential impact of importation of patients at high risk of C. difficile shedding from outside facilities.

Evaluating Movement of Patients With Carbapenem-resistant Enterobacteriaceae Infections in the Greater Atlanta Metropolitan Area Using Social Network Analysis

BACKGROUND

Carbapenem-resistant Enterobacteriaceae (CRE) are an urgent threat with potential for rapid spread. We evaluated the role of Medicare patient movement between facilities to model the spread of CRE within a region.

METHODS

Through population-based CRE surveillance in the 8-county Atlanta (GA) metropolitan area, all Escherichia coli, Enterobacter spp., or Klebsiella spp. resistant to ≥1 carbapenem were reported from residents. CRE was attributed to a facility based on timing of culture and facility exposures. Centrality metrics were calculated from 2016 Medicare data and compared to CRE-transfer derived centrality metrics by Spearman correlation.

RESULTS

During 2016, 283 incident CRE cases with concurrent or prior year facility stays were identified; cases were attributed mostly to acute care hospitals (ACHs; 141, 50%) and skilled nursing facilities (SNFs; 113, 40%), and less frequently to long-term acute care hospitals (LTACHs; 29, 10%). Attribution was widespread, originating at 17 of 20 ACHs (85%), 7 of 8 (88%) LTACHs, but only 35 of 65 (54%) SNFs. Betweenness of Medicare patient transfers strongly correlated with betweenness of CRE case-transfer data in ACHs (r = 0.75; P < .01) and LTACHs (r = 0.77; P = .03), but not in SNFs (r = 0.02; P = 0.85). We noted 6 SNFs with high CRE-derived betweenness but low Medicare-derived betweenness.

CONCLUSIONS

CRE infections originate from almost all ACHs and half of SNFs. We identified a subset of SNFs central to the CRE transfer network but not the Medicare transfer network; other factors may explain CRE patient movement in these facilities.

Modelling pathogen spread in a healthcare network: Indirect patient movements

Inter-hospital patient transfers (direct transfers) between healthcare facilities have been shown to contribute to the spread of pathogens in a healthcare network. However, the impact of indirect transfers (patients re-admitted from the community to the same or different hospital) is not well studied. This work aims to study the contribution of indirect transfers to the spread of pathogens in a healthcare network. To address this aim, a hybrid network–deterministic model to simulate the spread of multiresistant pathogens in a healthcare system was developed for the region of Lower Saxony (Germany). The model accounts for both, direct and indirect transfers of patients. Intra-hospital pathogen transmission is governed by a SIS model expressed by a system of ordinary differential equations. Our results show that the proposed model reproduces the basic properties of healthcare-associated pathogen spread. They also show the importance of indirect transfers: restricting the pathogen spread to direct transfers only leads to 4.2% system wide prevalence. However, adding indirect transfers leads to an increase in the overall prevalence by a factor of 4 (18%). In addition, we demonstrated that the final prevalence in the individual healthcare facilities depends on average length of stay in a way described by a non-linear concave function. Moreover, we demonstrate that the network parameters of the model may be derived from administrative admission/discharge records. In particular, they are sufficient to obtain inter-hospital transfer probabilities, and to express the patients’ transfers as a Markov process. Using the proposed model, we show that indirect transfers of patients are equally or even more important as direct transfers for the spread of pathogens in a healthcare network.

Direct patient transfers between hospitals have been shown to play an important role in the spread of pathogens in a healthcare network. However, readmission of patients from the community (indirect transfers) to the same or a different hospital is not well studied, and its role for the spread of pathogens in a healthcare network is not quantified. In this work, we developed a network model of a healthcare system to study the impact of indirect transfers on the prevalence in the individual hospitals as well as in the overall healthcare system. The model includes both, direct and indirect transfers of patients between the healthcare facilities due to transferring as well as readmission of infectious (colonized or infected) patients. Our results show that the readmission of patients (indirect transfers), either to the same or different facility, is an important potential channel of pathogen transmission. Such indirect transfers are of no less importance than direct patient transfers in controlling the spread of pathogens in a healthcare network.

Assessing the role of inter-facility patient transfer in the spread of carbapenemase-producing Enterobacteriaceae: the case of France between 2012 and 2015

The spread of carbapenemase-producing Enterobacteriaceae (CPE) in healthcare settings is a major public health threat that has been associated with cross-border and local patient transfers between healthcare facilities. Since the impact of transfers on spread may vary, our study aimed to assess the contribution of a patient transfer network on CPE incidence and spread at a countrywide level, with a case study of France from 2012 to 2015. Our results suggest a transition in 2013 from a CPE epidemic sustained by internationally imported episodes to an epidemic sustained by local transmission events through patient transfers. Incident episodes tend to occur within close spatial distance of their potential infector. We also observe an increasing frequency of multiple spreading events, originating from a limited number of regional hubs. Consequently, coordinated prevention and infection control strategies should focus on transfers of carriers of CPE to reduce regional and inter-regional transmission.

Web-Based Interactive Tool to Identify Facilities at Risk of Receiving Patients with Multidrug-Resistant Organisms

To identify facilities at risk of receiving patients colonized or infected with multidrug-resistant organisms (MDROs), we developed an interactive web-based interface for visualization of patient-sharing networks among healthcare facilities in Tennessee, USA. Using hospital discharge data and the Centers for Medicare and Medicaid Services' claims and Minimum Data Set, we constructed networks among hospitals and skilled nursing facilities. Networks included direct and indirect transfers, which accounted for <365 days in the community outside of facility admissions. Authorized users can visualize a facility of interest and tailor visualizations by year, network dataset, length of time in the community, and minimum number of transfers. The interface visualizes the facility of interest with its connected facilities that receive or send patients, the number of interfacility transfers, and facilities at risk of receiving transfers from the facility of interest. This tool will help other health departments enhance their MDRO outbreak responses.

