Earlier diagnosis plays a pivotal role in clinical applications, since it can strongly reduce the incidence and impact of many diseases and, consequently, the reduction of health care costs. This last aspect depends strongly from right therapy prescriptions, especially when there are various opportunities. Within this context, Clinical Decision Support Systems (CDSS) could bring several benefits. In this paper, we propose a CDSS with the aim of improving the clinician practice based on recommendations, assessment of the patient and screening of patients with risk factors to prevent chronic venous insufficiency (CVI) complications. The proposed CDSS is implemented in the Nu.Sa. cloud system, which involves thousands of italian General Practitioners (GPs) collecting data (EHR data, personal data, patient’s medical history) from millions of patients. The proposed architecture is designed to collect data from a distributed scenario where GPs are collecting clinical history and pharmacy or second level hospitals gather data from medical devices connected to the cloud over a standard data architecture. We show that exploiting the integration of the medical device VenoScreen Plus with the patient EHR, this CDSS is capable to improve preventive care, to enhance clinical performance, to influence clinical decision making and to significantly improve the decision quality levering on data driven approach.
Facilitating action planning within audit and feedback interventions: a mixed-methods process evaluation of an action implementation toolbox in intensive care
