Technology Acceptance, Acceptabilty and Appropriation in Professionnal Bureaucracies : The Case of RFID for Improving Mobile Assets Management in Hospitals

RÉSUMÉ : Les hôpitaux, même ceux de petite taille, peuvent gérer sur une base quotidienne plusieurs milliers d’actifs fixes et mobiles. Les actifs mobiles sont très diversifiés et incluent des pompes à infusion, du matériel chirurgical, des électrocardiogrammes, des machines portables à rayons X, des défibrillateurs, etc. Ces actifs circulent en permanence entre les différents services et les divers départements. Pratiquement tous les patients dépendent d'un ou plusieurs actifs mobiles lors de leur hospitalisation. Ces actifs sont également indispensables à la prestation des soins de santé et le personnel clinique consacre une partie importante de leur temps pour chercher ces actifs lorsque requis. L'incapacité de retrouver ces actifs en cas d’urgence peut mettre la vie des patients en danger. La technologie RFID (Radio Frequency Identification) a le potentiel de retracer et d’effectuer le suivi, et ce, de façon unique et transparente, les actifs mobiles et, par conséquent, d’en améliorer leur gestion dans les hôpitaux. Comparé à d’autres secteurs d’activité, le secteur de la santé adopte RFID à un rythme beaucoup plus lent, ce qui se traduit par un nombre limité d'études empiriques portant sur l’implantation de RFID dans ce secteur. Cette thèse se propose donc de contribuer à ce vide empirique par une analyse en profondeur d’une implantation réelle de RFID. Cette implantation vise à améliorer la gestion d'un type d’actifs mobiles, nommément les pompes à infusion dans un hôpital. Les données empiriques ont été recueillies pendant une période de 25 mois, de la phase de préfaisabilité jusqu’à la phase de post-implantation. Huit organisations (incluant l'hôpital qui est le principal site d'observation) et 35 participants ont été impliqués. Les résultats de la recherche peuvent être résumés comme suit. À la question, pourquoi RFID est implanté? La réduction des inefficacités existantes liées à la gestion des actifs mobiles en est la principale raison. De plus, la familiarité avec les technologies de l’information au sein de l'hôpital, la compatibilité de l’infrastructure existante (l'hôpital est presque 100% Wi-Fi) et l'expérience des partenaires technologiques sont des facteurs positifs reliés à l’implantation RFID. Comment l’implantation RFID est-elle effectuée? Les résultats montrent que le processus d’implantation est fortement itératif : les participants reviennent en effet sur les phases précédentes et modifient les décisions approuvées antérieurement. L'amélioration continue des services de soins est sans aucun doute la préoccupation principale exprimée par tous les participants de l'hôpital. Toutefois, les attentes et les exigences diffèrent entre les différents groupes de participants. Les résultats démontrent un clivage entre les points de vue de l’administration et ceux du côté clinique. Des divergences sont notées entre les infirmières et les médecins, et, entre les techniciens de l'hôpital (responsables des TIC, ingénieurs biomédicaux, et spécialistes de la maintenance) et les administrateurs. Les enjeux les plus importants ne sont pas technologiques, mais sont principalement organisationnels, ce qui semble découler de la présence de points de vue divergents. Est-ce que la RFID améliore la gestion des actifs mobiles? Les résultats suggèrent que les avantages identifiés et évalués lors l’implantation de RFID appartiennent aux catégories suivantes: amélioration de la visibilité des actifs, augmentation de l'efficacité opérationnelle, réduction de certains coûts et émergence de processus intelligents. Ce dernier point apparait comme particulièrement important. Les processus intelligents misent principalement sur les capacités d'auto-identification et de sensibilité au contexte (context-awareness) de RFID, sur le changement automatique de statuts, et sur la mise à jour automatique des applications d’hôpital (par exemple, WMS). Les résultats démontrent également que les processus intelligents améliorent la planification et la prise de décision. Est-ce que les caractéristiques intrinsèques des organisations dans lesquelles la technologie RFID est envisagée posent des contraintes à son implantation? Les hôpitaux, qualifiés de bureaucraties professionnelles, constituent un ensemble unique de contraintes dont on doit tenir compte lors d’une implantation RFID. En particulier, l'inertie, la complexité et la rigidité organisationnelles ne sont pas favorables à des changements à grande échelle dans l’hôpital et affectent la façon dont RFID est implanté. En outre, l'existence d'une structure à double pouvoir et les pièges liés à une culture forte (culture entrapment)ont un impact profond sur l'importance des avantages découlant de RFID. Est-ce que l’acceptation de la technologie, son acceptabilité et son appropriation représentent des concepts clés pour comprendre l’implantation de la RFID? Ces trois concepts ont été explorés lors de cette recherche et ont conduit à deux observations principales. Tout d'abord, on peut affirmer que si la technologie est acceptée, acceptable et appropriée, elle est utilisée, de façon partielle ou plus large. Par extension, l'acceptation, l'acceptabilité et l'appropriation pourraient être importantes non seulement pour expliquer l'ampleur de l'utilisation d'une technologie (utilisation partielle par rapport à la pleine utilisation), mais aussi pour expliquer les raisons pour lesquelles une technologie a été initialement adoptée, puis ensuite rejetée. Deuxièmement, les résultats empiriques ne confirment pas un ordre chronologique entre ces trois concepts. Par exemple, l'appropriation ne suit pas l'acceptation, même au début de l’implantation. Au contraire, l'acceptation, l'acceptabilité et l'appropriation coexistent à tout moment pendant le processus d’implantation. Cependant, l’ordre chronologique joue quand même un rôle puisque les niveaux d'acceptation, l'acceptabilité et l'appropriation varient au fil du temps. En outre, ces trois concepts sont sensibles à la fois à la technologie (dans ce cas, RFID) et au contexte dans lequel cette technologie est utilisée (l'hôpital), qui continuent de leur côté à changer au fil du temps. La thèse se termine en examinant les limites de la recherche, en proposant quelques pistes de recherche. Les contributions de cette thèse peuvent être pertinentes pour les chercheurs, les décideurs du secteur de la santé, les administrateurs d'hôpitaux, et les spécialistes et consultants en TI.