Black Box Technology Research Articles

Using OR Black Box Technology to Determine Quality Improvement Outcomes for In-situ Timeout and Debrief Simulation.

The purpose of this study was to determine quality improvement outcomes following the pilot implementation of an in-situ simulation designed to enhance surgical safety checklist performance. OR Black Box (ORBB) technology allows near real-time assessment for surgical safety checklist performance. Before our study, timeout quality was 73.3%, compliance was 99.9%, and engagement was 89.7% (n=1993 cases); Debrief Quality was 76.0%, compliance was 66.9%, and engagement was 66.7% (n=1842 cases). This IRB-approved study used prospective convergent multi-methods. During 2 months, a 15-minute in-situ simulation, incorporating rapid cycle deliberate practice, was implemented for OR teams. ORBB analytics generated Timeout and Debrief scores for actual operations performed by surgeons who participated in simulation (Sim-group) versus those who did not (No-sim group) over 6 months, including 2 months pre-intervention, during-intervention, and post-intervention. Inductive content analysis was performed based on simulation discussions to determine team member perspectives. Thirty simulations with 163 interprofessional participants were conducted. ORBB data from 1570 cases were analyzed. Scores were significantly better for the Sim-group compared with the No-sim group for debrief quality (84% vs. 79% P<0.001, during-intervention), compliance (73% vs. 66%, P<0.001, post-intervention), and engagement (80% vs. 73%, P=0.012, during-intervention). There were no between-group differences for Timeout scores. Thematic analysis identified 2 primary categories: "culture of safety" and "policy." This simulation-based QI intervention created a psychologically safe training environment for OR teams. The novel use of ORBB technology facilitated outcome analysis and showed significantly better Debrief scores for simulation-trained surgeons compared with nontrained surgeons.

Interprofessional staff perspectives on the adoption of or black box technology and simulations to improve patient safety: a multi-methods survey

IntroductionMedical errors still plague healthcare. Operating Room Black Box (ORBB) and ORBB-simulation (ORBBSIM) are innovative emerging technologies which continuously capture as well as categorize intraoperative data, team information, and audio-visual files, in effort to improve objective quality measures. ORBB and ORBBSIM have an opportunity to improve patient safety, yet a paucity of implementation literature exists. Overcoming implementation barriers is critical. This study sought to obtain rich insights while identifying facilitators and barriers to adoption of ORBB and ORBBSIM in alignment with Donabedian’s model of health services and healthcare quality. Enrichment themes included translational performance improvement and real-world examples to develop sessions.MethodsInterprofessional OR staff were invited to complete two surveys assessing staff’s perceptions using TeamSTEPPS’s validated Teamwork Perceptions Questionnaire (T-TPQ) and open-ended questions. Descriptive statistics were calculated for quantitative variables, and inductive phenomenological content analysis was used for qualitative.ResultsSurvey 1 captured 71 responses from 334 invited (RR 21%) while survey 2 captured 47 responses from 157 (RR 29.9%). The T-TPQ score was 65.2, with Communication (70.4) the highest construct and Leadership (58.0) the lowest. Quality Improvement (QI), Patient Safety, and Objective Case Review were the most common perceived ORBB benefits. Trends suggested a reciprocal benefit of dual ORBB and ORBBSIM adoption. Trends also suggested that dual implementation can promote Psychological Safety, culture, trust, and technology comfort. The need for an implementation plan built on change management principles and a constructive culture were key findings.ConclusionsFindings supported ORBB implementation themes from previous literature and deepened our understanding through the exploration of team culture. This blueprint provides a model to help organizations adopt ORBB and ORBBSIM. Outcomes can establish an empirical paradigm for future studies.

Healthcare professionals’ perception of safety culture and the Operating Room (OR) Black Box technology before clinical implementation: a cross-sectional survey

IntroductionComprehensive data capture systems such as the Operating Room Black Box (OR Black Box) are becoming more widely implemented to access quality data in the complex environment of the OR....

