Pro-Con Debate: Universal Versus Selective Continuous Monitoring of Postoperative Patients.

In this Pro-Con commentary article, we discuss use of continuous physiologic monitoring for clinical deterioration, specifically respiratory depression in the postoperative population. The Pro position advocates for 24/7 continuous surveillance monitoring of all patients starting in the postanesthesia care unit until discharge from the hospital. The strongest arguments for universal monitoring relate to inadequate assessment and algorithms for patient risk. We argue that the need for hospitalization in and of itself is a sufficient predictor of an individual's risk for unexpected respiratory deterioration. In addition, general care units carry the added risk that even the most severe respiratory events will not be recognized in a timely fashion, largely due to higher patient to nurse staffing ratios and limited intermittent vital signs assessments (e.g., every 4 hours). Continuous monitoring configured properly using a "surveillance model" can adequately detect patients' respiratory deterioration while minimizing alarm fatigue and the costs of the surveillance systems. The Con position advocates for a mixed approach of time-limited continuous pulse oximetry monitoring for all patients receiving opioids, with additional remote pulse oximetry monitoring for patients identified as having a high risk of respiratory depression. Alarm fatigue, clinical resource limitations, and cost are the strongest arguments for selective monitoring, which is a more targeted approach. The proponents of the con position acknowledge that postoperative respiratory monitoring is certainly indicated for all patients, but not all patients need the same level of monitoring. The analysis and discussion of each point of view describes who, when, where, and how continuous monitoring should be implemented. Consideration of various system-level factors are addressed, including clinical resource availability, alarm design, system costs, patient and staff acceptance, risk-assessment algorithms, and respiratory event detection. Literature is reviewed, findings are described, and recommendations for design of monitoring systems and implementation of monitoring are described for the pro and con positions.

Critical Care Alarm Fatigue and Monitor Customization: Alarm Frequencies and Context Factors.

BACKGROUND: Alarm fatigue among nurses working in the intensive care unit has garnered considerable attention as a national patient safety priority. A viable solution for reducing the frequency of alarms and unnecessary noise is intensive care unit alarm monitor customization. LOCAL PROBLEM: A 24-bed cardiovascular and thoracic surgery intensive care unit in a large academic medical center identified a high rate of alarms and associated noise as a problem contributing to nurse alarm fatigue. METHODS: An alarm monitor quality improvement project used both alarm frequency and nurse surveys before and after implementation to determine the effectiveness of interventions. Multimodal interventions included nurse training sessions, informational flyers, organizational policies, and an alarm monitor training video. Unexpected results inspired an extensive investigation and secondary analysis, which included examining the data-capturing capabilities of the alarm monitors and the impact of context factors. RESULTS: Alarm frequencies unexpectedly increased after the intervention. The software data-capturing features of the alarm monitors for determining frequency did not accurately measure nurse interactions with monitors. Measured increases in patient census, nurse staffing, and data input from medical devices from before to after the intervention substantially affected project results. CONCLUSIONS: Alarm frequencies proved an unreliable measure of nurse skills and practices in alarm customization. Documented changes in context factors provided strong anecdotal evidence of changed circumstances that clarified project results and underscored the critical importance of contemporaneous collection of context data. Designs and methods used in quality improvement projects must include reliable outcome measures to achieve meaningful results.

ARTEMIS: An alarm threshold and policy mining system for the intensive care unit.

BACKGROUND: Alarm fatigue is a major technology-induced hazard for patients and staff in intensive care units. Too many - mostly unnecessary - alarms cause desensitisation and lack of response in medical staff. Unsuitable alarm policies are one reason for alarm fatigue. But changing alarm policies is a delicate issue since it concerns patient safety. OBJECTIVE: We present ARTEMIS, a novel, computer-aided clinical decision support system for policy makers that can help to considerably improve alarm policies using data from hospital information systems. METHODS: Policy makers can use different policy components from ARTEMIS' internal library to assemble tailor-made alarm policies for their intensive care units. Alternatively, policy makers can provide even more highly customised policy components as Python functions using data the hospital information systems. This can even include machine learning models - for example for setting alarm thresholds. Finally, policy makers can evaluate their system of policies and compare the resulting alarm loads. RESULTS: ARTEMIS reports and compares numbers of alarms caused by different alarm policies for an easily adaptable target population. ARTEMIS can compare policies side-by-side and provides grid comparisons and heat maps for parameter optimisation. For example, we found that the utility of alarm delays varies based on target population. Furthermore, policy makers can introduce virtual parameters that are not in the original data by providing a formula to compute them. Virtual parameters help measuring and alarming on the right metric, even if the patient monitors do not directly measure this metric. CONCLUSION: ARTEMIS does not release the policy maker from assessing the policy from a medical standpoint. But as a knowledge discovery and clinical decision support system, it provides a strong quantitative foundation for medical decisions. At comparatively low cost of implementation, ARTEMIS can have a substantial impact on patients and staff alike - with organisational, economic, and clinical benefits for the implementing hospital.

