Affiliation:
1. Laboratory of Studies and Evidence Based Nursing, Department of Medicine, University of Padua, 35131 Padua, Italy
Abstract
Among hospitalised patients, functional decline and increased dependence on others are common health problems. Identifying critical needs is an important starting point to empower patients to improve their own health and behaviour. Once these needs are determined, the most relevant goals for addressing patients’ needs and health potential can be established. This study aimed to test a model for profiling patients using the General Assessment of Hospitalised Patients (ASGO) compared to the Barthel Index (BI) as the gold standard. A retrospective approach was conducted by reviewing administrative data recorded between 2017 and 2020 at the University of Padova, Italy. Data from patients (a) older than 18 years, (b) admitted to a local hospital, and (c) with a stay of at least three days were included in the study. The ASGO and the BI were both used on patients’ admission and discharge from the ward. Data were analysed using STATA software (v.16) (StataCorp. 2019. Stata Statistical Software: Release 16. College Station, TX: StataCorp LLC). The database used for the analysis consisted of 842 patient records, with more than 50% over 75 years of age and consisting mainly of men. The results of the ASGO and the BI were more correlated at discharge (rho = −0.79) than at admission (rho = −0.59). Furthermore, sensitivity and specificity, calculated with reference to the optimal cut-off point (Youden index), demonstrated the highest reliability of the test at discharge (sensitivity: 0.87; specificity: 0.78) compared to admission (sensitivity: 0.77; specificity: 0.72). This result was confirmed by the analysis of the ROC curve: The area under the curve was greater at discharge (89%) than at admission (82%). Analysis of the results obtained from assessments created with the ASGO demonstrates the applicability of this model in the context of hospital care and how well it can represent functional dependence. This study was not registered.
Reference24 articles.
1. Ocagli, H., Lanera, C., Lorenzoni, G., Prosepe, I., Azzolina, D., Bortolotto, S., Stivanello, L., Degan, M., and Gregori, D. (2020). Profiling Patients by Intensity of Nursing Care: An Operative Approach Using Machine Learning. J. Pers. Med., 10.
2. Salvatore, F.P., and Fanelli, S. (2020). Patient-Related Complexity of Care in Healthcare Organizations: A Management and Evaluation Model. Int. J. Environ. Res. Public Health, 17.
3. Parreira, P., Santos-Costa, P., Neri, M., Marques, A., Queiros, P., and Salgueiro-Oliveira, A. (2021). Work Methods for Nursing Care Delivery. Int. J. Environ. Res. Public Health, 18.
4. Use of Functional Assessment to Define Therapeutic Goals and Treatment;High;J. Am. Geriatr. Soc.,2019
5. Assessment tools to evaluate Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL) in older adults: A systematic review;Pashmdarfard;Med. J. Islam. Repub. Iran,2020