Airway and Transpulmonary Driving Pressure by End-Inspiratory Holds During Pressure Support Ventilation.

BACKGROUND: The precision of quasi-static airway driving pressure (ΔP) assessed in pressure support ventilation (PSV) as a surrogate of tidal lung stress is debatable because persistent muscular activity frequently alters the readability of end-inspiratory holds. In this study, we used strict criteria to discard excessive muscular activity during holds and assessed the accuracy of ΔP in predicting global lung stress in PSV. Additionally, we explored whether the physiological effects of high PEEP differed according to the response of respiratory system compliance (CRS). METHODS: Adults with ARDS undergoing PSV were enrolled. An esophageal catheter was inserted to calculate lung stress through transpulmonary driving pressure (ΔPL). ΔP and ΔPL were assessed in PSV at PEEP 5, 10, and 15 cm H2O by end-inspiratory holds. CRS was calculated as tidal volume (VT)/ΔP. We analyzed the effects of high PEEP on pressure-time product per minute (PTPmin), airway pressure at 100 ms (P0.1), and VT over PTP per breath (VT/PTPbr) in subjects with increased versus decreased CRS at high PEEP. RESULTS: Eighteen subjects and 162 end-inspiratory holds were analyzed; 51/162 (31.5%) of the holds had ΔPL ≥ 12 cm H2O. Significant association between ΔP and ΔPL was found at all PEEP levels (P < .001). ΔP had excellent precision to predict ΔPL, with 15 cm H2O being identified as the best threshold for detecting ΔPL ≥ 12 cm H2O (area under the receiver operating characteristics 0.99 [95% CI 0.98-1.00]). CRS changes from low to high PEEP corresponded well with lung compliance changes (R2 0.91, P < .001) When CRS increased, a significant improvement of PTPmin and VT/PTPbr was found, without changes in P0.1. No benefits were observed when CRS decreased. CONCLUSIONS: In subjects with ARDS undergoing PSV, high ΔP assessed by readable end-inspiratory holds accurately detected potentially dangerous thresholds of ΔPL. Using ΔP to assess changes in CRS induced by PEEP during assisted ventilation may inform whether higher PEEP could be beneficial.

'Quer N0 AVC' for Monitoring Stroke Patients' Healthcare Using a Mobile App.

Stroke is one of the leading causes of death and impairments worldwide. After hospital discharge, it is necessary to monitor these patients during their recovery. This research addresses the implementation of a mobile app, entitled 'Quer N0 AVC', to improve the quality of stroke patient care in Joinville, Brazil. The study method was divided into two parts. The adaptation phase included all the necessary information in the app for monitoring stroke patients. The implementation phase aimed to prepare a routine for the Quer mobile app installation. One of the questionnaires collected data from 42 patients and identified that before hospital admission 29% of them did not have medical appointments, 36% had one or two appointments, 11% had three appointments, and 24% had four or more appointments. This research portrayed adaptation feasibility and the implementation of a cell phone app for following up on stroke patients.

Design and Evaluation of a Technological Platform for Monitoring Patients with Dementia: Unifying Requirements from Mexican Day Centers.

The monitoring of patients with dementia who receive comprehensive care in day centers allows formal caregivers to make better decisions and provide better care to patients. For instance, cognitive and physical therapies can be tailored based on the current stage of disease progression. In the context of day centers of the Mexican Federation of Alzheimer, this work aims to design and evaluate Alzaid, a technological platform for assisting formal caregivers in monitoring patients with dementia. Alzaid was devised using a participatory design methodology that consisted in eliciting and validating requirements from 22 and 9 participants, respectively, which were unified to guide the construction of a high-fidelity prototype evaluated by 14 participants. The participants were formal caregivers, medical staff, and management. This work contributes a high-fidelity prototype of a technological platform for assisting formal caregivers in monitoring patients with dementia considering restrictions and requirements of four Mexican day centers. In general, the participants perceived the prototype as quite likely to be useful, usable, and relevant in the job of monitoring patients with dementia (p-value < 0.05). By evaluating and designing Alzaid that unifies requirements for monitoring patients of four day centers, this work is the first effort towards a standard monitoring process of patients with dementia in the context of the Mexican Federation of Alzheimer.

Multidimensional Assessment of Individuals with Parkinson's Disease: Development and Structure Validation of a Self-Assessment Questionnaire.

