NDLI: The influence of cold weather on the usage of emergency link calls: a case study in Hong Kong

Content Provider	Springer Nature : BioMed Central
Author	Chen, Feng Yip, Paul SF
Abstract	Background In response to an unexpected long cold spell in February 1996 which killed more than 100 older adults (mostly living alone) in Hong Kong, the Hong Kong Senior Citizen Home Safety Association established a Personal Emergency Link Service to provide emergency contact to the older adults, which uses a telephone system to render emergency relief and total care service around the clock. To facilitate the dynamic and efficient allocation of service resources, it is crucial to understand the factors linked with use of the services and number of hospital admissions arising from PE link service. Methods We initially use the Poisson generalized linear model (GLM) with polynomial effect functions of relevant covariates. If the time series of residuals from fitting the Poisson GLM reveals significant serial correlation, a Poisson generalized linear autoregressive moving average (GLARMA) model is refitted to the data to account for the auto-correlation among the time series of daily call numbers. If the data is overdispersed relative to the best fitting Poisson GLARMA model, then the negative binomial GLARMA model is refitted to account for any overdispersion. In all the models, dummy variables for weekdays and months are included to account for any cyclic trends due weekday effect or month of the year effect. The secular time trend is modeled by a polynomial function of calendar time over the study period. Finally any critical temperatures are identified by visually inspecting the graph of the effect function of temperature. Results The weekday and month effects are both significant with Monday seeing more PE Link calls than Sunday and June seeing less than January. Temperature has significant effect on the PE Link call rate with the effect highly nonlinear. A critical temperature, below which excessive increase in PE link calls that lead to hospital admissions, is identified to be around 15 °C. Conclusion Identifying a threshold temperature which generates an excessive increase in the expected number of PE Link calls would be useful in service provision planning and support for elderly in need of hospital admission.
Related Links	https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-015-0191-1.pdf
Ending Page	9
Page Count	9
Starting Page	1
File Format	HTM / HTML
ISSN	14726947
DOI	10.1186/s12911-015-0191-1
Journal	BMC Medical Informatics and Decision Making
Issue Number	1
Volume Number	15
Language	English
Publisher	BioMed Central
Publisher Date	2015-08-13
Access Restriction	Open
Subject Keyword	Health Informatics Information Systems and Communication Service Management of Computing and Information Systems Auto-regression Count data Generalized linear auto-regressive moving-average (GLARMA) model Generalized linear model (GLM) negative binomial Nonlinear effect Overdispersion Poisson regression Time series
Content Type	Text
Resource Type	Article
Subject	Health Informatics Computer Science Applications Health Policy
Journal Impact Factor	3.3/2023
5-Year Journal Impact Factor	3.9/2023

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