1.Socio-demographic and clinical profile of admissions to community hospitals in Singapore from 1996 to 2005: a descriptive study.
Gerald C H KOH ; Liang E N WEE ; Nashia Ali RIZVI ; Cynthia CHEN ; Angela CHEONG ; Ngan Phoon FONG ; Kin Ming CHAN ; Boon Yeow TAN ; Edward MENON ; Chye Hua EE ; Kok Keng LEE ; Robert PETRELLA ; Amardeep THIND ; David KOH ; Kee Seng CHIA
Annals of the Academy of Medicine, Singapore 2012;41(11):494-510
INTRODUCTIONLittle data is available on community hospital admissions. We examined the differences between community hospitals and the annual trends in sociodemographic characteristics of all patient admissions in Singaporean community hospitals over a 10- year period from 1996 to 2005.
MATERIALS AND METHODSData were manually extracted from medical records of 4 community hospitals existent in Singapore from 1996 to 2005. Nineteen thousand and three hundred and sixty patient records were examined. Chisquare test was used for univariate analysis of categorical variables by type of community hospitals. For annual trends, test for linear by linear association was used. ANOVA was used to generate beta coefficients for continuous variables.
RESULTSMean age of all patient admissions has increased from 72.8 years in 1996 to 74.8 years in 2005. The majority was Chinese (88.4%), and female (58.1%) and admissions were mainly for rehabilitation (88.0%). Almost one third had foreign domestic workers as primary caregivers and most (73.5%) were discharged to their own home. There were significant differences in socio-demographic profile of admissions between hospitals with one hospital having more patients with poor social support. Over the 10-year period, the geometric mean length of stay decreased from 29.7 days (95% CI, 6.4 to 138.0) to 26.7 days (95% CI, 7.5 to 94.2), and both mean admission and discharge Barthel Index scores increased from 41.0 (SD = 24.9) and 51.8 (SD = 30.0), respectively in 1996 to 48.4 (SD = 24.5) and 64.2 (SD = 27.3) respectively in 2005.
CONCLUSIONThere are significant differences in socio-demographic characteristics and clinical profile of admissions between various community hospitals and across time. Understanding these differences and trends in admission profiles may help in projecting future healthcare service needs.
Aged ; Aged, 80 and over ; Analysis of Variance ; Confidence Intervals ; Diagnosis ; Female ; Hospitals, Community ; Humans ; Male ; Medical Records ; statistics & numerical data ; Middle Aged ; Odds Ratio ; Patient Admission ; statistics & numerical data ; trends ; Singapore ; Social Class
Result Analysis
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