Advances in Data-Driven Responses to Preventing Spread of Antibiotic Resistance Across Health-Care Settings

Among the most urgent and serious threats to public health are 7 antibiotic-resistant bacterial infections predominately acquired during health-care delivery. There is an emerging field of health-care epidemiology that is focused on preventing health care-associated infections with antibiotic-resistant bacteria and incorporates data from patient transfers or patient movements within and between facilities. This analytic field is being used to help public health professionals identify best opportunities for prevention. Different analytic approaches that draw on uses of big data are being explored to help target the use of limited public health resources, leverage expertise, and enact effective policy to maximize an impact on population-level health. Here, the following recent advances in data-driven responses to preventing spread of antibiotic resistance across health-care settings are summarized: leveraging big data for machine learning, integration or advances in tracking patient movement, and highlighting the value of coordinating response across institutions within a region.

Modeling inpatient and outpatient antibiotic stewardship interventions to reduce the burden of Clostridioides difficile infection in a regional healthcare network

Antibiotic exposure can lead to unintended outcomes, including drug-drug interactions, adverse drug events, and healthcare-associated infections like Clostridioides difficile infection (CDI). Improving antibiotic use is critical to reduce an individual's CDI risk. Antibiotic stewardship initiatives can reduce inappropriate antibiotic prescribing (e.g., unnecessary antibiotic prescribing, inappropriate antibiotic selection), impacting both hospital (healthcare)-onset (HO)-CDI and community-associated (CA)-CDI. Previous computational and mathematical modeling studies have demonstrated a reduction in CDI incidence associated with antibiotic stewardship initiatives in hospital settings. Although the impact of antibiotic stewardship initiatives in long-term care facilities (LTCFs), including nursing homes, and in outpatient settings have been documented, the effects of specific interventions on CDI incidence are not well understood. We examined the relative effectiveness of antibiotic stewardship interventions on CDI incidence using a geospatially explicit agent-based model of a regional healthcare network in North Carolina. We simulated reductions in unnecessary antibiotic prescribing and inappropriate antibiotic selection with intervention scenarios at individual and network healthcare facilities, including short-term acute care hospitals (STACHs), nursing homes, and outpatient locations. Modeled antibiotic prescription rates were calculated using patient-level data on antibiotic length of therapy for the 10 modeled network STACHs. By simulating a 30% reduction in antibiotics prescribed across all inpatient and outpatient locations, we found the greatest reductions on network CDI incidence among tested scenarios, namely a 17% decrease in HO-CDI incidence and 7% decrease in CA-CDI. Among intervention scenarios of reducing inappropriate antibiotic selection, we found a greater impact on network CDI incidence when modeling this reduction in nursing homes alone compared to the same intervention in STACHs alone. These results support the potential importance of LTCF and outpatient antibiotic stewardship efforts on network CDI burden and add to the evidence that a coordinated approach to antibiotic stewardship across multiple facilities, including inpatient and outpatient settings, within a regional healthcare network could be an effective strategy to reduce network CDI burden.

Creation of a Geospatially Explicit, Agent-based Model of a Regional Healthcare Network with Application to Clostridioides difficile Infection

Agent-based models (ABMs) describe and simulate complex systems comprising unique agents, or individuals, while accounting for geospatial and temporal variability among dynamic processes. ABMs are increasingly used to study healthcare-associated infections (ie, infections acquired during admission to a healthcare facility), including Clostridioides difficile infection, currently the most common healthcare-associated infection in the United States. The overall burden and transmission dynamics of healthcare-associated infections, including C difficile infection, may be influenced by community sources and movement of people among healthcare facilities and communities. These complex dynamics warrant geospatially explicit ABMs that extend beyond single healthcare facilities to include entire systems (eg, hospitals, nursing homes and extended care facilities, the community). The agents in ABMs can be built on a synthetic population, a model-generated representation of the actual population with associated spatial (eg, home residence), temporal (eg, change in location over time), and nonspatial (eg, sociodemographic features) attributes. We describe our methods to create a geospatially explicit ABM of a major regional healthcare network using a synthetic population as microdata input. We illustrate agent movement in the healthcare network and the community, informed by patient-level medical records, aggregate hospital discharge data, healthcare facility licensing data, and published literature. We apply the ABM output to visualize agent movement in the healthcare network and the community served by the network. We provide an application example of the ABM to C difficile infection using a natural history submodel. We discuss the ABM's potential to detect network areas where disease risk is high; simulate and evaluate interventions to protect public health; adapt to other geographic locations and healthcare-associated infections, including emerging pathogens; and meaningfully translate results to public health practitioners, healthcare providers, and policymakers.

Incidence, Predictors, and Impact of Clostridium difficile Infection on Cardiac Surgery Outcomes

BACKGROUND

Clostridium difficile infection (CDI) has been associated with morbidity and mortality after cardiac operations. The present study examined incidence, predictors, and impact of CDI on inpatient mortality and resource utilization.

METHODS

An analysis of adult patients undergoing elective coronary artery bypass grafting or valvular operations from 2005 to 2016 was performed using the National Inpatient Sample. Trends in CDI were assessed using a modified Cochran-Armitage analysis. Multivariable multilevel regressions were used to identify predictors of CDI, and propensity-matched pairs were generated using Mahalanobis 1-to-1 matching to compare mortality, length of stay, and costs of CDI patients with the non-CDI cohort.

