Latent Errors Research Articles

Achieving high data reliability at low scrubbing cost via failure-aware scrubbing

Latent Sector Errors (LSEs) happen at a significant frequency in the field and can impose a huge risk to data reliability. Disk scrubbing is a background process that reads disks periodically to detect LSEs timely, thus shortening the window of vulnerability to data loss. Nowadays, proactive error prediction, using machine learning techniques, has been proposed to improve storage system reliability by increasing the scrubbing rate for disks with higher error rates. Unfortunately, the majority of works incur non-trivial scrubbing costs and overlook the relationship between complete disk failures and LSEs.In this paper, we attempt to maintain or improve data reliability at reduced scrubbing costs. In particular, we design a novel adaptive approach that enforces a lower scrubbing rate for healthy disks and a higher scrubbing rate for disks which are subject to LSEs. Besides LSEs that are specific to partial disk failures, we also adjust scrubbing rates according to complete disk failure rates, because disks typically develop LSEs before they finally fail. Moreover, a voting-based method that exploits the periodic characteristic of scrubbing is proposed to ensure prediction accuracy. Experimental results on a real-world field dataset have demonstrated the effectiveness of our proposed approach. Specifically, the results show that we can achieve the same level of reliability, in terms of Mean-Time-To-Detection (MTTD), as the traditional fixed-rate scrubbing scheme with almost 49% less scrubbing costs or we can improve the reliability by a factor of 2.4X without extra scrubbing costs. Compared with the state-of-the-art approaches, our method can achieve the same level of reliability with nearly 32% less scrubbing costs.

Patient Safety and Clinical Risk Management for General Practice

General practitioners are the first contact between the person, the family and the community with the health system. The philosopher and epistemologist K. Popper (1902-1994) recommended the need to register errors, in order to know them, catalog them and therefore prevent them. J.Reason in 1963 introduced the systemic approach to the study of errors with the theory of latent errors. The knowledge of the causal factors, or which in any case contribute, of possible errors, as well as of the latent gaps in the system, is a fundamental prerequisite for the construction of paths aimed at improving the quality of assistance, structures and organizational aspects.

A Formal and Quantifiable Log Analysis Framework for Test Driving of Autonomous Vehicles.

We propose a log analysis framework for test driving of autonomous vehicles. The log of a vehicle is a fundamental source to detect and analyze events during driving. A set of dumped logs are, however, usually mixed and fragmented since they are generated concurrently by a number of modules such as sensors, actuators and programs. This makes it hard to analyze them to discover latent errors that could occur due to complex chain reactions among those modules. Our framework provides a logging architecture based on formal specifications, which hierarchically organizes them to find out a priori relationships between them. Then, algorithmic or implementation errors can be detected by examining a posteriori relationships. However, a test in a situation of certain parameters, so called an oracle test, does not necessarily trigger latent violations of the relationships. In our framework, this is remedied by adopting metamorphic testing to quantitatively verify the formal specification. As a working proof, we define three metamorphic relations critical for testing autonomous vehicles and verify them in a quantitative manner based on our logging system.

Study of determinants in deaths occurring in an Italian teaching hospital during a year.

The main source of mortality data is the death certificate. The forms must be filled in correctly because inaccuracy can lead to the misallocation of resources in health care programs and research. The main purpose was to verify the existence of any relationships and/or correlations between the deaths of the Polyclinic of Bari and some specific elements by carrying out a "risk adjusted" analysis that represents a real indicator of the quality of care. All death records of patients who died in the Bari Polyclinic (over 1.500 beds) in 2017 (1.005 patients) were analysed. For each card, the corresponding medical records have been evaluated. The main causes of death are cardiovascular and neoplastic diseases, in line with statistics carried out on a national basis. Infectious and parasitic diseases represent the third cause of death with a discrepancy with the national average mainly due to the high incidence of nosocomial infections in European hospitals. There were no statistically significant differences in the frequency of deaths per shift and per ward. Patients suffering from infectious and digestive system diseases are more at risk of dying in the afternoon. An increased risk of death in the last hours of the night shift has been demonstrated. These findings indicate the need to adopt, in case of adverse events due to changes in the quality of care, the necessary barriers to prevent the occurrence of active or latent errors against patients exposed to this risk.

It's time for the mandatory use of simulation and human factors in hospital design.

