Patient Tracking System Research Articles

Frequencies and causes of ABO-incompatible red cell transfusions in France, Germany and the United Kingdom.

Prevention of ABO-incompatible red cell transfusions (ABO-it) requires accurate donor and patient identification and correct application of processes for transfusion safety. In France and Germany, a bedside identity check and ABO compatibility test are performed. In the UK, an identity check, often structured as a bedside checklist, is performed with or without electronic patient identification (ePID). To compare the efficacy of ABO-it bedside preventive measures, frequencies and causes of ABO-it between 2013 and 2022 were investigated in all three countries. Despite differing bedside safety measures, similar average ABO-it frequencies were observed in France (0.19 [SD:0.09]/100 000 issued red cell units) and in the UK (0.28 [SD:0.17]/100 000), whereas a higher frequency (0.71 [SD:0.23]/100 000) was observed in Germany which has similar bedside safety measures to France. ABO-it resulted mostly from erroneous patient identification and transfusion of a red cell unit intended for another patient. In France and Germany, all ABO-it were associated with incorrectly performed identity check and ABO compatibility test. In the UK, most ABO-it were associated with incorrectly performed identity checks. Current measures to prevent ABO-it are not fully effective. Further development and implementation of effective patient identification systems, including electronic information systems, across the entire transfusion process, should be considered.

Implementation of CPOE, ERBI, and ePPID in Critical Care Operating Rooms at a Tertiary Care Academic Center

Abstract Introduction/Objective Blood transfusion in operating rooms (ORs) is a critical and complex process, often complicated by issues such as paper-based orders, lack of guidelines, and delays in blood delivery. In response, a multidisciplinary task force developed a quality improvement plan. This study assesses the impact of implementing an electronic positive patient identification (ePPID) system, standardized computer provider order entry (CPOE), and electronic remote blood issue (ERBI) process in a critical care OR setting at our institution. Methods/Case Report The team initially implemented ePPID in cardiac surgery ORs before expanding hospital-wide. CPOE was developed in collaboration with the laboratory information systems (LIS) and hospital information technology (IT). ERBI required cross-departmental coordination to establish a bi-directional interface between LIS and ERBI software. Staff received training through a train-the-trainer approach, interactive sessions, videos, and surveys. CPOE focused on order set development and creating the Maximum Surgical Blood Order Schedule (MSBOS). ePPID began with a pilot program and expanded with training sessions. Data collection tracked blood ordering, ERBI workflow, and transfusion data for compliance and utilization rates. Results (if a Case Study enter NA) The implementation of ePPID saw a rise in compliance rates from 71% to 98%, with 60 completed cases and 233 blood products transfused by 24 clinicians. ePPID’s utilization for blood products increased from 60% to 98% within 90 days. ERBI lowered RBC return rates from 30% to 15% and plasma return rates from 45% to 35% over a 2.5 year span. ERBI utilization rates reached 81% at 24 months post-implementation. Conclusion The implementation of ePPID, CPOE, and ERBI in critical care ORs was well-received among clinicians. Significant improvements in compliance and utilization rates for blood products following ePPID implementation were evident. ERBI implementation also led to substantial reductions in return rates of blood products allocated to ORs. The steady increase in ERBI utilization indicates successful integration into OR workflows.

A-179 Improving specimen labeling errors in the pediatric emergency department at a tertiary care hospital

Abstract Background Specimen labeling errors, such as unlabeled, mislabeled, or sample-requisition mismatches, pose risks to patient care. Correcting these errors, particularly for pediatric patients, is crucial to avoid unnecessary stress to the family and time spent on follow-up. In 2018, the BCCH Emergency Department (ED) reported the highest labeling error rates among all departments at our tertiary care hospital, accounting for approximately 30% of all errors. Methods To address this issue, a quality improvement project following the Model for Improvement framework was initiated in 2019 at the ED. An interdisciplinary team approach was adopted initially, and a positive patient identification system (PPID) was implemented later in February 2022. Patient Safety Learning System (PSLS) data from January 2019 to November 2023 were analyzed to evaluate the impact of these interventions. Results 1763 (22.6%) of the 7802 PSLS events recorded during this period were sample labeling errors. Ward collections accounted for the majority of labeling errors compared to laboratory collections (20.3% vs 2.4%). In the ED, most of the labeling errors occurred with unspecified samples (25%), swabs (24%), urine (23%), and blood culture (19%). The interdisciplinary team intervention initially reduced labeling errors, but its impact was inconsistent. However, the implementation of PPID in 2022 led to a significant and consistent decrease in labeling errors in the ED (4.51 errors/month vs 1.14 errors/month; p = 0.01) (Figure. 1). Conclusions While the implementation of PPID has notably improved labeling errors in the ED, complete elimination remains challenging. In addition, more specific PSLS filing categories are needed to capture sources of labeling error from unspecified samples. Continued efforts are necessary to achieve the goal of zero labeling errors.