RESULTS

The overall rate of CDI for an estimated 2,026,267 patients who underwent elective major cardiac surgery was 0.5% with no change in incidence (P for trend = .99). Predictors of CDI included advanced age (≥65 y; adjusted odds ratio [AOR], 1.88; 95% confidence interval [CI], 1.58-2.24), female gender (AOR, 1.29; 95% CI, 1.15-1.44), heart failure (AOR, 1.57; 95% CI, 1.40-1.76), and combined coronary artery bypass grafting/valve operations (AOR, 1.60; 95% CI, 1.24-2.08). Neither region nor bed size was associated with CDI. In contrast CDI mortality was lower at teaching hospitals compared with rural hospitals. Among matched pairs CDI was independently associated with higher mortality, length of stay, and Gross Domestic Product-adjusted costs.

CONCLUSIONS

CDI occurs in less than 1% of all elective, major cardiac operations. Patient predictors included advanced age, female gender, and several chronic comorbidities. Teaching institutions had the highest odds of CDI but lowest odds of case fatality. Further investigation of factors contributing to CDI is warranted to disseminate institutional best practices.

Compliance with statewide regulations for communication of patients' multidrug-resistant organism and Clostridium difficile status during transitions of care

In 2014, Oregon implemented an interfacility transfer communication law requiring notification of multidrug-resistant organism status on patient transfer. Based on 2015 and 2016 statewide facility surveys, compliance was 77% and 87% for hospitals, and 67% and 68% for skilled nursing facilities. Methods for complying with the rule were heterogeneous, and fewer than half of all facilities surveyed reported use of a standardized interfacility transfer communication form to assess a patient's multidrug-resistant organism status on transfer.

Predictors of Hospital-Acquired Clostridioides difficile Infection: A Systematic Review

BACKGROUND

Clostridioides difficile infections (CDIs) have been identified as a major health concern due to the high morbidity, mortality, and cost of treatment. The aim of this study was to review the extant literature and identify the various patient-related, medication-related, and organizational risk factors associated with developing hospital-acquired CDIs in adult patients in the United States.

METHODS

A systematic review of four (4) online databases, including Scopus, PubMed, CINAHL, and Cochrane Library, was conducted to identify empirical studies published from 2007 to 2017 pertaining to risk factors of developing hospital-acquired CDIs.

FINDINGS

Thirty-eight studies (38) were included in the review. Various patient-level and medication-related risk factors were identified including advanced patient age, comorbidities, length of hospital stay, previous hospitalizations, use of probiotic medications and proton pump inhibitors. The review also identified organizational factors such as room size, academic affiliation, and geographic location to be significantly associated with hospital-acquired CDIs.

CONCLUSION

Validation of the factors associated with high risk of developing hospital-acquired CDIs identified in this review can aid in the development of risk prediction models to identify patients who are at a higher risk of developing CDIs and developing quality improvement interventions that might improve patient outcomes by minimizing risk of infection.

Analysis of network interventions with an application to hospital-acquired infections

Regional interventions to prevent the spread of hospital-acquired infections, vaccination campaigns, and information dissemination strategies are examples of treatment interventions applied to members of a network with the intent of effecting a network-wide change. In designing clinical trials or determining policy changes, it may not be cost effective or otherwise possible to treat all actors of a network. There is a notable lack of study designs and statistical frameworks with which to plan a network-wide intervention in this context and analyze the resulting data. This paper builds off of the network autocorrelation model in order to provide such a framework for a pre-post study design. We derive key quantitative measures of the network-wide treatment effect, exact formulas for power analyses of these measures, and extensions for the context in which the network is unknown. As the treatment assignation is part of the network-wide treatment, we provide methods for determining the assignation which optimizes the overall treatment effect over all members of the network subject to any arbitrary set of implementation costs and cost constraint. We implement these methods on Clostridioides difficile data for the state of California, where the hospitals are linked through patient sharing.

Regional Spread of an Outbreak of Carbapenem-Resistant Enterobacteriaceae Through an Ego Network of Healthcare Facilities

Background

In 2013, New Delhi metallo-β-lactamase (NDM)-producing Escherichia coli, a type of carbapenem-resistant Enterobacteriaceae uncommon in the United States, was identified in a tertiary care hospital (hospital A) in northeastern Illinois. The outbreak was traced to a contaminated duodenoscope. Patient-sharing patterns can be described through social network analysis and ego networks, which could be used to identify hospitals most likely to accept patients from a hospital with an outbreak.

Methods

Using Illinois' hospital discharge data and the Illinois extensively drug-resistant organism (XDRO) registry, we constructed an ego network around hospital A. We identified which facilities NDM outbreak patients subsequently visited and whether the facilities reported NDM cases.

Results

Of the 31 outbreak cases entered into the XDRO registry who visited hospital A, 19 (61%) were subsequently admitted to 13 other hospitals during the following 12 months. Of the 13 hospitals, the majority (n = 9; 69%) were in our defined ego network, and 5 of those 9 hospitals consequently reported at least 1 additional NDM case. Ego network facilities were more likely to identify cases compared to a geographically defined group of facilities (9/22 vs 10/66; P = .01); only 1 reported case fell outside of the ego network.

Conclusions

The outbreak hospital's ego network accurately predicted which hospitals the outbreak patients would visit. Many of these hospitals reported additional NDM cases. Prior knowledge of this ego network could have efficiently focused public health resources on these high-risk facilities.

Frequent Undetected Ward-Based Methicillin-Resistant Staphylococcus aureus Transmission Linked to Patient Sharing Between Hospitals

Background

Recent evidence suggests that hospital transmission of methicillin-resistant Staphylococcus aureus (MRSA) is uncommon in UK centers that have implemented sustained infection control programs. We investigated whether a healthcare-network analysis could shed light on transmission paths currently sustaining MRSA levels in UK hospitals.

