Utilization of automated location tracking for clinical workflow analytics and visualization

abstract: The analysis of clinical workflow offers many challenges to clinical stakeholders and researchers, especially in environments characterized by dynamic and concurrent processes. Workflow analysis in such environments is essential for monitoring performance and finding bottlenecks and sources of error. Clinical workflow analysis has been enhanced with the inclusion of modern technologies. One such intervention is automated location tracking which is a system that detects the movement of clinicians and equipment. Utilizing the data produced from automated location tracking technologies can lead to the development of novel workflow analytics that can be used to complement more traditional approaches such as ethnography and grounded-theory based qualitative methods. The goals of this research are to: (i) develop a series of analytic techniques to derive deeper workflow-related insight in an emergency department setting, (ii) overlay data from disparate sources (quantitative and qualitative) to develop strategies that facilitate workflow redesign, and (iii) incorporate visual analytics methods to improve the targeted visual feedback received by providers based on the findings. The overarching purpose is to create a framework to demonstrate the utility of automated location tracking data used in conjunction with clinical data like EHR logs and its vital role in the future of clinical workflow analysis/analytics. This document is categorized based on two primary aims of the research. The first aim deals with the use of automated location tracking data to develop a novel methodological/exploratory framework for clinical workflow. The second aim is to overlay the quantitative data generated from the previous aim on data from qualitative observation and shadowing studies (mixed methods) to develop a deeper view of clinical workflow that can be used to facilitate workflow redesign. The final sections of the document speculate on the direction of this work where the potential of this research in the creation of fully integrated clinical environments i.e. environments with state-of-the-art location tracking and other data collection mechanisms, is discussed. The main purpose of this research is to demonstrate ways by which clinical processes can be continuously monitored allowing for proactive adaptations in the face of technological and process changes to minimize any negative impact on the quality of patient care and provider satisfaction.Dissertation/ThesisDoctoral Dissertation Biomedical Informatics 201

A Priority-based Fair Queuing (PFQ) Model for Wireless Healthcare System

Healthcare is a very active research area, primarily due to the increase in the elderly population that leads to increasing number of emergency situations that require urgent actions. In recent years some of wireless networked medical devices were equipped with different sensors to measure and report on vital signs of patient remotely. The most important sensors are Heart Beat Rate (ECG), Pressure and Glucose sensors. However, the strict requirements and real-time nature of medical applications dictate the extreme importance and need for appropriate Quality of Service (QoS), fast and accurate delivery of a patient’s measurements in reliable e-Health ecosystem. As the elderly age and older adult population is increasing (65 years and above) due to the advancement in medicine and medical care in the last two decades; high QoS and reliable e-health ecosystem has become a major challenge in Healthcare especially for patients who require continuous monitoring and attention. Nevertheless, predictions have indicated that elderly population will be approximately 2 billion in developing countries by 2050 where availability of medical staff shall be unable to cope with this growth and emergency cases that need immediate intervention. On the other side, limitations in communication networks capacity, congestions and the humongous increase of devices, applications and IOT using the available communication networks add extra layer of challenges on E-health ecosystem such as time constraints, quality of measurements and signals reaching healthcare centres. Hence this research has tackled the delay and jitter parameters in E-health M2M wireless communication and succeeded in reducing them in comparison to current available models. The novelty of this research has succeeded in developing a new Priority Queuing model ‘’Priority Based-Fair Queuing’’ (PFQ) where a new priority level and concept of ‘’Patient’s Health Record’’ (PHR) has been developed and integrated with the Priority Parameters (PP) values of each sensor to add a second level of priority. The results and data analysis performed on the PFQ model under different scenarios simulating real M2M E-health environment have revealed that the PFQ has outperformed the results obtained from simulating the widely used current models such as First in First Out (FIFO) and Weight Fair Queuing (WFQ). PFQ model has improved transmission of ECG sensor data by decreasing delay and jitter in emergency cases by 83.32% and 75.88% respectively in comparison to FIFO and 46.65% and 60.13% with respect to WFQ model. Similarly, in pressure sensor the improvements were 82.41% and 71.5% and 68.43% and 73.36% in comparison to FIFO and WFQ respectively. Data transmission were also improved in the Glucose sensor by 80.85% and 64.7% and 92.1% and 83.17% in comparison to FIFO and WFQ respectively. However, non-emergency cases data transmission using PFQ model was negatively impacted and scored higher rates than FIFO and WFQ since PFQ tends to give higher priority to emergency cases. Thus, a derivative from the PFQ model has been developed to create a new version namely “Priority Based-Fair Queuing-Tolerated Delay” (PFQ-TD) to balance the data transmission between emergency and non-emergency cases where tolerated delay in emergency cases has been considered. PFQ-TD has succeeded in balancing fairly this issue and reducing the total average delay and jitter of emergency and non-emergency cases in all sensors and keep them within the acceptable allowable standards. PFQ-TD has improved the overall average delay and jitter in emergency and non-emergency cases among all sensors by 41% and 84% respectively in comparison to PFQ model