----------ABSTRACT : Hospitals, even small ones, handle on a daily basis several thousands of mobile and fixed assets. Mobile assets are very diverse, ranging from infusion pumps, surgical equipment, electrocardiograms, portable x-ray machines, defibrillators to wheelchairs and rotate constantly between different medical wards. Since virtually every patient depends on one or more mobile assets during his or her hospital stay, they are also indispensable in healthcare delivery. Clinical staff spends a significant share of their working time searching for these essential, but commonly misplaced assets. Locating mobile assets is not only a time consuming activity, but the inability to find them when needed is remarkably costly, and possibly life threatening. RFID (Radio Frequency Identification) holds the potential to uniquely and seamlessly track and trace mobile assets and, thus, to improve mobile asset management in hospitals. Compared to other sectors, healthcare organizations adopt RFID at a much slower pace and only a limited number of empirical studies address RFID adoption and implementation in the context of healthcare. This thesis intends to contribute the research arena by analysing a real-life RFID implementation in order improve the management activities of one type of mobile assets, namely infusion pumps in hospital settings. The research focuses on a real-life RFID implementation in one European hospital. Empirical data was collected for a 25 month period from the pre-feasibility stage to post-implementation stage from eight organizations (including the hospital as the main observation site) and from thirty-five participants. Research results can be summarized as follows. To the question why RFID is implemented? The most straightforward answer is to reduce the existing inefficiencies related to mobile assets management. Technological preparedness and readiness drive RFID implementation: This includes familiarity with IT innovations within the hospital, compatibility with existing IT infrastructure (the hospital is almost 100% Wi-Fi enabled), and experience of technological partners with RFID implementation in various sectors. How RFID implementation is carried out? The answer seems to be through a highly iterative five stage process where participants revisited and modified previously agreed steps. The continuous improvement of care services was without a doubt the superseding concern expressed by all participants from the hospital. However, expectations and requirements differ among different groups of participants. The empirical evidence demonstrates not only a cleavage between the administrative and clinical perspectives, but also within the clinical perspective. Divergences run deep within each perspective (for instance, nurses vs. doctors) and between the technologists in the hospital (ICT managers, biomedical engineers, and maintenance specialists) and the administrators. The most significant issues related to such implementation are not technological but are mainly organizational, as they seem to arise from the presence of diverging perspectives. Does RFID really improve mobile assets management? Results suggest that the benefits identified and evaluated during the real life RFID implementation belong to the following broad categories: improving assets visibility, promoting operational efficiency, reducing costs and facilitating the emergence of intelligent processes. Intelligent processes are mainly derived from the RFID capabilities for auto-identification and context-awareness, process automatic status change, and automatic update in hospital’s enterprise applications (i.e. WMS). Results further demonstrate that intelligent processes improve planning and decision-making. Do the intrinsic characteristics of organizations play a role in RFID implementation? The very characteristics of hospitals, qualified as complex professional bureaucracies, constitute a unique set of constraints to be taken into account for RFID implementation. In particular, organizational inertia, complexity and inflexibility are not conductive to hospital-wide changes and affect how RFID is implemented. Moreover, the existence of a dual power structure and a tendency to culture entrapment may have a profound impact on the importance of the benefits derived from RFID. Do technology acceptance, acceptability and appropriation represent key concepts that should be considered to understand the implementation of RFID? These three concepts were explored in the research. This leads to two main observations. First, it could be stated that if technology is accepted, acceptable and appropriated, then it is fully used. By extension, acceptance, acceptability and appropriation could be significant not only in explaining the extent of use of a technology (partial use vs. full use), but also the reasons why a technology was initially adopted and then discarded. Second, empirical results reject the presence of a chronological order between the three concepts. For instance, appropriation does not follow acceptance, even initially. Rather, acceptance, acceptability and appropriation coexist at any time during the implementation process. However, chronology still matters since the levels of acceptance, acceptability and appropriation vary over time. Furthermore, these three concepts are sensitive to both the technology (in this case RFID) and to the context where it is use (the hospital), which are also changing over time. The thesis examines research limitations, proposes some research avenues and outlines contributions that may be relevant for researchers, healthcare policy makers, hospital administrators, IT specialists and IT consultants