Building a new healthcare facility is complex and poses challenges in delivering a facility that is fit for purpose and designed to minimise latent environmental and process errors. This article summarises what the disciplines of Human Factors/Ergonomics and Simulation can offer to the design and testing of new hospital builds. It argues the incorporation of both disciplines throughout the planning, design, commissioning and operations phases of the building project can minimise latent safety risks to promote patient safety and staff well-being across the building lifecycle. Future directions and policies should include incorporation of human factors design and mandatory process testing before opening.

Human Factors/Ergonomics (HFE) in Leadership and Management: Organizational Interventions to Reduce Stress in Healthcare Delivery

Clinician Burnout is a personal and public health issue. Most occupational stressors contributing to clinician burnout are systemic. The combination of organizational interventions along with individual interventions is necessary to make significant lasting difference in reducing burnout, improving clinician and patient satisfaction and reducing latent error in healthcare delivery. Application of Human Factors/Ergonomics (HFE) science in healthcare leadership and management is a gap in current training for leaders. HFE uses concepts from organizational, educational and cognitive science, systems science and industrial engineering. HFE application is especially necessary in a fast changing highly stressful healthcare environment which impacts the wellbeing of clinicians and the safety of patients under care. Practical suggestions for working with various healthcare leadership styles and organizational dynamics, while aligning wellness efforts with institutional mission are discussed. Concrete examples of decreasing extraneous mental load on clinicians to preserve their brainpower to achieve quality patient care are illustrated. Organizational interventions in combination with individual interventions to reduce and manage burnout have enormous potential to improve clinician wellbeing and satisfaction in taking care of patients, reduce costs, risk of error and create the safe working environment needed to sustainably give high quality care to patients.

Application of generative deep learning models for approximation of image distribution density

Generative neural network models for visual concept learning and the problem of approximating image distribution density are studied. A criterion for an image to belong to a simulated class is introduced based on an estimate of the probability in the space of latent variables and reconstruction errors. Several generative deep learning models are compared. Quality estimates of the solution to the problem of one-class classifications for a set of images of handwritten digits are experimentally obtained.

Tooth contact analysis with latent error of double circular-arc spiral bevel gears for industrial robot joint nutation drive

The influence of the cone vertex error and tilt error on the tooth contact trace of double circular-arc spiral bevel gears for industrial robot joint nutation drive has been studied in this paper. According to the meshing relationship between double circular-arc spiral bevel gear and crown gear, the meshing coordinate systems with latent error parameters of cone vertex error and tilt error were established, and the tooth profile equations of external and internal spiral bevel gears were deduced. According to the meshing equation and coordinate transformation, the contact trace equation of the tooth surface was established, and the influence of different latent error values on the location of the contact trace was solved and analyzed. The finite element loading contact simulation of the double circular-arc spiral bevel gears with different latent error values was carried out. The results of the simulation analysis and numerical analysis were basically consistent. The latent errors would cause noise and vibration of industrial robot joint nutation drive and affect the service life of double circular-arc spiral bevel gears.

Reliability of Fault Tolerance in Cloud using Machine Learning Algorithm

The basic fault tolerance issues seen in cloud computing are identification and recovery. To fight with these issues, so many fault tolerance methods have been designed to decrease the faults. However, due to the reliability and web based service giving behavior, fault tolerance in cloud computing will be a huge challenge. The present model is not just on tolerating faults but also to decrease the possibility of future faults as well[4].The fault tolerance deals with the exact and constant operation of the fault segments. The processing on computing nodes can be done remotely in the real time cloud applications, so there could be more possibilities of errors. Hence there lies an immense necessity for fault tolerance to attain consistency to the real time computing on cloud infrastructure. The “fault tolerance” can be explained through fault processing that have two basic stages. The stages are (i) The effective error processing stage which is used to intended for carrying the “effective error” back to inactive state, i.e., before the error occurred (ii) The latent error processing stage intended for guaranteeing that the fault does not get effective once again.

