Predicting the length of hospital stay of post-acute care patients in Taiwan using the Chinese version of the continuity assessment record and evaluation item set

Abstract

BackgroundThe Chinese version of the Continuity Assessment Record and Evaluation (CARE-C) item set was developed to facilitate the assessment of post-acute care (PAC) patients in Taiwan. Considering that the length of hospital stay (LOS) has a significant effect on the total healthcare cost, determining whether the CARE-C scores could predict the LOS of PAC patients is of great interest to the PAC providers.MethodsThis prospective trial included PAC patients with stroke or central nervous system injuries. The demographic data and CARE-C scores were collected after admission and before discharge. A multivariable stepwise linear regression model was used to identify the predictors of the LOS using age, sex, tube placement status, CARE-C component scores at admission, and score differences between admission and discharge as independent variables.ResultsThis study included 178 patients (66 women and 112 men), with a mean age of 61.9 ± 15.6 years. Indwelling urinary catheter placement status at admission (β = 0.241, p = 0.002) was a positive predictor of the LOS, whereas age (β = −0.189, p = 0.010), core transfer subscale score at admission (β = −0.176, p = 0.020), and difference in continence subscale score (β = −0.203, p = 0.008) were negative predictors of the LOS. The model explained 14% of the total variance.ConclusionsIndwelling urinary catheter placement status at admission, age, core transfer subscale score at admission, and difference in the CARE-C continence subscale score were identified as predictors of the LOS. The explanatory power of these predictors might be limited due to the regulations of Taiwan’s National Health Insurance.

Combining Procalcitonin and Rapid Multiplex Respiratory Virus Testing for Antibiotic Stewardship in Older Adult Patients With Severe Acute Respiratory Infection

“…The long hospitalization duration in our study was due to old age, severe illness, and low hospitalization cost. 33,34 Lastly, the incidence of various respiratory viruses may have varied across the 2 seasons of the study period. The strengths of our study include the older adult population, the twin-center prospective cohort design, the simple antibiotic stewardship algorithm, and the comparison to a PS-matched cohort.…”

Influence of Cognition on Length of Stay and Rehospitalization in Older Veterans Admitted for Post-Acute Care

“…After controlling for age, medical, and functional characteristics, cognitive function significantly predicted both CLC-PAC LOS and rehospitalization rates. These results make an important contribution to the post-acute rehospitalization literature (e.g., Burke et al, 2016;Hung et al, 2017;Poynter et al, 2011;Seematter-Bagnoud, Martin, & Büla, 2012), highlighting that the identification of cognitive impairment on admission to PAC can influence rehabilitation outcomes and transitions of care.…”

“…However, most of this work has focused on non-PAC settings (Campbell et al, 2004;Furlanetto, da Silva, & Bueno, 2003) or specific reasons for admission to PAC, such as hip fracture (Seematter-Bagnoud, Frascarolo, & Bula, 2018) or stroke (Galski, Bruno, Zorowitz, & Walker, 1993). To our knowledge, only three studies have examined cognitive function as a predictor of PAC LOS (e.g., Hung et al, 2017;Poynter, Kwan, Sayer, & Vassallo, 2011;Seematter-Bagnoud, Martin, & Büla, 2012), and these studies have been limited to using mental status screening measures (e.g., Mini-Mental State Exam, MMSE;Folstein, Folstein, & McHugh, 1975).…”

Reliability and validity of the Mandarin version of the Continuity Assessment Record and Evaluation for older people who are transferred between hospitals and nursing homes in China

“…A Taiwanese version of CARE was developed for use among patients who had suffered a stroke in 2015. This instrument shows good reliability and validity (Chang et al, ) and successfully predicts the length of the hospital stay (Hung, Wu, Chang, Wang, & Han, ). However, it only contains 52 items and focuses on an evaluation of functional quality metrics in the stroke population.…”