(1) Background: Several instruments are used to assess individuals with Parkinson's disease (PD). However, most instruments necessitate the physical presence of a clinician for evaluation, were not designed for PD, nor validated for remote application. (2) Objectives: To develop and validate a self-assessment questionnaire that can be used remotely, and to assess the respondents' health condition. (3) Methods: A questionnaire, so-called Multidimensional Assessment Questionnaire for Individuals with PD (MAQPD), was developed, administered remotely, and completed by 302 people with PD. MAQPD was validated using factor analysis (FA). The participants' level of impairment was estimated using factor loadings. The scale's accuracy was assessed estimating floor and ceiling effects and Cronbach's alpha. (4) Results: FA suggested classifying the questions into daily activities, cognition, and pain. The respondents did not have extremely severe impairment (most scores ranged from 100 to 180 points), and the factors with the lowest scores were cognition and pain. The instrument had no significant floor or ceiling effects (rates less than 15%), and the Cronbach's alpha value was larger than 0.90. (5) Conclusion: MAQPD is the only remote self-administered tool found in the literature capable of providing a detailed assessment of the general health status of individuals with PD.

Telemonitoring of motor skills using the Alberta Infant Motor Scale for at-risk infants in the first year of life.

INTRODUCTION: Remote assessment creates opportunities for monitoring child development at home. Determining the possible barriers to and facilitators of the quality of telemonitoring motor skills allows for safe and effective practices. We aimed to: (1) determine the quality, barriers and facilitators of Alberta Infant Motor Scale (AIMS) home videos made by mothers; (2) verify interrater reliability; (3) determine the association between contextual factors and the quality of assessments. METHODS: Thirty infants at biological risk aged between three and ten months, of both sexes, and their mothers were included. Assessments were based on asynchronous home videos, where motor skills were evaluated by mothers at home according to AIMS guidelines. The following were analyzed: video quality; stimulus quality; camera position; and physical environment. The video characteristics were analyzed descriptively. The intraclass correlation coefficient was used to calculate interrater reliability and the regression model to determine the influence of contextual factors on the outcome variables. Significance was set at 5%. RESULTS: Remote assessment of AIMS exhibited high image and stimulus quality, and a suitable physical environment. Interrater reliability was high for all domains: prone (r = 0.976); supine (r = 0.965); sitting (r = 0.987); standing (r = 0.945) and total score (r = 0.980). The contextual factors had no relation with assessment quality. DISCUSSION: Assessments conducted remotely by the mothers showed high video quality and interrater reliability, and represent a promising assessment tool for telemedicine in at-risk infants in the first year of life.

Telephone calls and glycemic control in type 2 diabetes: A PRISMA-compliant systematic review and meta-analysis of randomized clinical trials.

AIMS: In-depth and updated systematic reviews evaluating telephone calls in type 2 diabetes (T2DM) management are missing. This study aimed to assess the effect of this intervention on glycemic control in T2DM patients when compared with usual care. METHODS: We systematically searched for randomized controlled trials (RCT) on T2DM using Medline, Embase, Cochrane Central Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and LILACS, up to March 2021. The Risk of Bias 2.0 (Rob 2.0) tool and GRADE were used for the quality evaluation. The intervention effect was estimated by the change in glycated hemoglobin (HbA1c). PROSPERO registry CRD42020204519. RESULTS: 3545 references were reviewed and 32 were included (8598 patients). Telephone calls, all approaching education, improved HbA1c by 0.33% [95% CI, -0.48% to -0.18%; I2 = 78%; p < 0.0001] compared to usual care. A greater improvement was found when the intervention included pharmacologic modification (-0.82%, 95% CI, -1.42% to -0.22%; I2 = 92%) and when it was applied by nurses (-0.53%, 95% CI, -0.86% to -0.2%; I2 = 87%). Meta-regression showed no relationship between DM duration and HbA1c changes. CONCLUSION: The telephone call intervention provided a benefit regarding T2DM glycemic control, especially if provided by nurses, or if associated with patient education and pharmacological treatment modification.

Technique failure in remote patient monitoring program in patients undergoing automated peritoneal dialysis: A retrospective cohort study.

BACKGROUND: Remote patient monitoring (RPM) programs in automated peritoneal dialysis (APD) allow clinical teams to be aware of many aspects and events of the therapy that occur in the home. The present study evaluated the association between RPM use and APD technique failure. METHODS: A retrospective, multicentre, observational cohort study of 558 prevalent adult APD patients included between 1 October 2016 and 30 June 2017 with follow-up until 30 June 2018 at Renal Therapy Services network in Colombia. Patients were divided into two cohorts based on the RPM use: APD-RPM (n = 148) and APD-without RPM (n = 410). Sociodemographic and clinical characteristics of all patients were summarized descriptively. A propensity score was used to create a pseudo-population in which the baseline covariates were well balanced. The association of RPM with technique failure was estimated adjusting for the competing events death and kidney transplant. RESULTS: Five hundred fifty-eight patients were analyzed. 26.5% had APD-RPM. In the matched sample comprising 148 APD-RPM and 148 APD-without RPM patients, we observed a lower technique failure rate of 0.08 [0.05-0.15] episodes per patient-year in APD-RPM versus 0.18 [0.12-0.26] in APD-without RPM cohort; incidence rate ratio = 0.45 95% confidence interval: [0.22-0.91], p-value = 0.03. CONCLUSIONS: The use of an RPM program in APD patients may be associated with a lower technique failure rate. More extensive and interventional studies are needed to confirm its potential benefits and to measure other patient-centered outcomes.