Methods

A cross-sectional observational study was performed in 2 National Health Service hospital groups and a general district hospital in Southeast London. All MRSA patients identified at inpatient, outpatient, and community settings between 1 November 2011 and 29 February 2012 were included. We identified genetically defined MRSA transmission clusters in individual hospitals and across the healthcare network, and examined genetic differentiation of sequence type (ST) 22 MRSA isolates within and between hospitals and inpatient or outpatient and community settings, as informed by average and median pairwise single-nucleotide polymorphisms (SNPs) and SNP-based proportions of nearly identical isolates.

Results

Two hundred forty-eight of 610 (40.7%) MRSA patients were linked in 90 transmission clusters, of which 27 spanned multiple hospitals. Analysis of a large 32 patient ST22-MRSA cluster showed that 26 of 32 patients (81.3%) had multiple contacts with one another during ward stays at any hospital. No residential, outpatient, or significant community healthcare contacts were identified. Genetic differentiation between ST22 MRSA inpatient isolates from different hospitals was less than between inpatient isolates from the same hospitals (P ≤ .01).

Conclusions

There is evidence of frequent ward-based transmission of MRSA brought about by frequent patient admissions to multiple hospitals. Limiting in-ward transmission requires sharing of MRSA status data between hospitals.

Using hospital network-based surveillance for antimicrobial resistance as a more robust alternative to self-reporting

Hospital performance is often measured using self-reported statistics, such as the incidence of hospital-transmitted micro-organisms or those exhibiting antimicrobial resistance (AMR), encouraging hospitals with high levels to improve their performance. However, hospitals that increase screening efforts will appear to have a higher incidence and perform poorly, undermining comparison between hospitals and disincentivising testing, thus hampering infection control. We propose a surveillance system in which hospitals test patients previously discharged from other hospitals and report observed cases. Using English National Health Service (NHS) Hospital Episode Statistics data, we analysed patient movements across England and assessed the number of hospitals required to participate in such a reporting scheme to deliver robust estimates of incidence. With over 1.2 million admissions to English hospitals previously discharged from other hospitals annually, even when only a fraction of hospitals (41/155) participate (each screening at least 1000 of these admissions), the proposed surveillance system can estimate incidence across all hospitals. By reporting on other hospitals, the reporting of incidence is separated from the task of improving own performance. Therefore the incentives for increasing performance can be aligned to increase (rather than decrease) screening efforts, thus delivering both more comparable figures on the AMR problems across hospitals and improving infection control efforts.

Reduction in Clostridium difficile infection rates following a multifacility prevention initiative in Orange County, California: A controlled interrupted time series evaluation

OBJECTIVE

To evaluate the Orange County Clostridium difficile infection (CDI) prevention collaborative's effect on rates of CDI in acute-care hospitals (ACHs) in Orange County, California.

DESIGN

Controlled interrupted time series.

METHODS

We convened a CDI prevention collaborative with healthcare facilities in Orange County to reduce CDI incidence in the region. Collaborative participants received onsite infection control and antimicrobial stewardship assessments, interactive learning and discussion sessions, and an interfacility transfer communication improvement initiative during June 2015-June 2016. We used segmented regression to evaluate changes in monthly hospital-onset (HO) and community-onset (CO) CDI rates for ACHs. The baseline period comprised 17 months (January 2014-June 2015) and the follow-up period comprised 28 months (September 2015-December 2017). All 25 Orange County ACHs were included in the CO-CDI model to account for direct and indirect effects of the collaborative. For comparison, we assessed HO-CDI and CO-CDI rates among 27 ACHs in 3 San Francisco Bay Area counties.

RESULTS

HO-CDI rates in the 15 participating Orange County ACHs decreased 4% per month (incidence rate ratio [IRR], 0.96; 95% CI, 0.95-0.97; P &lt; .0001) during the follow-up period compared with the baseline period and 3% (IRR, 0.97; 95% CI, 0.95-0.99; P = .002) per month compared to the San Francisco Bay Area nonparticipant ACHs. Orange County CO-CDI rates declined 2% per month (IRR, 0.98; 95% CI, 0.96-1.00; P = .03) between the baseline and follow-up periods. This decline was not statistically different from the San Francisco Bay Area ACHs (IRR, 0.97; 95% CI, 0.95-1.00; P = .09).

CONCLUSIONS

Our analysis of ACHs in Orange County provides evidence that coordinated, regional multifacility initiatives can reduce CDI incidence.

Estimating the Attributable Disease Burden and Effects of Interhospital Patient Sharing on Clostridium difficile Infections

Objective:

To estimate the burden of Clostridium difficile infections (CDIs) due to interfacility patient sharing at regional and hospital levels.

Design:

Retrospective observational study.

Methods:

We used data from the Healthcare Cost and Utilization Project California State Inpatient Database (2005–2011) to identify 26,878,498 admissions and 532,925 patient transfers. We constructed a weighted, directed network among the hospitals by defining an edge between 2 hospitals to be the monthly average number of patients discharged from one hospital and admitted to another on the same day. We then used a network autocorrelation model to study the effect of the patient sharing network on the monthly average number of CDI cases per hospital, and we estimated the proportion of CDI cases attributable to the network.

Results:

We found that 13% (95% confidence interval [CI], 7.6%–18%) of CDI cases were due to diffusion through the patient-sharing network. The network autocorrelation parameter was estimated at 5.0 (95% CI, 3.0–6.9). An increase in the number of patients transferred into and/or an increased CDI rate at the hospitals from which those patients originated led to an increase in the number of CDIs in the receiving hospital.

