Table 1.
Overview of the included articles. Sample size and population refer to the test setting. The used identification technique, its technical specifications, and its application are outlined. /: the scales used for the assessment of quality and bias are described in Appendix B.
| Authors | Year | Design | Sample Size | Sample Characteristics | Quality Assessment a | Bias b | Technique/System | Specifications | Application |
|---|---|---|---|---|---|---|---|---|---|
| Anne et al. [15] | 2020 | Longitudinal study | 8794 | Patients | *** | - | Iris scanner | Binocular iris recognition cameras (SMITech model BMT-20) | Patient identification for routine HIV program data for surveillance |
| Cao et al. [16] | 2014 | Case study | 13 | IT personnel | ** | B | Active RFID tags | Battery-powered fixed receivers; mobile, battery-powered RFID beacons placed on badges | Personnel RTLS |
| Chang et al. [17] | 2011 | Pilot study | n.a. | n.a. | ** | B | Active RFID tags | Four active RFID tags (125 kHz) and two tag readers | Identification of ICU staff to trace contact history of caregivers at the ICU with patients |
| Chen et al. [18] | 2013 | Pilot study | n.a. | n.a. | ** | B | Active RFID tags | Active RFID with far-field communication (UHF 865–928 MHZ) with compact readers | Patient identification for tracking during hospital stay |
| Fisher et al. [19] | 2012 | Qualitative study | 80 interviews and 23 hospitals | Interviews and hospitals | ** | B | RTLS | RFID, WiFi, Wireless Local Area Network (WLAN), Ultra-Wide Band (UWB), infrared (IR), Zig-Bee, Bluetooth, or ultrasound (US) | Patient identification/tracking or personnel tracking in a.o.surgery, delivering medicine, and general hospital setting |
| Frisby et al. [20] | 2016 | Cross-sectional study | n.a. | n.a. | *** | - | Active RFID tags | Active RFID tags on badges (Bluetooth low energy beacon) and Raspberry Pi in rooms | Personnel attendance to patients to compute door to doctor time at the emergency department |
| Hsu et al. [21] | 2016 | Cross-sectional study | 3 per test | 1 patient, 2 healthcare workers | * | A* | Active RFID tags | Active RFID tags with 3 active antennas | Location confirmation by RTLS to authorize X-ray use |
| Jeong et al. [22] | 2017 | Criterion validation study | 25 | 25 neuroscience patients | ** | B | Infrared (IR) transmitting badges | Infrared (IR) transmitting badges that are detected by ceiling sensors | Real-time location tracking for patients during 2 min walking test in the Neuroscience Acute Care/Brain Rescue Unit |
| Jeon et al. [23] | 2019 | Case study | 30 | Patients | *** | B | Face recognition | Self-developed app on smartphone with external database | Patient identification throughout hospital stay |
| Kranzfelder et al. [24] | 2012 | Preclinical evaluation | 6 | 3 surgeons, 3 engineers | ** | B, C* | Active RFID tags | Active RFID transponder badges (2.45 GHz) with three sector antennas and one RFID sector controller | Position monitoring team members in the operating room |
| Lin et al. [25] | 2012 | Case study | 20 | medical staff | ** | B | Active RFID tags | Active RFID tags (433 MHz) in a garment, one active antenna in the room | Personnel count for air filtration optimization in the operating room |
| Liu et al. [26] | 2011 | Pilot study | Test: n.a.; survey: 174 | n.a. 56 surgeons, 41 anesthesia and recovery room nurses, 26 operative room and instrument room nurses, 30 staff of the ED | *** | C* | Active RFID tags | Active RFID wristbands (2.4 GHz) with 80m transmission and RFID readers on the ceilings | Patient identification to control the workflow for surgical patients in the operation theater |
| Odei-Lartey et al. [27] | 2016 | Cross-sectional study | n.a. | n.a. | *** | B | Fingerprint recognition | Hamster plus IV, SecuGen Inc. | Identification and registration of entering patients in a rural African setting. |
| Ohashi et al. [28] | 2010 | Feasibility study | 5 | Nurses and people pretending to be patients | ** | A*, B | Active RFID tags | RFID Power Tag from Matrix Inc. (300 MHz), with a maximum communication distance of 3000 mm | A system using RFID for reducing misidentifications of patients in a smart hospital at the University in Tokyo |
| Pérez et al. [29] | Nov. 2016 | Cross-sectional study | n.a. | n.a. | *** | B | Active RFID tags | WiFi Active Aeroscout T2 | Patient identification throughout hospital for safer medication matching |
| Pérez et al. [30] | Aug. 2016 | Case study | n.a. | n.a. | *** | B | Active RFID tags | WiFi Active Aeroscout tags | Patient tracking through hospital for efficient medication supply and safer medication matching |
| Pineles et al. [31] | 2014 | Pilot study | n.a. | n.a. | ** | B, C | Active RFID tags | Active RFID badges | Presence detection in front of soap dispenser |
| Polycarpou et al. [32] | 2012 | Observational study | n.a. | Patients in the ward | ** | B | Active RFID tags | Class 1 Generation 2 USB stick-like UHF RFID badges and wristbands | Patient identification in a hospital environment |
| Saito et al. [33] | 2013 | Case study | 20 tests with 1–4 users | Lab personnel | * | A*, B, C* | RFID | RFID tags (953 MHz UHF) in a garment combined with one active antenna per room | Presence detection in the lab |
| Steffen et al. [34] | 2010 | Cross-sectional study | n.a. | volunteers | ** | A*, B, C | Passive RFID tags | Copper etched and aluminum etched RFID tags | Identification of patients after MRI or CT scanning |
| Ting et al. [35] | 2011 | Exploratory case study | Test: 10; survey: unknown | None | ** | A*, B | RFID | n.a. | Implementation of RFID with a patient identification system in a healthcare company |
| Wall et al. [36] | 2015 | Cross-sectional study | 120, 42 | Staff members, female sex workers | ** | B, C | Fingerprint recognition | n.a. | Identification of female sex workers for HIV treatment |
| White at al. [37] | 2018 | Parallel, convergent study | 919 | Patients | *** | B | Fingerprint reader | Optical fingerprint reader | Patient identification in a tuberculosis clinic |