How Information Availability Changes Healthcare Chronicity Management: Findings from a Pilot Case Study

Chronic diseases are a crucial matter for worldwide National Health Systems; they represent one of the first causes of disability, mortality and morbidity, due to their persistency and tendency to develop some degree of disability (WHO, 2013). To ensure the economic and social sustainability of such diseases, new healthcare business models development should be considered. Accordingly, Chronic Diseases Management shows how patients are enabled to actively take part of their healthcare by taking advantage of Internet of Things (IoT) (Batalden et al., 2018). This is particularly highlighted in cardiac chronicity: patients enhance their health status, by increasing the participation level (Osborne et al., 2016) on their care pathway, through telemedicine. Accordingly, the main purpose of this work is to explain how is possible to improve real time medical information exchange between patient and hospital, by using technological infrastructures. Just in time information allows the clinical staff to improve the chronicity management. This means: increasing quality of life for patients, optimisation of hospital workload, cost saving. Design/methodology/approach – It was adopted a pilot case study method (Yin, 2014), classified as “Extreme Case Sampling” (Patton, 2002). Study concerns with the observation of remote management of a group of heart failure (HF) patients that, at moment of discharge, are equipped with: i) electrocardiograph; ii) weight scale; iii) pulse- oximeter; iv) sphygmomanometer. All those medical devices are connected with a mobile transmitter. Thus, according with his/her own clinical protocol, each patient provides both the self-measurement and dispatch of his/her own clinical data. These data are sent on a website platform, where, on a daily basis, cardiology staff check them. Originality/value – The availability of these biomedical parameters allows medical staff to predict patient’s health status evolution. Before a patient’s health condition worsens, a predictive model, based on patients’ co- production and IoT, allows the medical staff to provide a TRIAGE aimed at promptly manage those troubled patients. Preliminary findings show that: i) patients were managed exclusive by telephone contact ii) no HF relapse, iii) no ER transit; iv) none hospitalization. Also a cost saving was observed. Practical implications – Empirical experience demonstrates that possibility to share clinical information might change the traditional paradigm (Cahn, 2000) of service providing. As complexity increases, information requirements increase; thus, managerial approaches to healthcare change. Patient’s participation and IoT technologies become critical drivers in chronicity management sustainability: operative inputs able to enhance also Social Value of services provided.