Conclusions:

A minority but substantial burden of CDI infections are attributable to hospital transfers. A hospital’s infection control may thus be nontrivially influenced by its neighboring hospitals. This work adds to the growing body of evidence that intervention strategies designed to minimize HAIs should be done at the regional rather than local level.

Individual- and community-level risk factors for ESBL Enterobacteriaceae colonization identified by universal admission screening in London

OBJECTIVES

We evaluated risk factors for gastrointestinal carriage of Enterobacteriaceae which produce extended-spectrum β-lactamases (ESBL-E), including individual-level variables such as antibiotic use and foreign travel, and community-level variables such as housing and deprivation.

METHODS

In an observational study in 2015, all patients admitted to a London hospital group were approached to be screened for ESBL-E carriage using rectal swabs for 4 months. Patients completed a risk factor questionnaire. Those with a residential postcode in the local catchment area were linked to a database containing community-level risk factor data. Risk factors for ESBL-E carriage were determined by binary logistic regression.

RESULTS

Of 4006 patients, 360 (9.0%) carried ESBL-E. Escherichia coli was the most common organism (77.8%), and CTX-M-type ESBLs were the most common genes (57.9% CTX-M-15 and 20.7% CTX-M-9). In multivariable analysis, risk factors for phenotypic ESBL-E among the 1633 patients with a residential postcode within the local catchment area were: travel to Asia (OR 4.4, CI 2.5-7.6) or Africa (OR 2.4, CI 1.2-4.8) in the 12 months prior to admission, two or more courses of antibiotics in the 6 months prior to admission (OR 2.0, CI 1.3-3.0), and residence in a district with a higher-than-average prevalence of overcrowded households (OR 1.5, CI 1.05-2.2). .

CONCLUSIONS

Both individual and community variables were associated with ESBL-E carriage at hospital admission. The novel observation that household overcrowding is associated with ESBL-E carriage requires confirmation, but raises the possibility that targeted interventions in the community could help prevent transmission of antibiotic-resistant Gram-negative bacteria.

A scoping review of patient-sharing network studies using administrative data

There is a robust literature examining social networks and health, which draws on the network traditions in sociology and statistics. However, the application of social network approaches to understand the organization of health care is less well understood. The objective of this work was to examine approaches to conceptualizing, measuring, and analyzing provider patient-sharing networks. These networks are constructed using administrative data in which pairs of physicians are considered connected if they both deliver care to the same patient. A scoping review of English language peer-reviewed articles in PubMed and Embase was conducted from inception to June 2017. Two reviewers evaluated article eligibility based upon inclusion criteria and abstracted relevant data into a database. The literature search identified 10,855 titles, of which 63 full-text articles were examined. Nine additional papers identified by reviewing article references and authors were examined. Of the 49 papers that met criteria for study inclusion, 39 used a cross-sectional study design, 6 used a cohort design, and 4 were longitudinal. We found that studies most commonly theorized that networks reflected aspects of collaboration or coordination. Less commonly, studies drew on the strength of weak ties or diffusion of innovation frameworks. A total of 180 social network measures were used to describe the networks of individual providers, provider pairs and triads, the network as a whole, and patients. The literature on patient-sharing relationships between providers is marked by a diversity of measures and approaches. We highlight key considerations in network identification including the definition of network ties, setting geographic boundaries, and identifying clusters of providers, and discuss gaps for future study.

Antimicrobial-Resistant Klebsiella pneumoniae Carriage and Infection in Specialized Geriatric Care Wards Linked to Acquisition in the Referring Hospital

Background

Klebsiella pneumoniae is a leading cause of extended-spectrum β-lactamase (ESBL)-producing hospital-associated infections, for which elderly patients are at increased risk.

Methods

We conducted a 1-year prospective cohort study, in which a third of patients admitted to 2 geriatric wards in a specialized hospital were recruited and screened for carriage of K. pneumoniae by microbiological culture. Clinical isolates were monitored via the hospital laboratory. Colonizing and clinical isolates were subjected to whole-genome sequencing and antimicrobial susceptibility testing.

Results

K. pneumoniae throat carriage prevalence was 4.1%, rectal carriage 10.8%, and ESBL carriage 1.7%, and the incidence of K. pneumoniae infection was 1.2%. The isolates were diverse, and most patients were colonized or infected with a unique phylogenetic lineage, with no evidence of transmission in the wards. ESBL strains carried blaCTX-M-15 and belonged to clones associated with hospital-acquired ESBL infections in other countries (sequence type [ST] 29, ST323, and ST340). One also carried the carbapenemase blaIMP-26. Genomic and epidemiological data provided evidence that ESBL strains were acquired in the referring hospital. Nanopore sequencing also identified strain-to-strain transmission of a blaCTX-M-15 FIBK/FIIK plasmid in the referring hospital.

Conclusions

The data suggest the major source of K. pneumoniae was the patient's own gut microbiome, but ESBL strains were acquired in the referring hospital. This highlights the importance of the wider hospital network to understanding K. pneumoniae risk and infection prevention. Rectal screening for ESBL organisms on admission to geriatric wards could help inform patient management and infection control in such facilities.

Factors associated with an outbreak of hospital-onset, healthcare facility-associated Clostridium difficile infection (HO-HCFA CDI) in a Mexican tertiary care hospital: A case-control study

Objective

To identify clinical and environmental factors associated with an outbreak of hospital-onset, healthcare facility-associated Clostridium difficile infection (HO-HCFA CDI).

Design

Case-control study.

Setting

Public, acute care, academic tertiary referral center in Mexico.