Black box technology, usage-based insurance, and prediction of purchase behavior: Evidence from the auto insurance sector

Disruptive technologies are changing the car insurance sector, with behavioral and adaptive impacts for individuals as well as organizations. An innovative factor in this industry is connected to telematics and concerns the installation of a small device called a ‘black box’, which is becoming more and more widespread, with consequent financial impacts on the insurance policy market. However, the psychological drivers that underpin consumers' intentions to purchase black box auto insurance are scarcely researched. To fill this gap, we used a mixed-methods sequential exploratory design to analyze a sample of 757 consumers. Our results, obtained through PLS-SEM, highlight that attitude, awareness, subjective norms, risk perception, and trust have a significant positive influence on consumers' intentions to purchase black box technology auto insurance, while the effect of perceived behavioral control is not supported. Furthermore, the blindfolding analysis underscores the predictive relevance of the model. Our results have important implications for auto insurance companies interested to better understand consumers' needs and motives in relation to the purchase of black box insurance.

Investing in Private Evidence: The Effect of Adversarial Discovery

Abstract Much of the conventional wisdom of evidence law rests on the premise that the amount of evidence available in any given case is exogenously determined. With the advent of evidence technology (e.g. dashcams, black-box technology, digital data storage, surveillance cameras), the availability of evidence is substantially controlled by individuals. In this article, we show that evidence rules play an important role in determining individuals’ decisions to invest in private evidence. We compare the evidence rules adopted in the USA and Europe and analyze their relative impact on the voluntary adoption of evidence technology. We find that by making private evidence not discoverable, more rather than less evidence would be made available to courts.

Understanding the Algorithm: Meaning, Socio-Legal Context and Concerns

At present, algorithms are becoming the heart of society by taking control over the decision-making process as societies are increasingly getting digitalised. There is a consistent theme that an unaccountable, black box technology has taken over the stage and is now making decisions for us, with us, and about us. But the contention around public participation in making decisions in science and technology needs to advance to a stage where there is a more direct conversation between the public and those developing the technologies. With the above mentioned conception of moderating emerging technologies’ development, primarily digital technology due to its overreaching effects on humans and what humans interpret it to be. Firstly, the research through a literature survey is aimed to understand the meaning and nuances of the word algorithm. Then the analysis based on case study is focused on the algorithmic questions, such as bias, privacy, design, transparency, and accountability. In a larger context, concerns over jobs, ways of social interactions, etc., had been discussed, since these concerns are the result of the application of algorithms. The analysis of academic literature pointed out the vital facet of multiple understanding of the word algorithm. Further, the research also emphasizes the meaning of philosophy and politics in technology and its non-neutral nature.

Challenging Black Box Technology Power Imbalances by Exposing Them: “Persuasive System” as a Prism for Decomposing Contemporary Surveillance

This article contributes to the discussion around surveillance invisibility by engaging with the existing literature and discussing Salvatore Vitale’s “Persuasive System” installation as a case study. Based on the conceptualization of surveillance as a “black box,” the article frames power imbalances involved in biometrics and video surveillance technologies and shows how Vitale’s installation aims at playing with and exposing these dynamics by reconfiguring them.

Alternating Direction Method of Multipliers Network for Bioluminescence Tomography Reconstruction.

Bioluminescence tomography (BLT) is an effective noninvasive molecular imaging modality for three dimensional visualization of in vivo tumor research in small animals. The approaches of deep learning have shown great potential in the field of optical molecular imaging in recent years. However, the common problem with these existing end-to-end networks is the black box technology, whose solving process is not theoretically proven. In this work, we proposed a novel Alternating Direction Method of Multipliers Network (ADMM-Net) to solve the poor interpretation problem of internal process. The ADMM-Net combines the framework of deep learning on the basis of traditional ADMM algorithm to dynamically learn various parameters of the algorithm in the form of network. To evaluate the performance of our proposed network, we implemented numerical simulation experiments. The results show that the ADMM-Net can accurately reconstruct the location of the source, and the morphological similarity with the real source is also higher.

