RFID-initiated workflow control to facilitate patient safety and utilization efficiency in operation theater

Evaluation of the Effects of Radio-Frequency Identification Technology on Patient Tracking in Hospitals: A Systematic Review

OBJECTIVE

The aim of this study was to systematically review all studies that evaluated the effects of using radio-frequency identification (RFID) for tracking patients in hospitals.

METHODS

The PubMed and Embase databases were searched (to August 2015) for relevant English language studies, and those that evaluated the effects of a real-time locating systems with RFID for patient tracking in hospitals were identified and extracted.

RESULTS

Of the 652 studies found, the 17 relevant studies were extracted for inclusion. Five of the extracted studies used RFID systems in operating theaters, two in emergency departments, one in a magnetic resonance imaging department, one in a radiology room, and the remaining eight studies were in other wards. In these studies, features such as the feasibility, accuracy, precision, reliability, security, level of satisfaction, cost of care, and time efficiency of the RFID systems were reported. Of all the extracted studies, seven evaluated the accuracy of the systems in crowded and unattended areas, and five of these were satisfied with their accuracy. Six evaluated the reliability of the systems, and all of these found the systems to be reliable. Six evaluated time-savings, and all of them reported the systems to be time effective. Two focused on the cost of care, and both of these reported the systems to be cost effective.

CONCLUSIONS

Although most studies reported a positive impact on the accuracy and precision of patient identification, there is insufficient good evidence to show that RFID systems can accurately localize patients in crowded settings.

Real-time locating systems to improve healthcare delivery: A systematic review

OBJECTIVE

Modern health care requires patients, staff, and equipment to navigate complex environments to deliver quality care efficiently. Real-time locating systems (RTLS) are local tracking systems that identify the physical locations of personnel and equipment in real time. Applications and analytic strategies to utilize RTLS-produced data are still under development. The objectives of this systematic review were to describe and analyze the key features of RTLS applications and demonstrate their potential to improve care delivery.

MATERIALS AND METHODS

We searched MEDLINE, SCOPUS, and IEEE following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Inclusion criteria were articles that utilize RTLS to evaluate or influence workflow in a healthcare setting. We summarized aspects of relevant articles, identified key themes in the challenges of applying RTLS to workflow improvement, and thematically reviewed the state of quantitative analytic methodologies.

RESULTS

We included 42 articles in the final qualitative synthesis. The most frequent study design was observational (n = 24), followed by descriptive (n = 12) and experimental (n = 6). The most common clinical environment for study was the emergency department (n = 12), followed by entire hospital (n = 7) and surgical ward (n = 6).

DISCUSSION

The focus of studies changed over time from early experience to optimization to evaluation of an established system. Common narrative themes highlighted lessons learned regarding evaluation, implementation, and information visibility. Few studies have developed quantitative techniques to effectively analyze RTLS data.

CONCLUSIONS

RTLS is a useful and effective adjunct methodology in process and quality improvement, workflow analysis, and patient safety. Future directions should focus on developing enhanced analysis to meaningfully interpret RTLS data.

Real-Time Person Identification in a Hospital Setting: A Systematic Review

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. The search was performed on 11 May 2020 in PubMed and the Web of Science Core Collection. PubMed and Web of Science yielded a total n = 265 and n = 228 records, respectively. The review process resulted in n = 23 included records. A total of seven techniques were identified: (a) active and (b) passive Radio-Frequency Identification (RFID) based systems, (c) fingerprint, (d) iris, and (e) facial identification systems and infrared (IR) (f) and ultrasound (US) (g) based systems. Active RFID was largely documented in the included literature. Only a few could be found about the passive systems. Biometric (c, d, and e) technologies were described in a variety of applications. IR and US techniques appeared to be a niche, as they were only spoken of in few (n = 3) studies.

