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Increasing resources are devoted to osteoarthritis surgical care in Australia annually, with significant expenditure attributed to hip and knee arthroplasties. Safe, efficient, and sustainable models of care are required. This study aimed to determine the impact on healthcare costs of implementing an enhanced short-stay model of care (ESS-MOC) for arthroplasty at a national level.
Methods
Budget impact analysis was conducted for hospitals providing arthroplasty surgery over the years 2023 to 2030. Population-based sample projections obtained from clinical registry and administrative datasets of individuals receiving hip or knee arthroplasty for osteoarthritis were applied. The ESS-MOC assigned 30 percent of eligible patients to a shortened acute-ward-stay pathway and outpatient rehabilitation. The remaining 70 percent received a current practice pathway. The primary outcome was total healthcare cost savings post-implementation of the ESS-MOC, with return on investment (ROI) ratio and hospital bed-days utilized also estimated. Costs are presented in Australian dollars (AUD) and United States dollars (USD), at 2023 prices.
Results
Estimated hospital cost savings for the years 2023 to 2030 from implementing the ESS-MOC were AUD641 million (USD427 million) (95% CI: AUD99 million [USD66 million] to AUD1,250 million) [USD834 million]). This corresponds to a ROI ratio of 8.88 (1.3 to 17.9) dollars returned for each dollar invested in implementing the care model. For the period 2023 to 2030, an estimated 337,000 (261,000 to 412,000) acute surgical ward bed-days, and 721,000 (471,000 to 1,028,000) rehabilitation bed-days could be saved. Total implementation costs for the ESS-MOC were estimated at AUD72 million (USD46 million) over eight years.
Conclusions
Implementation of an ESS-MOC for eligible arthroplasty patients in Australia would generate significant cost and healthcare resource savings. This budget impact analysis demonstrates a best practice approach to comprehensively assessing value, at a national level, of implementing sustainable models of care in high-burden healthcare contexts. Findings are relevant to other settings where hospital stay following joint arthroplasty remains excessively long.
Assess healthcare workers’ (HCW) attitudes toward universal masking, and gowns and gloves used as part of transmission-based precautions.
Design:
Cross-sectional survey.
Setting:
Academic, tertiary care medical center in Baltimore, Maryland.
Participants:
HCW who work in patient care areas and have contact with patients.
Methods:
In May 2023, a 15-question web-based survey was distributed by the hospital’s communications team via email. The survey contained questions to assess HCW perceptions of universal masking policies prior to the availability of COVID-19 vaccines and at the time of the survey, and the use of gowns and gloves for transmission-based precautions. Descriptive statistics were used to summarize data. Differences in agreement with universal masking over time, level of agreement with gown and glove policies, and with all PPE types across respondent characteristics were assessed.
Results:
257 eligible respondents completed the survey. Nurses and patient care technicians (43%) and providers (17%) were the most commonly reported roles. Agreement with universal mask use decreased from 84% early in the pandemic to 55% at the time of the survey. 70% and 72% of HCW agreed masks protect themselves and others, respectively. 63% expressed any level of annoyance with mask wearing, the most often due to communication challenges or physical discomfort. 75% agreed with gown use for antibiotic-resistant bacteria compared with 90% for glove use.
Conclusions:
The majority of HCW agree with the use of PPE to prevent pathogen transmission in the healthcare setting. Agreement with universal mask use for patient care shifted during the COVID-19 pandemic.
COVID-19 changed the epidemiology of community-acquired respiratory viruses. We explored patterns of respiratory viral testing to understand which tests are most clinically useful in the postpandemic era.
Methods:
We conducted a retrospective observational study of discharge data from PINC-AI (formerly Premier), a large administrative database. Use of multiplex nucleic acid amplification respiratory panels in acute care, including small (2–5 targets), medium (6–11), and large panels (>11), were compared between the early pandemic (03/2020–10/2020), late pandemic (11/2020–4/2021), and prepandemic respiratory season (11/2019 - 02/2020) using ANOVA.
Results:
A median of 160.5 facilities contributed testing data per quarter (IQR 155.5–169.5). Prepandemic, facilities averaged 103 respiratory panels monthly (sd 138), including 79 large (sd 126), 7 medium (sd 31), and 16 small panels (sd 73). Relative to prepandemic, utilization decreased during the early pandemic (62 panels monthly/facility; sd 112) but returned to the prepandemic baseline by the late pandemic (107 panels monthly/facility; sd 211). Relative to prepandemic, late pandemic testing involved more small panel use (58 monthly/facility, sd 156) and less large panel use (47 monthly/facility, sd 116). Comparisons among periods demonstrated significant differences in overall testing (P < 0.0001), large panel use (P < 0.0001), and small panel use (P < 0.0001).