Socio-Technical Affordances for Large-Scale Collaborations: Introduction to a Virtual Special Issue

In this special issue, we review 14 articles published in Organization Science over the past 25 years examining large-scale collaborations (LSCs) tasked with knowledge dissemination and innovation. LSCs involve sizeable pools of participants carrying out a common mission such as developing open-source software, detector technologies, complex architecture, encyclopedias, medical cures, or responses to climate change. LSCs depend on technologies because they are often geographically distributed, incorporate multiple and diverse epistemic perspectives. How such technologies need to be structured and appropriated for effective LSC collaborations has been researched in piecemeal fashion by examining a single technology used in a single collaboration context with little opportunity for generalization. Studies have tended to black box technology use even though they acknowledge such uses to be critical to the LSC operation. We unveil the black box surrounding LSC collaboration technologies by identifying three challenges that LSCs face when they pursue an LSC effort: (1) knowledge exchange challenges, (2) knowledge deliberation challenges, and (3) knowledge combination challenges. We examine how technology was used in responding to these challenges, synthesizing their use into three socio-technical affordances to improve knowledge dissemination efficiency and innovation effectiveness: knowledge collaging, purposeful deliberating, and knowledge interlacing. We demonstrate the intellectual benefit of incorporating socio-technical affordances in studies of LSCs including what small group collaboration research can learn from LSCs.

Utilizing the Operating Room Black Box to Characterize Intraoperative Delays, Distractions, and Threats in the Gynecology Operating Room: A Pilot Study.

IntroductionOperating Room Black Box (ORBB) technology can be used to capture information during surgery for analysis and potential identification of root causes that jeopardize safety and efficiency. In this study, our objective was to identify and characterize procedural steps, intraoperative distractions, errors, and threats, as well as the non-technical skills of the team during a common minimally invasive gynecologic procedure.MethodologyThis was a cross-sectional pilot study of 25 patients undergoing total laparoscopic hysterectomy between May 2019 and February 2020 at a Canadian tertiary care academic hospital. Video, audio, and patient physiologic data from all procedures were obtained through a multichannel synchronized recording device (ORBB). Trained analysts reviewed and coded the recordings.ResultsThe median total case time was 165 minutes (interquartile range [IQR]: 160-178 minutes) with the shortest step being cystoscopy and the longest being vaginal cuff closure. Time pressure and device absence or malfunction occurred in 48% of the cases, and a median of 262 (IQR: 228-304) auditory distractions were noted per case. There was a median of 3 (IQR: 2-4) safety threats identified per case and at least one error was identified in 11/25 cases (44%). Only two adverse events were noted among all 25 cases. Observed non-technical skills were mainly positive, and observations were the highest for situational awareness and leadership among the surgical team and communication and teamwork among the nursing/scrub technician and anesthesia teams.ConclusionsThis study is a novel application of the ORBB in the gynecology operating room to capture information regarding procedure times, intraoperative distractions, errors, and non-technical skills of the team. Frequent intraoperative cognitive and auditory distractions were noted. Although adverse events were rare, safety threats were identified. Ongoing and future research from our group will aim to identify key areas for organizational, technological, and team improvement to minimize inefficiencies and optimize patient safety in the operating room.

ARPA–E explores paths to emissions-free metal making

The agency is seeking advice from industry and academia on how to make mining, smelting, and remediation less polluting and more energy efficient.

Improving the Transferability of Adversarial Examples with Image Affine Transformation

Deep learning is widely regarded as a black-box technology. We all know its performance is very good, but we have limited understanding of why it is so good. At present, there are many researches on the interpretability of deep neural network. By studying adversarial example, we can understand the internal semantics of neural network and find the decision boundary with problems, which in turn helps to improve the robustness and performance of neural network and its interpretability. With the development of adversarial example research, more and more adversarial example generation methods are proposed. Although the attack from adversarial example poses a great security threat to the deep learning system, it can also be used as an effective tool to measure the robustness and reliability of the model, and the attack and defense are two mutually promoting processes. Therefore, how to generate adversarial example with stronger attack ability is worth further study. And this study proposes a method named Affine-Invariant Method, aimed to improve the transferability of adversarial examples in black-box environment.