Patients

Adults hospitalized ≥48 hours between January 2015 and December 2016 were included. Cases were patients with a first episode of HO-HCFA CDI. Controls were patients with any other diagnosis; they were randomly selected from the hospital discharge database and matched in a 1:2 manner according to the date of diagnosis of case ± 10 days. Variables with p<0.1 were considered for multivariable analysis.

Results

One hundred and fifty-five cases and 310 controls were included. Variables independently associated with HO-HCFA CDI were: exposure to both ciprofloxacin and proton pump inhibitor (PPI) within the last 3 months (OR = 8.07, 95% CI = 1.70–38.16), febrile neutropenia (OR = 4.61, 95% CI = 1.37–15.46), intraabdominal infection (OR = 2.06, 95% CI = 0.95–4.46), referral from other hospitals (OR = 1.99, 95% CI = 0.98–4.05) and an increasing number of antibiotics previously used (OR = 1.28, 95% CI = 1.13–1.46).

Conclusions

Multiple factors were found to be associated with the first episode of HO-HCFA CDI in the setting of an outbreak; of the modifiable risk factors, prior exposure to both ciprofloxacin and PPI was the most important. Referral from other hospitals was an environmental risk factor that deserves further study.

Interhospital patient transfers between Ontario's academic and large community hospitals increase the risk of Clostridium difficile infection

BACKGROUND

The objective of this study is to determine the impact of interhospital patient transfers on the risk of Clostridium difficile infection (CDI).

METHODS

The number of interhospital patient transfers and CDI cases for 11 academic and 40 large community hospitals (LCHs) were available from 2010-2015. These data were used to compute a CDI score for each sending facility as a measure of CDI pressure on the receiving facility. This CDI score was included as a variable in a multilevel mixed-effect Poisson regression model of CDI cases. Other covariates included year, CDI testing strategy, antimicrobial stewardship program (ASP), and criteria used for patient isolation. Hospital-specific random effects were estimated for the baseline rate of CDI (intercept) and ASP effect (slope).

RESULTS

The CDI score ranged from 0-103, with a mean score ± SD of 20.4 ± 21.8. Every 10-point increase in the CDI score was associated with a 4.5% increase in the incidence of CDI in the receiving academic hospital (95% confidence interval [CI], 0.9-8.5) and 3.6% increase in the receiving LCHs (95% CI, 0.3-7). The random components of the model varied significantly, with a strong negative correlation of -0.85 (95% CI, -0.94 to -0.65).

CONCLUSIONS

Our results suggest interhospital patient transfers increase the risk of CDI. ASPs appear to reduce this risk; however, these ASP effects demonstrate significant heterogeneity across hospitals.

Applications of network analysis to routinely collected health care data: a systematic review

Objective

To survey network analyses of datasets collected in the course of routine operations in health care settings and identify driving questions, methods, needs, and potential for future research.

Materials and Methods

A search strategy was designed to find studies that applied network analysis to routinely collected health care datasets and was adapted to 3 bibliographic databases. The results were grouped according to a thematic analysis of their settings, objectives, data, and methods. Each group received a methodological synthesis.

Results

The search found 189 distinct studies reported before August 2016. We manually partitioned the sample into 4 groups, which investigated institutional exchange, physician collaboration, clinical co-occurrence, and workplace interaction networks. Several robust and ongoing research programs were discerned within (and sometimes across) the groups. Little interaction was observed between these programs, despite conceptual and methodological similarities.

Discussion

We use the literature sample to inform a discussion of good practice at this methodological interface, including the concordance of motivations, study design, data, and tools and the validation and standardization of techniques. We then highlight instances of positive feedback between methodological development and knowledge domains and assess the overall cohesion of the sample.

Influence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections

Antibiotic-resistant bacterial infections are a substantial source of morbidity and mortality and have a common reservoir in inpatient settings. Transferring patients between facilities could be a mechanism for the spread of these infections. We wanted to assess whether a network of hospitals, linked by inpatient transfers, contributes to the spread of nosocomial infections and investigate how network structure may be leveraged to design efficient surveillance systems. We construct a network defined by the transfer of Medicare patients across US inpatient facilities using a 100% sample of inpatient discharge claims from 2006-2007. We show the association between network structure and C. difficile incidence, with a 1% increase in a facility's C. difficile incidence being associated with a 0.53% increase in C. difficile incidence of neighboring facilities. Finally, we used network science methods to determine the facilities to monitor to maximize surveillance efficiency. An optimal surveillance strategy for selecting "sensor" hospitals, based on their network position, detects 80% of the C. difficile infections using only 2% of hospitals as sensors. Selecting a small fraction of facilities as "sensors" could be a cost-effective mechanism to monitor emerging nosocomial infections.

The relative importance of large problems far away versus small problems closer to home: insights into limiting the spread of antimicrobial resistance in England

BACKGROUND

To combat the spread of antimicrobial resistance (AMR), hospitals are advised to screen high-risk patients for carriage of antibiotic-resistant bacteria on admission. This often includes patients previously admitted to hospitals with a high AMR prevalence. However, the ability of such a strategy to identify introductions (and hence prevent onward transmission) is unclear, as it depends on AMR prevalence in each hospital, the number of patients moving between hospitals, and the number of hospitals considered 'high risk'.

METHODS

We tracked patient movements using data from the National Health Service of England Hospital Episode Statistics and estimated differences in regional AMR prevalences using, as an exemplar, data collected through the national reference laboratory service of Public Health England on carbapenemase-producing Enterobacteriaceae (CPE) from 2008 to 2014. Combining these datasets, we calculated expected CPE introductions into hospitals from across the hospital network to assess the effectiveness of admission screening based on defining high-prevalence hospitals as high risk.