Computer vision to enhance healthcare domain: An overview of features, implementation, and opportunities

The emergence of Artificial Intelligence (AI) has already brought several advantages to the healthcare sector. Computer Vision (CV) is one of the growing modern AI technologies. The distribution and administration of medications are about to change by using CV for medication management. This system scans pharmaceutical labels and keeps track of the process from delivery to administration using cameras, sensors, and computer algorithms. In order to assure accuracy in medicine delivery and dose, the system also makes it easier for doctors, nurses, and chemists to communicate. The computer vision-driven medication management system can significantly lower the number of medical mistakes that result from inaccurate or missing prescriptions, improper doses, or simply forgetting to take a particular drug. An exhaustive literature review has been done to identify work related to the research objectives. This paper is about CV and their need in healthcare. Various tasks associated with CV in the healthcare domain are discussed. Targeted healthcare goals through CV traits are briefed. Finally, the significant applications of CVs in healthcare were identified and discussed. Nowadays, CV has practical uses in healthcare. Its methods are widely used since they have shown excellent utility in several medical contexts, including medical imaging and surgical planning. The CV is used to study how to program computers to comprehend digital pictures. Numerous medical applications utilise this technology, such as automated abnormality identification, illness diagnosis, and surgical procedure guiding. CV is expanding quickly and has enormous promise to enhance healthcare. Some of the many CV applications in the healthcare sector include patient identification systems, medical picture analysis, surgical simulation and illness diagnosis.

Enhancing tuberculosis treatment adherence and motivation through gamified real-time mobile app utilization: a single-arm intervention study

BackgroundFinding innovative methods to enhance Tuberculosis treatment adherence in Malaysia is imperative, given the rising trend of non-adhere TB patients. Direct Observed Therapy (DOTS) has been used to ensure Tuberculosis (TB) drug compliance worldwide. However, due to its inconvenience, digitalizing this system into a virtual monitoring system via a mobile app can help deliver a more efficient tuberculosis management system. A gamified video-observed therapy is developed that connects three users the patient, supervisor, and administrator, allowing drug monitoring and patient loss to follow up with the patient tracking system. Thus, the objective of this study is to determine the impact of Gamified Real-time Video Observed Therapy (GRVOTS) mobile apps on patient medication adherence rates and motivation.Methods71 patients from 18 facilities participated in the 8-week single-arm intervention study. GRVOTS mobile apps were installed in their mobile apps, and patients were expected to fulfill tasks such as providing Video Direct Observe Therapy (VDOTS) daily as well as side effect reporting. At 3-time intervals of baseline,1-month, and 2-month intervals, the number of VDOT taken, the Malaysian Medication Adherence Assessment Tool (MyMAAT), and the Intrinsic Motivation Inventory (IMI) questionnaire were collected. One-sample t-test was conducted comparing the VDOT video adherence to the standard rate of 80%. RM ANOVA was used to analyze any significant differences in MyMAAT and IMI scores across three-time intervals.ResultsThis study involved 71 numbers of patients from 18 healthcare facilities who showed a significantly higher treatment adherence score of 90.87% than a standard score of 80% with a mean difference of 10.87(95% CI: 7.29,14.46; p < 0.001). The participants’ MyMAAT and IMI scores significantly increased over 3-time intervals with the IMI Interest domain showing the highest mean difference 19.76 (95% CI: 16.37, 21.152: p < 0.001).ConclusionsBy utilizing GRVOTS, a mobile application based on gamification and real-time features, we can enhance motivation and medication adherence among TB patients, while also addressing the limitations of physical DOTS.Trial registrationIRCT20230308057657N1, Registered on (15/03/23).