Is One-Pen, One-Patient Achievable in the Hospital? A Quality Improvement Project to Reduce Risks of Inadvertent Insulin Pen Sharing at a Large Academic Medical Center

The Food and Drug Administration (FDA), Centers for Disease Control and Prevention (CDC), and Institute for Safe Medicine Practices (ISMP) have issued warnings regarding the risk of potential transmission of blood-borne diseases if an insulin pen is used for more than one person. Many hospitals continue to use insulin pens due to their benefits of decreased risk of dosing error and improved work efficiency. Best practices for insulin pen use have been published; however, little is known about how these perform in hospitals. This article describes a multifaceted quality improvement project to address the safety issues of single-patient insulin pens. Major interventions included adding patient-specific bar coding on insulin pens, redesign of labels, systematic removal of discharged patients' medications, and ongoing staff education. Self-reported events of insulin pen sharing events over 40 months showed a significant increase in the number of patient-days between events. The significant change occurred after implementation of patient-specific bar code scanning. There was a gradual decrease in latent errors found during medication drawer audits, and nursing compliance with patient-specific bar code scanning improved over time, reaching 90% on the last recorded month. Of 35 expert recommendations for insulin pen safety, 28 directly affected pen sharing-8 had been implemented prior to this project, and 20 had been implemented by the conclusion. Insulin pen use is highly complex in hospital settings where multiple steps provide opportunities for error. To protect patients, all gaps need to be reviewed, and interventions that address major contributing factors are required to ensure safe insulin pen use.

Organizational Errors and Individual Errors: Perspective on Accident Causation

The development of human-machine system has brought better economic benefits, but simultaneously resulted in more serious accidents. What is more notable is that similar accidents may happen repeatedly in the same organization, and cannot be avoided even though different individuals are employed at the same position. The causes are attributed to individual errors but not organizational errors in most instances, since individual errors are much more apparent than organizational errors. Herein, we distinguish individual errors and organizational errors, by proposing the definition and characteristics of organizational errors and individual errors from the perspective of accident causation. Organizational errors refer to the latent errors in organizational level and organizational function, which will lead to individual errors and violations of these deviant behaviors, while individual errors refer to individual unconscious deviant behaviors.

PFP: Improving the Reliability of Deduplication-based Storage Systems with Per-File Parity

Data deduplication weakens the reliability of storage systems since by design it removes duplicate data chunks common to different files and forces these files to share a single physical date chunk, or critical chunk, after deduplication. Thus, the loss of a single such critical data chunk can potentially render all referencing (sharing) files unavailable. However, the reliability issue in deduplication-based storage systems has not received adequate attention. Existing approaches introduce data redundancy after files have been deduplicated, either by replication on critical data chunks, i.e., chunks with high reference count, or RAID schemes on unique data chunks, which means that these schemes are based on individual unique data chunks rather than individual files. This can leave individual files vulnerable to losses, particularly in the presence of transient and unrecoverable data chunk errors such as latent sector errors. To address this file reliability issue, this paper proposes a Per-File Parity (short for PFP) scheme to improve the reliability of deduplication-based storage systems. PFP computes the XOR parity within parity groups of data chunks of each file after the chunking process but before the data chunks are deduplicated. Therefore, PFP can provide parity redundancy protection for all files by intra-file recovery and a higher-level protection for data chunks with high reference counts by inter-file recovery. Our reliability analysis and extensive data-driven, failure-injection based experiments conducted on a prototype implementation of PFP show that PFP significantly outperforms the existing redundancy solutions, DTR and RCR, in system reliability, tolerating multiple data chunk failures and guaranteeing file availability upon multiple data chunk failures. Moreover, a performance evaluation shows that PFP only incurs an average of 5.7 percent performance degradation to the deduplication-based storage system.

Sample Selection Models with Monotone Control Functions

The celebrated Heckman selection model yields a selection correction function (control function) proportional to the inverse Mills ratio, which is monotone. This paper studies a sample selection model which does not impose parametric distributional assumptions on the latent error terms, while maintaining the monotonicity of the control function. We show that a positive (negative) dependence condition on the latent error terms is sufficient for the monotonicity of the control function. The condition is equivalent to a restriction on the copula function of latent error terms. Utilizing the monotonicity, we propose a tuning-parameter-free semiparametric estimation method and establish root n-consistency and asymptotic normality for the estimates of finite-dimensional parameters. A new test for selectivity is also developed exploring the shape-restricted estimation. Simulations and an empirical application are conducted to illustrate the usefulness of the proposed methods.