Using an Educational Module and Simulation Learning Experience to Improve Medication Safety

The purpose of this evidence-based change in practice project was to provide nurses with an experiential learning opportunity, using simulation, to identify and report near miss events during the medication administration process related to patient-controlled analgesia (PCA) usage. Despite extensive in-service training on a Medical/Surgical (Med/Surg) floor in an acute care hospital, inconsistent, inaccurate and incomplete documentation with use of the new PCA pumps continued to be problematic. A conceptual framework of just culture was used with the quality improvement method of the Plan-Do-Study-Act (PDSA) cycle for testing change. Medication safety education was a valid andragogical strategy to decrease rates of medication errors and improve patient outcomes by identifying complex system issues that interfered with safe practices. The education program consisted of a series of self-learning modules, definitions of near miss events and medication errors; in addition a simulation learning experience was included. A needs assessment was conducted to help determine gaps in practice. Results of the survey demonstrated inconsistencies in the current practice of documenting vital signs on patients with a PCA in contrast to the existing policy and procedure; these results were shared with the staff nurses at a staff meeting and via email. Although no changes in care delivery were directly observed, the doctorate of nursing practice (DNP) student was able to reinforce the documentation requirements per the hospital’s policy

Low complexity system architecture design for medical Cyber-Physical-Human Systems (CPHS)