IoT-based centralized wireless patient tracking and surveillance system with a cutting-edge approach for advanced healthcare oversight and data-driven analysis

The construction of smart cities has been progressing quickly due to advancements in 5G and Internet of Things (IoT) technology. Smart transportation systems and smart medical ideas are also being explored alongside smart city initiatives. Integrating the two mentioned technologies, a smart navigational method for ambulances is being developed. When severe patients arrive via ambulance, significant time is wasted in relaying data, and the hospital needs to gain prior knowledge of the patient's condition. An efficient system called the IoT-based Wireless Patient Tracking Method (IoT-WPTM) is proposed to diagnose patients quickly by recording vital metrics such as heartbeat, temperature, and breathing rate using detectors. These variables are transmitted wirelessly to the healthcare before the ambulance is dispatched, allowing doctors to begin medical care promptly. If necessary, the patient monitors the ambulance's position to anticipate arrival and get immediate directions to the closest hospital. The user carries the gadget and is also placed in the ambulance. The gadget allows IoT devices and Android apps to enhance user interaction and streamline information delivery. IoT-WPTM can be surpassed with ease and in a more effective manner for smart medical surveillance systems.

ALZO: an outdoor Alzheimer's patient tracking system using internet of things

ALZO: an outdoor Alzheimer's patient tracking system using internet of things

Patient Identification and Healthcare System

Abstract: Personal Health Records Identification is a system that allows an individual to store his/her health related information with doctor. The Personal Health Records Identification can control his/her data stored on the system using the fingerprint. This work aims to propose a privacy-preserved identification scheme to be used in the Personal Health Records Identification system during an emergency situation especially when the victim is unconscious. The fingerprint- based scheme under a Protected Biometric Template concept is applied to identify the victim without compromising the privacy of the victim. The usability and security discussions in the proposed scheme is practical under the current existing communication technology

HPB O08 Championing benign biliary patients in Emergency General Surgery: A 3 year quality improvement project

Abstract Background A biliary quality improvement project (QuIP) was established in 2019 following 3 audit cycles highlighting delays to laparoscopic cholecystectomy (Lap-C) in patients with gallstone pancreatitis. Limited theatre space and other urgent care priorities hindered efforts to meet other biliary key performance indicator targets between 2015 and 2019. The last phase of the QuIP has introduced a dedicated consultant lead biliary service, a live biliary patient tracking system, increased in-patient Lap-C, implementation of ambulatory pathways and a patient centred integrated care approach. Methods Prospectively collected data from a live biliary tracking system was compared with retrospective audit data from 2015-2019. Key performance indicators were; average time to Lap-C, rate of Lap-C with-in 2 weeks following pancreatitis, inpatient Lap-C rate and out-patient appointments saved. Results 523 patients were managed through inpatient and ambulatory biliary pathways from November 2021-June 2023. 2 week Lap-C post pancreatitis improved from 27% to 79% (43% as inpatients) with average time to Lap-C improving from 68 days to 13 days. 191 outpatient appointments were saved by counselling and pre-assessing patients for Lap-C as inpatients, saving £22920 in outpatient costs. In-patient Lap-C rate improved from 2% to 19% for fit and consenting patients. Conclusions A higher quality of care can be achieved for biliary patients through; effective patient prioritisation, increasing inpatient Lap-C, the establishment of ambulatory pathways and a robust outpatient tracking system.

Usability and usefulness of (electronic) patient identification systems—A cross-sectional evaluation in German-speaking radiation oncology departments

PurposePatient misidentification in radiation oncology (RO) is a significant concern due to the potential harm to patient health and the burden on healthcare systems. Electronic patient identification systems (ePIS) are increasingly being used as an alternative or supplement to organizational systems (oPIS). The objective of this study was to assess the usability and usefulness of ePIS and oPIS in German-speaking countries.MethodsA cross-sectional survey was designed by a group of experts from various professional backgrounds in RO. The survey consisted of 38 questions encompassing quantitative and qualitative data on usability, user experience, and usefulness of PIS. It was available between August and October 2022.ResultsOf 118 eligible participants, 37% had implemented some kind of ePIS. Overall, 22% of participants who use an oPIS vs. 10% of participants who use an ePIS reported adverse events in terms of patients’ misidentification in the past 5 years. Frequent or very frequent drop-outs of electronic systems were reported by 31% of ePIS users. Users of ePIS significantly more often affirmed a positive cost–benefit ratio of ePIS as well as an improvement of workflow, whereas users of oPIS more frequently apprehended a decrease in staffs’ attention through ePIS. The response rate was 8%.ConclusionThe implementation of ePIS can contribute to efficient PI and improved processes. Apprehensions by oPIS users and assessments of ePIS users differ significantly in aspects of the perceived usefulness of ePIS. However, technical problems need to be addressed to ensure the reliability of ePIS. Further research is needed to assess the impact of different PIS on patient safety in RO.