QIM19-128: Improving Oral Chemotherapy Safety in Adult Neuro-Oncology Clinics

Background: The development of oral chemotherapies (OC) have transformed cancer care for millions of patients. Most patients with brain tumors have temozolomide (TMZ) delivered to their home. While this has improved the patient experience, it presents significant challenges to safety of prescription, administration, and side effect monitoring. While there are guidelines for documentation, there is not a best practices system for managing OC. This project identified areas of latent errors and implemented a standardized process for OC management. Methods: After review of the literature, we developed a process map for our institution’s practice and performed hazard analysis. We then evaluated the process at 3 other neuro-oncology practices. Based on these evaluations, changes were implemented at several stages (Table 1). Objective binary measures that could be recorded for every TMZ prescription were collected by chart review of the 6 months prior to process change. These measures were monitored every 2 weeks after process change implementation using run charts. A baseline process mean was calculated for each measure from the 6 months before program implementation. Successful change implementation was defined as 7 consecutive 2-week averages that were continually on one side of the process mean. Results: At the time of this abstract submission, we had successfully reduced refills for OC and increased documentation of dose calculation and dose ordered. There is improvement in independent dose calculation by 2 providers and dedicated chemotherapy teaching visits; however, these have not yet reached criteria for process change. Additionally, oral chemotherapy order sets were created in the electronic medical records system and an on-site specialty pharmacy was added as another safety measure in OC management. Conclusions: This project used published studies and multi-institutional process mapping and hazard analysis to implement a standardized ordering of TMZ for patients with brain tumors. This process can be implemented for OC management in other oncology practices.

The Failure Route between Active and Latent Error in Bus Accident

It is imperative to examine the differences between active and latent errors in bus accidents. This research aims to study and assess human factors to determine the impact of behavior has in this domain. For this research we examine a set of 452 bus accident investigation reports. Nine evaluators were invited to assess human factors using the Human Factors Analysis and Classification System (HFACS) framework. The inter-evaluator reliability is assessed using the Krippendorff’s coefficient. Interdependencies between adjacent horizontal factors and the statistics for human factors were analyzed using odds ratios and lambda and chi-square methods. There are twenty-one significant associations between human factors and the adjacent levels of HFACS. Among them, organizational process and inadequate supervision, inadequate supervision and personal readiness, and personal readiness and violations appear to be the most significant. The four most significant HFACS factors are organizational process, personal readiness, inadequate supervision, and violations. These together form a route of failure. The active error of violations is closely related to the latent errors organizational process, inadequate supervision and personal readiness. Efforts to reduce the incidence of these three errors will significantly decrease the rate of bus-related accidents.

Human Factor Based Leadership: Critical Leadership Tools to Reduce Burnout and Latent Error in a Time of Accelerating Change

The majority of errors in healthcare are from systems factors that create the latent conditions for error to occur. The majority of occupational stressors causing burnout are also the result of systemic factors. Advances in technology create new levels of stress and expectations on healthcare workers (HCW) with an endless infusion of requirements from multiple authoritative sources that are tracked and monitored. The quality of care and safety of patients is affected by the wellbeing of HCWs who now practice in an environment that has become more complex to navigate, often expending limited neural resource (brainpower) on classifying, organizing, constantly making decisions on how and when they can accomplish what is required(extraneous cognitive load) in addition to direct patient care. New information demonstrates profound biological impact on the brains of those who have burnout in areas that affect the quality and safety of the decisions they make-which affects risk to patients in healthcare. Healthcare administration curriculum currently does not include ways to address these stress-induced problems in healthcare delivery. The science of human factors and ergonomics (HFE) promotes system performance and worker wellbeing. Patient safety is one component of system performance. Since many requirements come without resource to accomplish them, it becomes incumbent upon health system leadership to organize the means for completion of these to minimize the needless loss of brain power diverted away from the delivery of patient care. Human Factor-Based Leadership (HFBL) is an interactive, problem solving seminar series designed for healthcare leaders. The purpose is to provide relevant human factor science to integrate into their leadership and management decisions to make HCWs occupational environment more manageable and sustainable-which makes safer conditions for clinician wellbeing and patient care. After learning the content, a cohort of healthcare leaders believed that adequately addressing HFE in healthcare delivery would significantly reduce clinician burnout and risk of latent errors from upstream leadership decisions. An overview of the content of the seminars is described. Leadership feedback on usability of these seminars is reported. Three HFBL seminars described are Human Factor Relevance in Leadership, Biopsychosocial Approach to Wellness and Burnout, Human Factor Based Leadership: Examples and Applications.

