Date of Award

1-1-2003

Degree Type

Thesis

Degree Name

Master of Health Science

Faculty

Faculty of Computing, Health and Science

First Advisor

Dr Gavin Leslie

Abstract

Introduction - Maximising efficient and effective use of resources without compromising quality of care is essential in the current healthcare climate. Intensive care unit services are one of the most resource intensive and therefore expensive services within a hospital. Because intensive care unit services comprise a significant portion of hospital costs and resources, appropriate utilisation of intensive care units is imperative. The occurrence of delayed discharges and the reason for the delays is important as they impact on the efficiency and effectiveness of intensive care unit services. Patients who no longer need intensive care unit care block beds for impending admissions, unnecessarily utilise the costly and often scarce resources and by remaining in a stressful environment may experience negative psychological and social effects detrimental to their well being. Study objectives - To determine to what extent delayed discharge from the intensive care unit occurs and ascertain the reasons for these delays. Design - A prospective cross sectional design to determine the number of delayed discharges from the intensive care unit and reasons causing the delay. A discharge was considered to be delayed if the patient was not discharged from the intensive care unit within 8 hours of being deemed suitable for discharge by intensive care unit medical staff. Setting - A level III intensive care unit with 22 beds (12 general and 10 surgical beds in 2 adjacent areas) in a metropolitan tertiary teaching hospital of 955 beds located across two campuses. Sample - A prospective convenience sample of consecutive patients admitted over a 6-month period from September 2000 to March 2001. Exclusions were patients who died whilst in the intensive care unit and those patients who could be discharged prior to commencement of the study. Method. - Intensive care unit medical staff informed nursing shift coordinators when patients could be discharged. The nursing shift coordinators completed the data collection tool on all patients discharged from intensive care unit. Admission and discharge times and APACHE-11 data (a predictive scoring system for ICU patient outcome) were recorded from intensive care unit records. Results - There were 652 discharges, 468 patients were not delayed (71.8%), 176 were delayed (27.0%, 95% CI 23,9%-30.7%) and 8 (1.2%) patients had no delay information available. There were substantial delays in discharging patients from the intensive care unit; for every 5 discharges that were not delayed, 2 patients would be delayed. Unavailable ward beds (81 %) were cited as the main reason for delay in discharge. Delay time from the intensive care unit ranged from 0.2 hours (1 0 minutes) to 617.5 hours (3 weeks, 4 days, 17.5 hours). Mean delay time was 42 hours (I day, 18 hours) and median delay time 21.3 hours. There was a statistical significance difference between-non delayed and delayed patients for APACHE II score on admission (Ɩ = -3.824 {642), p <0.0001) and worst APACHE 11 score in first 24 hours e (Ɩ = -5.123 (642), p <0.0001 ). There was also a statistically significant difference between delay from the intensive care unit and non delayed discharge by admitting diagnosis (Chi sq (12) = 43.235, p < 0.0001); primary organ system failure (chi sq (6) = 14.231, p = 0.027); ward destination (chi sq (7) = -51.486, p < 0.0001 ); specialty (chi sq (23) = -43.371, p = 0.006) and day of eligible discharge (chi sq (6) = 34.008; p < 0.0001 ). Conclusion - Discharge from the intensive care unit is delayed on average by 27% in the study hospital. These delays can be related to how sick the patient was, principle admitting diagnosis, discharge destination and weekend discharge. Reducing these delays would free up beds for other admissions, may result in a cost saving for the health care facility through more efficient resource utilisation and ultimately benefit patients by better managing the discharge process.

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