Background <p>Nursing homes were severely affected by the COVID-19 pandemic. Standardised parameters are essential to understand and monitor the unintended consequences of pandemic control measures and changes in work processes. In this scoping review, we aimed to identify COVID-19-related parameters studied in nursing homes that could form a minimum data set suitable for database development. We focused on the perspectives of all interest-holders: facilities, residents, their relatives and nursing home staff.</p> Methods <p>We searched MEDLINE and CINAHL and included quantitative studies published in English since the beginning of the pandemic (2020 to 2024). The extracted parameters were initially categorised according to five dimensions: pandemic-related data, facility level, staff level, residents and relatives. Within each dimension, the original terms were compared and inductively organised into (sub-)categories based on conceptual similarities, with synonymous terms subsequently standardised.</p> Results <p>From 82 included articles, 96 different parameters related to COVID-19 in nursing homes were identified. Infection and mortality rates emerged as the pandemic-related data most often reported, particularly within this dimension but also across all dimensions. However, we found a broad range of resident-related parameters. Our most often identified facility-related parameters include the number of staff and the provision of personal protective equipment. Staff-related parameters most often studied were personal burden and stress. Only a few parameters (<i>n</i> = 9) were considered for relatives.</p> Conclusions <p>The diversity of the reported parameters indicates that a comprehensive database is required to adequately assess a pandemic situation in this vulnerable population. In terms of pandemic preparedness, our overview of the reported parameters offers a basis for the development of country- and context-specific data capture approaches.</p>

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Internationally studied parameters related to the COVID-19 pandemic in nursing homes: a scoping review

  • Almuth Berg,
  • Christin Richter,
  • Gabriele Meyer

摘要

Background

Nursing homes were severely affected by the COVID-19 pandemic. Standardised parameters are essential to understand and monitor the unintended consequences of pandemic control measures and changes in work processes. In this scoping review, we aimed to identify COVID-19-related parameters studied in nursing homes that could form a minimum data set suitable for database development. We focused on the perspectives of all interest-holders: facilities, residents, their relatives and nursing home staff.

Methods

We searched MEDLINE and CINAHL and included quantitative studies published in English since the beginning of the pandemic (2020 to 2024). The extracted parameters were initially categorised according to five dimensions: pandemic-related data, facility level, staff level, residents and relatives. Within each dimension, the original terms were compared and inductively organised into (sub-)categories based on conceptual similarities, with synonymous terms subsequently standardised.

Results

From 82 included articles, 96 different parameters related to COVID-19 in nursing homes were identified. Infection and mortality rates emerged as the pandemic-related data most often reported, particularly within this dimension but also across all dimensions. However, we found a broad range of resident-related parameters. Our most often identified facility-related parameters include the number of staff and the provision of personal protective equipment. Staff-related parameters most often studied were personal burden and stress. Only a few parameters (n = 9) were considered for relatives.

Conclusions

The diversity of the reported parameters indicates that a comprehensive database is required to adequately assess a pandemic situation in this vulnerable population. In terms of pandemic preparedness, our overview of the reported parameters offers a basis for the development of country- and context-specific data capture approaches.