Patient identification system based on NFC and blockchain technology

Objective: To develop a system in the field of medicine that allows to identify patients by making use of security for NFC cards based on blockchain. Methodology: A study of the physical characteristics of NFC cards was carried out to design an external security system, supported by the decentralization of the blockchain, which allows the use of these cards in a field that handles highly sensitive information, such as medicine, in order to take advantage of the practicality of NFC technology when identifying patients in a hospital without exposing their medical history. Results: It was appreciated that the blockchain offers a lot of advantages in the field of security, but these advantages come with a decompensation in the times of writing new blocks and reading previous blocks. Conclusions: A system supported on a centralized and decentralized part provides greater security, however, a decentralized system such as the blockchain comes with a decompensation in terms of writing speed and, above all, reading speed.

Evaluating the availability and quality of services for lymphatic filariasis morbidity in Ghana.

In districts where lymphatic filariasis (LF) is endemic, the goal is to provide 100% geographical coverage of the essential package of care. Additionally, countries seeking elimination status must document the availability of services for lymphoedema and hydrocele in all endemic areas. To do this, the WHO recommends conducting assessments of the readiness and quality of services provided to identify service delivery and quality gaps. This study used the recommended WHO Direct Inspection Protocol (DIP), which consists of 14 core indicators related to LF case management, medicine and commodities, staff knowledge and patient tracking. The survey was administered in 156 health facilities across Ghana designated and trained to provide LF morbidity management services. Patient and health provider interviews were also conducted to assess challenges and feedback. The highest performing indicators across the 156 surveyed facilities were related to staff knowledge; 96.6% of health workers correctly identified two or more signs and symptoms. The lowest scoring indicators concerned medication availability, with the two lowest scoring indicators in the survey being availability of antifungals (26.28%) and antiseptics (31.41%). Hospitals performed best with an overall score of 79.9%, followed by health centers (73%), clinics (67.1%) and CHPS compounds (66.8%). The most commonly reported challenge from health worker interviews was lack of medications and supplies, followed by a lack of training or poor motivation. The findings from this study can help the Ghana NTD Program identify areas of improvement as they seek to achieve LF elimination targets and continue to improve access to care for those with LF-related morbidity as part of overall health systems strengthening. Key recommendations include prioritizing refresher and MMDP training for health workers, ensuring reliable patient tracking systems, and integrating lymphatic filariasis morbidity management into the routine healthcare system to ensure medicine and commodity availably.

Implementation of Face Recognition for Patient Identification Using the Transfer Learning Method

The hospital's status as a health center requires it to ensure patient safety, decrease incidents and treat patients. Identification of the patient is the primary source of patient safety difficulties. In addition to the patient's name and number, further patient-identifying components are needed to reduce this neglect. This work provides a solution in the form of biometric authentication, namely, face recognition. The convolutional neural network (CNN) approach can enable machine facial recognition. CNN is one of the deep learning techniques used to detect and identify picture objects. In this study, facial recognition was carried out using the transfer learning technique, VGGFace2 model pretraining, and SENet 50 model architecture. The dataset was collected via one-shot learning or a single sample per individual sampling. Applying the CNN model to the patient identification system yields two distinct outcomes: patient registration and verification. Registration utilizes a minimum distance of 0.35 and matches data with the complete database, whereas patient verification has a minimum distance of 0.28 and matches only the face in question. At the time of patient registration, the accuracy was between 90% and 100%. However, at the time of patient verification, the accuracy was 100%.

