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Background: Many countries around the world have adopted social distancing as one of the public health measures to reduce COVID-19 transmissions in the community. Such measures could have negative effects on the mental health of the population. The aims of this study are to (1) track the impact of COVID-19 on self-reported mood, self-rated health, other health and psychosocial indicators, and health services utilization of people who have an interRAI assessment during the first year of COVID-19; (2) compare these indicators with the same indicators in people who had an interRAI assessment in the year before COVID-19; and (3) report these indicators publicly as soon as data analysis is completed every 3 months.Methods: interRAI COVID-19 Study (iCoS) is an observational study on routinely collected national data using the interRAI Home Care and Contact Assessment, which are standardized geriatric assessment tools mandated for all people assessed for publicly funded home support services and aged residential care in New Zealand. Based on the 2018/19 figures, we estimated there are 36,000 interRAI assessments per annum. We will compare the four post-lockdown quarters (from 25th March 2020) with the respective pre-lockdown quarters. The primary outcomes are self-reported mood (feeling sad, depressed or hopeless: 0 = no, 1 = yes) and self-rated health (0 = excellent, 1 = good, 2 = fair, 3 = poor). We will also analyze sociodemographics, other secondary health and psychosocial indicators, and health services utilization. Descriptive statistics will be conducted for primary outcomes and other indicators for each of the eight quarters. We will compare the quarters using regression models adjusted for demographic characteristics using weights or additional variables. Key health and psychosocial indicators will be reported publicly as soon as data analysis is completed for each quarter in the 12-month post-lockdown period by using a data visualization tool.Discussion: This rapid translation of routinely collected national interRAI data will provide a means to monitor the health and psychosocial well-being of vulnerable older New Zealanders. Insights from this study can be shared with other countries that use interRAI and prepare health and social services for similar epidemics/pandemics in the future. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the impact of the COVID-19 pandemic on falls rates in long-term care residents with cognitive impairment. An observational study using routinely collected national interRAI data. Participants were from long-term care residents (age ≥60 years) who received an interRAI Long Term Care Facility assessment anywhere in New Zealand between August 17, 2018, and August 16, 2022. The primary outcome was "At least 1 fall in the last 30 days." Based on the Cognitive Performance Scale (CPS), cognitive impairment was categorized into 3 levels: intact or borderline intact (0-1), mild to moderate impairment (2-3), and moderately to very severe impairment (4-6). The COVID-19 pandemic was divided into 3 periods (First wave: March 21, 2020, to June 8, 2020; Varying level of community outbreaks: June 9, 2020 to August 16, 2021; and Delta-Omicron wave: August 17, 2021, to August 16, 2021) and compared to a pre-COVID-19 period (August 17, 2018, to March 20, 2020). Cox regression modeling was used to study falls and interactions between CPS and COVID-19 pandemic periods, along with other established falls risk factors in the literature. A total of 282,518 interRAI-LTCF assessments from 75,132 unique residents were included. Interactions between CPS and COVID-19 pandemic periods found that cognitive impairment was associated with a higher hazard ratio (ranged from 1.22 to 1.37) in each of the 3 COVID-19 pandemic periods. We also found unstable health, unsteady gait, wandering, and moderate to severe ADL dependency were the strongest risk factors for falls. Cognitively impaired long-term care residents had an increased risk for falls during the COVID-19 pandemic. This risk was influenced by several factors. In future pandemic or infection control related isolation, residents who are most at risk can be identified for targeted falls prevention programs. [ABSTRACT FROM AUTHOR]