Author:
Scala Arianna,Trunfio Teresa Angela,Improta Giovanni
Abstract
AbstractEffectiveness in health care is a specific characteristic of each intervention and outcome evaluated. Especially with regard to surgical interventions, organization, structure and processes play a key role in determining this parameter. In addition, health care services by definition operate in a context of limited resources, so rationalization of service organization becomes the primary goal for health care management. This aspect becomes even more relevant for those surgical services for which there are high volumes. Therefore, in order to support and optimize the management of patients undergoing surgical procedures, the data analysis could play a significant role. To this end, in this study used different classification algorithms for characterizing the process of patients undergoing surgery for a femoral neck fracture. The models showed significant accuracy with values of 81%, and parameters such as Anaemia and Gender proved to be determined risk factors for the patient’s length of stay. The predictive power of the implemented model is assessed and discussed in view of its capability to support the management and optimisation of the hospitalisation process for femoral neck fracture, and is compared with different model in order to identify the most promising algorithms. In the end, the support of artificial intelligence algorithms laying the basis for building more accurate decision-support tools for healthcare practitioners.
Publisher
Springer Science and Business Media LLC
Reference49 articles.
1. Rossini M, Piscitelli P, Fitto F et al. (2005) Incidenza e costi delle fratture di femore in Italia. Reumatismo.2005; Vol. 57 No. 2, pp. 97–102.
2. Ancona C, Barone AP, Belleudi V et al. Valutazione degli esiti della frattura del femore - Lazio 2005–2007. Programma Regionale di Valutazione degli esiti degli interventi sanitari 2008.
3. Moldovan F. 2023. Bone Cement Implantation Syndrome: A Rare Disaster Following Cemented Hip Arthroplasties—Clinical Considerations Supported by Case Studies. Journal of Personalized Medicine, 13(9), p.1381.
4. De Mast J, Does RJMM, de Koning H. Lean Six Sigma for Service and Healthcare. Alphen aan den RijnBeaumont Quality Publications (2006).
5. Van Den Heuvel J, Does RJMM, De Koning H. Lean six Sigma in a hospital. Int J Six Sigma Compet Adv. 2006;2:377–88. https://doi.org/10.1504/IJSSCA.2006.