RESULTS

Based on numbers of exchanged patients, the English hospital network can be divided into 14 referral regions. England saw a sharp increase in numbers of CPE isolates referred to the national reference laboratory over 7 years, from 26 isolates in 2008 to 1649 in 2014. Large regional differences in numbers of confirmed CPE isolates overlapped with regional structuring of patient movements between hospitals. However, despite these large differences in prevalence between regions, we estimated that hospitals received only a small proportion (1.8%) of CPE-colonised patients from hospitals outside their own region, which decreased over time.

CONCLUSIONS

In contrast to the focus on import screening based on assigning a few hospitals as 'high risk', patient transfers between hospitals with small AMR problems in the same region often pose a larger absolute threat than patient transfers from hospitals in other regions with large problems, even if the prevalence in other regions is orders of magnitude higher. Because the difference in numbers of exchanged patients, between and within regions, was mostly larger than the difference in CPE prevalence, it would be more effective for hospitals to focus on their own populations or region to inform control efforts rather than focussing on problems elsewhere.

Receipt of Antibiotics in Hospitalized Patients and Risk for Clostridium difficile Infection in Subsequent Patients Who Occupy the Same Bed

OBJECTIVE

To assess whether receipt of antibiotics by prior hospital bed occupants is associated with increased risk for CDI in subsequent patients who occupy the same bed.

DESIGN, SETTING, AND PARTICIPANTS

This is a retrospective cohort study of adult patients hospitalized in any 1 of 4 facilities between 2010 and 2015. Patients were excluded if they had recent CDI, developed CDI within 48 hours of admission, had inadequate follow-up time, or if their prior bed occupant was in the bed for less than 24 hours.

MAIN OUTCOMES AND MEASURES

The primary exposure was receipt of non-CDI antibiotics by the prior bed occupant and the primary outcome was incident CDI in the subsequent patient to occupy the same bed. Incident CDI was defined as a positive result from a stool polymerase chain reaction for the C difficile toxin B gene followed by treatment for CDI. Demographics, comorbidities, laboratory data, and medication exposures are reported.

RESULTS

Among 100 615 pairs of patients who sequentially occupied a given hospital bed, there were 576 pairs (0.57%) in which subsequent patients developed CDI. Receipt of antibiotics in prior patients was significantly associated with incident CDI in subsequent patients (log-rank P < .01). This relationship remained unchanged after adjusting for factors known to influence risk for CDI including receipt of antibiotics by the subsequent patient (adjusted hazard ratio [aHR], 1.22; 95% CI, 1.02-1.45) and also after excluding 1497 patient pairs among whom the prior patients developed CDI (aHR, 1.20; 95% CI, 1.01-1.43). Aside from antibiotics, no other factors related to the prior bed occupants were associated with increased risk for CDI in subsequent patients.

CONCLUSIONS AND RELEVANCE

Receipt of antibiotics by prior bed occupants was associated with increased risk for CDI in subsequent patients. Antibiotics can directly affect risk for CDI in patients who do not themselves receive antibiotics.

The epidemiology of Clostridium difficile infection in patients with cancer

INTRODUCTION

Clostridium difficile infection (CDI) is a significant cause of healthcare-associated diarrhoea, and the emergence of endemic strains resulting in poorer outcomes is recognised worldwide. Patients with cancer are a specific high-risk group for development of infection. Areas covered: In this review, modifiable and non-modifiable risk factors for CDI in adult patients with haematological malignancy or solid tumours are evaluated. In particular, the contribution of antimicrobial exposure, hospitalisation and gastric acid suppression to risk of CDI are discussed. Recent advances in CDI treatment are outlined, namely faecal microbiota transplantation and fidaxomicin therapy for severe/refractory infection in cancer populations. Outcomes of CDI, including mortality are presented, together with the need for valid severity rating tools customised for cancer populations. Expert commentary: Future areas for research include the prognostic value of C. difficile colonisation in cancer patients and the potential impact of dedicated antimicrobial stewardship programs in reducing the burden of CDI in cancer units.

Asymptomatic Clostridium difficile colonization in two Australian tertiary hospitals, 2012-2014: prospective, repeated cross-sectional study

OBJECTIVES

To investigate the prevalence and risk factors for asymptomatic toxigenic (TCD) and nontoxigenic Clostridium difficile (NTCD) colonization in a broad cross section of the general hospital population over a 3-year period.

METHODS

Patients without diarrhoea admitted to two Australian tertiary hospitals were randomly selected through six repeated cross-sectional surveys conducted between 2012 and 2014. Stool specimens were cultured under anaerobic conditions, and C. difficile isolates were tested for the presence of toxin genes and ribotyped. Patients were then grouped into noncolonized, TCD colonized or NTCD colonized for identifying risk factors using multinomial logistic regression models.

RESULTS

A total of 1380 asymptomatic patients were enrolled; 76 patients (5.5%) were TCD colonized and 28 (2.0%) were NTCD colonized. There was a decreasing annual trend in TCD colonization, and asymptomatic colonization was more prevalent during the summer than winter months. TCD colonization was associated with gastro-oesophageal reflux disease (relative risk ratio (RRR) = 2.20; 95% confidence interval (CI) 1.17-4.14), higher number of admissions in the previous year (RRR = 1.24; 95% CI 1.10-1.39) and antimicrobial exposure during the current admission (RRR = 2.78; 95% CI 1.23-6.28). NTCD colonization was associated with chronic obstructive pulmonary disease (RRR = 3.88; 95% CI 1.66-9.07) and chronic kidney failure (RRR = 5.78; 95% CI 2.29-14.59). Forty-eight different ribotypes were identified, with 014/020 (n = 23), 018 (n = 10) and 056 (n = 6) being the most commonly isolated.

