Relevant bibliographies by topics / Alert fatigue

Academic literature on the topic 'Alert fatigue'

Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Alert fatigue"

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Pashtan, Itai Max, Tara Kosak, Kevin Beaudette, Amy Buckman, Abigail Clark, Jill Connolly, Lynne Hicks, et al. "Addressing alert fatigue by reducing radiation oncology software alert volume." Journal of Clinical Oncology 39, no. 28_suppl (October 1, 2021): 261. http://dx.doi.org/10.1200/jco.2020.39.28_suppl.261.

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261 Background: Radiation therapists (RTTs) administer radiation treatments to patients with cancer. Treatments are delivered using linear accelerators (LINACs), operated by vendor specific software. Prior to delivering treatment, RTTs perform a time-out, and read aloud critical electronic communications (alerts) entered by members of the radiation oncology care team. Alerts are effective at communicating critical information, including treatment setup and imaging instructions, but can become a source of error due to alert fatigue when placed indiscriminately. Methods: A multicenter retrospective review of alert use per patient was conducted in 4 radiation oncology centers with a total of 6 LINACs. Alert usage was reviewed pre-intervention for 40 randomly selected patients using manual chart review. Each alert was reviewed for frequency and utilization. In attempt of improving communication and reducing alert fatigue, a multidisciplinary process improvement working group (with Radiation Oncologists, RTTs, nursing, physicists, and administration) was formed to review the utilization of alerts in our department and propose interventions. Three months after intervention, an additional 40 chart review was performed. Our aim was to reduce the volume of alerts by 20% within 3 months. A 2-tail t-test was used for statistical analysis. Results: Process improvements were implemented to reduce the volume of alerts per patient. Interventions included 1) defining an alert for all departmental staff, 2) creating guidelines for appropriate utilization of alerts, 3) routing communications not critical to RTTs at the time of radiation treatment administration through other channels, and 4) training staff as to the above. The pre-intervention review yielded 239 alerts. Post-intervention, there were 173 alerts, a reduction of 27% (p =.008). Conclusions: This practice change reduced average alert volume by 27%. As a result, alerts which are critical to safe treatment delivery by RTTs (i.e. daily setup alerts), became more heavily represented. Other alerts, which could be communicated effectively in other ways (i.e. OTVs [weekly on treatment visit with Radiation Oncologist]), were eliminated. By decreasing alert volume, the risk of RTT alert fatigue is reduced, communication improved, and treatment safety enhanced.[Table: see text]
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Cash, Jared J. "Alert fatigue." American Journal of Health-System Pharmacy 66, no. 23 (December 1, 2009): 2098–101. http://dx.doi.org/10.2146/ajhp090181.

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Schleyer, Titus, and Thankam P. Thyvalikakath. "Alert Fatigue." Journal of the American Dental Association 143, no. 4 (April 2012): 332–33. http://dx.doi.org/10.14219/jada.archive.2012.0166.

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BARTON, AMY J. "Alert Fatigue." Clinical Nurse Specialist 25, no. 5 (September 2011): 218–19. http://dx.doi.org/10.1097/nur.0b013e318229962d.

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Wan, Paul Kengfai, Abylay Satybaldy, Lizhen Huang, Halvor Holtskog, and Mariusz Nowostawski. "Reducing Alert Fatigue by Sharing Low-Level Alerts With Patients and Enhancing Collaborative Decision Making Using Blockchain Technology: Scoping Review and Proposed Framework (MedAlert)." Journal of Medical Internet Research 22, no. 10 (October 28, 2020): e22013. http://dx.doi.org/10.2196/22013.