Increasing Patient Tracking Compliance by Harnessing Frontline Clinician Engagement

Introduction:A large urban jurisdiction identified a lack of experience and knowledge in use of the established regional patient tracking system among frontline emergency department employees. Lack of nursing retention, shifted departmental priorities throughout the pandemic response, and decreased opportunities for exercising were notable causes of this identified knowledge gap. Effective patient tracking has a significant impact during response to any event with the capacity to strain the hospital and healthcare system. Mass casualty incidents pose a global threat to all jurisdictions. Recognition of this threat magnifies the importance of establishing a patient tracking system and empowering frontline staff, through education and training, to immediately implement the exercised patient tracking platform.Method:Bolstering hospital readiness through site visits and first-receiver clinician engagement during special event planning improved effective use of a citywide patient tracking system during planned events. “Just-in-time” training tools were developed and distributed during site visits. Notably, identification of key clinical staff at each institution was an important step in meaningful clinician engagement. Utilization of these systems during special events is an opportunity to exercise a high stakes procedure during a low stakes incident.Results:Site visits and training material distribution effectively enhanced first-receiver participation in patient tracking during a special event in comparison to previous special events. Users required less prompting throughout the response, and the post-intervention survey indicated an increase in user confidence levels. Increased utilization of the system improved visibility into the hospital's lived experience while engaged in the response.Conclusion:Targeted site visits and educational material tailored to first-receiver clinicians during special events improved patient tracking efforts throughout a large urban healthcare system. During real and planned events, person and patient tracking allows for patient load balancing across the healthcare system, assists with patient and family reunification, and directs future planning, funding, and first responder and receiver education.

Clinical decision support with a comprehensive in-EHR patient tracking system improves genetic testing follow up.

We sought to develop and evaluate an electronic health record (EHR) genetic testing tracking system to address the barriers and limitations of existing spreadsheet-based workarounds. We evaluated the spreadsheet-based system using mixed effects logistic regression to identify factors associated with delayed follow up. These factors informed the design of an EHR-integrated genetic testing tracking system. After deployment, we assessed the system in 2 ways. We analyzed EHR access logs and note data to assess patient outcomes and performed semistructured interviews with users to identify impact of the system on work. We found that patient-reported race was a significant predictor of documented genetic testing follow up, indicating a possible inequity in care. We implemented a CDS system including a patient data capture form and management dashboard to facilitate important care tasks. The system significantly sped review of results and significantly increased documentation of follow-up recommendations. Interviews with key system users identified a range of sociotechnical factors (ie, tools, tasks, collaboration) that contribute to safer and more efficient care. Our new tracking system ended decades of workarounds for identifying and communicating test results and improved clinical workflows. Interview participants related that the system decreased cognitive and time burden which allowed them to focus on direct patient interaction. By assembling a multidisciplinary team, we designed a novel patient tracking system that improves genetic testing follow up. Similar approaches may be effective in other clinical settings.

Experience of Florence University Hospital: the Disaster Emergency Plan in a third level hospital

Objective. The study aims to explain how to prepare a disaster manual, describes it and shows how it is applied it in a tertiary care hospital when emergency occur. Methods. We based the article on the principles of disaster medicine, on recent literature and on the experiences gained during the pandemic COVID emergency. Results. Recent terrorist attacks have highlighted the importance of a contingency plan to effectively and efficiently manage a large influx of wounded. Careggi Hospital’s PEMAF (emergency plans for a massive influx of injured) is a comprehensive and well-coordinated response to a disaster situation. The hospital’s specialized disaster response team, surge capacity plan, and patient tracking system provide the necessary resources to provide immediate and efficient care to patients in the event of a disaster. Conclusions. Disaster medicine protocols play a critical role in preparing healthcare professionals to respond to large-scale disasters, including terrorist attacks. By following established protocols and principles of disaster medicine, healthcare professionals can provide effective care to those affected by disasters and help to mitigate the impact of future disasters.