A classification of electrical component failures and their human error types in South Korean NPPs during last 10 years

The international nuclear industry has undergone a lot of changes since the Fukushima, Chernobyl and TMI nuclear power plant accidents. However, there are still large and small component deficiencies at nuclear power plants in the world. There are many causes of electrical equipment defects. There are also factors that cause component failures due to human errors. This paper analyzed the root causes of failure and types of human error in 300 cases of electrical component failures. We analyzed the operating experience of electrical components by methods of root causes in K-HPES (Korean-version of Human Performance Enhancement System) and by methods of human error types in HuRAM+ (Human error-Related event root cause Analysis Method Plus). As a result of analysis, the most electrical component failures appeared as circuit breakers and emergency generators. The major causes of failure showed deterioration and contact failure of electrical components by human error of operations management. The causes of direct failure were due to aged components. Types of human error affecting the causes of electrical equipment failure are as follows. The human error type group Ⅰ showed that errors of commission (EOC) were 97%, the human error type group Ⅱ showed that slip/lapse errors were 74%, and the human error type group Ⅲ showed that latent errors were 95%. This paper is meaningful in that we have approached the causes of electrical equipment failures from a comprehensive human error perspective and found a countermeasure against the root cause. This study will help human performance enhancement in nuclear power plants. However, this paper has done a lot of research on improving human performance in the maintenance field rather than in the design and construction stages. In the future, continuous research on types of human error and prevention measures in the design and construction sector will be required.

Multidisciplinary Team Training Simulation in Interventional Radiology

Efficient teamwork and communication is critical for the delivery of safe and high quality patient care. Studies have shown that medical errors can occur as a result of poor communication. Simulation scenarios can help improve communication and teamwork, therefore decreasing errors and improving team morale. Simulation is best employed through a multidisciplinary approach, including all members of the team involved in the patient's care. Team simulation can be difficult to plan and execute, therefore we will review the steps to planning an effective multidisciplinary team simulation, as well as the barriers to overcome when implementing these programs. In addition, the structure and value of debriefing sessions will be discussed. Debriefing has been shown to help participants identify latent errors and voice concerns in a safe, confidential setting. Lastly, we will review the value of multidisciplinary team simulation, focusing on the current literature among multiple medical disciplines. There has been a push for implementation of team simulation in healthcare in recent years, yet there is still a need for future research on this subject to demonstrate the direct effect of team simulation on patient care, especially in the dynamic field of Interventional Radiology.

Developing a standardized process for oral chemotherapy management for neuro-oncology.

258 Background: Oral chemotherapies (OC) have transformed cancer care for millions of patients. While this has improved the patient experience, it presents significant challenges to safety of prescription, administration and side effect monitoring. While there are guidelines for documentation, there is not a best practices system for managing OC. This project identified areas of latent errors and implemented a standardized process for OC management. Methods: After review of the literature, we developed a process map for OC prescriptions at our institution. We then compared processes at three other neuro oncology clinics. We completed a hazard analysis and implemented several changes (see table). We identified binary measures in the medical record for every OC prescription that related to the process changes. Chart review of the 6 months prior to process change was used to create a baseline process mean for each variable. These same variables were monitored every 2 weeks after process change implementation using run charts. Successful process shift was defined as 7 consecutive 2-week averages that were continually on one side of the baseline process mean. Results: 5 months after process change was implemented, we had successfully reduced refills for OC and increased documentation of dose and dose calculation. There is a trend towards improvement in independently verified dose calculation and dedicated chemotherapy teaching visits, however these have not yet reached criteria for process change. Conclusions: This project used published studies, multi-institutional process mapping and hazard analysis to develop and implement a standardize process for OC. This process can be implemented for OC management in other oncology practices. [Table: see text]

Interventions That Can Help Reduce Diagnostic Errors.

Latent healthcare errors are defects in organization or design that create fertile ground for multiple errors (1). One latent error produces multiple defects at the “sharp” end of healthcare where patient care and clinical decision-making take place (2). Thus, for example, an electronic health record that hinders rapid retrieval of laboratory results produces a large number of errors related to the failure to retrieve these results, which is a significant cause of diagnostic error related to laboratory services (3). Dr. Laposata's article lists the latent errors underlying the problem of diagnostic error in American healthcare (4). The errors in healthcare system design that he describes are also a root cause of several related ailments of American healthcare, including high costs, physician burnout, patient dissatisfaction, and high variability in outcomes for the same condition. After listing the latent problems underlying the diagnostic error dilemma, Dr. Laposata enumerates 8 specific goals to address these problems. A logical extension of Laposata's work is the creation of a set of specific interventions that help achieve the goals. We focus here on interventions that enable 3 or more of the goals and encourage readers to expand the list of interventions to address all …