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Background Clinical decision support (CDS) is a tool that helps clinicians in decision making by generating clinical alerts to supplement their previous knowledge and experience. However, CDS generates a high volume of irrelevant alerts, resulting in alert fatigue among clinicians. Alert fatigue is the mental state of alerts consuming too much time and mental energy, which often results in relevant alerts being overridden unjustifiably, along with clinically irrelevant ones. Consequently, clinicians become less responsive to important alerts, which opens the door to medication errors. Objective This study aims to explore how a blockchain-based solution can reduce alert fatigue through collaborative alert sharing in the health sector, thus improving overall health care quality for both patients and clinicians. Methods We have designed a 4-step approach to answer this research question. First, we identified five potential challenges based on the published literature through a scoping review. Second, a framework is designed to reduce alert fatigue by addressing the identified challenges with different digital components. Third, an evaluation is made by comparing MedAlert with other proposed solutions. Finally, the limitations and future work are also discussed. Results Of the 341 academic papers collected, 8 were selected and analyzed. MedAlert securely distributes low-level (nonlife-threatening) clinical alerts to patients, enabling a collaborative clinical decision. Among the solutions in our framework, Hyperledger (private permissioned blockchain) and BankID (federated digital identity management) have been selected to overcome challenges such as data integrity, user identity, and privacy issues. Conclusions MedAlert can reduce alert fatigue by attracting the attention of patients and clinicians, instead of solely reducing the total number of alerts. MedAlert offers other advantages, such as ensuring a higher degree of patient privacy and faster transaction times compared with other frameworks. This framework may not be suitable for elderly patients who are not technology savvy or in-patients. Future work in validating this framework based on real health care scenarios is needed to provide the performance evaluations of MedAlert and thus gain support for the better development of this idea.
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Raman, Kirbana Jai, Afizan Azman, Siti Zainab Ibrahim, Sumendra Yogarayan, Mohd Fikri Azli Abdullah, Siti Fatimah Abdul Razak, Anang Hudaya Muhamad Amin, and Kalaiarasi Sonai Muthu. "Fatigue Alert System." Indian Journal of Science and Technology 11, no. 20 (May 1, 2018): 1–7. http://dx.doi.org/10.17485/ijst/2018/v11i20/123348.

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Nanji, Karen C., Diane L. Seger, Sarah P. Slight, Mary G. Amato, Patrick E. Beeler, Qoua L. Her, Olivia Dalleur, et al. "Medication-related clinical decision support alert overrides in inpatients." Journal of the American Medical Informatics Association 25, no. 5 (October 27, 2017): 476–81. http://dx.doi.org/10.1093/jamia/ocx115.

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Abstract Objective To define the types and numbers of inpatient clinical decision support alerts, measure the frequency with which they are overridden, and describe providers’ reasons for overriding them and the appropriateness of those reasons. Materials and Methods We conducted a cross-sectional study of medication-related clinical decision support alerts over a 3-year period at a 793-bed tertiary-care teaching institution. We measured the rate of alert overrides, the rate of overrides by alert type, the reasons cited for overrides, and the appropriateness of those reasons. Results Overall, 73.3% of patient allergy, drug-drug interaction, and duplicate drug alerts were overridden, though the rate of overrides varied by alert type (P < .0001). About 60% of overrides were appropriate, and that proportion also varied by alert type (P < .0001). Few overrides of renal- (2.2%) or age-based (26.4%) medication substitutions were appropriate, while most duplicate drug (98%), patient allergy (96.5%), and formulary substitution (82.5%) alerts were appropriate. Discussion Despite warnings of potential significant harm, certain categories of alert overrides were inappropriate >75% of the time. The vast majority of duplicate drug, patient allergy, and formulary substitution alerts were appropriate, suggesting that these categories of alerts might be good targets for refinement to reduce alert fatigue. Conclusion Almost three-quarters of alerts were overridden, and 40% of the overrides were not appropriate. Future research should optimize alert types and frequencies to increase their clinical relevance, reducing alert fatigue so that important alerts are not inappropriately overridden.
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McDaniel, Robert B., Jonathan D. Burlison, Donald K. Baker, Murad Hasan, Jennifer Robertson, Christine Hartford, Scott C. Howard, Andras Sablauer, and James M. Hoffman. "Alert dwell time: introduction of a measure to evaluate interruptive clinical decision support alerts." Journal of the American Medical Informatics Association 23, e1 (October 24, 2015): e138-e141. http://dx.doi.org/10.1093/jamia/ocv144.

