Frequency of admittance and probability of inpatient treatment

Experience of Emergency Department, Hospital Universiti Kebangsaan Malaysia

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In Malaysia, the number of Emergency Department visits in government hospitals recently has climbed and as a result causing overcrowding in such departments. Overcrowding occurs when all rooms, stretchers and chairs in the Emergency Department are full with sick people waiting for a long period of time to receive emergency care. The main factors contributing to this state of affair are the increasing number of unexpected patients, lack of staffs and lack of beds for inpatient treatment. Overcrowding has significant negative effects on patient's safety, comfort and satisfaction in addition to depicting the inability of emergency staffs to care for patients. Based on past studies, statistics showed that the number of patients frequently admitted to the Emergency Department were patients injured in road accidents. This study aims to develop two models for solving overcrowding in the Emergency Department. The first will be applied to estimate frequency of admittance due to injuries of road accidents and its relationship to the contributing factors whereas the latter will be employed to estimate probability of receiving inpatient treatment once patients are already admitted to the Emergency Department. Samples are collected from the experience of the Emergency Department, Hospital Universiti Kebangsaan Malaysia (HUKM) and they are analyzed using regression models. Poisson regression is used for the first model whereby the factors considered are patient's age, gender, race and admittance date. The result may be utilized by the hospital management to predict the frequency of admittance based on the contributing factors. Logistic regression is utilized in the second model to identify the probability of receiving inpatient treatment after being admitted to the Emergency Department. The result may be employed by the hospital management to prepare and provide sufficient emergency beds and staffs especially for inpatient treatment. The contributing factors studied in the second model are the same as the first model.

Original languageEnglish
Pages (from-to)76-87
Number of pages12
JournalEuropean Journal of Social Sciences
Volume8
Issue number1
Publication statusPublished - Mar 2009

Fingerprint

inpatient treatment
Malaysia
experience
staff
regression
accident
road
lack
management
logistics
statistics
gender

Keywords

  • Emergency department
  • Frequency of admittance
  • Logistic regression
  • Poisson regression
  • Probability of inpatient treatment

ASJC Scopus subject areas

  • Social Sciences(all)

Cite this

@article{bf23103bc65f4b99ac4a24b89e49cfff,
title = "Frequency of admittance and probability of inpatient treatment: Experience of Emergency Department, Hospital Universiti Kebangsaan Malaysia",
abstract = "In Malaysia, the number of Emergency Department visits in government hospitals recently has climbed and as a result causing overcrowding in such departments. Overcrowding occurs when all rooms, stretchers and chairs in the Emergency Department are full with sick people waiting for a long period of time to receive emergency care. The main factors contributing to this state of affair are the increasing number of unexpected patients, lack of staffs and lack of beds for inpatient treatment. Overcrowding has significant negative effects on patient's safety, comfort and satisfaction in addition to depicting the inability of emergency staffs to care for patients. Based on past studies, statistics showed that the number of patients frequently admitted to the Emergency Department were patients injured in road accidents. This study aims to develop two models for solving overcrowding in the Emergency Department. The first will be applied to estimate frequency of admittance due to injuries of road accidents and its relationship to the contributing factors whereas the latter will be employed to estimate probability of receiving inpatient treatment once patients are already admitted to the Emergency Department. Samples are collected from the experience of the Emergency Department, Hospital Universiti Kebangsaan Malaysia (HUKM) and they are analyzed using regression models. Poisson regression is used for the first model whereby the factors considered are patient's age, gender, race and admittance date. The result may be utilized by the hospital management to predict the frequency of admittance based on the contributing factors. Logistic regression is utilized in the second model to identify the probability of receiving inpatient treatment after being admitted to the Emergency Department. The result may be employed by the hospital management to prepare and provide sufficient emergency beds and staffs especially for inpatient treatment. The contributing factors studied in the second model are the same as the first model.",
keywords = "Emergency department, Frequency of admittance, Logistic regression, Poisson regression, Probability of inpatient treatment",
author = "Noriszura Ismail and Karim, {Zatul Iradah Abdul} and {Jaaman @ Sharman}, {Saiful Hafizah} and Noriza Majid",
year = "2009",
month = "3",
language = "English",
volume = "8",
pages = "76--87",
journal = "European Journal of Social Sciences",
issn = "1450-2267",
publisher = "EuroJournals, Inc.",
number = "1",