Utilizing Black Box Technology to Identify and Describe Intraoperative Delays, Distractions and Threats in the Gynecology OR: A Pilot Study

Study Objective Operating room delays can result from a chain of intra-operative events including technical factors, equipment failures or unavailability, and non-technical human factors. Operating Room Black Box (ORBB) technology can be used to capture information during surgery for analysis and potential identification of root causes of inefficiencies. Our objective was to measure and characterize procedural steps, intra-operative distractions and delays during a common minimally invasive gynecologic procedure and identify if these delays correlated with team technical and non-technical scores. Design Cross-sectional study. Setting Canadian tertiary care academic hospital. Patients or Participants Eleven patients undergoing total laparoscopic hysterectomy (TLH) between May and October 2019. Interventions Video, audio, and patient physiologic data from all procedures were obtained through a multichannel synchronized recording device. Trained analysts reviewed the recordings and coded procedural timing, distractions, delays, threats and team technical and non-technical scores. Measurements and Main Results Mean total case time was 172 minutes (SD +/- 16 minutes) and mean procedure time was 117 minutes (SD +/- 17 minutes). Mean surgical times for the pre-operative, intra-operative and post-operative phases were 85 mins (SD ± 40 mins), 116 mins (SD ± 17 mins) and 28 mins (SD ± 16 mins) respectively. Correlations between total case time and team non-technical scores and procedure time and team non-technical scores were positive and moderate in strength. Medians of 83 door openings [interquartile range (IQR) 76-104], 173 distractions (IQR 19-190) and 3 threats (IQR 2-5) were identified per case. Conclusion The ORBB allowed us to identify variations in procedural case times for elective TLH. There were frequent intraoperative distractions as well as latent threats noted and there was a moderately positive correlation between case times and team non-technical skills.

Introduction of the Operating Room Black Box in Gynecology: Development of a Procedural Framework for Total Laparoscopic Hysterectomy

Study Objective Operating room (OR) delays due to inefficiency can result from a chain of intraoperative events including technical factors, equipment failures or unavailability, and non-technical human factors. The newly developed Operating Room Black Box (ORBB) technology can be used to capture information during surgery which can be analyzed to potentially identify the root causes of delays and inefficiencies. We aimed to develop a procedural framework for total laparoscopic hysterectomy (TLH) in order to accurately and consistently capture the essential time points that occur during this complex laparoscopic procedure. Design Multi-disciplinary collaborative working group. Setting Canadian tertiary care academic hospital. Patients or Participants Team consisted of gynecologic surgeons, an anesthetist, an OR nurse and systems analysts. Interventions Multi-disciplinary working group collaborated to develop a procedural framework encompassing the critical steps and check points occurring during the course of a TLH. All phases of the operation were considered including pre-operative, intra-operative, and post-operative steps. Measurements and Main Results The completed framework consists of a series of procedural steps divided into three time phases: pre-operative, intraoperative and post-operative. Consensus from the group led to the identification of 7 discrete steps during the pre-operative phase, 11 intra-operative steps and 6 post-operative steps. Conclusion The development of a standardized procedural framework for TLH is the first step towards capturing data with the ORBB technology. The analysis of the captured data will allow us to analyze the non-technical skills and team performance in the OR, and ultimately develop a multi-disciplinary operating room “playbook” that can be utilized to minimize time delays and maximize OR utilization.

An Interdisciplinary Review of Surgical Data Recording Technology Features and Legal Considerations.

Surgical data recording technology has great promise to generate patient safety and quality data that can be utilized to potentially reduce medical errors. Variations of these systems aim to improve surgical technique, develop better training simulation, and promote adverse event investigation similar to the aims of black box technology utilized in other industries. However, many unknowns remain for surgical data recording utilization in operating rooms and clinical settings in the United States. This includes the need to appropriately design systems so they collect meaningful and useful data that can be discussed by surgical team members in an open and safe environment to optimize clinical care processes. In order to better understand the clinical and regulatory environment for surgical data recording systems, we conducted an interdisciplinary review to identify key technology approaches, and assess legal and regulatory implications associated with this potentially disruptive technology. We found technology ranging from audio and visual data, to systems utilizing mobile applications, and kinematic data capture. The data collected present legal questions over ownership of information and privacy, along with regulatory issues at the federal and state levels. The benefits of these data should be balanced with the need to develop appropriate policies and regulations that protect the interests of both clinicians and patients in order to encourage further innovation and better realize the potential of surgical data recording technology to improve clinical decision making and patient safety outcomes.