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Abstract Metrics for evaluating interruptive prescribing alerts have many limitations. Additional methods are needed to identify opportunities to improve alerting systems and prevent alert fatigue. In this study, the authors determined whether alert dwell time—the time elapsed from when an interruptive alert is generated to when it is dismissed—could be calculated by using historical alert data from log files. Drug–drug interaction (DDI) alerts from 3 years of electronic health record data were queried. Alert dwell time was calculated for 25,965 alerts, including 777 unique DDIs. The median alert dwell time was 8 s (range, 1–4913 s). Resident physicians had longer median alert dwell times than other prescribers ( P < .001). The 10 most frequent DDI alerts ( n = 8759 alerts) had shorter median dwell times than alerts that only occurred once ( P < .001). This metric can be used in future research to evaluate the effectiveness and efficiency of interruptive prescribing alerts.
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Elias, Pierre, Eric Peterson, Bob Wachter, Cary Ward, Eric Poon, and Ann Marie Navar. "Evaluating the Impact of Interruptive Alerts within a Health System: Use, Response Time, and Cumulative Time Burden." Applied Clinical Informatics 10, no. 05 (October 2019): 909–17. http://dx.doi.org/10.1055/s-0039-1700869.

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Abstract Background Health systems often employ interruptive alerts through the electronic health record to improve patient care. However, concerns of “alert fatigue” have been raised, highlighting the importance of understanding the time burden and impact of these alerts on providers. Objectives Our main objective was to determine the total time providers spent on interruptive alerts in both inpatient and outpatient settings. Our secondary objectives were to analyze dwell time for individual alerts and examine both provider and alert-related factors associated with dwell time variance. Methods We retrospectively evaluated use and response to the 75 most common interruptive (“popup”) alerts between June 1st, 2015 and November 1st, 2016 in a large academic health care system. Alert “dwell time” was calculated as the time between the alert appearing on a provider's screen until it was closed. The total number of alerts and dwell times per provider per month was calculated for inpatient and outpatient alerts and compared across alert type. Results The median number of alerts seen by a provider was 12 per month (IQR 4–34). Overall, 67% of inpatient and 39% of outpatient alerts were closed in under 3 seconds. Alerts related to patient safety and those requiring more than a single click to proceed had significantly longer median dwell times of 5.2 and 6.7 seconds, respectively. The median total monthly time spent by providers viewing alerts was 49 seconds on inpatient alerts and 28 seconds on outpatient alerts. Conclusion Most alerts were closed in under 3 seconds and a provider's total time spent on alerts was less than 1 min/mo. Alert fatigue may lie in their interruptive and noncritical nature rather than time burden. Monitoring alert interaction time can function as a valuable metric to assess the impact of alerts on workflow and potentially identify routinely ignored alerts.
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Zeng, Chao, Wenjun Wang, Chaoyang Chen, Chaofei Zhang, and Bo Cheng. "Sex Differences in Time-Domain and Frequency-Domain Heart Rate Variability Measures of Fatigued Drivers." International Journal of Environmental Research and Public Health 17, no. 22 (November 17, 2020): 8499. http://dx.doi.org/10.3390/ijerph17228499.

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The effects of fatigue on a driver’s autonomic nervous system (ANS) were investigated through heart rate variability (HRV) measures considering the difference of sex. Electrocardiogram (ECG) data from 18 drivers were recorded during a simulator-based driving experiment. Thirteen short-term HRV measures were extracted through time-domain and frequency-domain methods. First, differences in HRV measures related to mental state (alert or fatigued) were analyzed in all subjects. Then, sex-specific changes between alert and fatigued states were investigated. Finally, sex differences between alert and fatigued states were compared. For all subjects, ten measures showed significant differences (Mann-Whitney U test, p < 0.01) between different mental states. In male and female drivers, eight and four measures, respectively, showed significant differences between different mental states. Six measures showed significant differences between males and females in an alert state, while ten measures showed significant sex differences in a fatigued state. In conclusion, fatigue impacts drivers’ ANS activity, and this impact differs by sex; more differences exist between male and female drivers’ ANS activity in a fatigued state than in an alert state.
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Dissertations / Theses on the topic "Alert fatigue"

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Herrera, Castro Paulo Cesar, and Barrientos Karla Andrea Sanchez. "Associated factors to fatigue perception in college athletes during the sanitary alert due to COVID-19." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2020. http://hdl.handle.net/10757/655594.