Implementation of a Continuous Patient Monitoring System in the Hospital Setting: A Qualitative Study.

BACKGROUND: Technology can improve care delivery, patient outcomes, and staff satisfaction, but integration into the clinical workflow remains challenging. To contribute to this knowledge area, this study examined the implementation continuum of a contact-free, continuous monitoring system (CFCM) in an inpatient setting. CFCM monitors vital signs and uses the information to alert clinicians of important changes, enabling early detection of patient deterioration. METHODS: Data were collected throughout the entire implementation continuum at a community teaching hospital. Throughout the study, 3 group and 24 individual interviews and five process observations were conducted. Postimplementation alarm response data were collected. Analysis was conducted using triangulation of information sources and two-coder consensus. RESULTS: Preimplementation perceived barriers were alarm fatigue, questions about accuracy and trust, impact on patient experience, and challenges to the status quo. Stakeholders identified the value of CFCM as preventing deterioration and benefitting patients who are not good candidates for telemetry. Educational materials addressed each barrier and emphasized the shared CFCM values. Mean alarm response times were below the desired target of two minutes. Postimplementation interview analysis themes revealed lessened concerns of alarm fatigue and improved trust in CFCM than anticipated. Postimplementation challenges included insufficient training for secondary users and impact on patient experience. CONCLUSION: In addition to understanding the preimplementation anticipated barriers to implementation and establishing shared value before implementation, future recommendations include studying strategies for optimal tailoring of education to each user group, identifying and reinforcing positive process changes after implementation, and including patient experience as the overarching element in frameworks for digital tool implementation.

Interdisciplinary collaboration in critical care alarm research: A bibliometric analysis.

BACKGROUND: Alarm fatigue in nurses is a major patient safety concern in the intensive care unit. This is caused by exposure to high rates of false and non-actionable alarms. Despite decades of research, the problem persists, leading to stress, burnout, and patient harm resulting from true missed events. While engineering approaches to reduce false alarms have spurred hope, they appear to lack collaboration between nurses and engineers to produce real-world solutions. The aim of this bibliometric analysis was to examine the relevant literature to quantify the level of authorial collaboration between nurses, physicians, and engineers. METHODS: We conducted a bibliometric analysis of articles on alarm fatigue and false alarm reduction strategies in critical care published between 2010 and 2022. Data were extracted at the article and author level. The percentages of author disciplines per publication were calculated by study design, journal subject area, and other article-level factors. RESULTS: A total of 155 articles with 583 unique authors were identified. While 31.73 % (n = 185) of the unique authors had a nursing background, publications using an engineering study design (n = 46), e.g., model development, had a very low involvement of nursing authors (mean proportion at 1.09 %). Observational studies (n = 58) and interventional studies (n = 33) had a higher mean involvement of 52.27 % and 47.75 %, respectively. Articles published in nursing journals (n = 32) had the highest mean proportion of nursing authors (80.32 %), while those published in engineering journals (n = 46) had the lowest (9.00 %), with 6 (13.04 %) articles having one or more nurses as co-authors. CONCLUSION: Minimal involvement of nursing expertise in alarm research utilizing engineering methodologies may be one reason for the lack of successful, real-world solutions to ameliorate alarm fatigue. Fostering a collaborative, interdisciplinary research culture can promote a common publication culture across fields and may yield sustainable implementation of technological solutions in healthcare.