Cyber-Physical-Human Systems (CHPS) are safety-critical systems, where the interaction between cyber components and physical components can be influenced by the human operator. Guaranteeing correctness and safety in these highly interactive computations is challenging. In particular, the interaction between these three components needs to be coordinated collectively in order to conduct safe and effective operations. The interaction nevertheless increases by orders of magnitude the levels of complexity and prevents formal verification techniques, such as model checking, from thoroughly verifying the safety and correctness properties of systems. In addition, the interactions could also significantly increase human operators' cognitive load and lead to human errors. In this thesis, we focus on medical CPHS and examine the complexity from a safety angle. Medical CPHS are both safety-critical and highly complex, because medical staff need to coordinate with distributed medical devices and supervisory controllers to monitor and control multiple aspects of the patient's physiology. Our goal is to reduce and control the complexity by introducing novel architectural patterns, coordination protocols and user-centric guidance system. This thesis makes three major contributions for improving safety of medical CPHS. Reducing verification complexity: Formal verification is a promising technique to guarantee correctness and safety, but the high complexity significantly increases the verification cost, which is known as state space explosion problems. We propose two architectural patterns: Interruptible Remote Procedure Call (RPC) and Consistent View Generation and Coordination (CVGC) protocol to properly handle asynchronous communication and exceptions with low complexity. Reducing cyber-medical treatment complexity: Cyber medical treatment complexity is defined as the number of steps and time to perform a treatment and monitor the corresponding physiological responses. We propose treatment and workflow adaptation and validation protocols to semi-autonomously validate the preconditions and adapt the workflows to patient conditions, which reduces the complexity of performing treatments and following best practice workflows. Reducing human cognitive load complexity: Cognitive load (also called mental workload) complexity measures human memory and mental computation demand for performing tasks. We first model individual medical staff's responsibility and team interactions in cardiac arrest resuscitation and decomposed their overall task into a set of distinct cognitive tasks that must be specifically supported to achieve successful human-centered system design. We then prototype a medical Best Practice Guidance (BPG) system to reduce medical staff's cognitive load and foster adherence to best practice workflows. Our BPG system transforms the implementation of best practice medical workflow

Mobile Crowd Sensing in Edge Computing Environment

abstract: The mobile crowdsensing (MCS) applications leverage the user data to derive useful information by data-driven evaluation of innovative user contexts and gathering of information at a high data rate. Such access to context-rich data can potentially enable computationally intensive crowd-sourcing applications such as tracking a missing person or capturing a highlight video of an event. Using snippets and pictures captured from multiple mobile phone cameras with specific contexts can improve the data acquired in such applications. These MCS applications require efficient processing and analysis to generate results in real time. A human user, mobile device and their interactions cause a change in context on the mobile device affecting the quality contextual data that is gathered. Usage of MCS data in real-time mobile applications is challenging due to the complex inter-relationship between: a) availability of context, context is available with the mobile phones and not with the cloud, b) cost of data transfer to remote cloud servers, both in terms of communication time and energy, and c) availability of local computational resources on the mobile phone, computation may lead to rapid battery drain or increased response time. The resource-constrained mobile devices need to offload some of their computation. This thesis proposes ContextAiDe an end-end architecture for data-driven distributed applications aware of human mobile interactions using Edge computing. Edge processing supports real-time applications by reducing communication costs. The goal is to optimize the quality and the cost of acquiring the data using a) modeling and prediction of mobile user contexts, b) efficient strategies of scheduling application tasks on heterogeneous devices including multi-core devices such as GPU c) power-aware scheduling of virtual machine (VM) applications in cloud infrastructure e.g. elastic VMs. ContextAiDe middleware is integrated into the mobile application via Android API. The evaluation consists of overheads and costs analysis in the scenario of ``perpetrator tracking" application on the cloud, fog servers, and mobile devices. LifeMap data sets containing actual sensor data traces from mobile devices are used to simulate the application run for large scale evaluation.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Low-power Wearable Healthcare Sensors

