Critical Patient Data Research Articles

Survey paper on Secured Data Retrieval from a distributed database using custom blockchain and Role Base Access Control.

These days, there has been a paradigm shift in the upkeep of Electronic Medical Records (EMRs) in mobile cloud environments. This involves integrating cloud computing with mobile devices to facilitate the transmission of healthcare information between patients and healthcare professionals. With the help of this innovative approach, healthcare may be provided with a high degree of flexibility, minimal overhead costs, and electronic health record access. This new strategy also raises concerns about the security of the networks that enable e-health systems and the privacy of patient data. Finding a solution to efficiently distribute EMRs across mobile users in mobile cloud settings while also upholding the highest security standards is a challenging task. In this paper, explored two different distributed blockchain and cloud frameworks for EMR sharing that combine blockchain technology with a mobile cloud's Decentralised Interplanetary File System (DIFS). Based on the empirical findings, it seems that the idea provides a practical way to protect critical patient data from possible threats and guarantee the dependability of data transfers on mobile clouds. There are notable performance improvements in areas like data privacy protections, minimal network latency, maximum security levels, and lightweight access control when comparing the results of this security analysis and performance assessment to those of earlier data sharing models.

ID: 222733 The Influence of Human Transcription Errors on Surgical Scheduling

Retrospective studies examining errors within a surgical scheduling setting do not fully represent the effects of human error involved in transcribing critical patient data. These errors can negatively impact patient care and reduce workplace efficiency, due to insurance claim denials and potential sentinel events. Previous reports underscore the high burdens physicians face associated with prior authorizations as it may lead to serious adverse events in patients or the abandonment of treatment due to these delays (1). This study simulates scheduling to examine the error rate of experienced schedulers when transcribing forms.

Health Systems Need to Transform Data Collection to Advance Health Equity.

Health Systems Need to Transform Data Collection to Advance Health Equity.

The Development and Validation of Data Elements and Process Steps for an Electronic Health Record for Hand Surgery Outreach Trips

Background The surgical burden in low- and middle-income countries (LMICs) as reported by the number of surgical cases per capita is great. To improve global health and help address this burden, there has been a rise in surgical outreach to LMICs. In high-income countries, an electronic health record (EHR) is used to document and communicate data critical to the quality of care and patient safety. Despite this, there is little guidance or precedence on the data elements or processes for utilizing an EHR on outreach trips. We validated data elements and process steps for utilizing an EHR for hand surgery outreach trips.Methods We conducted a literature review to identify data elements collected during surgical outreach trips. A future-state process map for the collection and documentation of data elements within an EHR was developed through literature review and semistructured interviews with experts in global outreach. An expert consortium completed a modified RAND/University of California at Los Angeles Delphi process to evaluate the importance and feasibility of each data element and process step.Results In total, 65 data elements (e.g., date of birth) and 24 process steps (e.g., surgical site marking) were validated for use in an EHR for hand surgery outreach trips to LMICs.Conclusion This validated portfolio of data elements/process steps can serve as the foundation for pilot testing of an EHR to document and communicate critical patient data on hand surgery outreach trips. Utilization of an EHR during outreach trips to LMICs may serve to improve the safety and quality of care provided. The validated data elements/process steps can serve as a guide for EHR development and implementation of other surgical specialties.

Remote Monitoring of COVID-19 Patients Using Multisensor Body Area Network Innovative System.

As of late 2019, the COVID19 pandemic has been causing huge concern around the world. Such a pandemic posed serious threats to public safety, the well-being of healthcare workers, and the overall health of the population. If automation can be implemented in healthcare systems, patients could be better cared for and health industries could be less burdened. To combat such challenges, e-health requires apps and intelligent systems. Using WBAN sensors and networks, a doctor or medical professional can advise patients on the best course of action. Patients' fitness could be assessed using WBAN sensors without interfering with their daily activities. When designing a monitoring system, system performance reliability for competent healthcare is critical. Existing research has failed to create a large device capable of handling a large network or to improve WBAN topologies for fast transmitting and receiving patient data. As a result, in this research, we create a multisensor WBAN (MSWBAN) intelligent system for transmitting and receiving critical patient data. To gather information from all cluster nodes and send it to multisensor WBAN, a novel additive distance-threshold routing protocol (ADTRP) is proposed. In small networks where data are managed by the transmitting node and the best data route is determined, this protocol has less redundancy. An edge-cutting-based routing optimization (ES-EC-R ES-EC-RO) is used to find the best route. The Trouped blowfish MD5 (TB-MD5) algorithm is used to encrypt and decrypt data, and the encrypted data are stored in a cloud database for security. The performance metrics of our proposed model are compared to current techniques for the best results. End-to-end latency is 63 ms, packet delivery is 95%, security is 95.7%, and throughput is 9120 bps, according to the results. The purpose of this article is to encourage engineers and front-line workers to develop digital health systems for tracking and controlling virus outbreaks.