Factores asociados a malestar psicológico durante la pandemia de COVID-19 en personal de salud de un hospital público de Ecuador / Related factors to psychological distress during the COVID-19 pandemic in the health staff of a public hospital in Ecuador

Fundamento: La pandemia por el coronavirus SARS-CoV-2, genera afectaciones en las esferas social, económica y sanitaria de un país, y de manera particular, consecuencias psicológicas negativas en el personal sanitario de hospitales públicos, considerados como la primera línea de atención a pacientes con esta enfermedad. Objetivo: Describir factores asociados a la presencia de malestar psicológico en el personal sanitario de un hospital general público en Ecuador, durante la pandemia de COVID-19. Metodología: Estudio no experimental, de corte transversal, con alcance descriptivo-correlacional. Los datos correspondieron a 276 funcionarios de la salud que respondieron un instrumento online, con un módulo de datos sociodemográficos y una escala de tamizaje de malestar psicológico, estos se aplicaron después de una intervención en salud dirigida al personal de salud realizada al inicio de la pandemia, en mayo del año 2020. Se realizaron análisis descriptivos y de asociación, mediante el software SPSS 25.0. Resultados: La muestra estuvo compuesta por 76.1 % de mujeres, 23.9 % de hombres, con una media de edad de 36 años, en mayor cantidad con profesionales de Enfermería (33.7 %), seguido de Medicina (24.3 %). El 70.7 % del personal de salud presentó malestar psicológico, de estos, el 26.1 % con indicativo de trastorno mental. Se encontraron tres variables asociadas a la presencia de malestar psicológico: clima laboral, teletrabajo y convivir con grupos de riesgo. Conclusiones: El personal de Salud ha presentado afectación en su salud mental asociado a las condiciones sociolaborales durante la pandemia.

Background: The SARS-CoV-2 coronavirus pandemic affects the social, economic and health spheres of a country, especially negative psychological consequences to the health staff of public hospitals, considered as the first line of care for patients with this disease. Objective: To describe factors related to the presence of psychological distress in the health personnel of a public general hospital in Ecuador, during the COVID-19 pandemic. Methodology: Non-experimental, cross-sectional study with a descriptive-correlational scope. The data corresponded to 276 health officials who answered to an online instrument, with a sociodemographic data module and a psychological distress screening scale, these were applied after a health intervention aimed at health personnel conducted at the beginning of the pandemic, in May 2020. Descriptive and association analyzes were performed using SPSS 25.0 software. Results: The sample was made up of 76.1 % women, 23.9 % men, mean age of 36 years, with a greater number of Nursing professionals (33.7 %), followed by Medicine (24.3 %). 70.7 % of the health personnel presented psychological distress, out of these, 26.1 % showed mental disorder. Three variables related to the presence of psychological distress were found: work environment, teleworking and living with risk groups. Conclusions: Health staff has presented mental health distress related to socio-labor conditions during the pandemic.

Parametrização dos alarmes de frequência respiratória em ventiladores mecânicos de pacientes durante o banho / Parameterization of respiratory rate alarms in mechanical ventilators of patients during the bath / Parametrización de las alarmas de frecuencia respiratoria en ventiladores mecánicos de pacientes durante el baño

RESUMO Objetivo: medir os efeitos da parametrização dos alarmes sonoros de frequência respiratória dos ventiladores mecânicos para redução do número de alarmes disparados durante o banho no leito. Método: ensaio clínico pragmático, para comparar o número de alarmes do ventilador mecânico nos grupos: intervenção - os alarmes de Frequência Respiratória foram parametrizados no início do banho; controle - não realizada parametrização. Estudo registrado em 27/08/2019 no Registro Brasileiro de Ensaios Clínicos, RBR-6y6tyc, Rio de Janeiro, Brasil. Resultados: os modelos de regressão evidenciaram que a parametrização, realizada e mantida durante e após o banho no grupo intervenção, teve o efeito de aumentar 12,5 e 6,4 vezes, respectivamente, o número médio de disparos de alarmes de frequência respiratória alta; e não teve efeito nos alarmes de frequência respiratória baixa. Conclusão: a contribuição deste estudo é auxiliar os profissionais de saúde na formulação de protocolos de parametrização individualizada dos alarmes dos Ventiladores Mecânicos.

