To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Objective: To characterize hospital-onset COVID-19 cases and to investigate the associations between these rates and population and hospital-level rates including trends in healthcare worker infections (HCW), community cases, and COVID-19 wastewater data. Design: Retrospective cohort study from January 1, 2021, to November 23, 2022. Setting: This study was conducted at a 589-bed urban Midwestern tertiary-care hospital system. Participants and interventions: The infection prevention team reviewed the electronic medical records (EMR) of patients who were admitted for >48 hours and subsequently tested positive for SARS-CoV-2 to determine whether COVID-19 was likely to be hospital-onset illness. Each case was further categorized as definite, probable, or possible based on viral sequencing, caregiver tracing analysis, symptoms, and cycle threshold values. Patients were excluded if there was a known exposure prior to admission. Clinical data including vaccination status were collected from the EMR. HCW case data were collected via our institution’s employee health services. Community cases and wastewater data were collected via the Wisconsin Department of Health Services database. Additionally, we evaluated the timing of changes in infection prevention guidance such as visitor restrictions. Results: In total, 156 patients met criteria for hospital-onset COVID-19. Overall, 6% of cases were categorized as definite, 24% were probable, and 70% were possible hospital-onset illness. Most patients were tested prior to a procedure (31%), for new symptoms (30%), and for discharge planning (30%). Also, 53% were symptomatic and 41% received treatment for their COVID-19. Overall, 38% of patients were immunocompromised and 27% were unvaccinated. Overall, 12% of patients died within 1 month of their positive SARS-CoV-2 test, and 11% required ICU admission during their hospital stay. Hospital-onset COVID-19 increased in fall of 2022. Specifically, October 2022 had 16 cases, whereas fall of 2021 (September–November) only had 3 cases total. Finally, similar peaks were observed in total cases by week between healthcare workers, county cases, and COVID-19 wastewater levels. These peaks correspond with the SARS-CoV-2 delta and omicron variant surges, respectively. Conclusions: Hospital-onset cases followed similar trends as population and hospital-level data throughout the study period. However, hospital-onset rate did not correlate as strongly in the second half of 2022 when cases were disproportionately high. Given that hospital-onset cases can result in significant morbidity, continued enhanced infection prevention efforts and low threshold for testing are warranted in the inpatient environment.
Surgical-site infections (SSIs) can be catastrophic. Bundles of evidence-based practices can reduce SSIs but can be difficult to implement and sustain.
We sought to understand the implementation of SSI prevention bundles in 6 US hospitals.
We conducted in-depth semistructured interviews with personnel involved in bundle implementation and conducted a thematic analysis of the transcripts.
The study was conducted in 6 US hospitals: 2 academic tertiary-care hospitals, 3 academic-affiliated community hospitals, 1 unaffiliated community hospital.
In total, 30 hospital personnel participated. Participants included surgeons, laboratory directors, clinical personnel, and infection preventionists.
Bundle complexity impeded implementation. Other barriers varied across services, even within the same hospital. Multiple strategies were needed, and successful strategies in one service did not always apply in other areas. However, early and sustained interprofessional collaboration facilitated implementation.
The evidence-based SSI bundle is complicated and can be difficult to implement. One implementation process probably will not work for all settings. Multiple strategies were needed to overcome contextual and implementation barriers that varied by setting and implementation climate. Appropriate adaptations for specific settings and populations may improve bundle adoption, fidelity, acceptability, and sustainability.
Despite understanding its impact on organizational effectiveness, practical guidance on how to train translational team (TT) leaders is lacking. Previously, we developed an evolutionary learning model of TT maturation consisting of three goal-directed phases: (1). team assembly (Formation); (2). conducting research (Knowledge Generation); and (3). dissemination and implementation (Translation). At each phase, the team acquires group-level knowledge, skills, and attitudes (KSAs) that enhance its performance. Noting that the majority of team-emergent KSAs are promoted by leadership behaviors, we examine the SciTS literature to identify the relevant behaviors for each phase. We propose that effective team leadership evolves from a hierarchical, transformational model early in team Formation to a shared, functional leadership model during Translation. We synthesized an integrated model of TT leadership, mapping a generic “functional leadership” taxonomy to relevant leadership behaviors linked to TT performance, creating an evidence-informed Leadership and Skills Enhancement for Research (LASER) training program. Empirical studies indicate that leadership behaviors are stable across time; to enhance leadership skills, ongoing reflection, evaluation, and practice are needed. We provide a comprehensive multi-level evaluation framework for tracking the growth of TT leadership skills. This work provides a framework for assessing and training relevant leadership behaviors for high-performance TTs.