IoT Based Tracking System for Patients

Abstract-Health-care Environment has developed in science and patients require ongoing monitoring of their ECG readings, body temperature, blood pressure (BP), heart rate, and other vital indicators. So, the primary goal of the working model is to use wireless technology to transmit the patient's health parameters to the doctor in case anything is abnormal. All the characteristics will be sensed, even if the patient is unconscious, and relayed to the medical professionals. So, we are proposing an innovative project to dodge such sudden death rates by using Patient Health Monitoring that uses sensor technology and uses the internet to communicate with assistance in case of problems. This system uses Temperature, Spo2, gyroscope, and heartbeat sensors for tracking patients’ health. These sensors are connected to the Arduino-Uno. A microcontroller that tracks the patient's health which is connected to an LCD display and a wireless network to transmit the information to a web server. In case of any abrupt changes in the patient’s heart rate, temperature, or blood oxygen saturation level, an alert message is sent about the patient using IoT. This tracking system also shows patients’ temperature, angular movements, and heartbeat tracked live data with timestamps over the Internetwork. Consequently, the IoT-based patient health tracking system actively monitors patient health through the internet, assists users in keeping an eye on their patients while at work, and perhaps saves lives. technology- based knowledge focused on Wireless-Sensing nodes. Key Words: Monitoring, Arduino-Uno, LCD display, temperature alert, Ubidots.

An Intelligent Diabetic Patient Tracking System Based on Machine Learning for E-Health Applications

Continuous surveillance helps people with diabetes live better lives. A wide range of technologies, including the Internet of Things (IoT), modern communications, and artificial intelligence (AI), can assist in lowering the expense of health services. Due to numerous communication systems, it is now possible to provide customized and distant healthcare. Healthcare data grows daily, making storage and processing challenging. We provide intelligent healthcare structures for smart e-health apps to solve the aforesaid problem. The 5G network must offer advanced healthcare services to meet important requirements like large bandwidth and excellent energy efficacy. This research suggested an intelligent system for diabetic patient tracking based on machine learning (ML). The architectural components comprised smartphones, sensors, and smart devices, to gather body dimensions. Then, the preprocessed data is normalized using the normalization procedure. To extract features, we use linear discriminant analysis (LDA). To establish a diagnosis, the intelligent system conducted data classification utilizing the suggested advanced-spatial-vector-based Random Forest (ASV-RF) in conjunction with particle swarm optimization (PSO). Compared to other techniques, the simulation's outcomes demonstrate that the suggested approach offers greater accuracy.

Patient Identification in the Hemodialysis Unit Using the Plan-Do-Study-Act Approach

This study determines the cause and solutions of the patient identification achievement that is not yet 100%, as the base to improve the patient identification system in the HD unit of GPI Hospital. Qualitative research using the Plan-Do-Study-Act (PDSA) approach involving triangulation of data collection, namely observation, documentation, and interviews with the PDSA NHS Improvement instrument. Informants were selected by snowball sampling. The PDSA results indicated that the problem cause was the HD team's lack of understanding of patient identification. This problem can be overcome by socialization and simulation of patient identification: a standard operating procedure for patient identification, implementation of patient identification, patient identification incident reporting flow, and money for patient identification. The problem of identifying patients in the HD unit can be resolved using the PDSA cycle that has been performed. Modifications are required for the next PDSA cycle, consisting of 1) regular socialization and simulation of patient identification; 2) SOP of patient identification in HD unit; 3) implementation of the identification process by involving the patient; 4) reporting and building awareness of realizing a patient safety culture if an incident occurs, and 5) reporting on the achievement of monev data and recommendations for improvement efforts.

MongoDB Based Real-Time Monitoring Heart Rate Using Websocket For Remote Healthcare

With the gradual development of Industry 4.0, the internet of things (IoT) concept has become an even more current and fundamental study topic. Consisting of devices and objects with communication capability, IoT is a network that uses internet infrastructure, especially for data collection, display, decision-making, control, and optimization of processes. Recently, patient tracking systems have become even more critical with Covid19 and have diversified in health for IoT topics such as biomedical device tracking and disease diagnosis. Within the scope of this study, a prototype of a patient tracking system was developed over the sensor in order to contribute to the biomedical field. We aimed to observe real-time heart rates using WebSockets to demonstrate its use in the medical field via the web application. Monitoring the heart rate using a WebSocket can help doctors make faster and better diagnoses. The current technology study instantly collected the patient's heart rhythm with the pulse sensor. The pulse data collected in real time was then transferred to a web platform with the NodeMCU ESP 8266 board. With this platform, the patient was monitoring in real-time. With the opportunities provided by the study, the doctor implemented an application monitors the instantaneous pulse of the patients.