ABSTRACT Objective: to measure the effects of parameterizing the audible respiratory rate alarms of mechanical ventilators to reduce the number of alarms triggered during bed bath. Method: pragmatic clinical trial, to compare the number of alarms of the mechanical ventilator, in the groups: intervention - the Respiratory Rate alarms were parameterized at the beginning of the bath; control - no parameterization performed. Study registered on 27/08/2019 in the Brazilian Registry of Clinical Trials, RBR-6y6tyc, Rio de Janeiro, Brazil. Results: Regression models showed that parameterization, performed and maintained during and after bath in the intervention group, had the effect of increasing the average number of high respiratory rate alarm triggers by 12.5 and 6.4 times, respectively; and had no effect on low respiratory rate alarms. Conclusion: The contribution of this study is to assist health professionals in formulating protocols for individualized parameterization of alarms for Mechanical Ventilators.

RESUMEN Objetivo: medir los efectos de la parametrización de las alarmas sonoras de frecuencia respiratoria de los ventiladores mecánicos para reducir el número de alarmas disparadas durante el baño en cama. Método: ensayo clínico pragmático, para comparar el número de alarmas del ventilador mecánico en los grupos: intervención - se parametrizaron las alarmas de Frecuencia Respiratoria al inicio del baño; control - no se realizó parametrización. Estudio registrado el 27/08/2019 en el Registro Brasileño de Ensayos Clínicos, RBR-6y6tyc, Río de Janeiro, Brasil. Resultados: Los modelos de regresión mostraron que la parametrización, realizada y mantenida durante y después del baño en el grupo de intervención, tuvo el efecto de aumentar 12,5 y 6,4 veces, respectivamente, el número medio de disparos de alarmas de frecuencia respiratoria alta; y no tuvo ningún efecto sobre las alarmas de frecuencia respiratoria baja. Conclusión: la contribución de este estudio es ayudar a los profesionales de la salud en la formulación de protocolos para la parametrización individual de las alarmas de los Ventiladores Mecánicos.

Factores asociados a malestar psicológico durante la pandemia de COVID-19 en personal de salud de un hospital público de Ecuador

Fundamento: La pandemia por el coronavirus SARS-CoV-2, genera afectaciones en las esferas social, económica y sanitariade un país, y de manera particular, consecuencias psicológicas negativas en el personal sanitario de hospitales públicos,considerados como la primera línea de atención a pacientes con esta enfermedad.Objetivo: Describir factores asociados a la presencia de malestar psicológico en el personal sanitario de un hospital generalpúblico en Ecuador, durante la pandemia de COVID-19.Metodología: Estudio no experimental, de corte transversal, con alcance descriptivo-correlacional. Los datos correspondierona 276 funcionarios de la salud que respondieron un instrumento online, con un módulo de datos sociodemográficos y una escalade tamizaje de malestar psicológico, estos se aplicaron después de una intervención en salud dirigida al personal de saludrealizada al inicio de la pandemia, en mayo del año 2020. Se realizaron análisis descriptivos y de asociación, mediante elsoftware SPSS 25.0.Resultados: La muestra estuvo compuesta por 76.1 porciento de mujeres, 23.9 porciento de hombres, con una media de edad de 36 años,en mayor cantidad con profesionales de Enfermería (33.7 porciento), seguido de Medicina (24.3 porciento). El 70.7 porciento del personal de saludpresentó malestar psicológico, de estos, el 26.1 porciento con indicativo de trastorno mental. Se encontraron tres variables asociadasa la presencia de malestar psicológico: clima laboral, teletrabajo y convivir con grupos de riesgo.Conclusiones: El personal de Salud ha presentado afectación en su salud mental asociado a las condiciones sociolaboralesdurante la pandemia. [AU]

'Alert Fatigue': Too Much of a Good Thing?

Studies show clinicians frequently ignore electronic warnings.

