Unsupervised Learning AI Algorithm-Data Management and Improved Lean Methodology in Healthcare Organizations

In the following article, we apply a set of machine learning algorithms to analyse a set of445 Californian Hospitals. We investigate a variable that can be considered as a synthesisof the economic, financial and organizational performance of the hospital i.e. Net Income.First of all, we have applied a regression analysis with OLS-Ordinary Least Squares to verifythe presence of significant relationships among the variables in respect to Net Income.Furthermore, we have applied the k-Means algorithm optimized with the Elbow Method toverify the presence of groups of hospitals in the dataset based on more than 200 variablesand centred on Net Income. Finally, we propose a comparison among eight differentmachine-learning algorithms to estimate the future value of Net Income based on anhistorical series in the period 2014-2018.Our idea is that the area of inefficiency that are showed thanks to the regression analysiscan be optimized with the application of AI and Lean Management. Specifically, theefficiency of hospitals to manage human resources and specifically physicians can be improved with the application of telemedicine and organizational tools, that can increaseeither the performance of the hospital and the level of care offered to patients.The mix of Artificial Intelligence and Lean Management can promote better models inhealthcare, reducing costs, improving the quality of services, increasing the level of humanresources especially physicians, to create a more sustainable and reliable healthcaresystem.