Emanuele Porazzi

Il decentramento del follow-up dei pazienti fragili con dolore cronico dalle strutture ospedaliere alle Case della Comunità rappresenta una risposta organizzativa alla crescente pressione assistenziale legata all'invecchiamento della popolazione e all'aumento delle cronicità. Presso ASST Ovest Milanese viene proposto un modello hub&spoke territoriale basato su un impiego ad isorisorse del medico di équipe e dell'infermiere di famiglia e di comunità (IFeC), finalizzato a trasferire in setting territoriali i controlli di pazienti clinicamente stabili. Nel 2025 l'ambulatorio di Terapia del Dolore di Cuggiono ha erogato 11.229 prestazioni totali, di cui 5.919 visite anestesiologiche/algologiche di controllo; 4.449 di queste hanno riguardato pazienti over 65. Il modello mira a migliorare appropriatezza, prossimità delle cure e continuità assistenziale, liberando almeno il 5% degli slot ambulatoriali ospedalieri per prestazioni a maggiore complessità e riducendo i costi sociali legati agli spostamenti di pazienti e caregiver. La proposta prevede una fase preliminare di screening di sei mesi per identificare i pazienti eleggibili, formazione dedicata degli IFeC, protocolli operativi condivisi e monitoraggio tramite indicatori di processo ed esito. L'iniziativa configura un modello replicabile di innovazione organizzativa territoriale, coerente con il DM 77/2022 e con l'evoluzione del ruolo infermieristico nella gestione della cronicità.

I n the current healthcare setting, challenges related to increasing demand for care, scarcity of resources, and the need to ensure high quality standards require a rethinking of organizational and management models. The introduction of advanced methodologies such as Lean Management and Operational Excellence offers concrete tools to optimize processes, reduce waste and make the most of available resources, with the support of organizational change and training initiatives to ensure their effective adoption. The article presents a practical overview of these methodologies, highlighting how they can facilitate the transformation of healthcare processes.

Purpose: The aim of the paper is to support the improvement of the design and management of distribution processes of health technologies, evaluating performance to understand the aspects of the service that affect the level of patient satisfaction, considering a real-life healthcare service (the absorbent devices for incontinence in the Piedmont Region (Italy)).
Methods: The following quantitative data were collected, with reference to the year 2020: (i) number of patients; (ii) volume of delivered devices; (iii) total costs of delivered absorbent. Authors also designed an on-line survey to gather patient perceptions about the organization of distribution of health technologies and related models.
Results: The results showed that the cost of devices per patient was higher than about 40% in the mixed distribution model (i.e. the coexistence of home delivery regulated by regional tender and distribution through territorial pharmacies/private shops regulated by convention regimen), but a greater number of devices are supplied to incontinence patients in that model. The results of the survey (721 respondents) about the level of satisfaction of the adopted distribution models demonstrated a general satisfaction with the organization of the service, although the mixed model seemed to be more appreciated.
Conclusions: A contribution of this manuscript was to investigate the topic of quality of care in the primary care setting, which was a research area that had received scarce attention until now, but as important for the future sustainability of healthcare system.

Digital healthcare is revolutionizing the way healthcare services are delivered, managed and distributed. In order to draw an overview of the Italian healthcare situation with respect to the role of operational management and the degree to which AI systems are used for management purposes, a questionnaire was conducted in collaboration with the Italian Association of Management Engineers in Healthcare and the Healthcare Data Science LAB of Carlo Cattaneo University - LIUC in Castellanza (VA).