Design of RFID based the Patient Management and Tracking System in hospital

The Development of an RFID Solution to Facilitate the Traceability of Patient and Pharmaceutical Data

One of the principal objectives of hospitals is to increase the quality of care of the patient. This is even more of a priority in Day Hospitals where certain medication requires special attention, from its preparation in the Pharmacy service to its delivery to the patient in the Day Hospital. In the case of expensive medicines, nursing staff have to comply with very detailed instructions in their administration to the patient (name of medicine, route, dosage, schedule, previous medication, conditions of conservation, etc.). This work focuses on the development of a multi-faceted hub application to facilitate the traceability of mixed intravenous medication from the beginning to the end of the process of prescription-validation-dosing-preparation-administration (PVD-PA) and be available to all health professionals involved: doctors, pharmacists, and the nursing staff of the Hospital Pharmacy and Day Hospital.

UHF wearable battery free sensor module for activity and falling detection

Falling is one of the most serious medical and social problems in aging population. Therefore taking care of the elderly by detecting activity and falling for preventing and mitigating the injuries caused by falls needs to be concerned. This study proposes a wearable, wireless, battery free ultra-high frequency (UHF) smart sensor tag module for falling and activity detection. The proposed tag is powered by UHF RF wave from reader and read by a standard UHF Electronic Product Code (EPC) Class-1 Generation-2 reader. The battery free sensor module could improve the wearability of the wireless device. The combination of accelerometer signal and received signal strength indication (RSSI) from a reader in the passive smart sensor tag detect the activity and falling of the elderly very successfully. The fabricated smart sensor tag module has an operating range of up to 2.5m and conducting in real-time activity and falling detection.

Sensor-enabled RFID system for monitoring arm activity: reliability and validity

After stroke, capacity to complete tasks in the treatment setting with the more-affected arm is an unreliable index of actual use of that extremity in daily life. Available objective methods for monitoring real-world arm use rely on placing movement sensors on patients. These methods provide information on amount but not type of arm activity, e.g., functional versus nonfunctional movement. This paper presents an approach that places sensors on patients and household objects, overcoming this limitation. An accelerometer and the transmitter component of a radio-frequency proximity sensor are attached to objects; the receiver component is attached to the arm of interest. The receiver triggers an on-board radio-frequency identification tag to signal proximity when that arm is within 23 cm of an instrumented object. In benchmark testing, this system detected perfectly which arm was used to move the target object on 200 trials. In a laboratory study with 35 undergraduates, increasing the amount of time target objects were moved with the arm of interest resulted in a corresponding increase in system output . Moreover, measurement error was low ( ≤ 2.5%). The results support this system's reliability and validity in individuals with unimpaired movement; testing is now warranted in stroke patients.

Application of RFID technology in patient tracking and medication traceability in emergency care

One of the most important factors that directly affects the quality of health care is patient safety. Minimize the occurrence of adverse events is one of the main challenges for health professionals. This requires continuous tracking of the patient by different areas and services, a process known as traceability and proper patient identification and medication prescribed. This article presents an information system for patient tracking and drugs developed for the Emergency Department of Hospital A Coruña. The systems use RFID technology to perform various tasks: (1) locate patients in different areas; (2) measure patient care times and waiting times; (3) identify unitary doses of medication; and (4) ensure the correct matching between the patient and the medication prescribed by the doctor. The hardware infrastructure as well as the optimal configuration of devices interconnected via a wireless network was determined by conducting a detailed coverage study. To support all the functionality needed, specific tools were designed and integrated with proprietary software applications. The RFID system was evaluated positively by staff from different professional profiles involved in its development or subsequent implementation.

Application of RFID technology in patient tracking and medication traceability in emergency care

One of the most important factors that directly affects the quality of health care is patient safety. Minimize the occurrence of adverse events is one of the main challenges for health professionals. This requires continuous tracking of the patient by different areas and services, a process known as traceability and proper patient identification and medication prescribed. This article presents an information system for patient tracking and drugs developed for the Emergency Department of Hospital A Coruña. The systems use RFID technology to perform various tasks: (1) locate patients in different areas; (2) measure patient care times and waiting times; (3) identify unitary doses of medication; and (4) ensure the correct matching between the patient and the medication prescribed by the doctor. The hardware infrastructure as well as the optimal configuration of devices interconnected via a wireless network was determined by conducting a detailed coverage study. To support all the functionality needed, specific tools were designed and integrated with proprietary software applications. The RFID system was evaluated positively by staff from different professional profiles involved in its development or subsequent implementation.

Sensor-enabled RFID system for monitoring arm activity in daily life

After stroke, capacity to carry out tasks in the treatment setting with the more-affected arm is a poor index of actual use of that extremity in daily life. However, objective methods currently available for monitoring real-world upper-extremity use only provide information on amount of activity. These methods, which rely on movement sensors worn by patients, do not provide information about type of activity (e.g., functional vs. nonfunctional movement). The benchmark testing reported here evaluated an approach that involves placing sensors on patients and objects. An accelerometer and the transmitter component of a prototype radio frequency proximity sensor were attached to household objects. The receiver component was placed on the experimenter's right arm. This device triggered an on-board radio frequency identification tag to signal proximity when that arm was within 23 cm of the objects. The system detected > 99% of 6 cm or greater movements of objects. When handling of objects by the right or left arm was determined randomly, 100% of right arm trials were detected. No signals were recorded when objects were at rest or moved by the left arm. Testing of this approach, which monitors manipulation of objects (i.e., functional movement), is now warranted in stroke patients.

Understanding performance and behavior of tightly coupled outpatient systems using RFID: initial experience

Understanding how clinical systems actually behave in an era of limited medical resources is critical. The purpose of this study was to determine if a radiofrequency-identification-based indoor positioning system (IPS) could objectively and unobtrusively capture outpatient clinic behavior. Primary outcomes were flowtime, wait time and patient/clinician face time. Two contrasting clinics were evaluated: a primary care clinic (PC) with templated scheduling and an urgent care clinic (UC) with unconstrained visit time and first-in, first-out scheduling. All staff wore transponders throughout the study period. Patients carried transponders from check in to check out. All patients and staff were allowed to opt out. The study was approved by hospital IRB. Standard descriptive and analytic statistical methods were used. Five hundred twenty-six patients (309 patients (PC), 217 patients (UC)) and 38 clinicians (eight (PC) and 30 (UC)) volunteered between April 30 and July 1, 2008. Total FT was not significantly different across clinics. PC wait time was significantly shorter (7.6 min [SD 15.8]) vs. UC (19.7 min [SD 25.3], p < 0.0001), and PC Face time was significantly longer (29.9 min, [SD 19.1] vs. UC (9.8 min [SD 8.5], p < 0.0001). PC Face time distributions reflected template scheduling structure. In contrast, face time distributions in UC had a smooth log normal distribution with a lower mean value. Our study seems to indicate that an IPS can successfully measure important clinic process measures in live clinical outpatient settings and capture behavioral differences across different outpatient organizational structures.