Abstract
Accurate predictions of patient length of stay (LOS) in the hospital can effectively manage hospital resources and increase efficiency of patient care. A study was done to assess emergency medicine physicians' ability of predicting the LOS of patients who enter the hospital through the ER. Results indicate that EM physicians are relatively accurate with their pediatric patients than any other age groups. In addition, as actual hospital LOS increases, the prediction accuracy decreases. Possible reasons may be due increasing medical complications associated with increasing age and this may lead to overall longer stays. Other variables such as the admitted service of the patient are not statistically significant in predicting LOS in this study. Future studies should be done in order to determine other variables that may affect LOS predictions.
Highlights
The ability to reasonably predict the length of stay (LOS) for patients admitted from the emergency department is important in determining and managing healthcare resources
Overall the difference between the two LOS means is statistically significant with a mean difference of −1.76 days (SD ± 7.55 days, 95% CI −2.47 to −1.04) t = 4.82, P < 0.00 (Table 1)
For patients less than 18 years the mean difference was 0.44, (SD 1.67, 95% CI −0.11 to 0.95, upper limit (UL) = 3.71, lower limit (LL) = −2.86), for patients between 18 years and 65 years, the mean difference was −0.21 (SD 2.96, 95% CI −0.59 to 0.17 UL = 5.61, LL = −6.02), and for those over age 65 the mean difference was
Summary
To optimize and effectively address patient care, consistent discrepancies between predicted and actual LOS may strain resources and cause consequences that can burden both the patient and the hospital. Previous efforts have been made to quantify predicted LOS and compare it with the actual patient LOS in specific types of cases such as surgery and trauma. These cases, tend to have proven and well-studied protocols and neural networks that dictate patient flow during admittance while predicting LOS [2]. Data from the psychiatric literature have shown that certain variables available during patient admittance are able to be assessed in predicting patient LOS [3]
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