A Team-Based Approach to Studying Complex Healthcare Processes

Communication is a critical aspect of clinical work. In 2010, the Joint Commission (JC) found that gaps in communication were among leading factors contributing to medical errors. Healthcare processes, such as patient discharge, depend on interdisciplinary communication to be successful. Electronic health records (EHRs) have the potential to facilitate communication and information sharing between interdisciplinary care team members; however, challenges remain in designing tools for team-based care and questions remain in understanding how EHRs impact interdisciplinary team communication. This dissertation focuses on understanding how EHRs can be designed to support communication and information sharing within interdisciplinary patient care teams. The first aim of the dissertation investigated how EHRs impact interdisciplinary clinical teams’ communication, shared mental models, and information sharing activities. The results showed that implementing new EHR tools appeared to have little impact on communication and shared mental models, but new information sharing activities mediated by EHR developed. These changes and lack thereof suggest that new EHR tools will be specifically needed to facilitate interdisciplinary team information sharing activities. The second aim of the dissertation investigates the information sharing activities and information needs of interdisciplinary team members during patient discharge. The results showed that the information clinicians sought out during discharge depended on the roles that person played as well as the progress of the discharge process. Future EHR tools should be aware of how patient care teams are progressing through the patient discharge process in order to provide information contextualized to their current tasks. In conclusion, interdisciplinary team communication and information sharing remain poorly supported by current EHRs and new tools designed specifically for interdisciplinary teams should provide information based on the completion of team activities

(Re)defining Healthcare Quality: Metrics, Protocols, and the Restructuring of Care Delivery

Healthcare organizations in the United States are increasingly evaluated by systems that link quality measurement with regulatory and payment approaches. Operationalized through quality measurement, quality is affirmed as the basis for improving healthcare processes, outcomes, and health systems broadly. At the same time, electronic health record (EHR) and other information technology (IT) systems aimed to make care safer and more efficient, have become standard tools in healthcare settings. Galvanized by these technical advancements, quality metrics are considered crucial components of ensuring accountability for improved health outcomes and care equity.This dissertation aims to understand healthcare quality measurement by investigating how systems of quality measurement are implemented in clinical spaces, particularly how they structure care delivery and define quality. This dissertation offers a qualitative study of the organizational and structural elements of quality and quality measurement. I conducted ethnographic observation (15 months) and interviews (n=31) at a 600-bed, acute-care hospital in New York City, which I call Borough Hospital. My analysis utilizes the accounts of healthcare clinicians and administrators, and their experiences navigating care delivery and quality in their hospital. Through this analysis, I investigate the variable meanings of quality, processes of measuring quality, and the conditions under which care is delivered at Borough Hospital. Using the qualitative analytic methods of grounded theory and situational analysis, I deconstruct the ways in which quality and quality measurement are constructed as neutral and inevitable, how care delivery is increasingly protocolized to ensure quality, and the ensuing distancing of quality care away from the bedside. Meeting and complying with quality metrics require specific clinical care protocols and extensive documentation for reporting. These new requirements have changed the roles and responsibilities of frontline clinicians, shifting the organization of labor in the clinic. I argue that measurement-based, clinical protocols that rely on surveillance and abstracted documentation data increasingly standardize processes of quality care and distance care—that is, clinician labor— away from the bedside. The findings of this dissertation suggest a tendency toward protocolization and narrowing definitions of quality, which can be extended into other hospital systems particularly in light of widespread consolidation. I argue that administrative prioritization of quality measurement, and in particular quality metrics, necessitates the protocolization of complex healthcare processes and increasingly relies on data-driven decision-making. Ultimately, I suggest quality care has been (re)defined by measurement-based, clinical protocols, which I call abstracted surveillance protocols, that increasingly standardize and constrain care delivery