Conclusions:
Postpandemic, clinical use of respiratory panel testing shifted from predominantly large panels to predominantly small panels. Factors driving this change may include resource availability, costs, and the clinical utility of targeting important pathogenic viruses instead of testing “for everything.”
Background: Residence or recent stay in a long-term care facility (LTCF) is one of the most important risk factors for multidrug-resistant organism (MDRO) carriage and infection, making reliable identification of LTCF-exposed inpatients a critical priority for infection control day-to-day practice and research. However, because most hospital electronic health records (EHRs) do not include a dedicated field for documenting LTCF exposure, absent manual review of patient charts, identifying LTCF-exposed inpatients is challenging. We aimed to develop an automated, natural language processing (NLP)-based classifier for identifying LTCF exposure from clinical notes. Methods: We randomly sampled 1020 adult admissions from 2016-2021 across the 12-hospital University of Maryland Medical System and manually reviewed each admission’s history & physical (H&P) note for mention of LTCF exposure (Figure 1). After H&P pre-processing, we calculated feature representations for documents based on term frequencies and visually explored between-group (LTCF-exposed vs. LTCF-unexposed) feature differences. To predict LTCF status from the H&P notes, we trained and tuned a LASSO regression-based classifier on 70% of the data with 3-fold cross-validation and 1:1 up-sampling to address class imbalance. The final classifier was evaluated on the 30% held-out sample (not up-sampled), with calculation of the C-statistic (area-under-the-curve, AUC) with bootstrapped 95% confidence intervals, and construction of receiver-operating-characteristic and variable importance plots (R Version 4.3.2). Results: 7% (n=76 cases) of H&P notes documented LTCF exposure. In our visual analysis, the H&P words and phrases that were over-represented among LTCF patients had high face validity (Figure 2). The final LASSO-regression-based classifier achieved a C-statistic of 0.89 (95% CI: 0.80–0.98) on the held-out data for identifying LTCF exposure from the H&P notes (Figure 3). The most important model predictors (i.e., words) for distinguishing LTCF-exposed from LTCF-unexposed patients are reflected in Figure 4. The most important predictor-words of LTCF-exposure were “rehab,” “place,” “status,” “egd,” and “dementia.” Conclusion: In this multi-center study, even a simple NLP classifier demonstrated very strong discrimination for identifying LTCF exposure status from H&P notes, which could substantially reduce the manual review time required to identify LTCF-exposed inpatients. If automated in the electronic health record, it could also inform real-time MDRO screening decisions. Future research is planned to build more sophisticated classifiers using machine learning best practices, to build classifiers for additional MDRO risk factors, and to externally validate NLP classifiers on notes from an external healthcare system.
“All or none” approaches to the use of contact precautions for methicillin-resistant Staphylococcus aureus (MRSA) both fail to recognize that transmission risk varies. This qualitative study assessed healthcare personnel perspectives regarding the feasibility of a risk-tailored approach to use contact precautions for MRSA more strategically in the acute care setting.
Identifying long-term care facility (LTCF)-exposed inpatients is important for infection control research and practice, but ascertaining LTCF exposure is challenging. Across a large validation study, electronic health record data fields identified 76% of LTCF-exposed patients compared to manual chart review.
Transient acquisition of methicillin-resistant Staphylococcus aureus (MRSA) on healthcare personnel (HCP) gloves and gowns following patient care has been examined. However, the potential for transmission to the subsequent patient has not been studied. We explored the frequency of MRSA transmission from patient to HCP, and then in separate encounters from contaminated HCP gloves and gowns to a subsequent simulated patient as well as the factors associated with these 2 transmission pathways.
Methods:
We conducted a prospective cohort study with 2 parts. In objective 1, we studied MRSA transmission from random MRSA-positive patients to HCP gloves and gowns after specific routine patient care activities. In objective 2, we simulated subsequent transmission from random HCP gloves and gowns without hand hygiene to the next patient using a manikin proxy.
Results:
For the first objective, among 98 MRSA-positive patients with 333 randomly selected individual patient–HCP interactions, HCP gloves or gowns were contaminated in 54 interactions (16.2%). In a multivariable analysis, performing endotracheal tube care had the greatest odds of glove or gown contamination (OR, 4.06; 95% CI, 1.3–12.6 relative to physical examination). For the second objective, after 147 simulated HCP–patient interactions, the subsequent transmission of MRSA to the manikin proxy occurred 15 times (10.2%).
Conclusion:
After caring for a patient with MRSA, contamination of HCP gloves and gown and transmission to subsequent patients following HCP-patient interactions occurs frequently if contact precautions are not used. Proper infection control practices, including the use of gloves and gown, can prevent this potential subsequent transmission.