This document introduces and explains common implementation concepts and frameworks relevant to healthcare epidemiology and infection prevention and control and can serve as a stand-alone guide or be paired with the “SHEA/IDSA/APIC Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals: 2022 Updates,” which contain technical implementation guidance for specific healthcare-associated infections. This Compendium article focuses on broad behavioral and socio-adaptive concepts and suggests ways that infection prevention and control teams, healthcare epidemiologists, infection preventionists, and specialty groups may utilize them to deliver high-quality care. Implementation concepts, frameworks, and models can help bridge the “knowing-doing” gap, a term used to describe why practices in healthcare may diverge from those recommended according to evidence. It aims to guide the reader to think about implementation and to find resources suited for a specific setting and circumstances by describing strategies for implementation, including determinants and measurement, as well as the conceptual models and frameworks: 4Es, Behavior Change Wheel, CUSP, European and Mixed Methods, Getting to Outcomes, Model for Improvement, RE-AIM, REP, and Theoretical Domains.
The intent of this document is to highlight practical recommendations in a concise format designed to assist acute-care hospitals in implementing and prioritizing their surgical-site infection (SSI) prevention efforts. This document updates the Strategies to Prevent Surgical Site Infections in Acute Care Hospitals published in 2014.1 This expert guidance document is sponsored by the Society for Healthcare Epidemiology of America (SHEA). It is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America (IDSA), the Association for Professionals in Infection Control and Epidemiology (APIC), the American Hospital Association (AHA), and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise.
In total, 50 healthcare facilities completed a survey in 2021 to characterize changes in infection prevention and control and antibiotic stewardship practices. Notable findings include sustained surveillance for multidrug-resistant organisms but decreased use of human resource-intensive interventions compared to previous surveys in 2013 and 2018 conducted prior to the COVID-19 pandemic.
We evaluated povidone-iodine (PVI) decolonization among 51 fracture-fixation surgery patients. PVI was applied twice on the day of surgery. Patients were tested for S. aureus nasal colonization and surveyed. Mean S. aureus concentrations decreased from 3.13 to 1.15 CFU/mL (P = .03). Also, 86% of patients stated that they felt neutral or positive about their PVI experience.
Background: Nasal decolonization significantly decreases the incidence of Staphylococcus aureus surgical-site infections (SSIs). Patient adherence with self-administration of a decolonization ointment (ie, mupirocin) is low, especially among patients having urgent surgery. Povidone-iodine decolonization may overcome patient adherence challenges because povidone-iodine needs to be applied only on the day of surgery. We assessed the effectiveness and acceptability of povidone-iodine decolonization given on the day of surgery among patients having orthopedic trauma surgery. Methods: Adult patients who underwent operative fixation of traumatic lower extremity fractures were consented to receive 10% intranasal povidone-iodine solution. Povidone-iodine was applied ~1 hour before surgical incision and was reapplied the evening after surgery. Patients were tested for S. aureus nasal colonization before surgery, the evening after surgery (before povidone-iodine reapplication), and the day after surgery. Swabs were inoculated into Dey-Engley neutralizer and processed in a vortexer. A series of dilutions were performed and plated on mannitol salt agar plates. S. aureus cultures were quantitatively assessed to determine the reduction in S. aureus after povidone-iodine use. Reductions in S. aureus nasal growth were evaluated using the Skillings-Mack test. SSIs manifesting within 30 and 90 days of surgery were identified using NHSN definitions. A survey was administered the morning after surgery to determine the acceptability of intranasal povidone-iodine. Results: In total, 51 patients participated in this pilot study between February 2020 and June 2021. Nasal samples from 12 participants (23.5%) grew S. aureus. The S. aureus concentration decreased significantly across the time points (P = .03) (Fig. 1). No SSIs were identified within 30 days of surgery. One SSI occurred within 90 days of surgery; this patient did not carry S. aureus, and cultures from the infected site were negative. Also, 31% of patients reported at least 1 mild side effect while using povidone-iodine: dripping (n = 7), itching (n = 6), dryness (n = 4), stinging (n = 4), staining (n = 3), unpleasant taste (n = 3), runny nose (n = 2), burning (n = 1), sneezing (n = 1), sore throat (n = 1), tickling (n = 1), and/or cough (n = 1). Also, 86% of patients stated that povidone-iodine felt neutral, pleasant, or very pleasant, and only 14% stated that it felt unpleasant or very unpleasant. Discussion: In this pilot study, 2 applications of nasal povidone-iodine on the day of surgery were acceptable for patients, and this protocol significantly reduced S. aureus concentration in nares of patients. Future large clinical trials should evaluate whether this 2-application regimen of povidone-iodine significantly decreases rates of SSI among orthopedic trauma surgery patients.