Impacto en la salud mental de los profesionales sanitarios que prestan asistencia a pacientes durante el brote del Covid-19 / Impact on the mental wellbeing of health professionals who provide care to patients during the Covid-19 outbreak

Las principales repercusiones de pandemias anteriores en el personal sanitario son los problemas de salud mental. Sin embargo, existe poca evidencia disponible relacionada a cómo el COVID-19 está afectando la salud mental en el personal sanitario. El objetivo de esta revisión de literatura fue analizar el impacto que ha tenido la pandemia en la salud mental de los profesionales de salud. Se realizó una revisión de literatura narrativa utilizando las bases de datos de Proquest y PubMed, 11 artículos fueron seleccionados de acuerdo al cumplimiento de los criterios definidos. Los trastornos mentales más frecuentes en el personal sanitario que trabaja directamente en la atención de pacientes Covid-19 son: el estrés, depresión, ansiedad y la angustia, insomnio, hiperactividad y baja calidad de vida, afectan también al personal sanitario. Estos trastornos mentales son provocados por diversos factores como el exceso de carga laboral, miedo a infectarse e infectar a sus familias, falta de medios de protección personal y temor de ser discriminados entre otros. La pandemia del COVID-19 afecta negativamente la salud mental de los profesionales de salud que trabajan directamente en la atención de pacientes, así también como la calidad de vida, por lo que es fundamental tomar acciones para proteger a los funcionarios de salud.

The main repercussions of previous pandemics on health workers are mental health problems. However, there is little evidence available related to how COVID-19 is affecting mental wellbeing in healthcare personnel. This literature review's objective was to analyze the impact that the pandemic has had on the mental wellbeing of health professionals. A narrative literature review was carried out using the Proquest and PubMed databases; 11 articles were selected according to the defined criteria' fulfillment. The most frequent mental disorders in health personnel who work directly in the care of Covid-19 patients are: stress, depression, anxiety and anguish, insomnia, hyperactivity, and low quality of life, which also affect health personnel. These mental disorders are caused by various factors such as excessive workload, fear of becoming infected and infecting their families, lack of means of personal protection, and fear of being discriminated against, among others. The COVID-19 pandemic negatively affects the mental wellbeing of health professionals who work directly in patient care and the quality of life, so it is essential to take action to protect health workers.

Riesgo de exposición a la COVID-19 en trabajadoras sanitarias embarazadas / Risk of COVID-19 exposure in pregnant health workers

El brote de enfermedad por coronavirus (COVID-19) se está extendiendo en todo el mundo con más de 34 000 000 casos confirmados y casi 1 000 000 muertes al final de septiembre de 2020.1 Las características clínicas varían de leves a enfermedades respiratorias graves. En algunos casos, los pacientes pueden requerir cuidados intensivos y ventilación mecánica.2,3 Se conoce que el riesgo de exposición al coronavirus es mayor en los trabajadores de salud, debido a su función en la asistencia y atención de los pacientes infectados con COVID-19.4 Los médicos, enfermeras y otros trabajadores de salud están en la primera línea de la emergencia médica. Los trabajadores sanitarios deben cumplir con las medidas de prevención y emplear equipos de protección personal; sin embargo, muchos de ellos se han visto afectados por COVID-19, por lo que su protección es una cuestión fundamental ahora más que nunca. Aunque algunos trabajos han abordado la exposición de las trabajadoras al COVID-19, aún no se ha abordado el problema relacionado con las trabajadoras embarazadas. El embarazo es un estado fisiológico en el que muchos cambios afectan al organismo de la mujer, incluidas las alteraciones inmunológicas. Se sabe que las mujeres embarazadas pueden ser más susceptibles a la adquisición de enfermedades infecciosas y pueden tener un mayor peligro durante el embarazo.5 El nuevo coronavirus SARS-CoV-2, se detectó por primera vez a fines de 2019 y los datos referidos a pacientes embarazadas aún son muy limitados. Se dispone de algunos datos limitados sobre infecciones previas por coronavirus, como el síndrome respiratorio agudo severo (SARS-CoV) y el síndrome respiratorio de Oriente Medio (MERS-CoV). El SARS durante el embarazo parece estar asociado con el aborto espontáneo, el parto prematuro y las restricciones del crecimiento intrauterino.6 El MERS durante el embarazo parece estar asociado con muerte neonatal y muerte fetal tardía.7 Dado que el análisis estructural del nuevo coronavirus ha sugerido que utilizaría el mismo mecanismo del SARS-CoV, es fundamental considerar el papel potencial del SARS-CoV-2 durante el embarazo.7 Sin embargo, la gravedad de infección y la mortalidad fueron mayores en mujeres embarazadas que en mujeres no embarazadas.8 Además, no hay evidencia de infección intrauterina debido a una transmisión vertical en mujeres embarazadas afectadas por COVID-19.9,10 Debe tenerse en cuenta no solo el tema relacionado con los efectos directos del COVID-19 en mujeres embarazadas, sino también el de los tratamientos, los cuales están relacionados con la importancia de su uso en caso de infección, debido a que estos pueden tener un impacto potencial para el feto. Sin embargo, es importante señalar que los datos sobre COVID-19 aún son deficientes, ya que es una pandemia muy reciente. Por estas razones, las trabajadoras de salud embarazadas no deben exponerse a pacientes confirmados o sospechosos de COVID-19, incluso si usan el equipo de protección personal adecuado. Se necesitan más estudios para evaluar y comprender mejor el papel potencial del nuevo coronavirus durante el embarazo. Además, las trabajadoras embarazadas deben cumplir con las mismas recomendaciones para otros trabajadores tales como el lavado de las manos con agua y jabón, mantener una distancia social de 2 metros, y evitar tocarse los ojos, la nariz y la boca(AU)

