TY - JOUR
T1 - Organisation, staffing and resources of critical care units in Kenya
AU - Kenya Critical Care Registry Investigators
AU - Mwangi, Wambui
AU - Kaddu, Ronnie
AU - Muiru, Carolyne Njoki
AU - Simiyu, Nabukwangwa
AU - Patel, Vishal
AU - Sulemanji, Demet
AU - Otieno, Dorothy
AU - Okelo, Stephen
AU - Chikophe, Idris
AU - Pisani, Luigi
AU - Dona, Dilanthi Priyadarshani Gamage
AU - Beane, Abi
AU - Haniffa, Rashan
AU - Misango, David
AU - Waweru-Siika, Wangari
AU - Siika, Wangari Waweru
AU - Mwangi, Wambui
AU - Kaddu, Ronnie
AU - Njoki, Carolyne
AU - Simiyu, Nabukwangwa
AU - Sumanji, Demet
AU - Chikophe, Idris
AU - Misango, David
AU - Otieno, Dorothy
AU - Thaddeus, Teddy
AU - Wangechi, Patricia
AU - Mutuku, Selina
AU - Kabanya, Thomas
AU - Kioko, Annastacia
AU - Okelo, Stephen
AU - Mburu, Peter
N1 - Publisher Copyright:
© 2023 Mwangi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2023/7
Y1 - 2023/7
N2 - Objective To describe the organisation, staffing patterns and resources available in critical care units in Kenya. The secondary objective was to explore variations between units in the public and private sectors. Materials and methods An online cross-sectional survey was used to collect data on organisational characteristics (model of care, type of unit, quality- related activities, use of electronic medical records and participation in the national ICU registry), staffing and available resources for monitoring, ventilation and general critical care. Results The survey included 60 of 75 identified units (80% response rate), with 43% (n = 23) located in government facilities. A total of 598 critical care beds were reported with a median of 6 beds (interquartile range [IQR] 5–11) per unit, with 26% beds (n = 157) being non functional. The proportion of ICU beds to total hospital beds was 3.8% (IQR 1.9–10.4). Most of the units (80%, n = 48) were mixed/general units with an open model of care (60%, n = 36). Consultants-in-charge were mainly anesthesiologists (69%, n = 37). The nurse-to-bed ratio was predominantly 1:2 with half of the nurses formally trained in critical care. Most units (83%, n = 47) had a dedicated ventilator for each bed, however 63% (n = 39) lacked high flow nasal therapy. While basic multiparametric monitoring was ubiquitous, invasive blood pressure measurement capacity was low (3% of beds, IQR 0–81%), and capnography moderate (31% of beds, IQR 0–77%). Blood gas analysers were widely available (93%, n = 56), with 80% reported as functional. Differences between the public and private sector were narrow. Conclusion This study shows an established critical care network in Kenya, in terms of staffing density, availability of basic monitoring and ventilation resources. The public and private sector are equally represented albeit with modest differences. Potential areas for improvement include training, use of invasive blood pressure and functionality of blood gas analysers.
AB - Objective To describe the organisation, staffing patterns and resources available in critical care units in Kenya. The secondary objective was to explore variations between units in the public and private sectors. Materials and methods An online cross-sectional survey was used to collect data on organisational characteristics (model of care, type of unit, quality- related activities, use of electronic medical records and participation in the national ICU registry), staffing and available resources for monitoring, ventilation and general critical care. Results The survey included 60 of 75 identified units (80% response rate), with 43% (n = 23) located in government facilities. A total of 598 critical care beds were reported with a median of 6 beds (interquartile range [IQR] 5–11) per unit, with 26% beds (n = 157) being non functional. The proportion of ICU beds to total hospital beds was 3.8% (IQR 1.9–10.4). Most of the units (80%, n = 48) were mixed/general units with an open model of care (60%, n = 36). Consultants-in-charge were mainly anesthesiologists (69%, n = 37). The nurse-to-bed ratio was predominantly 1:2 with half of the nurses formally trained in critical care. Most units (83%, n = 47) had a dedicated ventilator for each bed, however 63% (n = 39) lacked high flow nasal therapy. While basic multiparametric monitoring was ubiquitous, invasive blood pressure measurement capacity was low (3% of beds, IQR 0–81%), and capnography moderate (31% of beds, IQR 0–77%). Blood gas analysers were widely available (93%, n = 56), with 80% reported as functional. Differences between the public and private sector were narrow. Conclusion This study shows an established critical care network in Kenya, in terms of staffing density, availability of basic monitoring and ventilation resources. The public and private sector are equally represented albeit with modest differences. Potential areas for improvement include training, use of invasive blood pressure and functionality of blood gas analysers.
UR - http://www.scopus.com/inward/record.url?scp=85165934545&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0284245
DO - 10.1371/journal.pone.0284245
M3 - Article
C2 - 37498872
AN - SCOPUS:85165934545
SN - 1932-6203
VL - 18
JO - PLoS ONE
JF - PLoS ONE
IS - 7 July
M1 - e0284245
ER -