Technology Target Studies: Technology Solutions to Make Patient Care Safer and More Efficient

Presents findings on technologies that could enhance care delivery, including patient records and medication processes; features and functionality nurses require, including tracking, interoperability, and hand-held capability; and best practices

Clinical Utility of Advanced Microbiology Testing Tools

Advanced microbiology technologies are rapidly changing our ability to diagnose infections, improve patient care, and enhance clinical workflow. These tools are increasing the breadth, depth, and speed of diagnostic data generated per patient, and testing is being moved closer to the patient through rapid diagnostic technologies, including point-of-care (POC) technologies. While select stakeholders have an appreciation of the value/importance of improvements in the microbial diagnostic field, there remains a disconnect between clinicians and some payers and hospital administrators in terms of understanding the potential clinical utility of these novel technologies. Therefore, a key challenge for the clinical microbiology community is to clearly articulate the value proposition of these technologies to encourage payers to cover and hospitals to adopt advanced microbiology tests. Specific guidance on how to define and demonstrate clinical utility would be valuable. Addressing this challenge will require alignment on this topic, not just by microbiologists but also by primary care and emergency room (ER) physicians, infectious disease specialists, pharmacists, hospital administrators, and government entities with an interest in public health. In this article, we discuss how to best conduct clinical studies to demonstrate and communicate clinical utility to payers and to set reasonable expectations for what diagnostic manufacturers should be required to demonstrate to support reimbursement from commercial payers and utilization by hospital systems

Refining Triage Documentation Practices in a Metropolitan Emergency Department

Problem California ranks ninth nationwide for its lengthy emergency department wait times, presenting a pressing challenge for healthcare facilities. Context This quality improvement project, set in the emergency department of a large urban hospital in the Bay Area, aimed to address this issue by targeting workflow efficiency through the reduction of triage times. Intervention The intervention centered on implementing changes to the triage documentation, informed by staff feedback obtained through an opinion survey. Proposed modifications included the elimination of redundant questions, consolidation of related categories, and a logical reorganization of triage topics. Measures Key measures utilized in the project included triage times and pre- and post-intervention nursing opinion surveys. Results Despite encountering time constraints and other limitations, the intervention was not fully implemented, and post-intervention data collection did not occur. However, pre-implementation surveys revealed strong staff support for the proposed changes, indicating the potential efficacy of the intervention. Conclusion Future recommendations for this project include prioritizing the implementation of the intervention and conducting post-implementation data collection to facilitate meaningful comparisons and further inform improvement efforts

HCI for health and wellbeing: challenges and opportunities

In terms of Human–Computer Interaction, healthcare presents paradoxes: on the one hand, there is substantial investment in innovative health technologies, particularly around “big data” analytics and personal health technologies; on the other hand, most interactive health technologies that are currently deployed at scale are difficult to use and few innovative technologies have achieved significant market penetration. We live in a time of change, with a shift from care being delivered by professionals towards people being expected to be actively engaged and involved in shared decision making. Technically, this shift is supported by novel health technologies and information resources; culturally, the pace of change varies across contexts. In this paper, I present a “space” of interactive health technologies, users and uses, and interdependencies between them. Based on a review of the past and present, I highlight opportunities for and challenges to the application of HCI methods in the design and deployment of digital health technologies. These include threats to privacy, patient trust and experience, and opportunities to deliver healthcare and empower people to manage their health and wellbeing in ways that better fit their lives and values