Renal medication-related clinical decision support (CDS) alerts and overrides in the inpatient setting following implementation of a commercial electronic health record: implications for designing more effective alerts.

OBJECTIVE: To assess the appropriateness of medication-related clinical decision support (CDS) alerts associated with renal insufficiency and the potential/actual harm from overriding the alerts. MATERIALS AND METHODS: Override rate frequency was recorded for all inpatients who had a renal CDS alert trigger between 05/2017 and 04/2018. Two random samples of 300 for each of 2 types of medication-related CDS alerts associated with renal insufficiency-"dose change" and "avoid medication"-were evaluated by 2 independent reviewers using predetermined criteria for appropriateness of alert trigger, appropriateness of override, and patient harm. RESULTS: We identified 37 100 "dose change" and 5095 "avoid medication" alerts in the population evaluated, and 100% of each were overridden. Dose change triggers were classified as 12.5% appropriate and overrides of these alerts classified as 90.5% appropriate. Avoid medication triggers were classified as 29.6% appropriate and overrides 76.5% appropriate. We identified 5 adverse drug events, and, of these, 4 of the 5 were due to inappropriately overridden alerts. CONCLUSION: Alerts were nearly always presented inappropriately and were all overridden during the 1-year period studied. Alert fatigue resulting from receiving too many poor-quality alerts may result in failure to recognize errors that could lead to patient harm. Although medication-related CDS alerts associated with renal insufficiency had previously been found to be the most clinically beneficial alerts in a legacy system, in this system they were ineffective. These findings underscore the need for improvements in alert design, implementation, and monitoring of alert performance to make alerts more patient-specific and clinically appropriate.

Optimizing clinical decision support alerts in electronic medical records: a systematic review of reported strategies adopted by hospitals.

OBJECTIVE: To identify and summarize the current internal governance processes adopted by hospitals, as reported in the literature, for selecting, optimizing, and evaluating clinical decision support (CDS) alerts in order to identify effective approaches. MATERIALS AND METHODS: Databases (Medline, Embase, CINAHL, Scopus, Web of Science, IEEE Xplore Digital Library, CADTH, and WorldCat) were searched to identify relevant papers published from January 2010 to April 2020. All paper types published in English that reported governance processes for selecting and/or optimizing CDS alerts in hospitals were included. RESULTS: Eight papers were included in the review. Seven papers focused specifically on medication-related CDS alerts. All papers described the use of a multidisciplinary committee to optimize alerts. Other strategies included the use of clinician feedback, alert data, literature and drug references, and a visual dashboard. Six of the 8 papers reported evaluations of their CDS alert modifications following the adoption of optimization strategies, and of these, 5 reported a reduction in alert rate. CONCLUSIONS: A multidisciplinary committee, often in combination with other approaches, was the most frequent strategy reported by hospitals to optimize their CDS alerts. Due to the limited number of published processes, variation in system changes, and evaluation results, we were unable to compare the effectiveness of different strategies, although employing multiple strategies appears to be an effective approach for reducing CDS alert numbers. We recommend hospitals report on descriptions and evaluations of governance processes to enable identification of effective strategies for optimization of CDS alerts in hospitals.