On Providing Multi-Level Quality of Service for Operating Rooms of the Future

The Operating Room (OR) plays an important role in delivering vital medical services to patients in hospitals. Such environments contain several medical devices, equipment, and systems producing valuable information which might be combined for biomedical and surgical workflow analysis. Considering the sensibility of data from sensors in the OR, independently of processing and network loads, the middleware that provides data from these sensors have to respect applications quality of service (QoS) demands. In an OR middleware, there are two main bottlenecks that might suffer QoS problems and, consequently, impact directly in user experience: (i) simultaneous user applications connecting the middleware; and (ii) a high number of sensors generating information from the environment. Currently, many middlewares that support QoS have been proposed by many fields; however, to the best of our knowledge, there is no research on this topic or the OR environment. OR environments are characterized by being crowded by persons and equipment, some of them of specific use in such environments, as mobile x-ray machines. Therefore, this article proposes QualiCare, an adaptable middleware model to provide multi-level QoS, improve user experience, and increase hardware utilization to middlewares in OR environments. Our main contributions are a middleware model and an orchestration engine in charge of changing the middleware behavior to guarantee performance. Results demonstrate that adapting middleware parameters on demand reduces network usage and improves resource consumption maintaining data provisioning.

Implementation and Evaluation of a RFID Smart Cabinet to Improve Traceability and the Efficient Consumption of High Cost Medical Supplies in a Large Hospital

The efficiency of a smart cabinet with RFID technology to improve the information about inventory management for cardiothoracic surgery as well as for time savings, was assessed in a large reference hospital. In a 6-month study, the implemented operational RFID process (StocKey® Smart Cabinet) consisted of: i) product reception, registration and labelling in the general warehouse; ii) product storage in the cabinet and registered as inputs by radiofrequency; iii) products registered as outputs as required for surgery; iv) product assignment to a patient in the operating room; and v) return of products not used to the cabinet. Stock-outs, stock mismatches, urgent restocking, assignment of high-value medical products to patients, and time allocated by the supervisory staff to the stock management, were assessed on a monthly basis. 0% stock-outs and 0% stock mismatches using RFID were observed during the study. Monthly percentages of products requiring urgent restocking ranged from 0% to 13.3%. No incorrect assignments to patients of surgery products or prostheses were detected. The percentage of correct assignments increased from 36.1%–86.1% to 100% in the first 4–5 months. The total average time allocated by the supervisory staff to the whole logistic chain was reduced by 58% (995 min with the traditional manual system vs. 428 min with RFID). The RFID system showed the ability to monitor both the traceability and consumption per patient of high-value surgery products as well as contributed to significant time savings.

Factors impacting technology adoption in hospital bed logistics

Purpose

The purpose of this paper is to refine and expand technology adoption theory for a healthcare logistics setting by combining the technology–organization–environment framework with a business process management (BPM) perspective. The paper identifies and ranks factors impacting the decision to implement instances of technologies in healthcare logistics processes.

Design/methodology/approach

A multiple case study is carried out at five Danish hospitals to investigate the bed logistics process. A combined technology adoption and BPM lens is applied to gain an understanding of the reasoning behind technology adoption.

Findings

A set of 17 factors impacting the adoption of technologies within healthcare logistics was identified. The impact factors perceived as most important to the adoption of technologies in healthcare logistics processes relate to quality, employee work conditions and employee engagement.

Research limitations/implications

This paper seeks to understand how managers can use knowledge about impact factors to improve processes through technology adoption. The findings of this study provide insights about the factors impacting the adoption of technologies in healthcare logistics processes. Differences in perceived importance of factors enable ranking of impact factors, and prioritization of changes to be implemented. The study is limited to five hospitals, but is expected to be representative of public hospitals in developed countries and applicable to similar processes.

Originality/value

The study contributes to the empirical research within the field of BPM and technology adoption in healthcare. Furthermore, the findings of this study enable managers to make an informed decision about technology adoption within a healthcare logistics setting.