Hybrid approach of baum-welch algorithm and SVM for sensor fault diagnosis in healthcare monitoring system

Internet of Things (IoT) based healthcare monitoring system is becoming the present and the future of the medical field around the world. Here the monitoring system acquires the regular health details of hospital discharged patients like elderly patients, patients out of critical operations, and patients from remote areas, etc., and transmits it to the doctors. But the system is highly susceptible to sensor faults. Hence a data-driven hybrid approach of Hidden Markov Model (HMM) based on baum-welch algorithm with Support Vector Machine (SVM) is proposed to predict the abnormality caused by the medical sensors. The proposed work first perform the abnormality detection on the sensor data using the HMM based on baum-welch algorithm in which the normal data is separated from abnormal data followed by classifying the abnormal data as critical patient data or sensor fault data using the SVM. Here the proposed work efficiently performs fault diagnosis with an overall accuracy of 99.94% which is 0.59% better than the existing SVM model. And also a comparison is made between the hybrid approach and the existing ML algorithms in terms of recall and F1-score where the proposed approach outperforms the other algorithms with a recall value of 100% and F1-score of 99.7%.

First PACS‐integrated artificial intelligence‐based software tool for rapid and fully automatic analysis of body composition from CT in clinical routine

AbstractBackgroundTo externally evaluate the first picture archiving communications system (PACS)‐integrated artificial intelligence (AI)‐based workflow, trained to automatically detect a predefined computed tomography (CT) slice at the third lumbar vertebra (L3) and automatically perform complete image segmentation for analysis of CT body composition and to compare its performance with that of an established semi‐automatic segmentation tool regarding speed and accuracy of tissue area calculation.MethodsFor fully automatic analysis of body composition with L3 recognition, U‐Nets were trained (Visage) and compared with a conventional image segmentation software (TomoVision). Tissue was differentiated into psoas muscle, skeletal muscle, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Mid‐L3 level images from randomly selected DICOM slice files of 20 CT scans acquired with various imaging protocols were segmented with both methods.ResultsSuccess rate of AI‐based L3 recognition was 100%. Compared with semi‐automatic, fully automatic AI‐based image segmentation yielded relative differences of 0.22% and 0.16% for skeletal muscle, 0.47% and 0.49% for psoas muscle, 0.42% and 0.42% for VAT and 0.18% and 0.18% for SAT. AI‐based fully automatic segmentation was significantly faster than semi‐automatic segmentation (3 ± 0 s vs. 170 ± 40 s, P < 0.001, for User 1 and 152 ± 40 s, P < 0.001, for User 2).ConclusionRapid fully automatic AI‐based, PACS‐integrated assessment of body composition yields identical results without transfer of critical patient data. Additional metabolic information can be inserted into the patient's image report and offered to the referring clinicians.

An Intelligent BAN Routing Mechanism for Transferring Remote Patient Monitoring Data using K Means Clustering

An intelligent Body Area Routing (BAN) routing mechanism for remote patient monitoring has been proposed in this paper. In case of remote patient monitoring different level of care and attentions have to be provided to the patient depending upon their criticality level. So in this proposed model patients are being categorized as Extremely Critical, Most Critical, Critical, Moderate and Low Risk using the machine learning technique- K means clustering. At the same time most competent route has to be selected according to the patient level of criticality. The nodes taking part in the routing are also being categorized as Extremely Competent, Most Competent, Competent, Moderate and Least Competent considering Hop Count, Congestion Level, Energy Level and Priority using K means clustering as well. Then mapping from patient cluster to node cluster to route the data following that the extremely critical patient data would be routed through extremely competent nodes. The proposed model can be an effective approach for monitoring remote patient in an optimal way.