Although multiple studies revealed high vaccine effectiveness of coronavirus disease 2019 (COVID-19) vaccines within 3 months after the completion of vaccines, long-term vaccine effectiveness has not been well established, especially after the δ (delta) variant became prominent. We performed a systematic literature review and meta-analysis of long-term vaccine effectiveness.
We searched PubMed, CINAHL, EMBASE, Cochrane Central Register of Controlled Trials, Scopus, and Web of Science from December 2019 to November 15, 2021, for studies evaluating the long-term vaccine effectiveness against laboratory-confirmed COVID-19 or COVID-19 hospitalization among individuals who received 2 doses of Pfizer/BioNTech, Moderna, or AstraZeneca vaccines, or 1 dose of the Janssen vaccine. Long-term was defined as >5 months after the last dose. We calculated the pooled diagnostic odds ratio (DOR) with 95% confidence interval for COVID-19 between vaccinated and unvaccinated individuals. Vaccine effectiveness was estimated as 100% × (1 − DOR).
In total, 16 studies including 17,939,172 individuals evaluated long-term vaccine effectiveness and were included in the meta-analysis. The pooled DOR for COVID-19 was 0.158 (95% CI: 0.157-0.160) with an estimated vaccine effectiveness of 84.2% (95% CI, 84.0- 84.3%). Estimated vaccine effectiveness against COVID-19 hospitalization was 88.7% (95% CI, 55.8%–97.1%). Vaccine effectiveness against COVID-19 during the δ variant period was 61.2% (95% CI, 59.0%–63.3%).
COVID-19 vaccines are effective in preventing COVID-19 and COVID-19 hospitalization across a long-term period for the circulating variants during the study period. More observational studies are needed to evaluate the vaccine effectiveness of third dose of a COVID-19 vaccine, the vaccine effectiveness of mixing COVID-19 vaccines, COVID-19 breakthrough infection, and vaccine effectiveness against newly emerging variants.
We evaluated barriers and facilitators to patient adherence with a bundled intervention including chlorhexidine gluconate (CHG) bathing and decolonizing Staphylococcus aureus nasal carriers in a real-world setting. Survey data identified 85.5% adherence with home use of CHG as directed and 52.9% adherence with home use of mupirocin as directed.
Ceftazidime/avibactam (C/A), ceftolozane/tazobactam (C/T), imipenem/relebactam (I/R), and meropenem/vaborbactam (M/V) combine either a cephalosporin (C/T and C/A) or a carbapenem antibiotic (M/V and I/R) with a β-lactamase inhibitor. They are used to treat carbapenem-resistant Enterobacterales (CRE) and/or multidrug-resistant Pseudomonas aeruginosa (MDRPA).
We compared the pooled clinical success of these medications to older therapies.
PubMed and EMBASE were searched from January 1, 2012, through September 2, 2020, for C/A, C/T, I/R, and M/V studies. The main outcome was clinical success, which was assessed using random-effects models. Stratified analyses were conducted for study drug, sample size, quality, infection source, study design, and multidrug-resistant gram-negative organism (MDRGNO) population. Microbiological success and 28- and 30-day mortality were assessed as secondary outcomes. Heterogeneity was determined using I2 values.
Overall, 25 articles met the inclusion criteria; 8 observational studies and 17 randomized control trials. We detected no difference in clinical success comparing new combination antibiotics with standard therapies for all included organisms (pooled OR, 1.21; 95% CI, 0.96–1.51). We detected a moderate level of heterogeneity among the included studies I2 = 56%. Studies that focused on patients with CRE or MDRPA infections demonstrated a strong association between treatment with new combination antibiotics and clinical success (pooled OR, 2.20; 95% CI, 1.60–3.57).