Fadiga de alarmes em bombas de infusão no contexto pediátrico: revisão integrativa / Alarm fatigue in infusion pumps in the pediatric context: integrative review / Fatiga de alarma en bombas de infusión en el contexto pediátrico: revisión integrativa

Objetivo: identificar as causas da fadiga de alarmes em estudos de usabilidade de bomba de infusão em terapia intensiva pediátrica. Métodos: Realizou-se uma revisão integrativa nas bases de dados LILACS, SciELO, IBECS, SCOPUS e MEDLINE. Resultados: Foram identificadas 1.164 publicações e selecionados seis estudos primários que emergiram em duas temáticas: compreender as causas dos alarmes da bomba de infusão que constou: biblioteca de fármacos incompleta, limites absolutos e relativos rígidos, falta de protocolo de preparo e administração de medicação, período de férias dos funcionários; e as medidas que podem evitar a fadiga de seus alarmes.Conclusão:falhas na usabilidade de bombas de infusão aumentam os alarmes desnecessários que podem promovem sua fadiga. A utilização segura de bombas de infusão demanda uma equipe que monitore suas práticas e atue promovendo mudanças no contexto de trabalho

Objective: to identify the causes of alarm fatigue in studies of infusion pump usability in pediatric intensive care. Methods: an integrative review was carried out in the LILACS, SciELO, IBECS, SCOPUS and MEDLINE databases. Results: 1,164 publications were identified and six primary studies were selected that emerged in two themes: understanding the causes of the infusion pump alarms that consisted of: incomplete drug library, absolute and strict relative limits, lack of preparation protocol and medication administration, employee vacation period; and measures that can prevent fatigue from your alarms. Conclusion: the causes of alarm fatigue involve low user interaction with the equipment, inadequate work processes and low investment in preventive measures for its occurrence The safe use of infusion pumps requires a team to monitor their practices and act by promoting changes in the work context

Objetivo: identificar las causas de la fatiga de alarma en estudios de usabilidad de bombas de infusión en cuidados intensivos pediátricos. Métodos: se realizó una revisión integradora en las bases de datos LILACS, SciELO, IBECS, SCOPUS y MEDLINE. Resultados: se identificaron 1.164 publicaciones y se seleccionaron seis estudios primarios que surgieron en dos temas: comprender las causas de las alarmas de la bomba de infusión que consistían en: biblioteca de medicamentos incompleta, límites relativos absolutos y estrictos, falta de protocolo de preparación y administración de medicamentos, período de vacaciones de los empleados; y medidas que pueden prevenir la fatiga de sus alarmas. Conclusión: las causas de la fatiga de las alarmas involucran baja interacción del usuario con el equipo, procesos de trabajo inadecuados y baja inversión en medidas preventivas para su ocurrencia. El uso seguro de las bombas de infusión requiere que un equipo monitoree sus prácticas y actúe promoviendo cambios en el contexto de trabajo

[Research of Methods to Reduce Alarm Fatigue of Monitoring System].

OBJECTIVE: In order to solve alarm fatigue, the algorithm optimization strategies were researched to reduce false and worthless alarms. METHODS: A four-lead arrhythmia analysis algorithm, a multiparameter fusion analysis algorithm, an intelligent threshold reminder, a refractory period delay technique were proposed and tested with collected 28 679 alarms in multi-center study. RESULTS: The sampling survey indicate that the 80.8% of arrhythmia false alarms were reduced by the four-lead analysis, the 55.9% of arrhythmia and pulse false alarms were reduced by the multi-parameter fusion analysis, the 28.0% and 29.8% of clinical worthless alarms were reduced by the intelligent threshold and refractory period delay techniques respectively. Finally, the total quantity of alarms decreased to 12 724. CONCLUSIONS: To increase the dimensionality of parametric analysis and control the alarm limits and delay time are conducive to reduce alarm fatigue in intensive care units.

Automated Identification of Adults at Risk for In-Hospital Clinical Deterioration.