Self-heat controlling energy efficient OPOT routing protocol for WBAN

Recent technological advancements in miniaturization of sensor and wireless communication lead to development of Wireless Body Area Networks (WBAN). It is similar to Wireless Sensor Networks but mainly focuses on health care applications to monitor the health condition of patient continuously. It consists of implantable and wearable computing devices placed inside or outside the surface of human body for sensing and data communication. Due to continuous operation, the sensor node introduces electromagnetic radiations which causes damage to delicate human tissues as well as degrades the performance of the network. In addition, WBAN data are sensitive to delay and it is necessary to send critical patient data to the remote server in a timely manner to protect patient’s life. However, alternating the routing path of critical data leads to collision, packet loss, high power consumption, maximum delay and reduced network life time. In this paper, Optimum Path Optimum Temperature Routing Protocol is introduced to address the above issues. The proposed protocol chooses optimum routing path by determining the temperature of sensor nodes and by defining two threshold limits (minimum and maximum). It also considers the critical data signals to be sent when the temperature of node exceeds the admissible threshold limit. The obtained simulation results are compared with conventional routing protocols and was analyzed that the proposed protocol has decreased delay, minimum energy, reduced power, uniform temperature distribution and maximum lifetime of sensor node.

Fuzzy Assessment of Health Information System Users’ Security Awareness

Health information systems (HIS) are a specific area of information systems (IS), where critical patient data is stored and quality health service is only realized with the correct use and efficient dissemination of this data to health workers. Therefore, a balance needs to be established between the levels of security and flow of information on HIS. Instead of implementing higher levels and further mechanisms of control to increase the security of HIS, it is preferable to deal with the arguably weakest link on HIS chain with respect to security: HIS users. In order to provide solutions and approaches for transforming users to the first line of defense in HIS but also to employ capable and appropriate candidates from the pool of newly graduated students, it is important to assess and evaluate the security awareness levels and characteristics of these existing and future users. This study aims to provide a new perspective to understand the phenomenon of security awareness of HIS users with the use of fuzzy analysis, and to assess the present situation of current and future HIS users of a leading medical and educational institution of Turkey, with respect to their security characteristics based on four different security scales. The results of the fuzzy analysis, the guide on how to implement this fuzzy analysis to any health institution and how to read and interpret these results, together with the possible implications of these results to the organization are provided.

A Randomized Controlled Trial Comparing Health and Quality of Life of Lung Transplant Recipients Following Nurse and Computer-Based Triage Utilizing Home Spirometry Monitoring

Lung transplantation is now a standard intervention for patients with advanced lung disease. Home monitoring of pulmonary function and symptoms has been used to follow the progress of lung transplant recipients in an effort to improve care and clinical status. The study objective was to determine the relative performance of a computer-based Bayesian algorithm compared with a manual nurse decision process for triaging clinical intervention in lung transplant recipients participating in a home monitoring program. This randomized controlled trial had 65 lung transplant recipients assigned to either the Bayesian or nurse triage study arm. Subjects monitored and transmitted spirometry and respiratory symptoms daily to the data center using an electronic spirometer/diary device. Subjects completed the Short Form-36 (SF-36) survey at baseline and after 1 year. End points were change from baseline after 1 year in forced expiratory volume at 1 s (FEV1) and quality of life (SF-36 scales) within and between each study arm. There were no statistically significant differences between groups in FEV1 or SF-36 scales at baseline or after 1 year.: Results were comparable between nurse and Bayesian system for detecting changes in spirometry and symptoms, providing support for using computer-based triage support systems as remote monitoring triage programs become more widely available. The feasibility of monitoring critical patient data with a computer-based decision system is especially important given the likely economic constraints on the growth in the nurse workforce capable of providing these early detection triage services.