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Background: Sports practice has been affected by confinement due to the COVID-19 pandemic. This fact could cause a detraining effect and vary the levels of physical effort, habits and of physical activity in athletes. These factors could influence the degree of adaptation to physical exercise, increase the fatigue perception and be a difficulty when the athletes return to regular workouts. Objectives: To determine the associated factors to fatigue in college team-sports athletes in the COVID-19 pandemic context. Methods: Analytical cross-sectional observational study in team-sports college athletes. Data collection was done through self-administered questionnaires and phone calls. Adapted Visual Analogue Fatigue Scale (VAS-F), Rating of Perceived Exertion (Borg Scale) and a survey with questions about habits and demographic characteristics were used. VAS-F was applied two times, at the beginning and the end of the day. Bivariate linear regression models were used to evaluate the associated factors. Results: 95 athletes met the inclusion criteria, 60% of them were male. Likewise, 95% of the participants kept training at home and the majority maintained a high level of physical activity. Male athletes presented on average 9.78 points less of fatigue perception at the end of the day than women. No association was found between the fatigue perception and physical effort, nor the level of physical activity. Conclusions: Fatigue perception is a phenomenon that is not associated with the level of physical activity and perception of physical effort. In this study, differences in fatigue perception were found in accordance to gender and practiced sport.
Introducción: La práctica deportiva se ha visto afectada por el confinamiento debido a la pandemia de COVID-19. Este hecho podría causar un efecto de desentrenamiento y variar los niveles de esfuerzo físico, hábitos y nivel de actividad física en deportistas. Estos factores podrían influir en su grado de adaptación al ejercicio físico, aumentar su percepción de la fatiga y ser una dificultad cuando se retorne a los entrenamientos habituales. Objetivos: Determinar los factores asociados a la fatiga en deportistas universitarios en el contexto de la pandemia por COVID-19. Métodos: Estudio observacional transversal analítico en atletas universitarios de deportes colectivos. La recolección de datos se realizó mediante cuestionarios y llamadas telefónicas. Se utilizó la escala visual analógica adaptada para la fatiga (VAS-F), de percepción del esfuerzo físico (escala de Borg) y una encuesta con preguntas sobre hábitos y características demográficas. El VAS-F fue evaluado en dos momentos, al inicio y al final del día. Se utilizó un modelo de regresión lineal bivariada para la evaluación de los factores asociados. Resultados: 95 atletas cumplieron con los criterios de inclusión. 60% de los deportistas eran varones. Así mismo, 95% de los participantes se mantuvo entrenando en casa y la mayoría mantuvo un nivel alto de actividad física. Los atletas varones presentaron en promedio 9.78 puntos menos de percepción de fatiga al final del día que las mujeres. No se encontró asociación entre la percepción de la fatiga y del esfuerzo físico, ni el nivel de actividad física. Conclusiones: La percepción de la fatiga es un fenómeno que no se asocia al nivel de actividad física y percepción del esfuerzo físico. En este estudio se hallaron diferencias de percepción de fatiga entre hombres, mujeres y algunos deportes.
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Herrera, Castro Paulo Cesar, and Barrientos Karla Andrea Sanchez. "Factores asociados a la percepción de la fatiga en deportistas universitarios durante la alerta sanitaria por COVID-19." Universidad Peruana de Ciencias Aplicadas (UPC), 2020. http://hdl.handle.net/10757/657351.

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Objetivo: Determinar los factores que se asocian a la percepción de fatiga en deportistas universitarios durante la etapa de cuarentena. Diseño: Esta investigación es de tipo observacional transversal analítico. Se eligió por conveniencia el desarrollo del estudio en atletas de deportes colectivos de la Universidad Peruana de Ciencias Aplicadas (UPC). Por otro lado, se va a desarrollar por medio de una encuesta en línea dirigida a los atletas elegibles.
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Dali, Souhir. "Study of the temporal deployment of attention : identification and characterization of psychological, neural and physiological indicators of mental effort." Thesis, Paris 10, 2019. http://faraway.parisnanterre.fr/login?url=http://bdr.parisnanterre.fr/theses/intranet/2019/2019PA100168/2019PA100168.pdf.

