Authors (including presenting author) :
Ma FK(1), Tong HY(1), Shiu LF(1), Mak KM(1), Wong N(1), Mok SS(1), Tsoi YK(1)
Affiliation :
(1) Department of Medicine, Haven of Hope Hospital
Introduction :
From May to September 2023, we found that 28.7% (74 out of 258) of patients transferred from acute hospitals to our ward were eventually discharged to institutions. The average length of stay (ALOS) for patients discharged to institutions was significantly longer than for those discharged to home (31.2 vs 23.7, p = 0.005), and the average search time for an old age home was 15 days. Also, the patient’s family typically relies on the expected discharge date to initiate the discharge planning process. Without an expected discharge date, they are often hesitant to begin planning. Prolonged waiting times for institutional placement caused avoidable delays during hospitalization, which disrupted patient flow and access to care due to bed shortages. These delays also increased the risk of hospital-acquired infections and escalated treatment costs.
Objectives :
1) To shorten ALOS of patients in the Geriatric ward
2) To further shorten ALOS of patients awaiting institutional placement by developing a predictive tool to identify a patient’s need for institutionalization at admission
Methodology :
1) Minimize avoidable delays in waiting for placement: Doctors establish an expected discharge date before the weekly case conference based on nursing admission screening and history taking, particularly for patients who are likely to require institutionalization at discharge or are at risk of prolonged hospital stays due to caregiving challenges. Setting an early discharge date helps align the rehabilitation expectations. Minimizing the waiting time to initiate discharge planning after repeated case conferences. 2) Minimize wasted time and effort in the discharge planning: To create a predictive tool by consolidating a list of factors from existing assessment forms that influence discharge destinations. This tool helps predict a patient’s need for institutionalization at the time of admission, enhancing the value of the admission assessment, facilitating decision-making for discharge planning and minimizing the time for waiting for placement after medically fit for discharge.
Result & Outcome :
The ALOS for patients admitted from May to Aug 2023 decreased from 26.3 days to 21.4 days during the same period in 2024. The ALOS for patients discharged to institutions and home decreased by 14% and 20%, respectively. The preliminary results showed that certain factors can be used to identify a patient's need for institutionalization. Among 283 patients recruited, 94 (33.2%) were discharged from home to an institution, and 105 (37.1%) were discharged back to their home. The analysis identified a statistically significant difference (p < 0.05) in the mean scores of the AMT (Abbreviated Mental Test) and the BI (Barthel Index) between patients discharged to an institution and those discharged to their home (AUC > 0.7). Also, significant associations were observed between discharge destination and factors such as household composition (p = 0.004) and the presence of dementia (p < 0.001). The next step is to consolidate more predictive factors, use ROC to determine AMT and BI cut off point (with AUC > 0.8), and apply logistic regression to integrate all factors and develop a tool for predicting a patient's need for institutionalization upon admission to further reduce ALOS.