Advances in technology have produced a range of on-body sensors and smartwatches that can be used to monitor a wearer’s health with the objective to keep the user healthy. However, the real potential of such devices not only lies in monitoring but also in interactive communication with expert-system-based cloud services to offer personalized and real-time healthcare advice that will enable the user to manage their health and, over time, to reduce expensive hospital admissions. To meet this goal, the research challenges for the next generation of wearable healthcare devices include the need to offer a wide range of sensing, computing, communication, and human–computer interaction methods, all within a tiny device with limited resources and electrical power. This Special Issue presents a collection of six papers on a wide range of research developments that highlight the specific challenges in creating the next generation of low-power wearable healthcare sensors

Modelling, optimisation and model predictive control of insulin delivery systems in Type 1 Diabetes Mellitus

Type 1 Diabetes Mellitus is a metabolic disease requiring lifelong treatment with exogenous insulin which significantly affects patient’s lifestyle. Therefore, it is of paramount importance to develop novel drug delivery techniques that achieve therapeutic efficacy and ensure patient safety with a minimum impact on their quality of life. Motivated by the challenge to improve the living standard of a diabetic patient, the idea of an artificial pancreas that mimics the endocrine function of a healthy pancreas has been developed in the scientific society. Towards this direction, model predictive control has been established as a very promising control strategy for blood glucose regulation in a system that is dominated by high intra- and inter-patient variability, long time delays, and presence of unknown disturbances such as diet, physical activity and stress levels. This thesis presents a framework for blood glucose regulation with optimal insulin infusion which consists of the following steps: 1. Development of a novel physiologically based compartmental model analysed up to organ level that describes glucose-insulin interactions in type 1 diabetes, 2. Derivation of an approximate model suitable for control applications, 3. Design of an appropriate control strategy and 4. In-silico validation of the closed loop control performance. The developed model’s accuracy and prediction ability is evaluated with data obtained from the literature and the UVa/Padova Simulator model, the model parameters are individually estimated and their effect on the model’s measured output, the blood glucose concentration, is identified. The model is then linearised and reduced to derive low-order linear approximations of the underlying system suitable for control applications. The proposed control design aims towards an individualised optimal insulin delivery that consists of a patient-specific model predictive controller, a state estimator, a personalised scheduling level and an open loop optimisation problem subjected to patient specific process model and constraints. This control design is modifiable to address the case of limited patient data availability resulting in an “approximation” control strategy. Both designs are validated in-silico in the presence of predefined, measured and unknown meal disturbances using both the proposed model and the UVa/Padova Simulator model as a virtual patient. The robustness of the control performance is evaluated in several conditions such as skipped meals, variability in the meal content, time and metabolic uncertainty. The simulation results of the closed loop validation studies indicate that the proposed control strategies can achieve promising glycaemic control as demonstrated by the study data. However, further prospective validation of the closed loop control strategy with real patient data is required.Open Acces

Data-driven resiliency assessment of medical cyber-physical systems

Advances in computing, networking, and sensing technologies have resulted in the ubiquitous deployment of medical cyber-physical systems in various clinical and personalized settings. The increasing complexity and connectivity of such systems, the tight coupling between their cyber and physical components, and the inevitable involvement of human operators in supervision and control have introduced major challenges in ensuring system reliability, safety, and security. This dissertation takes a data-driven approach to resiliency assessment of medical cyber-physical systems. Driven by large-scale studies of real safety incidents involving medical devices, we develop techniques and tools for (i) deeper understanding of incident causes and measurement of their impacts, (ii) validation of system safety mechanisms in the presence of realistic hazard scenarios, and (iii) preemptive real-time detection of safety hazards to mitigate adverse impacts on patients. We present a framework for automated analysis of structured and unstructured data from public FDA databases on medical device recalls and adverse events. This framework allows characterization of the safety issues originated from computer failures in terms of fault classes, failure modes, and recovery actions. We develop an approach for constructing ontology models that enable automated extraction of safety-related features from unstructured text. The proposed ontology model is defined based on device-specific human-in-the-loop control structures in order to facilitate the systems-theoretic causality analysis of adverse events. Our large-scale analysis of FDA data shows that medical devices are often recalled because of failure to identify all potential safety hazards, use of safety mechanisms that have not been rigorously validated, and limited capability in real-time detection and automated mitigation of hazards. To address those problems, we develop a safety hazard injection framework for experimental validation of safety mechanisms in the presence of accidental failures and malicious attacks. To reduce the test space for safety validation, this framework uses systems-theoretic accident causality models in order to identify the critical locations within the system to target software fault injection. For mitigation of safety hazards at run time, we present a model-based analysis framework that estimates the consequences of control commands sent from the software to the physical system through real-time computation of the system’s dynamics, and preemptively detects if a command is unsafe before its adverse consequences manifest in the physical system. The proposed techniques are evaluated on a real-world cyber-physical system for robot-assisted minimally invasive surgery and are shown to be more effective than existing methods in identifying system vulnerabilities and deficiencies in safety mechanisms as well as in preemptive detection of safety hazards caused by malicious attacks