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L'objectif principal de cette thèse est de montrer que l’entrainement mental (EM) induit par imagerie motrice entraine un déploiement temporel de l'attention et optimise la préparation temporelle. Le deuxième objectif est de montrer que lorsque l'effort mental est maintenu une longue période, il peut entraîner une fatigue mentale. Nous essayons de trouver des marqueurs psychologiques, neurologiques et physiologiques de l'effort mental pour mieux caractériser la fatigue mentale. Dans la première étude, nous avons montré que l’entraînement mental optimisait les attentes temporelles pour les courts foreperiods « FP » avec un renforcement de la connectivité effective entre l'insula antérieure (AI) et le cortex cingulaire antérieur (ACC), l'AI et le cortex préfrontal dorsolatéral (DLPFC) (FP = 250/280ms: alerte intrinsèque) et entre le DLPFC et l'ACC (FP=650ms : alerte extrinsèque). La deuxième étude a montré après l'imagerie motrice, une augmentation des temps de réaction vers la fin de la tâche pour l’alerte intrinsèque (FP=250/280 ms) avec une diminution de la connectivité entre AI-ACC et AI-DLPFC. Nous suggérons que la FP et l’EM pourraient jouer un rôle dans le déploiement temporel de l'attention et constitueraient des marqueurs psychologiques et neurologiques de l'effort mental via le réseau AI-ACC-DLPFC. Dans la troisième étude, nous avons examiné la relation entre l'effort mental et une composante physiologique «cortisol». Les résultats ont montré que la concentration de cortisol était élevée au niveau de la tâche d’imagerie et était liée à l'augmentation de l'activité de l'hypothalamus et du tronc cérébral. Cette étude montre que ces régions pourraient jouer un rôle dans la régulation de la sécrétion de cortisol en réponse à une situation cognitivement exigeante
The main objective of this thesis is to show that attentional reinforcement induced by an intensive short session of mental training (MT), induces a temporal deployment of attention and optimize temporal preparation. The second objective is to show that when the mental effort is maintained for a long time, it may lead to mental fatigue. We try to find psychological, neurological and physiological markers of mental effort for a better characterization of the mental fatigue described in everyday life and neurological diseases. In the first study, we showed that MT optimized temporal expectancies for shortest foreperiods “FPs” (250/280ms in intrinsic alertness and 650ms in extrinsic task). Strengthened effective connectivity between the right anterior insula (AI) and anterior cingulate (ACC), AI and dorsolateral prefrontal cortex (DLPFC) during intrinsic alertness and between the DLPFC and ACC, during extrinsic alertness was observed. The second study showed after MT, increased reaction times by the end of the session only in intrinsic alertness (250/280ms FPs) associated with decreased connectivity between AI-ACC and AI-DLPFC. We suggest that FP and MT may play a crucial role in temporal deployment of attention and would constitute psychological and neurological markers of mental effort or fatigue, notably through AI-ACC-DLPFC network. In the third study, we examined the relation between a physiological component “cortisol” and mental effort. Preliminary results show that the motor imagery task was more demanding in terms of cortisol secretion and was related to increase of hypothalamus and brainstem activity. This study shows that hypothalamus and brainstem may play a major role in the regulation of cortisol secretion in response to cognitively demanding situation
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Yu, Xue Han, and 余學翰. "Facial and Head Status Detection for Driver Fatigue Alert Systems." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/9784w8.

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Books on the topic "Alert fatigue"

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Reissman, Carla J. The alert driver: A trucker's guide to sleep, fatigue, and rest in our 24-hour society. Alexandria, VA: American Trucking Associations, 1997.

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Prado, Raquel. Multistate models for mental fatigue. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.29.

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This article discusses the use of structured, multivariate Bayesian dynamic models in the analysis of experimental data involving large-scale electroencephalography (EEG) signals or time series generated on individuals subject to tasks inducing mental fatigue. It first provides an overview of the goals and challenges in the analysis of brain signals, using the EEG case as example, before describing the development and application of novel time-varying autoregressive and regime switching models, which incorporate relevant prior information via structured priors and fitted using novel, customized Bayesian computational methods. In the experiment, a subject was asked to perform simple arithmetic operations for a period of three hours. Prior to the experiment, the subject was confirmed to be alert. After the experiment ended, the subject was fatigued. The study demonstrates that Bayesian analysis is useful for real time detection of cognitive fatigue.
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Book chapters on the topic "Alert fatigue"

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van der Sijs, Heleen. "Errors Related to Alert Fatigue." In Safety of Health IT, 41–54. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31123-4_4.

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Aminanto, Muhamad Erza, Lei Zhu, Tao Ban, Ryoichi Isawa, Takeshi Takahashi, and Daisuke Inoue. "Combating Threat-Alert Fatigue with Online Anomaly Detection Using Isolation Forest." In Neural Information Processing, 756–65. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36708-4_62.