BACKGROUND: Hospitalized adults whose condition deteriorates while they are in wards (outside the intensive care unit [ICU]) have considerable morbidity and mortality. Early identification of patients at risk for clinical deterioration has relied on manually calculated scores. Outcomes after an automated detection of impending clinical deterioration have not been widely reported. METHODS: On the basis of a validated model that uses information from electronic medical records to identify hospitalized patients at high risk for clinical deterioration (which permits automated, real-time risk-score calculation), we developed an intervention program involving remote monitoring by nurses who reviewed records of patients who had been identified as being at high risk; results of this monitoring were then communicated to rapid-response teams at hospitals. We compared outcomes (including the primary outcome, mortality within 30 days after an alert) among hospitalized patients (excluding those in the ICU) whose condition reached the alert threshold at hospitals where the system was operational (intervention sites, where alerts led to a clinical response) with outcomes among patients at hospitals where the system had not yet been deployed (comparison sites, where a patient's condition would have triggered a clinical response after an alert had the system been operational). Multivariate analyses adjusted for demographic characteristics, severity of illness, and burden of coexisting conditions. RESULTS: The program was deployed in a staggered fashion at 19 hospitals between August 1, 2016, and February 28, 2019. We identified 548,838 non-ICU hospitalizations involving 326,816 patients. A total of 43,949 hospitalizations (involving 35,669 patients) involved a patient whose condition reached the alert threshold; 15,487 hospitalizations were included in the intervention cohort, and 28,462 hospitalizations in the comparison cohort. Mortality within 30 days after an alert was lower in the intervention cohort than in the comparison cohort (adjusted relative risk, 0.84, 95% confidence interval, 0.78 to 0.90; P<0.001). CONCLUSIONS: The use of an automated predictive model to identify high-risk patients for whom interventions by rapid-response teams could be implemented was associated with decreased mortality. (Funded by the Gordon and Betty Moore Foundation and others.).

Reducing Alert Fatigue by Sharing Low-Level Alerts With Patients and Enhancing Collaborative Decision Making Using Blockchain Technology: Scoping Review and Proposed Framework (MedAlert).

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.

Síndrome de burnout en personal de salud durante la pandemia COVID-19: un semáforo naranja en la salud mental / Burnout syndrome in healthcare personnel during the COVID-19 pandemic: An orange traffic light in mental health

Resumen La pandemia de COVID-19 es un reto enorme para la salud pública y la economía mundial; también es un reto mayor para la salud mental, siendo uno de los grupos potencialmente más afectados el personal de salud. Uno de los efectos que ya se observa entre los trabajadores de este grupo ocupacional es el síndrome de burnout. En este artículo se revisa el origen del síndrome de burnout entre el personal sanitario, su importancia en el contexto de la pandemia y se proponen estrategias para disminuir o controlar su ocurrencia.

Abstract The COVID-19 pandemic is a huge challenge for public health and the global economy; It is also a major challenge for mental health, with health personnel being one of the potentially most affected groups. One of the effects that is already observed among workers in this occupational group is burnout syndrome. This article reviews the origin of burnout syndrome among health personnel, its importance in the context of the pandemic, and strategies are proposed to reduce or control its occurrence.

Skin Preparation and Electrode Replacement to Reduce Alarm Fatigue in a Community Hospital Intensive Care Unit.

BACKGROUND: Nurses in intensive care units are exposed to hundreds of alarms during a shift, and research shows that most alarms are not clinically relevant. Alarm fatigue can occur when a nurse becomes desensitized to alarms. Alarm fatigue can jeopardize patient safety, and adverse alarm events can lead to patients dying. OBJECTIVE: To evaluate how a process intervention affects the number of alarms during an 8-hour shift in an intensive care unit. METHODS: A total of 62 patients from an intensive care unit were included in the study; 32 of these patients received the intervention, which included washing the patient's chest with soap and water and applying new electrocardiography electrodes at the start of a shift. The number of alarms, clinical diagnoses, and demographic variables were collected for each patient. A Poisson regression model was used to evaluate the impact of the intervention on the overall number of clinical alarms during the shift, with no adjustments to the alarm settings or other interventions. RESULTS: After relevant covariates are controlled for, the results suggest that patients in the intervention group presented significantly fewer alarms than did patients in the control group. CONCLUSIONS: Managing clinical alarms is a main issue in terms of both patient safety and staff workload management. The results of this study demonstrate that a relatively simple process-oriented strategy can decrease the number of alarms.