scholarly journals Risk Factors Associated With Mortality Among Residents With Coronavirus Disease 2019 (COVID-19) in Long-term Care Facilities in Ontario, Canada

2020 ◽  
Vol 3 (7) ◽  
pp. e2015957 ◽  
Author(s):  
David N. Fisman ◽  
Isaac Bogoch ◽  
Lauren Lapointe-Shaw ◽  
Janine McCready ◽  
Ashleigh R. Tuite
Keyword(s):  
Risk Factors ◽  
Long Term Care ◽  
Term Care ◽  
Factors Associated ◽  
Care Facilities

scholarly journals Factors associated with transmission in COVID-19 outbreaks in long-term care facilities

2021 ◽  
Author(s):  
Rohit Vijh ◽  
Carmen H Ng ◽  
Mehdi Shirmaleki ◽  
Aamir Bharmal
Keyword(s):  
Public Health ◽  
Risk Factors ◽  
Long Term Care ◽  
Term Care ◽  
Outbreak Management ◽  
Factors Associated ◽  
Health Measures ◽  
Modifiable Factors ◽  
Care Facilities

Background: Severe acute respiratory syndrome coronavirus 2 (SARSCoV2) has had a disproportionate impact on residents in long-term care facilities (LTCFs). Through our experience and data from managing COVID-19 exposures and outbreaks in LTCFs in the Fraser Health region in British Columbia, Canada, we identified risk factors associated with outbreak severity to inform current outbreak management strategies and future pandemic preparedness planning efforts. Methods: We used a retrospective cohort study design to evaluate the association between non-modifiable factors (facility building, organization level, and resident population characteristics), modifiable factors (assessments for infection prevention and control (IPC) and public health measures), and severity of COVID-19 outbreaks (attack rate) in LTCFs. We modelled the COVID-19 attack rates in LTCF outbreaks using negative binomial regression models. Results: From March 1, 2020 to January 10, 2021, a total of 145 exposures to at least one confirmed case of COVID-19 in 82 LTCFs occurred. For every item not met in the assessment tool, a 22% increase in the attack rate was observed (rate ratio 1.2 [95% CI 1.1 to 1.4]) after adjusting for other risk factors such as age of the facility, index case type (resident vs. staff) and proportion of single bed rooms. Conclusion: Our findings highlight the importance of assessing IPC and public health measures for outbreak management. They also demonstrate the important modifiable and non-modifiable risk factors associated with COVID-19 outbreaks in our jurisdiction. We hope these findings will inform ongoing outbreak management and future pandemic planning efforts.

Design and Development of a Web-based Delirium Preventive Application for Long-term Care Facilities: A Methodological Study (Preprint)

2020 ◽  
Author(s):  
Kyoung Ja Moon ◽  
Chang-Sik Son ◽  
Jong-Ha Lee ◽  
Mina Park
Keyword(s):  
Risk Factors ◽  
Long Term Care ◽  
Cloud System ◽  
Evidence Based ◽  
Methodological Study ◽  
Term Care ◽  
Web Based ◽  
Care Facilities ◽  
Delirium Prevention

BACKGROUND Long-term care facilities demonstrate low levels of knowledge and care for patients with delirium and are often not properly equipped with an electronic medical record system, thereby hindering systematic approaches to delirium monitoring. OBJECTIVE This study aims to develop a web-based delirium preventive application (app), with an integrated predictive model, for long-term care (LTC) facilities using artificial intelligence (AI). METHODS This methodological study was conducted to develop an app and link it with the Amazon cloud system. The app was developed based on an evidence-based literature review and the validity of the AI prediction model algorithm. Participants comprised 206 persons admitted to LTC facilities. The app was developed in 5 phases. First, through a review of evidence-based literature, risk factors for predicting delirium and non-pharmaceutical contents for preventive intervention were identified. Second, the app, consisting of several screens, was designed; this involved providing basic information, predicting the onset of delirium according to risk factors, assessing delirium, and intervening for prevention. Third, based on the existing data, predictive analysis was performed, and the algorithm developed through this was calculated at the site linked to the web through the Amazon cloud system and sent back to the app. Fourth, a pilot test using the developed app was conducted with 33 patients. Fifth, the app was finalized. RESULTS We developed the Web_DeliPREVENT_4LCF for patients of LTC facilities. This app provides information on delirium, inputs risk factors, predicts and informs the degree of delirium risk, and enables delirium measurement or delirium prevention interventions to be immediately implemented with a verified tool. CONCLUSIONS This web-based application is evidence-based and offers easy mobilization and care to patients with delirium in LTC facilities. Therefore, the use of this app improves the unrecognized of delirium and predicts the degree of delirium risk, thereby helping initiatives for delirium prevention and providing interventions. This would ultimately improve patient safety and quality of care. CLINICALTRIAL none

scholarly journals Factors associated with SARS-CoV-2 infection and outbreaks in long-term care facilities in England: a national cross-sectional survey