C/T, C/A, I/R, and M/V are not inferior to standard therapies for treating various complicated infections, but they may have greater clinical success for treating MDRPA and CRE infections. More studies that evaluate the use of these antibiotics for drug-resistant infections are needed to determine their effectiveness.
Healthcare workers (HCWs) are at risk of COVID-19 due to high levels of SARS-CoV-2 exposure. Thus, effective vaccines are needed. We performed a systematic literature review and meta-analysis on COVID-19 short-term vaccine effectiveness among HCWs.
We searched PubMed, CINAHL, EMBASE, Cochrane Central Register of Controlled Trials, Scopus, and Web of Science from December 2019 to June 11, 2021, for studies evaluating vaccine effectiveness against symptomatic COVID-19 among HCWs. To meta-analyze the extracted data, we calculated the pooled diagnostic odds ratio (DOR) for COVID-19 between vaccinated and unvaccinated HCWs. Vaccine effectiveness was estimated as 100% × (1 − DOR). We also performed a stratified analysis for vaccine effectiveness by vaccination status: 1 dose and 2 doses of the vaccine.
We included 13 studies, including 173,742 HCWs evaluated for vaccine effectiveness in the meta-analysis. The vast majority (99.9%) of HCWs were vaccinated with the Pfizer/BioNTech COVID-19 mRNA vaccine. The pooled DOR for symptomatic COVID-19 among vaccinated HCWs was 0.072 (95% confidence interval [CI], 0.028–0.184) with an estimated vaccine effectiveness of 92.8% (95% CI, 81.6%–97.2%). In stratified analyses, the estimated vaccine effectiveness against symptomatic COVID-19 among HCWs who had received 1 dose of vaccine was 82.1% (95% CI, 46.1%–94.1%) and the vaccine effectiveness among HCWs who had received 2 doses was 93.5% (95% CI, 82.5%–97.6%).
The COVID-19 mRNA vaccines are highly effective against symptomatic COVID-19, even with 1 dose. More observational studies are needed to evaluate the vaccine effectiveness of other COVID-19 vaccines, COVID-19 breakthrough after vaccination, and vaccine efficacy against new variants.
To evaluate the frequency of antibiotic prescribing for common infections via telemedicine compared to face-to-face visits.
Systematic literature review and meta-analysis.
We searched PubMed, CINAHL, Embase (Elsevier platform) and Cochrane CENTRAL to identify studies comparing frequency of antibiotic prescribing via telemedicine and face-to-face visits without restrictions by publish dates or language used. We conducted meta-analyses of 5 infections: sinusitis, pharyngitis, otitis media, upper respiratory infection (URI) and urinary tract infection (UTI). Random-effect models were used to obtain pooled odds ratios (ORs). Heterogeneity was evaluated with I2 estimation and the Cochran Q statistic test.
Among 3,106 studies screened, 23 studies (1 randomized control study, 22 observational studies) were included in the systematic literature review. Most of the studies (21 of 23) were conducted in the United States. Studies were substantially heterogenous, but stratified analyses revealed that providers prescribed antibiotics more frequently via telemedicine for otitis media (pooled odds ratio [OR], 1.26; 95% confidence interval [CI], 1.04–1.52; I2 = 31%) and pharyngitis (pooled OR, 1.16; 95% CI, 1.01–1.33; I2 = 0%). We detected no significant difference in the frequencies of antibiotic prescribing for sinusitis (pooled OR, 0.86; 95% CI, 0.70–1.06; I2 = 91%), URI (pooled OR, 1.18; 95% CI, 0.59–2.39; I2 = 100%), or UTI (pooled OR, 2.57; 95% CI, 0.88–7.46; I2 = 91%).
Telemedicine visits for otitis media and pharyngitis were associated with higher rates of antibiotic prescribing. The interpretation of these findings requires caution due to substantial heterogeneity among available studies. Large-scale, well-designed studies with comprehensive assessment of antibiotic prescribing for common outpatient infections comparing telemedicine and face-to-face visits are needed to validate our findings.
