Competing risks modeling of length of hospital stay enhances risk-stratification of patient care: application to under-five children hospitalized in Malawi.

Cox proportional hazards Kaplan-Meier curve Malawi competing risks hospital stay modeling

Journal

Frontiers in epidemiology
ISSN: 2674-1199
Titre abrégé: Front Epidemiol
Pays: Switzerland
ID NLM: 9918419158106676

Informations de publication

Date de publication:
2023
Historique:
received: 08 08 2023
accepted: 26 10 2023
medline: 8 3 2024
pubmed: 8 3 2024
entrez: 8 3 2024
Statut: epublish

Résumé

Length of hospital stay (LOS), defined as the time from inpatient admission to discharge, death, referral, or abscondment, is one of the key indicators of quality in patient care. Reduced LOS lowers health care expenditure and minimizes the chance of in-hospital acquired infections. Conventional methods for estimating LOS such as the Kaplan-Meier survival curve and the Cox proportional hazards regression for time to discharge cannot account for competing risks such as death, referral, and abscondment. This study applied competing risk methods to investigate factors important for risk-stratifying patients based on LOS in order to enhance patient care. This study analyzed data from ongoing safety surveillance of the malaria vaccine implementation program in Malawi's four district hospitals of Balaka, Machinga, Mchinji, and Ntchisi. Children aged 1-59 months who were hospitalized (spending at least one night in hospital) with a medical illness were consecutively enrolled between 1 November 2019 and 31 July 2021. Sub-distribution-hazard (SDH) ratios for the cumulative incidence of discharge were estimated using the Fine-Gray competing risk model. Among the 15,463 children hospitalized, 8,607 (55.7%) were male and 6,856 (44.3%) were female. The median age was 22 months [interquartile range (IQR): 12-33 months]. The cumulative incidence of discharge was 40% lower among HIV-positive children compared to HIV-negative (sub-distribution-hazard ratio [SDHR]: 0.60; [95% CI: 0.46-0.76]; This study applied the Fine-Gray competing risk approach to more accurately model LOS as the time to discharge when there were significant rates of in-hospital mortality, referrals, and abscondment. Patient care can be enhanced by risk-stratifying by LOS based on children's age, HIV status, diagnosis, and nutritional status.

Identifiants

pubmed: 38455913
doi: 10.3389/fepid.2023.1274776
pmc: PMC10911049
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1274776

Informations de copyright

© 2023 Stanley, Zulu, Msuku, Phiri, Kazembe, Chinkhumba, Mvalo and Mathanga.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors TM, LK declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Auteurs

Christopher C Stanley (CC)

MAC-Communicable Diseases Action Centre, Kamuzu University of Health Sciences, Blantyre, Malawi.
School of Global and Public Health, Kamuzu University of Health Sciences, Blantyre, Malawi.

Madalitso Zulu (M)

University of North Carolina Project Malawi, Lilongwe, Malawi.

Harrison Msuku (H)

MAC-Communicable Diseases Action Centre, Kamuzu University of Health Sciences, Blantyre, Malawi.

Vincent S Phiri (VS)

School of Global and Public Health, Kamuzu University of Health Sciences, Blantyre, Malawi.

Lawrence N Kazembe (LN)

Department of Computing, Mathematical and Statistical Sciences, University of Namibia, Windhoek, Namibia.

Jobiba Chinkhumba (J)

MAC-Communicable Diseases Action Centre, Kamuzu University of Health Sciences, Blantyre, Malawi.
School of Global and Public Health, Kamuzu University of Health Sciences, Blantyre, Malawi.

Tisungane Mvalo (T)

University of North Carolina Project Malawi, Lilongwe, Malawi.
Department of Pediatrics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.

Don P Mathanga (DP)

MAC-Communicable Diseases Action Centre, Kamuzu University of Health Sciences, Blantyre, Malawi.
School of Global and Public Health, Kamuzu University of Health Sciences, Blantyre, Malawi.

Classifications MeSH