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Thota, Jyotsna Rani, B. J. Jaidhan, Mukkamala S. N. V. Jitendra, A. Shanmuk Srinivas, and A. S. Venkata Praneel. "Computer Vision-Based Alert System to Detect Fatigue in Vehicle Drivers." In Advances in Data Science and Management, 533–44. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-5685-9_52.

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Arnaldo, Rosa M., Fernando Gomez Comendador, Luis Pérez Sanz, and Alvaro Rodriguez Sanz. "Friendly Fatigue Alert Mobile Apps to Help Aviation Workers Prevent, Identify and Manage Alertness and Fatigue." In Advances in Intelligent Systems and Computing, 421–32. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41929-9_39.

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Poly, Tahmina Nasrin, Md Mohaimenul Islam, and Yu-Chuan (Jack) Li. "Clinical Usefulness of Drug-Disease Interaction Alerts from a Clinical Decision Support System, MedGuard, for Patient Safety: A Single Center Study." In MEDINFO 2021: One World, One Health – Global Partnership for Digital Innovation. IOS Press, 2022. http://dx.doi.org/10.3233/shti220089.

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Clinical decision support systems have been widely used in healthcare, yet few studies have concurrently measured the clinical effectiveness of CDSSs, and the appropriateness of alerts with physicians’ response to alerts. We conducted a retrospective analysis of prescriptions caused disease-medication related alerts. Medication orders for outpatients’ prescriptions, all aged group were included in this study. All the prescriptions were reviewed, and medication orders compared with a widely used medication reference (UpToDate) and other standard guidelines. We reviewed 1,409 CDS alerts (2.67% alert rate) on 52,654 prescriptions ordered during the study period. 545 (38.70%) of alerts were overridden. Override appropriateness was 2.20% overall. However, the rate of alert acceptance was higher, ranging from 11.11 to 92.86%. The MedGuard system had a lower overridden rate than other systems reported in previous studies. The acceptance rate of alerts by physicians was high. Moreover, false-positive rate was low. The MedGuard system has the potential to reduce alert fatigue and to minimize the risk of patient harm.
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Muhiyaddin, Raghad, Asma Elfadl, Ebtehag Mohamed, Zubair Shah, Tanvir Alam, Alaa Abd-Alrazaq, and Mowafa Househ. "Electronic Health Records and Physician Burnout: A Scoping Review." In Studies in Health Technology and Informatics. IOS Press, 2022. http://dx.doi.org/10.3233/shti210962.

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This scoping review aims to identify the causes and consequences of physician burnout resulting from using Electronic Health Records (EHRs), as reported by current literature. We identified studies by searching PubMed, Wiley Online Library, and Google Scholar. Study selection and data extraction were conducted by three reviewers independently. Extracted data was then synthesized narratively. Out of 500 references retrieved, 30 studies met all eligibility criteria. We identified six main causes that lead to physician burnout related to the use of EHRs: EHRs’ documentation and related tasks, EHRs’ poor design, workload, overtime work, inbox alerts, and alert fatigue. We also identified the following consequences of physician burnout: low-quality care, behavioral issues, mental health complications, substance abuse, career dissatisfaction, costly turnover, and a decline in patient safety and satisfaction.
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Goforth, Harold W., and Mary Ann Cohen. "Symptoms Associated with HIV and AIDS." In Handbook of AIDS Psychiatry. Oxford University Press, 2010. http://dx.doi.org/10.1093/oso/9780195372571.003.0013.

