Reasons for prolonged hospital stay

Rosenfeld, Leonard S.; Goldmann, Franz; Kaprio, Leo A.

doi:10.1016/0021-9681(57)90048-6

Cited by 21 publications

(5 citation statements)

References 8 publications

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“…This could be because most people still pay out of pocket for health care services in Nigeria. This 11,12 finding is at variance with other studies. only 3% of Nigerians are covered by the health insurance scheme despite the extension of its selective coverage to universal coverage.…”

Section: Discussioncontrasting

confidence: 70%

Factors that contribute to prolonged hospital stay after discharge among surgical patients in a tertiary hospital in North Central Nigeria

Akhiwu,

AKHIWU,

NJEM

et al. 2024

N.D.J

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Background: Surgical practice has hospitalization of patients for surgery and treatment as an inherent part of it; after which the patients are found fit for discharge. There is however a group of patients who remain on bed even after they have been deemed fit for discharge. This study aimed to determine the number of days surgical patients classified as having prolonged stay remain in hospital after they were deemed fit for discharge and identify the reasons for this. Methods: Surgical patients still on bed more than 48 hours after they were discharged who consented to participate in the study were recruited. Results: A total of 341 patients were recruited. The mean duration of stay after discharge was 17.6± 13 days. The specialty with the highest number of patients was Neurosurgery. Lack of finance and absence of a caregiver were the causes (96.5% and 3.5% respectively). The top three suggestions by patients on how to reduce prolonged hospital stay were bill waiver for indigent patients, reduced cost of health care services and financial aid by philanthropists. Conclusion: The mean number of days patient remained in hospital after discharge was 17.6 days. Financial reasons and absence of a caregiver are the major reasons for prolonged hospital stay. There is a need for a multi-sectoral approach to improve enrollment in the National Health Insurance Scheme and provide social support for patients in need of care post-discharge to reduce the adverse effects of prolonged hospital stay on the hospital and patients.

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Section: Discussioncontrasting

confidence: 70%

Factors that contribute to prolonged hospital stay after discharge among surgical patients in a tertiary hospital in North Central Nigeria

Akhiwu,

AKHIWU,

NJEM

et al. 2024

N.D.J

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“…Inpatient LOS is associated with quality but can be a challenging metric to evaluate due to the influence of non-clinical factors. 24 25 COVID-19 also has a highly variable disease course, 26 27 where many comorbidities are associated with worse outcomes. 28 29 This heterogeneity is evident by the wide range and skew of observed gLOS and LOS ( Table 2 and Supplementary Appendix Fig.…”

Section: Discussionmentioning

confidence: 99%

Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial

et al. 2022

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Background We previously developed and validated a predictive model to help clinicians identify hospitalized adults with coronavirus disease 2019 (COVID-19) who may be ready for discharge given their low risk of adverse events. Whether this algorithm can prompt more timely discharge for stable patients in practice is unknown. Objectives The aim of the study is to estimate the effect of displaying risk scores on length of stay (LOS). Methods We integrated model output into the electronic health record (EHR) at four hospitals in one health system by displaying a green/orange/red score indicating low/moderate/high-risk in a patient list column and a larger COVID-19 summary report visible for each patient. Display of the score was pseudo-randomized 1:1 into intervention and control arms using a patient identifier passed to the model execution code. Intervention effect was assessed by comparing LOS between intervention and control groups. Adverse safety outcomes of death, hospice, and re-presentation were tested separately and as a composite indicator. We tracked adoption and sustained use through daily counts of score displays. Results Enrolling 1,010 patients from May 15, 2020 to December 7, 2020, the trial found no detectable difference in LOS. The intervention had no impact on safety indicators of death, hospice or re-presentation after discharge. The scores were displayed consistently throughout the study period but the study lacks a causally linked process measure of provider actions based on the score. Secondary analysis revealed complex dynamics in LOS temporally, by primary symptom, and hospital location. Conclusion An AI-based COVID-19 risk score displayed passively to clinicians during routine care of hospitalized adults with COVID-19 was safe but had no detectable impact on LOS. Health technology challenges such as insufficient adoption, nonuniform use, and provider trust compounded with temporal factors of the COVID-19 pandemic may have contributed to the null result. Trial registration ClinicalTrials.gov identifier: NCT04570488.

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“…Early in the review period, literature was searched for reports of similar studies, with special attention given to the type of data acquired and the methodology employed in conducting such studies (2)(3)(4)(5). It soon became apparent that the nature and scope of the study of hospitalbased, long-term care units in North Carolina required a new approach and more detailed data.…”

Section: Instrument Developmentmentioning

confidence: 99%

Reasons for prolonged hospital stay

Cited by 21 publications

References 8 publications

Factors that contribute to prolonged hospital stay after discharge among surgical patients in a tertiary hospital in North Central Nigeria

Factors that contribute to prolonged hospital stay after discharge among surgical patients in a tertiary hospital in North Central Nigeria

Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial

Survey Instrument to Study Institutional Care Services for Convalescent and Long-Term Patients

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