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

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

2000 ◽  
Vol 21 (10) ◽  
pp. 680-683 ◽  
Author(s):  
Mark Loeb

AbstractThe extensive use of antibiotics in long-term–care facilities has led to increasing concern about the potential for the development of antibiotic resistance. Relatively little is known, however, about the quantitative relation between antibiotic use and resistance in this population. A better understanding of the underlying factors that account for variance in antibiotic use, unexplained by detected infections, is needed. To optimize antibiotic use, evidence-based standards for empirical antibiotic prescribing need to be developed. Limitations in current diagnostic testing for infection in residents of long-term–care facilities pose a substantial challenge to developing such standards.


2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Mary J. Burgess ◽  
James R. Johnson ◽  
Stephen B. Porter ◽  
Brian Johnston ◽  
Connie Clabots ◽  
...  

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.


Author(s):  
Aung-Hein Aung ◽  
Kala Kanagasabai ◽  
Jocelyn Koh ◽  
Pei-Yun Hon ◽  
Brenda Ang ◽  
...  

BACKGROUND Movement of patients in a healthcare network poses challenges for the control of carbapenemase-producing Enterobacteriaceae (CPE). We aimed to identify intra- and inter-facility transmission events and facility type-specific risk factors of CPE in an acute care hospital (ACH) and its intermediate-term and long-term care facilities (ILTCFs). METHODS Serial cross-sectional studies were conducted in June-July of 2014-2016 to screen for CPE. Whole genome sequencing was done to identify strain relatedness and CPE genes (blaIMI; blaIMP-1; blaKPC-2; blaNDM-1; blaOXA-48). Multivariable logistic regression models, stratified by facility type were used to determine independent risk factors. RESULTS Of 5357 patients, half (55%) were from the ACH. CPE prevalence was 1.3% in the ACH and 0.7% in ILTCFs (p=0.029). After adjusting for socio-demographics, screening year, and facility type, the odds of CPE colonization increased significantly with hospital stay ≥ 3 weeks (aOR 2.67, 95%CI 1.17-6.05), penicillins use (aOR 3.00, 95%CI 1.05–8.56), proton pump inhibitors use (aOR 3.20, 95%CI 1.05–9.80), dementia (aOR 3.42, 95%CI 1.38–8.49), connective tissue disease (aOR 5.10, 95%CI 1.19-21.81), and prior carbapenem-resistant Enterobacteriaceae (CRE) carriage (aOR 109.02, 95%CI 28.47–417.44) in the ACH. For ILTCFs, presence of wound (aOR 5.30, 95%CI 1.01–27.72), respiratory procedures (aOR 4.97, 95%CI 1.09-22.71), vancomycin-resistant Enterococci carriage (aOR 16.42, 95%CI 1.52–177.48), and CRE carriage (aOR 758.30, 95%CI 33.86-16982.52) showed significant association. Genomic analysis revealed only possible intra-ACH transmission, and no evidence for ACH-to-ILTCFs transmission. CONCLUSIONS Although CPE colonization was predominantly in the ACH, risk factors varied between facilities. Targeted screening and precautionary measures are warranted.


2020 ◽  
Author(s):  
Laura Shallcross ◽  
Danielle Burke ◽  
Owen Abbott C Stat ◽  
Alasdair Donaldson ◽  
Gemma Hallatt ◽  
...  

AbstractBackgroundOutbreaks of SARS-CoV-2 have occurred worldwide in Long Term Care Facilities (LTCFs), but the reasons why some facilities are particularly vulnerable to infection are poorly understood. We aimed to identify risk factors for SARS-CoV-2 infection and outbreaks in LTCFs.MethodsCross-sectional survey of all LTCFs providing dementia care or care to adults >65 years in England with linkage to SARS-CoV-2 test results. Exposures included: LTCF characteristics, staffing factors, and use of disease control measures. Main outcomes included risk factors for infection and outbreaks, estimated using multivariable logistic regression, and survey and test-based weighted estimates of SARS-CoV-2 prevalence.Findings5126/9081 (56%) LTCFs participated in the survey, with 160,033 residents and 248,594 staff. The weighted period prevalence of infection in residents and staff respectively was 10.5% (95% CI: 9.9-11.1%) and 3.8% (95%: 3.4-4.2%) and 2724 LTCFs (53.1%) had ≥1 infection. Odds of infection and/or outbreaks were reduced in LTCFs that paid sickness pay, cohorted staff, did not employ agency staff and had higher staff to resident ratios. Higher odds of infection and outbreaks were identified in facilities with more admissions, lower cleaning frequency, poor compliance with isolation and “for profit” status.InterpretationHalf of LTCFs had no cases suggesting they remain vulnerable to outbreaks. Reducing transmission from staff requires adequate sick pay, minimal use of temporary staff, improved staffing ratios and staff cohorting. Transmission from residents is associated with the number of admissions to the facility and poor compliance with isolation.FundingUK Government Department of Health & Social CareResearch in contextEvidence before this studyCOVID-19 outbreaks have occurred worldwide in long-term care facilities (LTCFs), which provide care to elderly and vulnerable residents, and are associated with high mortality. The reasons why LTCFs are particularly vulnerable to COVID-19 are poorly understood. Most studies of risk factors for COVID-19 to date have been limited by scale, and poor quality administrative, demographic and infection control data. We conducted a systematic search on 27 July 2020 in MEDLINE Ovid, WHO COVID-19 database and in MedRxiv to identify studies reporting risk factors for COVID-19 infection or outbreaks in LTCFs, with no date or language restrictions. We used the search terms “COVID-19”, “SARS-CoV-2”, “coronavirus” and “care home”, “nursing home”, “long term care facilit” and excluded studies that did not investigate LTCF-level risk factors. 14 studies met our inclusion criteria comprising 11 cross-sectional studies and 3 surveys. The largest cross-sectional study was conducted in 9395 specialised nursing facilities across 30 states in USA; the largest survey was conducted in 124 LTCFs in Haute-Garrone region of France. Risk of bias was high across all studies, and results could not be pooled due to heterogeneity between studies. Main risk factors for infection and/or outbreaks related to the size of the facility, lower ratios of staff to residents, urban location, higher occupancy, and the community prevalence of infection. Only one study collected data on the use of disease control measures during the pandemic, and no studies provided data on risk factors such as the use of temporary staff, or the impact of staff working across multiple locations.Added value of this studyWe conducted a national telephone survey with managers of all LTCFs in England which provided dementia care or care to residents aged > 65 years to collect data on the number of staff and residents in each facility, confirmed SARS-CoV-2 infections, characteristics of the facility e.g.size, staffing (use of temporary staff, staffing ratios, sickness pay) and disease control measures such as cohorting and isolation. We identified risk factors for infection in residents and staff, outbreaks (defined as ≥1 case per LTCF) and large outbreaks using logistic regression. We also estimated the proportion of staff and residents who had been infected with SARS-CoV-2. Responses were obtained from 5126 of out 9081 (56%) of eligible LTCFs. To our knowledge, this is the largest and most detailed survey of risk factors for SARS-CoV-2 infection and outbreaks that has been conducted in LTCFs.Implications of all the available evidenceAlmost half of LTCFs surveyed in this study did not report any cases of infection, and remain vulnerable to infection and outbreaks, highlighting the need for effective control measures. Reducing transmission from staff requires adequate sick pay, minimal use of temporary staff, improved staffing ratios and staff cohorting. Transmission from residents is associated with the number of admissions to the facility and poor compliance with control measures such as isolation.


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