Introduction of a Surgical Black Box System in a Hybrid Angiosuite: Challenges and Opportunities

Introduction: Patient and team safety are paramount in healthcare, but medical errors remain the third leading cause of death. In laparoscopy, a surgical black box, based on aviation industry principles, provides valuable information about events occurring during these procedures.1 The system collects and synchronizes audio-visual and patient-related data for semi-automatic evaluation of technical- and non-technical skills (NTS) and environmental factors. In endovascular surgery, this technology may also provide useful knowledge about type, cause and frequency of perioperative events. Yet, high reliance on multidisciplinary teams and high equipment demands including radiation and a mobile C-arm pose additional challenges to transfer the black box technology in this field. We present our experience to adapt a black box system for evaluation of endovascular surgical procedures. Methods: Prior to installation, approval was obtained from all relevant hospital parties. Together with the original black box team and partners from biomedical, infrastructural and IT departments, an implementation plan was created for adapting the black box to our hybrid angiosuite, equipped with a Philips Allura Xper FD20 system. Video-evaluation frameworks were chosen with the black box research team. Technical skill evaluation tools were chosen after a non-structured analysis of the literature. NTS and environmental factor evaluation frameworks were already available in the system. A framework for radiation safety evaluation has been self-developed and is currently being validated. Results: Ethics approval took 54 days and approval of juridical and financial agreement took 252 days. All team members (surgeons, nurses, anaesthesiologists) were informed during informative sessions and informed consent was collected. Site assessment and hardware installation both required two days. Four ceiling-mounted cameras were used to capture team movement and activity in the angiosuite, which were sometimes blocked by the C-arm. Three multidirectional ceiling microphones were installed to capture team conversations and environmental noise. A direct connection with the C-arm system captures the fluoroscopy image and radiation safety parameters. Patient hemodynamic monitoring is captured through the anaesthesia monitor and provides information about event severity and physiologic consequences. Surgical technical performance is assessed with the 'Global Rating Scale of Endovascular Performance' and the 'Examiner's Checklist' frameworks. The NOTSS, SPLINTS and ANTS frameworks were picked to assess non-technical skills of surgical, nursing and anaesthesiology teams, respectively. The 'Disruption in Surgery Index' framework assesses disruptive and environmental factors. A pilot study of 20 elective endovascular treatments of symptomatic iliac and femoropopliteal atherosclerotic disease to assess feasibility and reliability of black box-driven analysis is in progress. Data will be available at the annual meeting. Conclusion: To our knowledge, this innovative black box technology is the first to be installed in a hybrid angiosuite worldwide. Ultimately, this may help identify the number of errors or near-misses occurring in a hybrid angiosuite. This may allow each centre to identify safety risks and map operational sequences leading to adverse events in endovascular surgery, ultimately leading to educational interventions based on real situations so that every error or near-miss remains unique. Disclosure: Nothing to disclose

Intelligent online catastrophe assessment and preventive control via a stacked denoising autoencoder

In all areas of engineering, catastrophe assessment is an essential prerequisite for remedial action schemes. Modelers constantly push for more accurate models, and often meet goals by using increasingly complex, data mining-based blackbox models. However, system operators tend to favor interpretable models for after-the-fact preventive control (PC). While switching from blackbox to interpretable solutions, a tradeoff occurs between accuracy and interpretability. To avoid this tradeoff, we develop an intelligent framework for online catastrophe assessment and PC via a blackbox stacked denoising autoencoder (SDAE) equipped with accuracy and the ability to derive a PC scheme. Specifically, we implement a transient stability cost-sensitive assessment (TSCA) and PC case in the context of a power grid. First, using only controllable variables, we build the TSCA model by adding a sigmoid unit on top of the SDAE. Considering power systems’ conservatism, we explore a novel TSCA model’s training criterion to determine the operation conditions’ degrees of stability and divide them into three classes: stable, unstable, and boundary. Second, given an operation condition identified as unstable or boundary by TSCA model and its desired degree of stability, the PC model (the reverse of a TSCA model’s mapping) consists of the top sigmoid’s backward mapping and the stack of denoising decoders from trained SDAE. The former is formalized as an optimization problem to push back the desired degree of stability to a desired SDAE’s highest-level abstraction. The latter decodes back the desired SDAE’s highest-level abstraction to a desired operation condition (essentially, a PC scheme nearest to the controlled operation condition in the coordinates along the underlying causes that generate the observed data). This approach actually resembles operators’ tendency to adjust and stabilize unstable conditions (in terms of underlying causes) with the fewest control actions. A simulation study on the IEEE New England 39-bus system shows that, as a blackbox technology, our framework not only provides superior online situational awareness, but also finds a viable PC scheme, thereby justifying its practicability in engineering.

