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To develop a pediatric research agenda focused on pediatric healthcare-associated infections and antimicrobial stewardship topics that will yield the highest impact on child health.
The study included 26 geographically diverse adult and pediatric infectious diseases clinicians with expertise in healthcare-associated infection prevention and/or antimicrobial stewardship (topic identification and ranking of priorities), as well as members of the Division of Healthcare Quality and Promotion at the Centers for Disease Control and Prevention (topic identification).
Using a modified Delphi approach, expert recommendations were generated through an iterative process for identifying pediatric research priorities in healthcare associated infection prevention and antimicrobial stewardship. The multistep, 7-month process included a literature review, interactive teleconferences, web-based surveys, and 2 in-person meetings.
A final list of 12 high-priority research topics were generated in the 2 domains. High-priority healthcare-associated infection topics included judicious testing for Clostridioides difficile infection, chlorhexidine (CHG) bathing, measuring and preventing hospital-onset bloodstream infection rates, surgical site infection prevention, surveillance and prevention of multidrug resistant gram-negative rod infections. Antimicrobial stewardship topics included β-lactam allergy de-labeling, judicious use of perioperative antibiotics, intravenous to oral conversion of antimicrobial therapy, developing a patient-level “harm index” for antibiotic exposure, and benchmarking and or peer comparison of antibiotic use for common inpatient conditions.
We identified 6 healthcare-associated infection topics and 6 antimicrobial stewardship topics as potentially high-impact targets for pediatric research.
Background: Measles is a highly contagious virus that reemerged in 2019 with the highest number of reported cases in the United States since 1992. Beginning in March 2019, The Johns Hopkins Hospital (JHH) responded to an influx of patients with concern for measles as a result of outbreaks in Maryland and the surrounding states. We report the JHH Department of Infection Control and Hospital Epidemiology (HEIC) response to this measles outbreak using a multidisciplinary measles incident command system (ICS). Methods: The JHH HEIC and the Johns Hopkins Office of Emergency Management established the HEIC Clinical Incident Command Center and coordinated a multipronged response to the measles outbreak with partners from occupational health services, microbiology, the adult and pediatric emergency departments, marketing and communication and local and state public health departments. The multidisciplinary structure rapidly developed, approved, and disseminated tools to improve the ability of frontline providers to quickly identify, isolate, and determine testing needs for patients suspected to have measles infection and reduce the risk of secondary transmission. The tools included a triage algorithm, visitor signage, staff and patient vaccination guidance and clinics, and standard operating procedures for measles evaluation and testing. The triage algorithms were developed for phone or in-person and assessed measles exposure history, immune status, and symptoms, and provided guidance regarding isolation and the need for testing. The algorithms were distributed to frontline providers in clinics and emergency rooms across the Johns Hopkins Health System. The incident command team also distributed resources to community providers to reduce patient influx to JHH and staged an outdoor measles evaluation and testing site in the event of a case influx that would exceed emergency department resources. Results: From March 2019 through June 2019, 37 patients presented with symptoms or concern for measles. Using the ICS tools and algorithms, JHH rapidly identified, isolated, and tested 11 patients with high suspicion for measles, 4 of whom were confirmed positive. Of the other 26 patients not tested, none developed measles infection. Exposures were minimized, and there were no secondary measles transmissions among patients. Conclusions: Using the ICS and development of tools and resources to prevent measles transmission, including a patient triage algorithm, the JHH team successfully identified, isolated, and evaluated patients with high suspicion for measles while minimizing exposures and secondary transmission. These strategies may be useful to other institutions and locales in the event of an emerging or reemerging infectious disease outbreak.
Disclosures: Aaron Milstone reports consulting for Becton Dickinson.