A Cyber-Physical System to Improve the Management of a Large Suite of Operating Rooms

Cyber-physical systems have been deployed with considerable success in many industries. However, the implementation of cyber-physical systems in hospitals has been limited. By nature, in clinical operations, patient safety and consideration for health outcomes are of the utmost importance, thus possibly slowing the implementation of innovative solutions with limited history. Revenues from operating room (OR) time and surgery account for about 50% of the income of major hospitals (Erdogan et al. 2011; Cuschieri 2006), but the efficiency of OR utilization is often reported to be relatively low. Therefore, improving OR management with a cyber-physical system should be a priority. In this article, we will report on our experience implementing a cyber-physical system at Houston Methodist Hospital and discuss some of the difficulties and potential drivers for success. Our pilot study was done in the context of the management of a large suite of ORs. It uses the agile codevelopment of a cyber-physical system through an intense collaboration of clinicians and computational scientists. While technology remains the foundation of a cyber-physical system, this experience reinforced that the human factor is an important driving force behind the design that promotes user acceptance.

Advantages and Disadvantages of 1-Incision, 2-Incision, 3-Incision, and 4-Incision Laparoscopic Cholecystectomy: A Workflow Comparison Study

A comparison of 1-port, 2-port, 3-port, and 4-port laparoscopic cholecystectomy techniques from the point of view of workflow criteria was made to both identify specific workflow components that can cause surgical disturbances and indicate good and bad practices. As a case study, laparoscopic cholecystectomies, including manual tasks and interactions within teamwork members, were video-recorded and analyzed on the basis of specially encoded workflow information. The parameters for comparison were defined as follows: surgery time, tool and hand activeness, operator's passive work, collisions, and operator interventions. It was found that 1-port cholecystectomy is the worst technique because of nonergonomic body position, technical complexity, organizational anomalies, and operational dynamism. The differences between laparoscopic techniques are closely linked to the costs of the medical procedures. Hence, knowledge about the surgical workflow can be used for both planning surgical procedures and balancing the expenses associated with surgery.

Design and Development of a Clinical Risk Management Tool Using Radio Frequency Identification (RFID)

Background:

Patient safety is one of the most important elements of quality of healthcare. It means preventing any harm to the patients during medical care process.

Objective:

This paper introduces a cost-effective tool in which the Radio Frequency Identification (RFID) technology is used to identify medical errors in hospital.

Methods:

The proposed clinical error management system (CEMS) is consisted of a reader device, a transfer/receiver device, a database and managing software. The reader device works using radio waves and is wireless. The reader sends and receives data to/from the database via the transfer/receiver device which is connected to the computer via USB port. The database contains data about patients’ medication orders.

Results:

The CEMS has the ability to identify the clinical errors before they occur and then warns the care-giver with voice and visual messages to prevent the error. This device reduces the errors and thus improves the patient safety.

Conclusion:

A new tool including software and hardware was developed in this study. Application of this tool in clinical settings can help the nurses prevent medical errors. It can also be a useful tool for clinical risk management. Using this device can improve the patient safety to a considerable extent and thus improve the quality of healthcare.

An intelligent hospital operating room to improve patient health care

Optimizing management of multiple hospital operating rooms (ORs) is a complex problem. A large hospital can have upwards of greater than 50 with a large number of different procedures per day and per OR that needs to be scheduled several weeks in advance. Each procedure requires gathering a team led by a surgeon for a specific block of time in the OR, but even common procedures such as cholecystectomies, which account for about 1.4 million cases per year in the USA, exhibit a significant variation in total procedure duration. OR time is one of the most significant budget chapters in a modern hospital, and it has also been shown that delays in OR procedures due to lapses in scheduling and/or OR resources availability have been responsible for post-surgical complications.