The gold standard for hand hygiene (HH) while wearing gloves requires removing gloves, performing HH, and donning new gloves between WHO moments. The novel strategy of applying alcohol-based hand rub (ABHR) directly to gloved hands might be effective and efficient.
Design:
A mixed-method, multicenter, 3-arm, randomized trial.
Setting:
Adult and pediatric medical-surgical, intermediate, and intensive care units at 4 hospitals.
Participants:
Healthcare personnel (HCP).
Interventions:
HCP were randomized to 3 groups: ABHR applied directly to gloved hands, the current standard, or usual care.
Methods:
Gloved hands were sampled via direct imprint. Gold-standard and usual-care arms were compared with the ABHR intervention.
Results:
Bacteria were identified on gloved hands after 432 (67.4%) of 641 observations in the gold-standard arm versus 548 (82.8%) of 662 observations in the intervention arm (P < .01). HH required a mean of 14 seconds in the intervention and a mean of 28.7 seconds in the gold-standard arm (P < .01). Bacteria were identified on gloved hands after 133 (98.5%) of 135 observations in the usual-care arm versus 173 (76.6%) of 226 observations in the intervention arm (P < .01). Of 331 gloves tested 6 (1.8%) were found to have microperforations; all were identified in the intervention arm [6 (2.9%) of 205].
Conclusions:
Compared with usual care, contamination of gloved hands was significantly reduced by applying ABHR directly to gloved hands but statistically higher than the gold standard. Given time savings and microbiological benefit over usual care and lack of feasibility of adhering to the gold standard, the Centers for Disease Control and Prevention and the World Health Organization should consider advising HCP to decontaminate gloved hands with ABHR when HH moments arise during single-patient encounters.
Background: Statistically significant decreases in methicillin-resistant Staphylococcus aureus (MRSA) healthcare-associated infections (HAIs) occurred in Veterans Health Administration (VA) facilities from 2007 to 2019 using active surveillance for facility admissions and contact precautions for patients colonized (CPC) or infected (CPI) with MRSA, but the value of these interventions is controversial. Objective: To determine the impact of active surveillance, CPC, and CPI on prevention MRSA HAIs, we conducted a prospective cohort study between July 2020 and June 2022 in all 123 acute-care VA medical facilities. In April 2020, all facilities were given the option to suspend any combination of active surveillance, CPC, or CPI to free up laboratory resources for COVID-19 testing and conserve personal protective equipment. We measured MRSA HAIs (cases per 1,000 patient days) in intensive care units (ICUs) and non-ICUs by the infection control policy. Results: During the analysis period, there were 917,591 admissions, 5,225,174 patient days, and 568 MRSA HAIs. Only 20% of facilities continued all 3 MRSA infection control measures in July 2020, but this rate increased to 57% by June 2022. The MRSA HAI rate for all infection sites in non-ICUs was 0.07 (95% CI, 0.05–0.08) for facilities practicing active surveillance plus CPC plus CPI compared to 0.12 (95% CI, 0.08–0.19; P = .01) for those not practicing any of these strategies, and in ICUs the MRSA HAI rates were 0.20 (95% CI, 0.15–0.26) and 0.65 (95% CI, 0.41–0.98; P < .001) for the respective policies. Similar differences were seen when the analyses were restricted to MRSA bloodstream HAIs. Accounting for monthly COVID-19 admissions to facilities over the analysis period using a negative binomial regression model did not change the relationships between facility policy and MRSA HAI rates in the ICUs or non-ICUs. There was no statistically significant difference in monthly facility urinary catheter-associated infection rates, a nonequivalent dependent variable, in the categories during the analysis period in either ICUs or non-ICUs. Conclusions: In Veterans Affairs medical centers, there were fewer MRSA HAIs when facilities practiced active surveillance and contact precautions for colonized or infected patients during the COVID-19 pandemic. The effect was greater in ICUs than non-ICUs.
Housing instability is a social determinant of health associated with multiple negative health outcomes including substance use disorders (SUDs). Real-world evidence of housing instability is needed to improve translational research on populations with SUDs.
Methods:
We identified evidence of housing instability by leveraging structured diagnosis codes and unstructured clinical data from electronic health records of 20,556 patients from 2017 to 2021. We applied natural language processing with named-entity recognition and pattern matching to unstructured clinical notes with free-text documentation. Additionally, we analyzed semi-structured addresses containing explicit or implicit housing-related labels. We assessed agreement on identification methods by having three experts review of 300 records.
Results:
Diagnostic codes only identified 58.5% of the population identifiable as having housing instability, whereas 41.5% are identifiable from addresses only (7.1%), clinical notes only (30.4%), or both (4.0%). Reviewers unanimously agreed on 79.7% of cases reviewed; a Fleiss’ Kappa score of 0.35 suggested fair agreement yet emphasized the difficulty of analyzing patients having ambiguous housing situations. Among those with poisoning episodes related to stimulants or opioids, diagnosis codes were only able to identify 63.9% of those with housing instability.