Background: Hospital-onset bacteremia and fungemia (HOB) may be a preventable hospital-acquired condition and a potential healthcare quality measure. We developed and evaluated a tool to assess the preventability of HOB and compared it to a more traditional consensus panel approach. Methods: A 10-member healthcare epidemiology expert panel independently rated the preventability of 82 hypothetical HOB case scenarios using a 6-point Likert scale (range, 1= “Definitively or Almost Certainly Preventable” to 6= “Definitely or Almost Certainly Not Preventable”). Ratings on the 6-point scale were collapsed into 3 categories: Preventable (1–2), Uncertain (3–4), or Not preventable (5–6). Consensus was defined as concurrence on the same category among ≥70% expert raters. Cases without consensus were deliberated via teleconference, web-based discussion, and a second round of rating. The proportion meeting consensus, overall and by predefined HOB source attribution, was calculated. A structured HOB preventability rating tool was developed to explicitly account for patient intrinsic and extrinsic healthcare-related risks (Fig. 1). Two additional physician reviewers independently applied this tool to adjudicate the same 82 case scenarios. The tool was iteratively revised based on reviewer feedback followed by repeat independent tool-based adjudication. Interrater reliability was evaluated using the Kappa statistic. Proportion of cases where tool-based preventability category matched expert consensus was calculated. Results: After expert panel round 1, consensus criteria were met for 29 cases (35%), which increased to 52 (63%) after round 2. Expert consensus was achieved more frequently for respiratory or surgical site infections than urinary tract and central-line–associated bloodstream infections (Fig. 2a). Most likely to be rated preventable were vascular catheter infections (64%) and contaminants (100%). For tool-based adjudication, following 2 rounds of rating with interim tool revisions, agreement between the 2 reviewers was 84% for cases overall (κ, 0.76; 95% CI, 0.64–0.88]), and 87% for the 52 cases with expert consensus (κ, 0.79; 95% CI, 0.65–0.94). Among cases with expert consensus, tool-based rating matched expert consensus in 40 of 52 (77%) and 39 of 52 (75%) cases for reviewer 1 and reviewer 2, respectively. The proportion of cases rated “uncertain“ was lower among tool-based adjudicated cases with reviewer agreement (15 of 69) than among cases with expert consensus (23 of 52) (Fig. 2b). Conclusions: Healthcare epidemiology experts hold varying perspectives on HOB preventability. Structured tool-based preventability rating had high interreviewer reliability, matched expert consensus in most cases, and rated fewer cases with uncertain preventability compared to expert consensus. This tool is a step toward standardized assessment of preventability in future HOB evaluations.
Background: In 2018, the Maryland Department of Health, in collaboration with the University of Maryland and Johns Hopkins University, created the Statewide Prevention and Reduction of Clostridioides difficile (SPARC) collaborative to reduce C. difficile as specified in Healthy People 2020. Methods: The SPARC collaborative recruited hospitals contributing most cases to statewide C. difficile standardized infection ratio (SIR), according to data reported to the National Healthcare Safety Network (NHSN). SPARC developed intervention bundles around 4 domains: infection prevention, environmental cleaning, and diagnostic and antimicrobial stewardship. Each facility completed a self-assessment followed by an on-site, day-long, peer-to-peer (P2P) evaluation with 8–12 SPARC subject matter experts (SMEs) representing each domain. The SMEs met with hospital executive leadership and then led 4 domain-based group discussions with relevant hospital team leaders. To identify policy and practice gaps, SMEs visited hospital inpatient units for informal interviews with frontline staff. In a closing session, SPARC SMEs, hospital executives, and team leaders reconvened to discuss preliminary findings. This included review of covert observation data (hand hygiene, personal protective equipment compliance, environmental cleaning) obtained by SPARC team 1–2 weeks prior. Final SPARC P2P written recommendations guided development of customized interventions at each hospital. SPARC provided continuous support (follow up phone calls, educational webinars, technical support, didactic training for antimicrobial stewardship pharmacists) to enhance facility-specific implementation. For every quarter, we categorized C. difficile NHSN data for each Maryland hospital into “SPARC” or “non-SPARC” based on participation status. Using negative binomial mixed models, we analyzed difference-in-difference of pre- and postincidence rate ratios (IRRs) for SPARC and non-SPARC hospitals, which allowed estimation of change attributable to SPARC participation independent of other time-varying factors. Results: Overall, 13 of 48 (27%) hospitals in Maryland participated in the intervention. The baseline SIR for all Maryland hospitals was 0.92, and the post-SPARC SIR was 0.67. The SPARC hospitals had a greater reduction in hospital-onset C. difficile incidence; 8.6 and 4.3 events per 10,000 patient days for baseline and most recent quarter, respectively. For non-SPARC hospitals, these hospital-onset C. difficile incidences were 5.1 preintervention and 4.3 postintervention. We found a statistically significant difference-in-difference between SPARC and non-SPARC hospital C. difficile reduction rates (ratio of IRR, 0.63; 95% CI, 0.44−0.89; P = .01). Conclusions: The Maryland SPARC collaborative, a public health-academic partnership, was associated with a 25% reduction in the Maryland C. difficile SIR. Hospitals participating in SPARC demonstrated significantly reduced C. difficile incidences to match that of high-performing hospitals in Maryland.