We propose an innovative, cost effective hardware/software OR awareness solution that automatically (i) detects what step of the procedure the OR team is at, (ii) determines if steps are out of order, (iii) identifies and pinpoints procedural delays, irregularities, and unused OR time, and (iv) can assist in root cause analyses and assessment. Most institutions have an electronic OR management software system in place that allows for easy projection and visualization of the daily OR schedule, but all rely heavily on manual data entry resulting in human error and bias. There exists a need not only for a fully automated, unbiased, and accurate OR management system that also collects key procedural data for both real-time and retrospective analyses but also for an intuitive and user-friendly digital interface. With our system, we have been able to track and collect data on almost 300 cases to not only identify but quantify sources of inefficiency as well as automatically indicate cases that exceed expected lengths.

RFID in Healthcare – Current Trends and the Future

Radio Frequency Identification (RFID) enables automatic identification of objects using radio waves. The identified objects can be in and out of the line of sight and there is no need for physical contact with them. RFID technology is deployed in a wide range of industries such as supply chain management, inventory control, farming (to track animals), e-Passports, the tracking of humans (in prisons and hospitals) and in healthcare [1]. The three key elements of an RFID system are the tags, readers and the backend server. Tags are devices physically attached to objects and readers (wired or mobile) recognize the presence of objects in its range.

Improved workflow modelling using role activity diagram-based modelling with application to a radiology service case study

The modelling of complex workflows is an important problem-solving technique within healthcare settings. However, currently most of the workflow models use a simplified flow chart of patient flow obtained using on-site observations, group-based debates and brainstorming sessions, together with historic patient data. This paper presents a systematic and semi-automatic methodology for knowledge acquisition with detailed process representation using sequential interviews of people in the key roles involved in the service delivery process. The proposed methodology allows the modelling of roles, interactions, actions, and decisions involved in the service delivery process. This approach is based on protocol generation and analysis techniques such as: (i) initial protocol generation based on qualitative interviews of radiology staff, (ii) extraction of key features of the service delivery process, (iii) discovering the relationships among the key features extracted, and, (iv) a graphical representation of the final structured model of the service delivery process. The methodology is demonstrated through a case study of a magnetic resonance (MR) scanning service-delivery process in the radiology department of a large hospital. A set of guidelines is also presented in this paper to visually analyze the resulting process model for identifying process vulnerabilities. A comparative analysis of different workflow models is also conducted.

A smart trocar for automatic tool recognition in laparoscopic surgery

BACKGROUND

Operating rooms have become increasingly complex environments and more prone to errors because of loss of situation awareness. Adding computer intelligence to the operating room may help overcome these limitations particularly if the system can automatically track which step of an operation a surgeon is performing. To develop such a platform, it is necessary to track which laparoscopic instruments are being used and in which port they are inserted. This article describes the development and validation of a "Smart Trocar" that can automatically perform this function.

METHODS

A Smart Trocar system prototype was developed that uses a wireless camera attached to a standard laparoscopic port and custom software algorithms. The system recognizes color wheels attached to the handle of a laparoscopic instrument and compares the unique color pattern to an instrument library for proper tool identification. The system was tested for reliability in a box trainer environment using a variety of tool positions and levels of room light illumination.

RESULTS

Correct color classification was achieved in 96.7% of trials. There were no errors in detection of the color wheel in space. In addition, the distance of the color wheel from the camera did not influence results and correct classifications were evenly distributed among the 12 laparoscopic tool positions tested.

CONCLUSION

This work describes a Smart Trocar system that identifies which laparoscopic tool is being used and in which port and proves its reliability. The system is an important element of a more comprehensive program being developed to automatically understand what step of an operation a surgeon is performing and use these data to improve situation awareness in the operating room.

Passive tracking of linac clinical flow using radiofrequency identification technology

PURPOSE

To analyze the implementation of a passive radiofrequency identification (RFID) clinical system and to evaluate the clinical workflow on 2 linear accelerators using the RFID technology.