Conclusions:
All three data sources yield valid evidence of housing instability; each has their own inherent practical use and limitations. Translational researchers requiring comprehensive real-world evidence of housing instability should optimize and implement use of structured and unstructured data. Understanding the role of housing instability and temporary housing facilities is salient in populations with SUDs.
Misdiagnosis of bacterial pneumonia increases risk of exposure to inappropriate antibiotics and adverse events. We developed a diagnosis calculator (https://calculator.testingwisely.com) to inform clinical diagnosis of community-acquired bacterial pneumonia using objective indicators, including incidence of disease, risk factors, and sensitivity and specificity of diagnostic tests, that were identified through literature review.
To evaluate the efficacy of a new continuously active disinfectant (CAD) to decrease bioburden on high-touch environmental surfaces compared to a standard disinfectant in the intensive care unit.
Design:
A single-blind randomized controlled trial with 1:1 allocation.
Setting:
Medical intensive care unit (MICU) at an urban tertiary-care hospital.
Participants:
Adult patients admitted to the MICU and on contact precautions.
Intervention:
A new CAD wipe used for daily cleaning.
Methods:
Samples were collected from 5 high-touch environmental surfaces before cleaning and at 1, 4, and 24 hours after cleaning. The primary outcome was the mean bioburden 24 hours after cleaning. The secondary outcome was the detection of any epidemiologically important pathogen (EIP) 24 hours after cleaning.
Results:
In total, 843 environmental samples were collected from 43 unique patient rooms. At 24 hours, the mean bioburden recovered from the patient rooms cleaned with the new CAD wipe (intervention) was 52 CFU/mL, and the mean bioburden was 92 CFU/mL in the rooms cleaned the standard disinfectant (control). After log transformation for multivariable analysis, the mean difference in bioburden between the intervention and control arm was −0.59 (95% CI, −1.45 to 0.27). The odds of EIP detection were 14% lower in the rooms cleaned with the CAD wipe (OR, 0.86; 95% CI, 0.31–2.32).
Conclusions:
The bacterial bioburden and odds of detection of EIPs were not statistically different in rooms cleaned with the CAD compared to the standard disinfectant after 24 hours. Although CAD technology appears promising in vitro, larger studies may be warranted to evaluate efficacy in clinical settings.
Previously published guidelines have provided comprehensive recommendations for detecting and preventing healthcare-associated infections (HAIs). The intent of this document is to highlight practical recommendations in a concise format designed to assist acute-care hospitals in implementing and prioritizing efforts to prevent methicillin-resistant Staphylococcus aureus (MRSA) transmission and infection. This document updates the “Strategies to Prevent Methicillin-Resistant Staphylococcus aureus Transmission and Infection 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.
Known concentrations of Staphylococcus aureus and Candida auris were applied on gloves and gowns then sampled with E-swabs and BBL liquid Amies swabs. The mean numbers of colony-forming units per milliliter (CFU/mL) obtained from culture of the 2 swab types were not different, suggesting that either can be used for recovery of these two pathogens from personal protective equipment.
Multiplex polymerase chain reaction (PCR) respiratory panels are rapid, highly sensitive tests for viral and bacterial pathogens that cause respiratory infections. In this study, we (1) described best practices in the implementation of respiratory panels based on expert perspectives and (2) identified tools for diagnostic stewardship to enhance the usefulness of testing.
Methods:
We conducted a survey of the Society for Healthcare Epidemiology of America Research Network to explore current and future approaches to diagnostic stewardship of multiplex PCR respiratory panels.
Results:
In total, 41 sites completed the survey (response rate, 50%). Multiplex PCR respiratory panels were perceived as supporting accurate diagnoses at 35 sites (85%), supporting more efficient patient care at 33 sites (80%), and improving patient outcomes at 23 sites (56%). Thirteen sites (32%) reported that testing may support diagnosis or patient care without improving patient outcomes. Furthermore, 24 sites (58%) had implemented diagnostic stewardship, with a median of 3 interventions (interquartile range, 1–4) per site. The interventions most frequently reported as effective were structured order sets to guide test ordering (4 sites), restrictions on test ordering based on clinician or patient characteristics (3 sites), and structured communication of results (2 sites). Education was reported as “helpful” but with limitations (3 sites).
Conclusions:
Many hospital epidemiologists and experts in infectious diseases perceive multiplex PCR respiratory panels as useful tests that can improve diagnosis, patient care, and patient outcomes. However, institutions frequently employ diagnostic stewardship to enhance the usefulness of testing, including most commonly clinical decision support to guide test ordering.