Background: Rapidly identifying patients colonized with multidrug-resistant organisms (MDROs) upon ICU admission is critical to control and prevent the spread of these pathogens in healthcare facilities. Electronic health records (EHR) provide a rich source of data to predict the likelihood of MDRO colonization at admission, whereas surveillance methods are resource intensive and results are not immediately available. Our objectives were (1) to predict VRE and CRO colonization at ICU admission and (2) to identify patient subpopulations at higher risk for colonization with these MDROs. Methods: We conducted a retrospective analysis of patients aged ≥16 years admitted to any of 6 medical or surgical intensive care units (ICU) in the Johns Hopkins Hospital from July 1, 2016, through June 30, 2018. Perirectal swabs were collected at ICU unit admission and were tested for VRE and CRO. Patient demographic data, prior hospitalizations, and preadmission clinical data, including prior medication administration, prior diagnoses, and prior procedures, were extracted to develop prediction models. We employed the machine-learning algorithms logistic regression (LR), random forest (RF), and XGBoost (XG). The sum of sensitivity and specificity (ie, Youden’s index) was selected as the performance metric. Results: In total, 5,033 separate ICU visits from 3,385 patients were included, where 555 (11%) and 373 (7%) admissions tested positive for VRE and CRO, respectively. The sensitivity and specificity of our models for VRE were 78% and 80% with LR, 80% and 82% with RF, and 77% and 87% with XG. Predictions for CRO were not as precise, with LR at 73% and 53%, RF at 81% and 48%, and XG at 69% and 61%. The XG algorithm was the best-performing algorithm for both VRE and CRO. Prior VRE colonization, recent (<180 days) long-term care facility stay, and prior hospitalization >60 days were the key predictors for VRE, whereas the primary predictor for CRO colonization was prior carbapenem use. Conclusions: We demonstrated that EHR data can be used to predict >75% of VRE positive cases with a <15% false-positive rate and ~70% of CRO cases with a <40% false-positive rate. Future studies using larger sample sizes may improve the prediction accuracy and inform model generalizability across sites and thus reduce the risk of transmission of MDROs by rapidly identifying MDRO-colonized patients.
Funding: This work was funded by the Centers for Disease Control and Prevention (CDC) Epicenters Program (Grant Number 1U54CK000447) and the CDC MInD-Healthcare Program (Grant Number 1U01CK000536).