Respiratory Support Adjustments and Monitoring of Mechanically Ventilated Patients Performing Early Mobilization: A Scoping Review.

This scoping review is aimed to summarize current knowledge on respiratory support adjustments and monitoring of metabolic and respiratory variables in mechanically ventilated adult patients performing early mobilization. DATA SOURCES: Eight electronic databases were searched from inception to February 2021, using a predefined search strategy. STUDY SELECTION: Two blinded reviewers performed document selection by title, abstract, and full text according to the following criteria: mechanically ventilated adult patients performing any mobilization intervention, respiratory support adjustments, and/or monitoring of metabolic/respiratory real-time variables. DATA EXTRACTION: Four physiotherapists extracted relevant information using a prespecified template. DATA SYNTHESIS: From 1,208 references screened, 35 documents were selected for analysis, where 20 (57%) were published between 2016 and 2020. Respiratory support settings (ventilatory modes or respiratory variables) were reported in 21 documents (60%). Reported modes were assisted (n = 11) and assist-control (n = 9). Adjustment of variables and modes were identified in only seven documents (20%). The most frequent respiratory variable was the Fio2, and only four studies modified the level of ventilatory support. Mechanical ventilator brand/model used was not specified in 26 documents (74%). Monitoring of respiratory, metabolic, and both variables were reported in 22 documents (63%), four documents (11%) and 10 documents (29%), respectively. These variables were reported to assess the physiologic response (n = 21) or safety (n = 13). Monitored variables were mostly respiratory rate (n = 26), pulse oximetry (n = 22), and oxygen consumption (n = 9). Remarkably, no study assessed the work of breathing or effort during mobilization. CONCLUSIONS: Little information on respiratory support adjustments during mobilization of mechanically ventilated patients was identified. Monitoring of metabolic and respiratory variables is also scant. More studies on the effects of adjustments of the level/mode of ventilatory support on exercise performance and respiratory muscle activity monitoring for safe and efficient implementation of early mobilization in mechanically ventilated patients are needed.

Detecting False Alarms by Analyzing Alarm-Context Information: Algorithm Development and Validation.

BACKGROUND: Although alarm safety is a critical issue that needs to be addressed to improve patient care, hospitals have not given serious consideration about how their staff should be using, setting, and responding to clinical alarms. Studies have indicated that 80%-99% of alarms in hospital units are false or clinically insignificant and do not represent real danger for patients, leading caregivers to miss relevant alarms that might indicate significant harmful events. The lack of use of any intelligent filter to detect recurrent, irrelevant, and/or false alarms before alerting health providers can culminate in a complex and overwhelming scenario of sensory overload for the medical team, known as alarm fatigue. OBJECTIVE: This paper's main goal is to propose a solution to mitigate alarm fatigue by using an automatic reasoning mechanism to decide how to calculate false alarm probability (FAP) for alarms and whether to include an indication of the FAP (ie, FAP_LABEL) with a notification to be visualized by health care team members designed to help them prioritize which alerts they should respond to next. METHODS: We present a new approach to cope with the alarm fatigue problem that uses an automatic reasoner to decide how to notify caregivers with an indication of FAP. Our reasoning algorithm calculates FAP for alerts triggered by sensors and multiparametric monitors based on statistical analysis of false alarm indicators (FAIs) in a simulated environment of an intensive care unit (ICU), where a large number of warnings can lead to alarm fatigue. RESULTS: The main contributions described are as follows: (1) a list of FAIs we defined that can be utilized and possibly extended by other researchers, (2) a novel approach to assess the probability of a false alarm using statistical analysis of multiple inputs representing alarm-context information, and (3) a reasoning algorithm that uses alarm-context information to detect false alarms in order to decide whether to notify caregivers with an indication of FAP (ie, FAP_LABEL) to avoid alarm fatigue. CONCLUSIONS: Experiments were conducted to demonstrate that by providing an intelligent notification system, we could decide how to identify false alarms by analyzing alarm-context information. The reasoner entity we described in this paper was able to attribute FAP values to alarms based on FAIs and to notify caregivers with a FAP_LABEL indication without compromising patient safety.

Artificial Intelligence Technologies for Coping with Alarm Fatigue in Hospital Environments Because of Sensory Overload: Algorithm Development and Validation.