METHODS AND MATERIALS

The clinical area of a typical radiation therapy center was equipped with RFID readers and antennae, which included linear accelerator (linac) treatment vaults. Both were dual energy linacs (6 and 15 MV). One linac was an iX with RapidArc (Varian Medical Systems, Inc, Palo Alto, CA) and the other was a TrueBeam (Varian Medical Systems, Inc, Palo Alto, CA). Patients were given an RFID transponder card on their first day of treatment. Location timestamps were collected when the patients entered and exited the linac vaults. Each fraction was categorized by treatment machine, treatment site (brain, head and neck, prostate, and other), and treatment type (static field intensity modulated radiation therapy [IMRT], RapidArc, and 3-dimensional [3D]). The Mann-Whitney nonparametric test was used to determine statistical significance between median times in the linac vault.

RESULTS

A total of 4302 fractions from 144 patients were analyzed over a 10-month period. With minimal staff training, an approximately 70% read reliability was achieved. The median treatment time for all treatment fractions on the TrueBeam linac was 11.0 minutes (n = 1425) while the median time was 11.9 minutes (n = 1576) on the iX linac (P < .0001). Median times for the RapidArc cases was 10.9 minutes (n = 610) and 12.0 minutes (n = 1729) for IMRT cases (P < .0001). Median values for 3D delivery versus modulated delivery (RapidArc and IMRT) were 9.8 minutes (n = 315) and 11.7 minutes (n = 2339), P < .0001.

CONCLUSIONS

Automatic remote reading of passive transponder cards is not without its challenges. However, with little or no clinical introduction, we experienced a read reliability that warrants further development. Our initial use of the system indicates that continual collection and analysis of workflow data may allow clinics to improve efficiency and safety.

Assessment of safety and interference issues of radio frequency identification devices in 0.3 Tesla magnetic resonance imaging and computed tomography

The objective of this study was to evaluate two issues regarding magnetic resonance imaging (MRI) including device functionality and image artifacts for the presence of radio frequency identification devices (RFID) in association with 0.3 Tesla at 12.7 MHz MRI and computed tomography (CT) scanning. Fifteen samples of RFID tags with two different sizes (wristband and ID card types) were tested. The tags were exposed to several MR-imaging conditions during MRI examination and X-rays of CT scan. Throughout the test, the tags were oriented in three different directions (axial, coronal, and sagittal) relative to MRI system in order to cover all possible situations with respect to the patient undergoing MRI and CT scanning, wearing a RFID tag on wrist. We observed that the tags did not sustain physical damage with their functionality remaining unaffected even after MRI and CT scanning, and there was no alternation in previously stored data as well. In addition, no evidence of either signal loss or artifact was seen in the acquired MR and CT images. Therefore, we can conclude that the use of this passive RFID tag is safe for a patient undergoing MRI at 0.3 T/12.7 MHz and CT Scanning.

A probabilistic model for reducing medication errors

Background

Medication errors are common, life threatening, costly but preventable. Information technology and automated systems are highly efficient for preventing medication errors and therefore widely employed in hospital settings. The aim of this study was to construct a probabilistic model that can reduce medication errors by identifying uncommon or rare associations between medications and diseases.

Methods and Finding(s)

Association rules of mining techniques are utilized for 103.5 million prescriptions from Taiwan’s National Health Insurance database. The dataset included 204.5 million diagnoses with ICD9-CM codes and 347.7 million medications by using ATC codes. Disease-Medication (DM) and Medication-Medication (MM) associations were computed by their co-occurrence and associations’ strength were measured by the interestingness or lift values which were being referred as Q values. The DMQs and MMQs were used to develop the AOP model to predict the appropriateness of a given prescription. Validation of this model was done by comparing the results of evaluation performed by the AOP model and verified by human experts. The results showed 96% accuracy for appropriate and 45% accuracy for inappropriate prescriptions, with a sensitivity and specificity of 75.9% and 89.5%, respectively.

Conclusions

We successfully developed the AOP model as an efficient tool for automatic identification of uncommon or rare associations between disease-medication and medication-medication in prescriptions. The AOP model helps to reduce medication errors by alerting physicians, improving the patients’ safety and the overall quality of care.