Abstract WP334: The Positive Impact of Role Definition and Communication on Door to Needle Times in Acute Stroke Patients Receiving Intravenous Alteplase

Background and Issues: Intravenous IV t-PA (IV t-PA) is indicated for the management of acute stroke in adults for improving neurological recovery and reducing the incidence of disability. The decision making process prior to administration of IV t-PA is complex and requires analysis of critical patient data to ensure safe administration. Communication of patient data is shared among many different departments and individual team members. The goal of administering IV t-PA within 60 minutes of patient arrival is heavily dependent upon the shared knowledge of this goal and the required patient data necessary for the treatment decision. From January 2011 through March 2012, 60 percent (76 of 127 patients) of our IV t-PA patients received treatment within 60 minutes. Our median door to treatment time remained at 58 minutes for the same 15 months. Purpose: The purpose of our team was to identify role responsibilities and points of essential communication of information to meet a goal of 75 percent of eligible patients to safely receive IV t-PA within 60 minutes of presentation to the hospital. Methods: Analysis of patients receiving IV t-PA during 2011 revealed 64.8 percent of TPA was administration during late afternoon and evening hours when stroke team resources were most lean. The importance of communication between the emergency department staff and responding stroke team was identified. After flow-charting the process, responsibilities for key processes and intentional points of communication required between team members were defined without regard to time of day stroke patients present to the hospital. Each department received education of their responsibilities. Results: In the first quarter after staff education and acknowledgement of their roles and required points of communication, 68.4 percent (13 of 19) of our IV t-PA patients received treatment within the goal of 60 minutes. The median time from patient presentation to IV t-PA administration dropped to 49 minutes suggesting decrease in variability of the process. Conclusion: Defining role responsibilities to ensure effective communication among stroke team members improves time to treatment decisions in eligible stroke patients.

Utilizing a Test Lab For Wireless Medical Devices

Changes in healthcare suggest that more and more medical devices will begin to utilize the information technology (IT) network infrastructure in the hospital, particularly the wireless network. Due to the increased risk of operating medical devices on the converged wireless IT network, there are multiple steps required to safely and effectively implement these types of devices. A key component of the implementation should be to perform testing of wireless devices for interference and functionality. In order to perform this testing, development of a test environment within the hospital is required. While recent focus has been on electromagnetic interference and the risk assessment and mitigation via IEC 80001-1— the new standard for the application of risk management for IT networks incorporating medical devices—more progress is needed in the development of a test lab and performance of testing within the hospital environment. There are many potential benefits of deploying medical devices on the wireless network; however, there are multiple risks, including loss of data or missed patient alarm notification due to a loss of wireless network connectivity. Testing can be vital in identifying and developing mitigations for these risks. Creating the Lab In order to create a test lab, a location first must be selected. In theory, an ideal wireless test environment would be shielded from all external sources of radio frequency (RF) interference. To achieve this goal, physical space and a substantial budget would be required. A stand-alone wireless network infrastructure would have to be developed in this shielded space to enable the connection and testing of any wireless medical devices. This type of test environment is impractical for clinical engineering use due to resource constraints and the inadequacy for realistic simulation of the true deployment environment. A more realistic and beneficial location to create the test lab would be a clinical engineering shop or a storage area in the basement of the hospital. The value of this type of location is that the physical space is relatively distant from clinical floors, thereby limiting the interference between the current patient-care equipment and the test lab and reducing the potential risk to either the device under test or to the devices on the clinical floor. It is also advantageous to be in the hospital in order to utilize a segregated portion of the network infrastructure that is already in place. Also, although a test lab in this environment would not be totally isolated About the Author

Mass Casualty Tracking with Air Traffic Control Methodologies

An intrahospital casualty throughput system modeled after air traffic control (ATC) tracking procedures was tested in mass casualty exercises. ATC uses a simple tactile process involving informational progress strips representing each aircraft, which are held in bays representing each stage of flight to prioritize and manage aircraft. These strips can be reordered within the bays to indicate a change in priority of aircraft sequence. In this study, a similar system was designed for patient tracking. We compared the ATC model and traditional casualty tracking methods of paper and clipboard in 18 four-hour casualty scenarios, each with 5 to 30 mock casualties. The experimental and control groups were alternated to maximize exposure and minimize training effects. Results were analyzed with Mann-Whitney statistical analysis with p value < 0.05 (two-sided). The ATC method had significantly (p = 0.017) fewer errors in critical patient data (eg, name, social security number, diagnosis). Specifically, the ATC method better tracked the mechanism of injury, working diagnosis, and disposition of patients. The ATC method also performed considerably better with patient accountability during mass casualty scenarios. Data strips were comparable with the control method in terms of ease of use. In addition, participants preferred the ATC method to the control (p = 0.003) and preferred using the ATC method (p = 0.003) to traditional methods in the future. The ATC model more effectively tracked patient data with fewer errors when compared with the clipboard method. Application of these principles can enhance trauma management and can have application in civilian and military trauma centers and emergency rooms.