CONCLUSIONS

Risk factors differ between patients with asymptomatic colonization by toxigenic and nontoxigenic strains. Given that morbidity is largely driven by toxigenic strains, this novel finding has important implications for disease control and prevention.

Spread of Carbapenem-Resistant Enterobacteriaceae Among Illinois Healthcare Facilities: The Role of Patient Sharing

BACKGROUND

Carbapenem-resistant Enterobacteriaceae (CRE) spread regionally throughout healthcare facilities through patient transfer and cause difficult-to-treat infections. We developed a state-wide patient-sharing matrix and applied social network analyses to determine whether greater connectedness (centrality) to other healthcare facilities and greater patient sharing with long-term acute care hospitals (LTACHs) predicted higher facility CRE rates.

METHODS

We combined CRE case information from the Illinois extensively drug-resistant organism registry with measures of centrality calculated from a state-wide hospital discharge dataset to predict facility-level CRE rates, adjusting for hospital size and geographic characteristics.

RESULTS

Higher CRE rates were observed among facilities with greater patient sharing, as measured by degree centrality. Each additional hospital connection (unit of degree) conferred a 6% increase in CRE rate in rural facilities (relative risk [RR] = 1.056; 95% confidence interval [CI], 1.030-1.082) and a 3% increase among Chicagoland and non-Chicago urban facilities (RR = 1.027; 95% CI, 1.002-1.052 and RR = 1.025; 95% CI, 1.002-1.048, respectively). Sharing 4 or more patients with LTACHs was associated with higher CRE rates, but this association may have been due to chance (RR = 2.08; 95% CI, .85-5.08; P = .11).

CONCLUSIONS

Hospitals with greater connectedness to other hospitals in a statewide patient-sharing network had higher CRE burden. Centrality had a greater effect on CRE rates in rural counties, which do not have LTACHs. Social network analysis likely identifies hospitals at higher risk of CRE exposure, enabling focused clinical and public health interventions.

Population Dynamics of Patients with Bacterial Resistance in Hospital Environment

During the past decades, the increase of antibiotic resistance has become a major concern worldwide. The researchers found that superbugs with new type of resistance genes (NDM-1) have two aspects of transmission characteristics; the first is that the antibiotic resistance genes can horizontally transfer among bacteria, and the other is that the superbugs can spread between humans through direct contact. Based on these two transmission mechanisms, we study the dynamics of population in hospital environment where superbugs exist. In this paper, we build three mathematic models to illustrate the dynamics of patients with bacterial resistance in hospital environment. The models are analyzed using stability theory of differential equations. Positive equilibrium points of the system are investigated and their stability analysis is carried out. Moreover, the numerical simulation of the proposed model is also performed which supports the theoretical findings.

Integrating Time-Varying and Ecological Exposures into Multivariate Analyses of Hospital-Acquired Infection Risk Factors: A Review and Demonstration

OBJECTIVES Hospital-acquired infections (HAIs) develop rapidly after brief and transient exposures, and ecological exposures are central to their etiology. However, many studies of HAIs risk do not correctly account for the timing of outcomes relative to exposures, and they ignore ecological factors. We aimed to describe statistical practice in the most cited HAI literature as it relates to these issues, and to demonstrate how to implement models that can be used to account for them. METHODS We conducted a literature search to identify 8 frequently cited articles having primary outcomes that were incident HAIs, were based on individual-level data, and used multivariate statistical methods. Next, using an inpatient cohort of incident Clostridium difficile infection (CDI), we compared 3 valid strategies for assessing risk factors for incident infection: a cohort study with time-fixed exposures, a cohort study with time-varying exposures, and a case-control study with time-varying exposures. RESULTS Of the 8 studies identified in the literature scan, 3 did not adjust for time-at-risk, 6 did not assess the timing of exposures in a time-window prior to outcome ascertainment, 6 did not include ecological covariates, and 6 did not account for the clustering of outcomes in time and space. Our 3 modeling strategies yielded similar risk-factor estimates for CDI risk. CONCLUSIONS Several common statistical methods can be used to augment standard regression methods to improve the identification of HAI risk factors. Infect.

Hospital Clostridium difficile Infection Rates and Prediction of Length of Stay in Patients Without C. difficile Infection

BACKGROUND Inpatient length of stay (LOS) has been used as a measure of hospital quality and efficiency. Patients with Clostridium difficile infections (CDI) have longer LOS. OBJECTIVE To describe the relationship between hospital CDI incidence and the LOS of patients without CDI. DESIGN Retrospective cohort analysis. METHODS We predicted average LOS for patients without CDI at both the hospital and patient level using hospital CDI incidence. We also controlled for hospital characteristics (eg, bed size) and patient characteristics (eg, comorbidities, age). SETTING Healthcare Cost and Utilization Project Nationwide Inpatient Sample, 2009-2011. PATIENTS The Nationwide Inpatient Sample includes patients from a 20% sample of all nonfederal US hospitals. RESULTS Inpatient LOS was significantly longer (P<.001) at hospitals with greater CDI incidence at both the hospital and individual level. At a hospital level, a percentage point increase in the CDI incidence rate was associated with more than an additional day's stay (between 1.19 and 1.61 days). At the individual level, controlling for all observable variables, a percentage point increase in the CDI incidence rate at their hospital was also associated with longer LOS (between 0.6 and 1.05 additional days). Hospital CDI incidence had a larger impact on LOS than many other commonly used predictors of LOS. CONCLUSION CDI rates are a predictor of LOS in patients without CDI at an individual and institutional level. CDI rates are easy to measure and report and thus may provide an important marker for hospital efficiency and/or quality.