2021 ◽  
Vol 2 (3) ◽  
pp. e129-e142 ◽  
Author(s):  
Laura Shallcross ◽  
Danielle Burke ◽  
Owen Abbott ◽  
Alasdair Donaldson ◽  
Gemma Hallatt ◽  
...  
Keyword(s):  
Long Term Care ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Term Care ◽  
Factors Associated ◽  
Care Facilities

scholarly journals Long-Term Care Facilities Are Reservoirs for Antimicrobial-Resistant Sequence Type 131 Escherichia coli

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Mary J. Burgess ◽  
James R. Johnson ◽  
Stephen B. Porter ◽  
Brian Johnston ◽  
Connie Clabots ◽  
...  
Keyword(s):  
Risk Factors ◽  
Escherichia Coli ◽  
Gel Electrophoresis ◽  
Long Term Care ◽  
Pulsed Field Gel Electrophoresis ◽  
Sequence Type ◽  
Term Care ◽  
E Coli ◽  
Care Facilities

Abstract Background.  Emerging data implicate long-term care facilities (LTCFs) as reservoirs of fluoroquinolone-resistant (FQ-R) Escherichia coli of sequence type 131 (ST131). We screened for ST131 among LTCF residents, characterized isolates molecularly, and identified risk factors for colonization. Methods.  We conducted a cross-sectional study using a single perianal swab or stool sample per resident in 2 LTCFs in Olmsted County, Minnesota, from April to July 2013. Confirmed FQ-R E. coli isolates underwent polymerase chain reaction-based phylotyping, detection of ST131 and its H30 and H30-Rx subclones, extended virulence genotyping, and pulsed-field gel electrophoresis (PFGE) analysis. Epidemiological data were collected from medical records. Results.  Of 133 fecal samples, 33 (25%) yielded FQ-R E. coli, 32 (97%) of which were ST131. The overall proportion with ST131 intestinal colonization was 32 of 133 (24%), which differed by facility: 17 of 41 (42%) in facility 1 vs 15 of 92 (16%) in facility 2 (P = .002). All ST131 isolates represented the H30 subclone, with virulence gene and PFGE profiles resembling those of previously described ST131 clinical isolates. By PFGE, certain isolates clustered both within and across LTCFs. Multivariable predictors of ST131 colonization included inability to sign consent (odds ratio [OR], 4.16 [P = .005]), decubitus ulcer (OR, 4.87 [ P = .04]), and fecal incontinence (OR, 2.59 [P = .06]). Conclusions.  Approximately one fourth of LTCF residents carried FQ-R ST131 E. coli resembling ST131 clinical isolates. Pulsed-field gel electrophoresis suggested intra- and interfacility transmission. The identified risk factors suggest that LTCF residents who require increased nursing care are at greatest risk for ST131 colonization, possibly due to healthcare-associated transmission.

Factors That Affect Influenza Vaccine Uptake Among Staff of Long-Term Care Facilities

2006 ◽  
Vol 27 (6) ◽  
pp. 638-641 ◽  
Author(s):  
Anja M. Hauri ◽  
Helmut Uphoff ◽  
Volker Gussmann ◽  
Stefan Gawrich
Keyword(s):  
Influenza Vaccine ◽  
Long Term Care ◽  
Vaccine Uptake ◽  
Term Care ◽  
Vaccination Uptake ◽  
Factors Associated ◽  
Care Facilities ◽  
Policies And Practices

A survey of directors and employees of 36 long-term care facilities in Hesse, Germany, revealed that influenza vaccine uptake among staff was less than 30% in 30 and greater than 50% in 6. The study identified policies and practices associated with vaccination uptake at long-term care facilities and factors associated with the decision of staff to get vaccinated.

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