From Craft to Reflective Art and Science Comment on "Metrics and Evaluation Tools for Patient Engagement in Healthcare Organization- and System-Level Decision-Making: A Systematic Review".

Patient engagement practices are increasingly incorporated in health research, governance, and care. More recently, a large number of evaluation tools and metrics have been developed to support engagement evaluation. This growing interest in evaluation reflects a maturation of the patient engagement field, moving from a "craft" to a reflective "art and science," with more explicit expected benefits and risks, better understood conditions for success and failure, and increasingly rigorous evaluation instruments to improve engagement theories and interventions. It also supports a more critical view of engagement science, moving beyond reductionist views of engagement as a "black box technology" to a more subtle view of this broad category of complex interventions. Structured evaluation can advance patient engagement by supporting more reflective partnerships between patients, clinicians, health system leaders and citizens. This can help clarify mutual (and potentially contradictory) expectations toward engagement, provide a reality check toward claims of benefits and harms, and increase health systems’ capacity to implement effective engagement practices over time. To do so, closer collaborations are required between engagement scientists and practitioners to align the theories, practice and evaluation of patient and community engagement.

On the Media-political Dimension of Artificial Intelligence

Abstract The essay critically investigates the media-political dimension of modern AI technology. Rather than examining the political aspects of certain AI-driven applications, the main focus of the paper is centred around the political implications of AI’s technological infrastructure, especially with regard to the machine learning approach that since around 2006 has been called Deep Learning (also known as the simulation of Artificial Neural Networks). Firstly, the paper discusses in how far Deep Learning is a fundamentally opaque black box technology, only partially accessible to human understanding. Secondly, and in relation to the first question, the essay takes a critical look at the agenda and activities of the research company OpenAI that supposedly aims to promote the democratization of AI and tries to make technologies like Deep Learning more accessible and transparent.

Chemical vs. Biological Crystals, all the Same?

Using microorganisms to mediate crystallisation of metals and minerals in open-culture bioreactors has potential to recover recyclable materials from dilute aqueous streams, but also to prevent their emission to the environment. Although this potential is already exploited in practice to some extent, biological crystallization for metal recovery is still largely a black box technology with limited understanding of the role of the microorganisms in the crystallization, and the differences with chemical crystallisation. Using biocrystallisation of scorodite (FeAsO4.2H2O) and sphalerite (ZnS) as examples we propose that the role of microorganisms strongly depends on established saturation state of the solution. For scorodite, microorganisms are used to exert control over the crystallization as their ferrous iron-oxidizing activity keeps the solution slightly oversaturated. Also, the oversaturation level is kept homogeneous because of continuous biological formation of the reactant ferrous iron throughout the solution. In continuous bioreactor experiments on which we reported previously, scorodite crystal sizes still increased after 72 days of bioreactor operation indicating that indeed crystal growth was favored over nucleation. On the other hand, in our experiments with zinc sulfide, crystallization proceeded in highly oversaturated solutions in a continuous sulfate reducing bioreactor fed with a zinc sulfate solution and H2/CO2 as electron donor and carbon source. The high oversaturation likely resulted in dominant primary nucleation in the bulk solution, with little or no control over crystal growth, even though agglomeration may still have occurred. This was exemplified by particle sizes which decreased in the bioreactor experiment and remained stable after already about 2 weeks of operation.