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Journal of Long-Term Care ; 2022:298-311, 2022.
Article in English | Scopus | ID: covidwho-2218074

ABSTRACT

Context: Throughout the current COVID-19 pandemic, tremendous effort has been made to implement innovative practices to address social isolation and loneliness (SIL) in long-term care facilities (LTCFs), disproportionally affected by COVID-19. These interventions have not yet been synthesized. This review intended to gather the current promising best practices (PBPs) implemented in LTCFs to alleviate SIL in older persons during the COVID-19 pandemic as well as during the SARS and H1N1 pandemics, using an intersectional lens. Methods: An extensive search was done in nine electronic databases. Arksey and O'Malley's framework was used to format the scoping review. Two independent reviewers screened citations for inclusion, blindly. The selection of articles was conducted blindly by two coauthors. Finally, 16 studies were analyzed out of 9,077 records. Results: Two main themes of findings arose from this review. They comprised proximal PBPs directly addressing SIL in LTCF residents such as pseudo-contact interventions (e.g., chat from balcony or behind transparent barriers/glasses), remote communication tools (e.g., phone or video chat, voice mail/text messaging), and humanoid robots. Distal PBPs included measures implemented to prevent or mitigate the development of COVID-19, including COVID-19 screening approaches, outbreak preparedness, quarantining approaches for both residents and staff. Conclusion: This scoping review found varied PBP implemented during the multiple waves of the COVID-19 pandemic as well as evidence supporting their effectiveness. The contribution of this study is significant as most of the PBP investigated should be prioritized by public policymakers or institutions to provide more satisfactory services to the elderly and their families. © 2022 The Author(s).

2.
J Hosp Infect ; 106(1): 134-154, 2020 Sep.
Article in English | MEDLINE | ID: covidwho-635299

ABSTRACT

Nosocomial or healthcare-associated infections (HCAIs) are associated with a financial burden that affects both patients and healthcare institutions worldwide. The clinical best care practices (CBPs) of hand hygiene, hygiene and sanitation, screening, and basic and additional precautions aim to reduce this burden. The COVID-19 pandemic has confirmed these four CBPs are critically important prevention practices that limit the spread of HCAIs. This paper conducted a systematic review of economic evaluations related to these four CBPs using a discounting approach. We searched for articles published between 2000 and 2019. We included economic evaluations of infection prevention and control of Clostridioides difficile-associated diarrhoea, meticillin-resistant Staphylococcus aureus, vancomycin-resistant enterococci, and carbapenem-resistant Gram-negative bacilli. Results were analysed with cost-minimization, cost-effectiveness, cost-utility, cost-benefit and cost-consequence analyses. Articles were assessed for quality. A total of 11,898 articles were screened and seven were included. Most studies (4/7) were of overall moderate quality. All studies demonstrated cost effectiveness of CBPs. The average yearly net cost savings from the CBPs ranged from $252,847 (2019 Canadian dollars) to $1,691,823, depending on the rate of discount (3% and 8%). The average incremental benefit cost ratio of CBPs varied from 2.48 to 7.66. In order to make efficient use of resources and maximize health benefits, ongoing research in the economic evaluation of infection control should be carried out to support evidence-based healthcare policy decisions.


Subject(s)
Coronavirus Infections/economics , Coronavirus Infections/prevention & control , Cross Infection/economics , Cross Infection/prevention & control , Economics, Hospital/statistics & numerical data , Infection Control/economics , Pandemics/economics , Pandemics/prevention & control , Pneumonia, Viral/economics , Pneumonia, Viral/prevention & control , Betacoronavirus , COVID-19 , Canada , Humans , Infection Control/statistics & numerical data , SARS-CoV-2
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