Background: In low- and middle-income country (LMIC) healthcare facilities, gaps in infection prevention and control (IPC) practices increase risk of healthcare-associated infections (HAIs) and mortality among hospitalized neonates. Method: In this quasi-experimental study, we implemented the Comprehensive Unit-based Safety Program (CUSP) to improve adherence to evidence-based IPC practices in neonatal intensive care units (NICUs) in 4 tertiary-care facilities in Pune, India. CUSP is a validated strategy to empower staff to improve unit-level patient safety. Baseline safety culture was measured using the Hospital Survey on Patient Safety Culture (HSOPS). Baseline IPC assessments using the Infection Control Assessment Tool (ICAT) were completed to describe existing IPC practices to identify focus areas, the first of which was hand hygiene (HH). Sites received training in CUSP methodology and formed multidisciplinary CUSP teams, which met monthly and were supported by monthly coaching calls. Staff safety assessments (SSAs) guided selection of multimodal interventions. HH compliance was measured by direct observation using trained external observers. The primary outcome was HH compliance, evaluated monthly during the implementation and maintenance phases. Secondary outcomes included CUSP meeting frequency and HH compliance by healthcare worker (HCW) role. Result: In March 2018, 144 HCWs and administrators participated in CUSP training. Site meetings occurred monthly. During the implementation phase (June 2018–January 2019), HH monitoring commenced, sites formed their teams, completed the SSA, and selected interventions to improve HH based on the WHO’s IPC multimodal improvement strategy: (1) system change; (2) training and education; (3) monitoring and feedback; (4) reminders and communication; and (5) a culture of safety (Fig. 1). During the maintenance phase (February–September 2019), HH was monitored monthly and sites adapted interventions as needed. HH compliance improved from 58% to 70% at participant sites from implementation to maintenance phases (Fig. 2), with an odds ratio (OR) of 1.66 (95% CI, 1.50–1.84; P < .001). HH compliance improved across all HCW roles: (1) physician compliance improved from 55% to 67% (OR, 1.69; 95% CI, 1.42–2.01; P < .001); (2) nurse compliance from 61% to 73% (OR, 1.68; 95% CI, 1.46–1.93; P < .001); and (3) other HCW compliance from 52% to 62% (OR, 1.48; 95% CI, 1.10–1.99; P = .010). Conclusion: CUSP was successfully adapted by 4 diverse tertiary-care NICUs in Pune, India, and it resulted in increased HH compliance at all sites. This multimodal strategy is a promising framework for LMIC healthcare facilities to sustainably address IPC gaps and reduce HAI and mortality in neonates.
Background: Blood cultures are essential diagnostic tools used to identify bloodstream infections and to guide antimicrobial therapy. However, collecting cultures without clear indications or that do not inform management can lead to false-positive results and unnecessary use of antibiotics. Blood culture practices vary significantly in critically ill children. Our objective was to create a consensus guideline focusing on when to safely avoid blood cultures in pediatric intensive care unit (PICU) patients. Methods: A panel of multidisciplinary experts, many participating in the Blood Culture Improvement Guidelines and Diagnostic Stewardship for Antibiotic Reduction in Critically Ill Children (Bright STAR) Collaborative, engaged in a 2-part modified Delphi process. Round 1 consisted of a preparatory literature summary and an electronic survey sent to subject matter experts (SMEs). In the survey, SMEs rated a series of recommendations about when to avoid blood cultures on a 5-point Likert scale, 1 being the lowest score and 5 being the highest score. Consensus was achieved for each recommendation if 75% of respondents chose a score of 4 or 5, and these were included in the final guideline. Any recommendations that did not meet these a priori criteria for consensus were set aside for discussion during the in-person expert panel review (round 2). An outside expert in consensus methodology facilitated round 2. After a review of the survey results and comments from round 1 and group discussion, the SMEs voted on these recommendations in real time. Voting was blinded. Participants included Bright STAR site leads, national content experts, and representatives from relevant national societies. Results: We received 29 completed surveys from 34 invited participants for an 85% response rate. Of the 27 round 1 recommendations, 18 met predetermined criteria for consensus. Round 2 included 26 in-person voting participants who (1) discussed and modified the 9 recommendations that had not met round 1 consensus, and (2) modified for clarity or condensed from multiple into single recommendations the 18 recommendations that had met the round 1 consensus. The final document contains 19 recommendations that provide guidance on how to safely improve blood culture use in PICU patients (Table 1). Also, 8 recommendations discussed did not reach consensus for inclusion. Conclusions: Using a modified Delphi process, we created consensus recommendations on when to avoid blood cultures and prevent overuse in critically ill children. These guidelines are a critical step in disseminating diagnostic stewardship and reducing unnecessary testing on a wider scale.