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Many persons with HIV and AIDS have symptoms that are unrelated to underlying psychiatric disorders but may masquerade as such. These symptoms may include insomnia, fatigue, nausea, or other troubling symptoms, and often result in suffering for patients, their families, and loved ones. The symptoms are common throughout the course of HIV and AIDS, from onset of infection to late-stage and end-stage AIDS. They need to be addressed whenever they occur and not only as part of end-of-life care. We present protocols to ameliorate or eliminate these symptoms and alleviate suffering. Fatigue is one of the most prevalent but underreported and undertreated aspects of HIV disease. The prevalence of fatigue in an HIV population has been estimated to affect at least 50% of seropositive individuals (Breitbart et al., 1998) and may affect up to 80% of the population. Darko and colleagues (1992) found that HIV-seropositive individuals were more fatigued, required more sleep and daytime naps, and showed less alert morning functioning than did persons who are HIV-seronegative. While the symptom of fatigue may fluctuate with increasing viral loads, there is no evidence base for a consistent correlation between fatigue and viral load. Fatigue is a pseudo-specific symptom common to a variety of disabilities found in an HIV population, and it has been linked to a variety of other AIDS-related disabilities including pain, anemia, impaired physical function, psychological distress, and depression. Hormonal alterations, such as those in testosterone and thyroxin, that occur in the context of HIV infection are also common in this group. While these findings are further discussed in Chapter 10, it is worth noting here that they can contribute substantially to tiredness and fatigue in this population. Other sources of fatigue include multimorbid chronic illnesses (opportunistic infections and cancers, chronic renal insufficiency, hepatitis C and other hepatic illnesses, and chronic obstructive pulmonary disease [COPD]) and some of their treatments (notably interferon/ribavirin for hepatitis C and cancer chemotherapy). Substances such as recreational drugs, nicotine, and caffeine are also factors in HIV-related fatigue.
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Robert, Laurine, Chloé Rousseliere, Jean-Baptiste Beuscart, Sophie Gautier, Emmanuel Chazard, Bertrand Decaudin, and Pascal Odou. "Integration of Explicit Criteria in a Clinical Decision Support System Through Evaluation of Acute Kidney Injury Events." In Studies in Health Technology and Informatics. IOS Press, 2021. http://dx.doi.org/10.3233/shti210249.

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In Clinical Decision Support System (CDSS), relevance of alerts is essential to limit alert fatigue and risk of overriding relevant alerts by health professionals. Detection of acute kidney injury (AKI) situations is of great importance in clinical practice and could improve quality of care. Nevertheless, to our knowledge, no explicit rule has been created to detect AKI situations in CDSS. The objective of the study was to implement an AKI detection rule based on KDIGO criteria in a CDSS and to optimize this rule to increase its relevance in clinical pharmacy use. Two explicit rules were implemented in a CDSS (basic AKI rule and improved AKI rule), based on KDIGO criteria. Only the improved rule was optimized by a group of experts during the two-month study period. The CDSS provided 1,125 alerts on AKI situations (i.e. 643 were triggered for the basic AKI rule and 482 for the improved AKI rule). As the study proceeds, the pharmaceutically and medically relevance of alerts from the improved AKI rule increased. A ten-fold increase was shown for the improved AKI rule compared to the basic AKI rule. The study highlights the usefulness of a multidisciplinary review to enhance explicit rules integrated in CDSS. The improved AKI is able to detect AKI situations and can improve workflow of health professionals.
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S.M, Revathi, Srinivasan R, Balamurugan C.R, and Kareemullah H. "Driver Stress Detection Based on IOT Motion Sensor Using Wearable Glove." In Applications of Artificial Intelligence and Machine Learning in Healthcare. Technoarete Publishing, 2022. http://dx.doi.org/10.36647/aaimlh/2022.01.b1.ch002.

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Stress conditions experienced by the driver is a serious problem in road safety. Driver error is the most common cause of road accidents. In this paper skin conductance is taken for analysis of driver drowsiness fatigue and mental stress. In order to minimize human error while driving it monitors stress and fatigue by measuring physiological parameters like skin acting like a conductor gives a response also called as Galvanic skin response and the motion is continuously monitored over a period of time. Internet of Things (IOT) based sensor used in driver’s health care is novel approach from the classical ways that includes visiting hospitals for clinical procedure and constant supervision of the person. It connects the health care professionals with the driver through smart device to monitor vitals without affecting the freedom of movement of the driver. This chapter introduces a viewof IOT functionality and its application with the sensing and wireless technique for implementing the required stress monitoring system for drivers. Further the Captured data is sent to an IOT Cloud Where Machine learning algorithms were deployed for computing the percentage of alertness and stress if the stress levels go beyond the threshold levels, then alert signal is sent to the driver from buzzer.
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Lovis, Christian. "Health, Digital Health and Decision Support: Sisyphus and Pandora." In Studies in Health Technology and Informatics. IOS Press, 2022. http://dx.doi.org/10.3233/shti220950.

