Real-time Person Identification: History
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Technologies enabling for real-time person identification are largely available and present differences in multiple characteristics. The use of these technologies within healthcare becomes increasingly relevant, for example in the trauma room where a critical situation calls for a real-time overview of attending healthcare worker. In this context, a systematic litterature research was conducted to determine the presently available systems for real-time person identification in healthcare.

  • identification
  • healthcare
  • tracking
  • smartware
  • usability
  • cost
  • response time
  • hygiene
  • privacy
  • data
  • mission-critical

In the critical setting of a trauma team activation, team composition is crucial information that should be accessible at a glance. This calls for a technological solution, which are widely available, that allows access to the whereabouts of personnel. This diversity presents decision makers and users with many choices and considerations. The aim of this review is to give a comprehensive overview of available real-time person identification techniques and their respective characteristics. A systematic literature review was performed to create an overview of identification techniques that have been tested in medical settings or already have been implemented in clinical practice. These techniques have been investigated on a total of seven characteristics: costs, usability, accuracy, response time, hygiene, privacy, and user safety.

  1. Definition

Real-time person identification devices in healthcare

  1. Introduction

Acute trauma care for severely injured patients is performed by a multi-disciplinary team of in-hospital specialists. The team takes care of every major trauma patient presented to a trauma center 24/7 and is activated within minutes after announcement. A trauma team activation is a critical time-sensitive procedure where communication is vital [1,2,3]. Miscommunication is one of the big factors that can lead to an unwanted patient outcome [4,5]. Knowledge of the team composition is the basis for good communication within a team [6]. This is a challenge during acute trauma care, since the team composition differs daily and consists of a variety of disciplines [1,3]. Therefore, the identification of caregivers, to create a real-time overview of, for example, the name and function of the present caregivers at the trauma room would be useful.

Currently there are many techniques allowing for real-time person identification in healthcare [7], defined in this review as being able to identify a person at any given time. These techniques have already been implemented in different parts of the healthcare system, ranging from patient tracking [8] in hospitals to physicians’ attendance [9]. Each technique, from Near-Field Communication (NFC) devices [10] to WiFi based systems [11], has different characteristics that make it suitable or not for specific applications. A project was initiated with the aim to design a system that would allow a real-time overview of present healthcare workers and team completeness during a trauma team activation. To achieve this design, a system to identify healthcare workers had to be chosen. This systematic literature review was performed to support the choice of such a system. In this trauma setting, where everything is mission critical, costs, accuracy, and speed are essential characteristics. Furthermore, the usability of the technologies is a context-specific aspect that has to be accounted for [12]. Many of these different characteristics have been investigated for the currently existing technologies. The diversity of the available technologies together with the number of aspects that have to be accounted for calls for a comprehensive overview. The aim of this qualitative systematic review is to assess the different types of real-time person identification available in healthcare and investigate their characteristics regarding costs, usability, accuracy, response time, hygiene, privacy, and user safety.

  1. Data, Model, Applications and Influences

Details about which area the research applies to or what kind of problems it can solve. Your insights, or hypotheses if necessary, regarding the research are also welcomed.

This entry is adapted from the peer-reviewed paper 10.3390/s20143937

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