Validation of Intelligent Patient Flow Management System in Kuopio University Hospital Emergency Department

1. Background

Continuous development of digital technology provides new opportunities also in healthcare area. As healthcare costs are constantly growing both worldwide and in Finland (1), innovations are needed to enhance allocation of limited healthcare resources and to reduce economic burden. Digital health technologies (DHT) have the potential to reduce these costs. They are increasingly developed to support healthcare systems around the world. DHT are, however, often lacking evidence-based medicine (2) and both the importance and the lack of their validation has been acknowledged widely (3, 4).

Work in triage and urgent care centers is highly demanding, with considerable time pressure. When operating with high patient volumes, acute conditions and severe stress, human errors are likely to result at least at some extent. Physicians have been found to have a ~5 % diagnostic error rate (5) with half of these potentially harmful (6). DHT have been suggested to have a significant role helping both patient management and triage (7), and thus, reducing also potential human errors. For instance, crude online clinical decision support tool has been found to reliably demonstrate emergency triage severity in experimental setting (7).

The validation of DHT and decision support tools is highly crucial. Tools with false negative rates could have serious consequences when ignoring severe conditions such as cardiac ischaemia (4). DHT should be thorough and optimal in the medical field and their internal and external validity should have been evaluated. Recently, guidelines for evaluating DHT have been published (4). According to guidelines, the first step in the assessment is to show the results in an early observational study in clinical setting. In addition to safety, also efficacy and effectiveness of DHT should be evaluated.

To meet these needs, Intelligent Patient Flow Management system (IPFM) has been developed to help the user (i.e. patient) and the healthcare professionals to evaluate user's condition and its severity. IPFM enables semi-automated triaging of patients and enhances the management of patient inflow and demand. In addition, IPFM provides written and precise information for the healthcare professionals communicated by the patients themselves of their conditions and symptoms. The core of IPFM is a broad medical database generated by medical doctors, combined with artificial intelligence (AI) and feedback loops for accuracy improvement. In other words, IPFM is an AI-induced triage and decision support tool developed and monitored by medical doctors to help healthcare professionals to evaluate the urgency of the patients. It evaluates user's condition and infers the urgency using user demographics, background information and symptoms.