}

TY - JOUR

T1 - Frequency of admittance and probability of inpatient treatment

T2 - Experience of Emergency Department, Hospital Universiti Kebangsaan Malaysia

AU - Ismail, Noriszura

AU - Karim, Zatul Iradah Abdul

AU - Jaaman @ Sharman, Saiful Hafizah

AU - Majid, Noriza

PY - 2009/3

Y1 - 2009/3

N2 - In Malaysia, the number of Emergency Department visits in government hospitals recently has climbed and as a result causing overcrowding in such departments. Overcrowding occurs when all rooms, stretchers and chairs in the Emergency Department are full with sick people waiting for a long period of time to receive emergency care. The main factors contributing to this state of affair are the increasing number of unexpected patients, lack of staffs and lack of beds for inpatient treatment. Overcrowding has significant negative effects on patient's safety, comfort and satisfaction in addition to depicting the inability of emergency staffs to care for patients. Based on past studies, statistics showed that the number of patients frequently admitted to the Emergency Department were patients injured in road accidents. This study aims to develop two models for solving overcrowding in the Emergency Department. The first will be applied to estimate frequency of admittance due to injuries of road accidents and its relationship to the contributing factors whereas the latter will be employed to estimate probability of receiving inpatient treatment once patients are already admitted to the Emergency Department. Samples are collected from the experience of the Emergency Department, Hospital Universiti Kebangsaan Malaysia (HUKM) and they are analyzed using regression models. Poisson regression is used for the first model whereby the factors considered are patient's age, gender, race and admittance date. The result may be utilized by the hospital management to predict the frequency of admittance based on the contributing factors. Logistic regression is utilized in the second model to identify the probability of receiving inpatient treatment after being admitted to the Emergency Department. The result may be employed by the hospital management to prepare and provide sufficient emergency beds and staffs especially for inpatient treatment. The contributing factors studied in the second model are the same as the first model.

AB - In Malaysia, the number of Emergency Department visits in government hospitals recently has climbed and as a result causing overcrowding in such departments. Overcrowding occurs when all rooms, stretchers and chairs in the Emergency Department are full with sick people waiting for a long period of time to receive emergency care. The main factors contributing to this state of affair are the increasing number of unexpected patients, lack of staffs and lack of beds for inpatient treatment. Overcrowding has significant negative effects on patient's safety, comfort and satisfaction in addition to depicting the inability of emergency staffs to care for patients. Based on past studies, statistics showed that the number of patients frequently admitted to the Emergency Department were patients injured in road accidents. This study aims to develop two models for solving overcrowding in the Emergency Department. The first will be applied to estimate frequency of admittance due to injuries of road accidents and its relationship to the contributing factors whereas the latter will be employed to estimate probability of receiving inpatient treatment once patients are already admitted to the Emergency Department. Samples are collected from the experience of the Emergency Department, Hospital Universiti Kebangsaan Malaysia (HUKM) and they are analyzed using regression models. Poisson regression is used for the first model whereby the factors considered are patient's age, gender, race and admittance date. The result may be utilized by the hospital management to predict the frequency of admittance based on the contributing factors. Logistic regression is utilized in the second model to identify the probability of receiving inpatient treatment after being admitted to the Emergency Department. The result may be employed by the hospital management to prepare and provide sufficient emergency beds and staffs especially for inpatient treatment. The contributing factors studied in the second model are the same as the first model.

KW - Emergency department

KW - Frequency of admittance

KW - Logistic regression

KW - Poisson regression

KW - Probability of inpatient treatment

UR - http://www.scopus.com/inward/record.url?scp=65349152659&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=65349152659&partnerID=8YFLogxK

M3 - Article

VL - 8

SP - 76

EP - 87

JO - European Journal of Social Sciences

JF - European Journal of Social Sciences

SN - 1450-2267

IS - 1

ER -