Identifying the Drivers of Inter-Regional Patients’ Mobility: An Analysis on Hospital Beds Endowment

Abstract

Background: In a Beveridgean decentralized healthcare system, like the Italian one, where regions are responsible for their own health planning and financing, the analysis of patients’ mobility appears very interesting as it has economic and social implications. The study aims to analyze both patients’ mobility for hospital rehabilitation and if the beds endowment is a driver for these flows; Methods: From 2011 to 2019, admissions data were collected from the Hospital Discharge Cards database of the Italian Ministry of Health, population data from the Italian National Institute of Statistics and data on beds endowment from the Italian Ministry of Health website. To evaluate patients’ mobility, we used Gandy’s Nomogram, while to assess if beds endowments are mobility drivers, we created two matrices, one with attraction indexes (AI) and one with escape indexes (EI). The beds endowment, for each Italian region, was correlated with AI and EI. Spearman’s test was carried out through STATA software; Results: Gandy’s Nomogram showed that only some northern regions had good hospital planning for rehabilitation. A statistically significant correlation between beds endowment and AI was found for four regions and with EI for eight regions; Conclusions: Only some northern regions appear able to satisfy the care needs of their residents, with a positive attractions minus escapes epidemiological balance. The beds endowment seems to be a driver of patients’ mobility, mainly for escapes. Certainly, the search for mobility drivers needs further investigation given the situation in Molise and Basilicata.

Machine Learning for Evaluating Hospital Mobility: An Italian Case Study

“…In this scenario, our study focuses on investigating patient mobility, a crucial aspect that reflects individual choices in accessing hospital care. Recent research has confirmed that the endowment of hospital beds is a determining factor in patient mobility, especially in decentralized healthcare contexts, suggesting a direct area of interest for our work [12].…”

The Relationship Between Static Characteristics of Physicians and Patient Consultation Volume in Internet Hospitals: Quantitative Analysis

“…In comparing patient choice patterns across different health care settings, Ruwaard and Douven’s [ 39 ] study revealed an interesting phenomenon: patients with cataracts tended to choose the most popular institutions when selecting physical hospitals, indicating that digital platform reputation and word of mouth were equally important for internet hospitals. Guarducci et al [ 40 ] emphasized the profound impact of hospital resource allocation on patient mobility, stressing the crucial role of optimizing resources, including physician workforce, technical support, and patient management systems, in enhancing service efficiency and patient satisfaction for internet hospitals [ 40 ]. Therefore, it is imperative for internet hospitals to prioritize patient feedback and service quality improvement to establish a favorable digital reputation.…”