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The history of medicine is punctuated by conquests, discoveries and revolutions. It is also marked by questioning. It is made of doubts and certainties. In this thousand years old history, certain recent battles bear witness to these questionings, such as quality, refocusing on the patient, medical errors, antibiotic resistance and the importance of gender, which has been neglected for so long in medicine. Digitalization is one of these many revolutions, and it is not immune to questioning. Building evidence and trust, equity of access for neglected populations, and training are among these issues. More specifically, in the field of decision support, the first enthusiastic hours of computing were followed by unexpected observations, such as the identification of human factors, such as alert fatigue. Today, immense hopes rest on the development of deep learning, and it is up to us to accelerate its development by investing energy, time and resources to build on evidence, trust, and a strong integration of health professionals and patients.
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Conference papers on the topic "Alert fatigue"

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Aminanto, Muhamad Erza, Lei Zhu, Tao Ban, Ryoichi Isawa, Takeshi Takahashi, and Daisuke Inoue. "Automated Threat-Alert Screening for Battling Alert Fatigue with Temporal Isolation Forest." In 2019 17th International Conference on Privacy, Security and Trust (PST). IEEE, 2019. http://dx.doi.org/10.1109/pst47121.2019.8949029.

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Ban, Tao, Ndichu Samuel, Takeshi Takahashi, and Daisuke Inoue. "Combat Security Alert Fatigue with AI-Assisted Techniques." In CSET '21: Cyber Security Experimentation and Test Workshop. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3474718.3474723.

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Ahmed, Tariq, Aayush Shah, Morarjee Kolla, and Ramadevi Yellasiri. "Reduction of Alert Fatigue using Extended Isolation Forest." In 2021 International Conference on Forensics, Analytics, Big Data, Security (FABS). IEEE, 2021. http://dx.doi.org/10.1109/fabs52071.2021.9702617.

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Hassan, Wajih Ul, Shengjian Guo, Ding Li, Zhengzhang Chen, Kangkook Jee, Zhichun Li, and Adam Bates. "NoDoze: Combatting Threat Alert Fatigue with Automated Provenance Triage." In Network and Distributed System Security Symposium. Reston, VA: Internet Society, 2019. http://dx.doi.org/10.14722/ndss.2019.23349.

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Jimenez-Pinto, Javier, and Miguel Torres-Torriti. "Driver alert state and fatigue detection by salient points analysis." In 2009 IEEE International Conference on Systems, Man and Cybernetics. SMC 2009. IEEE, 2009. http://dx.doi.org/10.1109/icsmc.2009.5346760.

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Chan, Daniel. "4 Reduction of order alerts through filters: impact on pharmacists’ override rate and perceptions of alert fatigue." In Faculty of Clinical Informatics Annual Scientific Conference 2022. BMJ Publishing Group Ltd, 2022. http://dx.doi.org/10.1136/bmjhci-2022-fciasc.4.

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Jothimani, S., K. Madhumitha, V. Narmadha, and R. Naveena. "Driver Fatigue Prediction with Real Time Driver Alert System Using Deep Learning." In 2022 International Conference on Applied Artificial Intelligence and Computing (ICAAIC). IEEE, 2022. http://dx.doi.org/10.1109/icaaic53929.2022.9792677.

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Ali, Misna, Shahsad Abdullah, C. S. Raizal, K. F. Rohith, and Varun G. Menon. "A Novel and Efficient Real Time Driver Fatigue and Yawn Detection-Alert System." In 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI). IEEE, 2019. http://dx.doi.org/10.1109/icoei.2019.8862632.

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Aboagye, Isaac A., Wiafe Owusu-Banahene, Kevin Amexo, Kwadwo A. Boakye-Yiadom, Robert A. Sowah, and Nii Longdon Sowah. "Design and Development of Computer Vision-Based Driver Fatigue Detection and Alert System." In 2021 IEEE 8th International Conference on Adaptive Science and Technology (ICAST). IEEE, 2021. http://dx.doi.org/10.1109/icast52759.2021.9681943.

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Tran, Yvonne, Ranjit Thuraisingham, Nirupama Wijesuriya, Ashley Craig, and Hung Nguyen. "Using S-transform in EEG analysis for measuring an alert versus mental fatigue state." In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2014. http://dx.doi.org/10.1109/embc.2014.6944966.

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Journal articles
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