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Background: Early postoperative and acute prosthetic joint infection (PJI) may be managed with debridement, antibiotics, and implant retention (DAIR). Among patients with nonstaphylococcal PJI, an initial 4–6-week course of intravenous or highly bioavailable oral antibiotics is recommended in the Infectious Diseases Society of America (IDSA) guidelines, with disagreement among committee members on the need for subsequent chronic oral antimicrobial suppression (CAS). We aimed to characterize patients with nonstaphylococcal PJI who received CAS and to compare them to those who did not receive CAS. Methods: This retrospective cohort study included patients admitted to Veterans’ Affairs (VA) hospitals from 2003 to 2017 who had a PJI caused by nonstaphylococcal bacteria, underwent DAIR, and received 4–6 weeks of antimicrobial treatment. PJI was defined by Musculoskeletal Infection Society (MSIS) 2011 criteria. CAS was defined as at least 6 months of oral antibiotics following initial treatment of the PJI. Patients were followed for 5 years after debridement. We used χ2 tests and t tests were used to compare patients who received CAS with those who did not receive CAS. Results: Overall, 561 patients had a nonstaphylococcal PJI treated with DAIR, and 80.6% of patients received CAS. The most common organisms causing PJI were streptococci. We detected no significant differences between patients who received CAS and those who did not receive CAS, except that modified Acute Physiology and Chronic Health Evaluation (mAPACHE) scores were higher among patients who did not receive CAS (Table 1). Conclusion: Patients not on CAS were more severely ill (by mAPACHE) than those on CAS. Otherwise, the 2 groups were not different. This finding was contrary to our hypothesis that patients with multiple comorbidities or higher mAPACHE scores would be more likely to get CAS. A future analysis will be conducted to assess treatment failure in both groups. We hope to find a specific cohort who may benefit from CAS and hope to deimplement CAS in others who may not benefit from it.
Hand hygiene compliance decreased significantly when opportunities exceeded 30 per hour. At higher workloads, the number of healthcare worker types involved and the proportion of hand hygiene opportunities for which physicians and other healthcare workers were responsible increased. Thus, care complexity and risk to patients may both increase with workload.
To determine whether the order in which healthcare workers perform patient care tasks affects hand hygiene compliance.
For this retrospective analysis of data collected during the Strategies to Reduce Transmission of Antimicrobial Resistant Bacteria in Intensive Care Units (STAR*ICU) study, we linked consecutive tasks healthcare workers performed into care sequences and identified task transitions: 2 consecutive task sequences and the intervening hand hygiene opportunity. We compared hand hygiene compliance rates and used multiple logistic regression to determine the adjusted odds for healthcare workers (HCWs) transitioning in a direction that increased or decreased the risk to patients if healthcare workers did not perform hand hygiene before the task and for HCWs contaminating their hands.
The study was conducted in 17 adult surgical, medical, and medical-surgical intensive care units.
HCWs in the STAR*ICU study units.
HCWs moved from cleaner to dirtier tasks during 5,303 transitions (34.7%) and from dirtier to cleaner tasks during 10,000 transitions (65.4%). Physicians (odds ratio [OR]: 1.50; P < .0001) and other HCWs (OR, 2.15; P < .0001) were more likely than nurses to move from dirtier to cleaner tasks. Glove use was associated with moving from dirtier to cleaner tasks (OR, 1.22; P < .0001). Hand hygiene compliance was lower when HCWs transitioned from dirtier to cleaner tasks than when they transitioned in the opposite direction (adjusted OR, 0.93; P < .0001).
HCWs did not organize patient care tasks in a manner that decreased risk to patients, and they were less likely to perform hand hygiene when transitioning from dirtier to cleaner tasks than the reverse. These practices could increase the risk of transmission or infection.
To develop a fully automated algorithm using data from the Veterans’ Affairs (VA) electrical medical record (EMR) to identify deep-incisional surgical site infections (SSIs) after cardiac surgeries and total joint arthroplasties (TJAs) to be used for research studies.
Retrospective cohort study.
This study was conducted in 11 VA hospitals.
Patients who underwent coronary artery bypass grafting or valve replacement between January 1, 2010, and March 31, 2018 (cardiac cohort) and patients who underwent total hip arthroplasty or total knee arthroplasty between January 1, 2007, and March 31, 2018 (TJA cohort).