Funding: Agency for Healthcare Research and Quality, R18 HS025642-01, 9/2017 – 9/2020 (Aaron Milstone, PI)
Background:Staphylococcus aureus (S. aureus) is the second most common cause of healthcare-acquired infections in neonates. S. aureus colonization is a known risk factor for invasive disease. Aside from healthcare workers (HCWs), recent data suggest that parents are important reservoirs of S. aureus in the neonatal intensive care unit (NICU). S. aureus typically colonizes the nares, but it can also colonize other anatomic locations such as the throat. Objective: Our objectives were to identify and compare S. aureus colonization among HCWs and parents and to identify and compare different sites of S. aureus colonization. Methods: Between April 2015 and July 2016, we performed 4 point-prevalence surveys and collected nares and throat swabs from HCWs (nurses, respiratory therapists, nurse practitioners, and physicians) at a quaternary-care NICU. During an overlapping period, we screened parents of neonates in the NICU for S. aureus colonization using nares, throat, groin, and perianal cultures as a part of an ongoing randomized control trial. Cultures from both studies were collected using standardized methods. ESwabs were used to collect samples, which were inoculated into broth for enrichment and subsequently cultured onto chromogenic agar to differentiate between MSSA and MRSA. Results: The prevalence of methicillin susceptible S. aureus (MSSA) colonization was 46% (105/226) in HCWs and 28% (239/842) in parents. The prevalence of methicillin resistant S. aureus (MRSA) colonization was 2.2% (5/226) in HCWs and 2.2% (19/842) in parents. Of those who were colonized with S. aureus, 35% (79/226) of HCWs and 46.5% (160/344) of parents had nares and throat colonization while 11.5% (26/226) of HCWs and 12.2% (42/344) of parents had only throat colonization but not nares colonization. Of those who were MRSA colonized, 1.3% (3/226) of HCWs and 1.8% (15/842) of parents had a positive nares and throat culture as compared to 0.9% (2/226) of HCWs and 0.2% (2/842) of parents had only positive throat cultures. Additionally, 68% (175/257) were colonized with S. aureus at any swabbed site including nares, throat, groin, or perinanal areas. However, only 30% (77/257) of parents had only nares colonization as compared to 58.8% (151/257) had throat and nares colonization, 38.1% (98/257) had nares and groin colonization, and 37.4% (96/257) had nares and perianal colonization. Conclusions: HCWs had greater prevalence of S. aureus colonization compared to parents. As expected, the nares was the most common site of MSSA and MRSA, but a large proportion of S. aureus colonized HCWs and parents had only throat colonization. Given the prevalence of S. aureus in non-nares sites of HCWs and parents in the NICU, further studies should examine the role of non-nares carriers in the transmission of S. aureus in this population.
Disclosures: Aaron Milstone reports consultancy with Becton Dickinson.
The ideal sampling method and benefit of qualitative versus quantitative culture for carbapenem-resistant Enterobacteriaceae (CRE) recovery in hospitalized patient rooms and bathrooms is unknown. Although the use of nylon-flocked swabs improved overall gram-negative organism recovery compared with cellulose sponges, they were similar for CRE recovery. Quantitative culture was inferior and unrevealing beyond the qualitative results.
To assess resource allocation and costs associated with US hospitals preparing for the possible spread of the 2014–2015 Ebola virus disease (EVD) epidemic in the United States.
A survey was sent to a stratified national probability sample (n=750) of US general medical/surgical hospitals selected from the American Hospital Association (AHA) list of hospitals. The survey was also sent to all children’s general hospitals listed by the AHA (n=60). The survey assessed EVD preparation supply costs and overtime staff hours. The average national wage was multiplied by labor hours to calculate overtime labor costs. Additional information collected included challenges, benefits, and perceived value of EVD preparedness activities.
The average amount spent by hospitals on combined supply and overtime labor costs was $80,461 (n=133; 95% confidence interval [CI], $56,502–$104,419). Multivariate analysis indicated that small hospitals (mean, $76,167) spent more on staff overtime costs per 100 beds than large hospitals (mean, $15,737; P<.0001). The overall cost for acute-care hospitals in the United States to prepare for possible EVD cases was estimated to be $361,108,968. The leading challenge was difficulty obtaining supplies from vendors due to shortages (83%; 95% CI, 78%–88%) and the greatest benefit was improved knowledge about personal protective equipment (89%; 95% CI, 85%–93%).
The financial impact of EVD preparedness activities was substantial. Overtime cost in smaller hospitals was >3 times that in larger hospitals. Planning for emerging infectious disease identification, triage, and management should be conducted at regional and national levels in the United States to facilitate efficient and appropriate allocation of resources in acute-care facilities.