Improving access to critical patient data

Gillian Braunold outlines the aims of the electronic summary care record being piloted in a number of PCTs in England, and explains the measures put in place to protect access to patient information

A Secure Mobile Multimedia System to Assist Emergency Response Teams

Long wait times after injury and greater distances to travel between accident scenes and medical facilities contribute to increased, possibly unnecessary deaths. This paper describes a mobile emergency system aimed at reducing mortality by improving the readiness of hospital personnel, therefore allowing for more efficient treatment procedures to be performed when the victim arrives. The system is designed to provide a secure transmission of voice, medical data, and video in real-time over third-generation cellular networks. Test results obtained on a commercial network under real-life conditions demonstrate the ability to effectively transmit medical data over 3G networks, making them a viable option available to healthcare professionals.

Theranostics Health: personalized therapy and diagnosis today.

Theranostics Health is a young company using mature proprietary technology to make personalized medicine possible today. The firm provides pharmaceutical scientists, clinical trial clinicians and treating physicians with highly detailed portraits of protein drug target pathways and critical patient data about drug activity, selectivity and specificity. Its assays and therapeutic tools provide unprecedented cancer treatment and drug response information and show strong prospects for application to a wide range of disease indications. Theranostics' leadership believes that its products and services will have major impact on individualized therapeutic efficacy and treatment toxicity, while reducing treatment and drug-development costs and expediting the introduction of new pharmaceutical solutions.

231: Discrepancies Between the Prehospital and Hospital Record: What is the Value of the Trip Sheet?

Critical patient data, such as abnormal vital signs, have relevance when noted in the prehospital (PH) environment, even if they normalize in the emergency department (ED). Prehospital medical records or “trip sheets” (TS) may detail these data, but are not always required to be delivered with the patient. We evaluated the extent to which the trip sheet contains prehospital clinical information that is not recorded in the emergency/hospital record.

Decisional strategies for the attribution of emotional distress in primary care.

In primary care the General Health Questionnaire (GHQ) is used to provide an independent assessment of probable caseness of psychological disorder against which to test the ability of the general practitioner (GP) to recognize patients with current emotional problems. The aim of the present study was to identify those clinical and psychosocial data on patients that increase the likelihood of GPs' attribution of emotional distress (GP model) and those that predict patients' emotional distress as defined by the GHQ-12 (GHQ model). The associations were explored using a classification tree technique (CHAID) and compared using bivariate logistic regression. Six GPs and 444 primary care patients took part. The accuracy indices of the hierarchical GP and GHQ models were 72% and 69% respectively. The availability of information on patients' psychopharmacological and psychiatric/psychological treatment in the last year was the most important predictor of attribution. Occupational, financial and housing problems and life events of loss were the most important predictors of the GHQ-12 case definition. The overall accuracy of the bivariate model was 73%. Compared with the GHQ-12, GPs gave significantly more importance to psychiatric treatment, psychopharmacological drug use and chronic illness. The findings suggest that to improve the detection of current emotional distress in primary care patients GPs should pay foremost and systematic attention to social problems and recent life events of loss. These problems are important clues for the possible presence of emotional distress, whereas critical patient data, in particular psychiatric history and psychopharmacological treatment, increase the probability of attribution errors.

Hierarchical data security in a Query-By-Example interface for a shared database

Whenever a shared database resource, containing critical patient data, is created, protecting the contents of the database is a high priority goal. This goal can be achieved by developing a Query-By-Example (QBE) interface, designed to access a shared database, and embedding within the QBE a hierarchical security module that limits access to the data. The security module ensures that researchers working in one clinic do not get access to data from another clinic. The security can be based on a flexible taxonomy structure that allows ordinary users to access data from individual clinics and super users to access data from all clinics [1]. All researchers submit queries through the same interface and the security module processes the taxonomy and user identifiers to limit access. Using this system, two different users with different access rights can submit the same query and get different results thus reducing the need to create different interfaces for different clinics and access rights.