Relevant clinical information and administrative code data were extracted from the EMR. The outcomes of interest were mediastinitis, endocarditis, or deep-incisional or organ-space SSI within 30 days after surgery. Multiple logistic regression analysis with a repeated regular bootstrap procedure was used to select variables and to assign points in the models. Sensitivities, specificities, positive predictive values (PPVs) and negative predictive values were calculated with comparison to outcomes collected by the Veterans’ Affairs Surgical Quality Improvement Program (VASQIP).
Overall, 49 (0.5%) of the 13,341 cardiac surgeries were classified as mediastinitis or endocarditis, and 83 (0.6%) of the 12,992 TJAs were classified as deep-incisional or organ-space SSIs. With at least 60% sensitivity, the PPVs of the SSI detection algorithms after cardiac surgeries and TJAs were 52.5% and 62.0%, respectively.
Considering the low prevalence rate of SSIs, our algorithms were successful in identifying a majority of patients with a true SSI while simultaneously reducing false-positive cases. As a next step, validation of these algorithms in different hospital systems with EMR will be needed.
Healthcare-associated infections (HAIs) remain a major challenge. Various strategies have been tried to prevent or control HAIs. Positive deviance, a strategy that has been used in the last decade, is based on the observation that a few at-risk individuals follow uncommon, useful practices and that, consequently, they experience better outcomes than their peers who share similar risks. We performed a systematic literature review to measure the impact of positive deviance in controlling HAIs.
A systematic search strategy was used to search PubMed, CINAHL, Scopus, and Embase through May 2020 for studies evaluating positive deviance as a single intervention or as part of an initiative to prevent or control healthcare-associated infections. The risk of bias was evaluated using the Downs and Black score.
Of 542 articles potentially eligible for review, 14 articles were included for further analysis. All studies were observational, quasi-experimental (before-and-after intervention) studies. Hand hygiene was the outcome in 8 studies (57%), and an improvement was observed in association with implementation of positive deviance as a single intervention in all of them. Overall HAI rates were measured in 5 studies (36%), and positive deviance was associated with an observed reduction in 4 (80%) of them. Methicillin-resistant Staphylococcus aureus infections were evaluated in 5 studies (36%), and positive deviance containing bundles were successful in all of them.
Positive deviance may be an effective strategy to improve hand hygiene and control HAIs. Further studies are needed to confirm this effect.
Background: Cardiovascular implantable electronic device (CIED) infections are highly morbid, yet infection control resources dedicated to preventing them are limited. Infection surveillance in outpatient care is also challenging because there are no infection reporting mandates, and monitoring patients after discharge is difficult. Objective: Thus, we sought to develop a replicable electronic infection detection methodology that integrates text mining with structured data to expand surveillance to outpatient settings. Methods: Our methodology was developed to detect 90-day CIED infections. We tested an algorithm to accurately flag only cases with a true CIED-related infection using diagnostic and therapeutic data derived from the Veterans Affairs (VA) electronic medical record (EMR), including administrative data fields (visit and hospital stay dates, diagnoses, procedure codes), structured data fields (laboratory microbiology orders and results, pharmacy orders and dispensed name, quantity and fill dates, vital signs), and text files (clinical notes organized by date and type containing unstructured text). We evenly divided a national dataset of CIED procedures from 2016–2017 to create development and validation samples. We iteratively tested various infection flag types to estimate a model predicting a high likelihood of a true infection, defined using chart review, to test criterion validity. We then applied the model to the validation data and reviewed cases with high and low likelihood of infection to assess performance. Results: The algorithm development sample included 9,606 CIED procedures in 67 VA hospitals. Iterative testing over 381 chart reviewed cases with 47 infections produced a final model with a C-statistic of 0.95 (Table 1). We applied the model to the 9,606 CIED procedures in our validation sample and found 100 infections of the 245 cases identified by the model to have a high likelihood of infection We identified no infections among cases the model as having low likelihood. The final model included congestive heart failure and coagulopathy as comorbidities, surgical site infection diagnosis, a blood or cardiac microbiology order, and keyword hits for infection diagnosis and history of infection from clinical notes. Conclusions: Evolution of infection prevention programs to include ambulatory and procedural areas is crucial as healthcare delivery is increasingly provided outside traditional settings. Our method of algorithm development and validation for outpatient healthcare-associated infections using EMR-derived data, including text-note searching, has broad application beyond CIED infections. Furthermore, as integrated healthcare systems employ EMRs in more outpatient settings, this approach to infection surveillance could be replicated in non-VA care.