Model-Based Analysis of User Behaviors in Medical Cyber-Physical Systems

Human operators play a critical role in various Cyber-Physical System (CPS) domains, for example, transportation, smart living, robotics, and medicine. The rapid advancement of automation technology is driving a trend towards deep human-automation cooperation in many safety-critical applications, making it important to explicitly consider user behaviors throughout the system development cycle. While past research has generated extensive knowledge and techniques for analyzing human-automation interaction, in many emerging applications, it remains an open challenge to develop quantitative models of user behaviors that can be directly incorporated into the system-level analysis. This dissertation describes methods for modeling different types of user behaviors in medical CPS and integrating the behavioral models into system analysis. We make three main contributions. First, we design a model-based analysis framework to evaluate, improve, and formally verify the robustness of generic (i.e., non-personalized) user behaviors that are typically driven by rule-based clinical protocols. We conceptualize a data-driven technique to predict safety-critical events at run-time in the presence of possible time-varying process disturbances. Second, we develop a methodology to systematically identify behavior variables and functional relationships in healthcare applications. We build personalized behavior models and analyze population-level behavioral patterns. Third, we propose a sequential decision filtering technique by leveraging a generic parameter-invariant test to validate behavior information that may be measured through unreliable channels, which is a practical challenge in many human-in-the-loop applications. A unique strength of this validation technique is that it achieves high inter-subject consistency despite uncertain parametric variances in the physiological processes, without needing any individual-level tuning. We validate the proposed approaches by applying them to several case studies

Impact of Sensing and Actuation Characteristics on Artificial Pancreas Design

Type 1 diabetes mellitus (T1DM) is a chronic disease characterized by the body’s inability to produce insulin, leading to chronically high blood glucose (BG) concentrations. T1DM is treated by frequent self-administration of insulin based on BG measurements; however, there is a fine line between too little and too much insulin, and an overdose can lead to a dangerous drop in BG. The artificial pancreas (AP), consisting of a glucose sensor, an insulin pump, and a feedback control algorithm, will replace self-treatment by automatically calculating and delivering insulin dosages based on continuous glucose measurements. Many iterations of the AP utilize commercially available subcutaneous (SC) insulin pumps and glucose sensors, but these devices introduce physiological limitations that make control difficult. In this work, we present a clinical evaluation of an AP that uses SC devices, as well as an investigation of the intraperitoneal (IP) space as an alternative site for insulin delivery and glucose sensing to improve AP performance. Our results show that glucose sensors placed in the IP space have a lower time constant than SC sensors, allowing the controller to respond more quickly to BG disturbances. Similarly, insulin delivered through the IP space has faster pharmacokinetic and pharmacodynamic characteristics than SC insulin. Based on models of the sensing and actuation dynamics, a proportional-integral-derivative control algorithm with anti-reset windup protection was designed for the IP-IP route and evaluated on 10 simulated T1DM subjects. Using the IP-IP route led to a more robust controller that provided excellent control during the simulation studies. Our results support the development of a fully implantable AP that will operate within the IP space to safely and effectively control BG levels