Factors Associated with Intensive Care Unit Admission Refusal
Background: The need for intensive care exceeds its availability most times because resources are limited. Our objectives were to determine the incidence of admission refusal and factors associated with such in our Intensive Care Unit (ICU). Methods: The following information was obtained from patie...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Surgical Society of Kenya
2017-07-01
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| Series: | The Annals of African Surgery |
| Subjects: | |
| Online Access: | https://www.annalsofafricansurgery.com/factors-associated-with-intensive-c |
| _version_ | 1819087847376814080 |
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| author | Babatunde Ayoade Tosin Olusanya |
| author_facet | Babatunde Ayoade Tosin Olusanya |
| author_sort | Babatunde Ayoade |
| collection | DOAJ |
| description | Background: The need for intensive care exceeds its availability most times because resources are limited. Our objectives were to determine the incidence of admission refusal and factors associated with such in our Intensive Care Unit (ICU). Methods: The following information was obtained from patients referred to our ICU over a 6-week period: age, gender, date and time of referral, source of referral, reason for referral, whether ICU was full or not full at the time of referral, and modified early warning score (MEWS). Others included; whether admitted or not, and if not admitted, reasons for admission refusal. Binomial logistic regression analysis was used to determine predictors of ICU admission refusal. Results: Patients admitted and those denied admission were 37(50.7%) and 36(49.3%) respectively. Following univariate analysis, there were no statistical differences in the age and MEWS of patients in the admitted and not admitted groups respectively. Refusal was highest for sepsis (80%) and respiratory failure (71.4%) and lowest for severe head injury (18.2%), no difference was found in the MEWS for patients with sepsis and those with severe head injury. Lack of ICU bed was the only independent predictor of ICU admission refusal. Conclusions: The crude ICU admission refusal rate was 49.3% and unavailability of ICU bed independently predicted ICU admission refusal. To ensure reduction in ICU admission refusals, the ratio of ICU beds over the population must be appropriate. |
| first_indexed | 2024-12-21T21:42:39Z |
| format | Article |
| id | doaj.art-6029f89276fc459cbf0adc39aba9763f |
| institution | Directory Open Access Journal |
| issn | 1999-9674 2523-0816 |
| language | English |
| last_indexed | 2024-12-21T21:42:39Z |
| publishDate | 2017-07-01 |
| publisher | Surgical Society of Kenya |
| record_format | Article |
| series | The Annals of African Surgery |
| spelling | doaj.art-6029f89276fc459cbf0adc39aba9763f2022-12-21T18:49:19ZengSurgical Society of KenyaThe Annals of African Surgery1999-96742523-08162017-07-01142Factors Associated with Intensive Care Unit Admission RefusalBabatunde Ayoade0Tosin Olusanya1Department of Anesthesia, University of Ibadan/University College Hospital, Ibadan, Oyo State, NigeriaDepartment of Anesthesia, University of Ibadan/University College Hospital, Ibadan, Oyo State, NigeriaBackground: The need for intensive care exceeds its availability most times because resources are limited. Our objectives were to determine the incidence of admission refusal and factors associated with such in our Intensive Care Unit (ICU). Methods: The following information was obtained from patients referred to our ICU over a 6-week period: age, gender, date and time of referral, source of referral, reason for referral, whether ICU was full or not full at the time of referral, and modified early warning score (MEWS). Others included; whether admitted or not, and if not admitted, reasons for admission refusal. Binomial logistic regression analysis was used to determine predictors of ICU admission refusal. Results: Patients admitted and those denied admission were 37(50.7%) and 36(49.3%) respectively. Following univariate analysis, there were no statistical differences in the age and MEWS of patients in the admitted and not admitted groups respectively. Refusal was highest for sepsis (80%) and respiratory failure (71.4%) and lowest for severe head injury (18.2%), no difference was found in the MEWS for patients with sepsis and those with severe head injury. Lack of ICU bed was the only independent predictor of ICU admission refusal. Conclusions: The crude ICU admission refusal rate was 49.3% and unavailability of ICU bed independently predicted ICU admission refusal. To ensure reduction in ICU admission refusals, the ratio of ICU beds over the population must be appropriate.https://www.annalsofafricansurgery.com/factors-associated-with-intensive-cicuadmission refusalbed availability. |
| spellingShingle | Babatunde Ayoade Tosin Olusanya Factors Associated with Intensive Care Unit Admission Refusal The Annals of African Surgery icu admission refusal bed availability. |
| title | Factors Associated with Intensive Care Unit Admission Refusal |
| title_full | Factors Associated with Intensive Care Unit Admission Refusal |
| title_fullStr | Factors Associated with Intensive Care Unit Admission Refusal |
| title_full_unstemmed | Factors Associated with Intensive Care Unit Admission Refusal |
| title_short | Factors Associated with Intensive Care Unit Admission Refusal |
| title_sort | factors associated with intensive care unit admission refusal |
| topic | icu admission refusal bed availability. |
| url | https://www.annalsofafricansurgery.com/factors-associated-with-intensive-c |
| work_keys_str_mv | AT babatundeayoade factorsassociatedwithintensivecareunitadmissionrefusal AT tosinolusanya factorsassociatedwithintensivecareunitadmissionrefusal |