BACKGROUND: Informed estimates claim that 80% to 99% of alarms set off in hospital units are false or clinically insignificant, representing a cacophony of sounds that do not present a real danger to patients. These false alarms can lead to an alert overload that causes a health care provider to miss important events that could be harmful or even life-threatening. As health care units become more dependent on monitoring devices for patient care purposes, the alarm fatigue issue has to be addressed as a major concern for the health care team as well as to enhance patient safety. OBJECTIVE: The main goal of this paper was to propose a feasible solution for the alarm fatigue problem by using an automatic reasoning mechanism to decide how to notify members of the health care team. The aim was to reduce the number of notifications sent by determining whether or not to group a set of alarms that occur over a short period of time to deliver them together, without compromising patient safety. METHODS: This paper describes: (1) a model for supporting reasoning algorithms that decide how to notify caregivers to avoid alarm fatigue; (2) an architecture for health systems that support patient monitoring and notification capabilities; and (3) a reasoning algorithm that specifies how to notify caregivers by deciding whether to aggregate a group of alarms to avoid alarm fatigue. RESULTS: Experiments were used to demonstrate that providing a reasoning system can reduce the notifications received by the caregivers by up to 99.3% (582/586) of the total alarms generated. Our experiments were evaluated through the use of a dataset comprising patient monitoring data and vital signs recorded during 32 surgical cases where patients underwent anesthesia at the Royal Adelaide Hospital. We present the results of our algorithm by using graphs we generated using the R language, where we show whether the algorithm decided to deliver an alarm immediately or after a delay. CONCLUSIONS: The experimental results strongly suggest that this reasoning algorithm is a useful strategy for avoiding alarm fatigue. Although we evaluated our algorithm in an experimental environment, we tried to reproduce the context of a clinical environment by using real-world patient data. Our future work is to reproduce the evaluation study based on more realistic clinical conditions by increasing the number of patients, monitoring parameters, and types of alarm.

Evaluación del desempeño del APACHE II y SAPS III, en una unidad de cuidados intensivos / Performance evaluation of APACHE II and SAPS III in an intensive care unit / Avaliação de desempenho do APACHE II e SAPS III, em unidade de terapia intensiva

RESUMEN Objetivo El objetivo principal de este trabajo, fue validar y comparar la capacidad predictiva de mortalidad de los indicadores de gravedad APACHE II (Acute Physiology and Chronic Health Evaluation, Score II) y SAPS III (Simplified Acute Physiology, Score III) en una muestra de pacientes admitidos en la Unidad de Cuidados Intensivos Adulto (UCI) del Hospital de Curicó, entre los años 2011 y 2013. Materiales y Métodos Estudio analítico, observacional de cohorte histórica de casos consecutivos desde la admisión a la UCI hasta el egreso hospitalario. Para el análisis, se usó el Modelo de Regresión Logística Binaria. De un total de 1 042 pacientes ingresados a la UCI, se incluyó a 793 pacientes sobrevivientes, y a 249 pacientes fallecidos, que representaban el 76,1% y 23,9% respectivamente, del total. Resultados El SAPS III presenta mejor capacidad predictiva que el APACHE II, según el área bajo la curva de características operativas del receptor 0,81 y 0,80 respectivamente. La sensibilidad para el modelo SAPS III es 0,95 y para APACHE II es 0,93. El índice de especificidad es 0,3 para el SAPS III y 0,4 para el APACHE II, con probabilidad superior a 0,5. Conclusión Los indicadores de predicción de mortalidad en UCI; APACHE II y SAPS III tienen una buena capacidad predictiva general, pero ambos indicadores presentan una baja especificidad.(AU)

ABSTRACT Objective The main objective of this work was to validate and compare the predictive capacity of mortality of the severity score systems APACHE II (Acute Physiology and Chronic Health Evaluation, Score II) and SAPS III (Simplified Acute Physiology, Score III) in a sample of patients admitted to the Adult Intensive Care Unit (ICU) of the Hospital de Curicó between 2011 and 2013. Materials and Methods Analytical, observational, retrospective cohort study of consecutive cases since admission to the ICU until hospital discharge. A binary logistic regression model was used for the analysis. Out of 1 042 patients admitted to the ICU, 793 surviving patients and 249 deceased patients were included, representing 76.1% and 23.9%, respectively, of the total sample. Results The SAPS III score has a better predictive capacity than the APACHE II, according to the area under the curve and the receiver operating characteristic curve: 0.81 and 0.80, respectively. Sensitivity for the SAPS III model was 0.95 and for APACHE II was 0.93. The specificity index was 0.3 for SAPS III and 0.4 for APACHE II, with a probability above 0.5. Conclusion APACHE II and SAPS III, as ICU mortality prediction indicators, have a good predictive power but low specificity.(AU)

RESUMO Objetivo O objetivo principal deste trabalho foi validar e comparar a capacidade preditiva de mortalidade dos sistemas de escore de gravidade APACHE II (Fisiologia Aguda e Avaliação Crônica de Saúde, Escore II) e SAPS III (Fisiologia Aguda Simplificada, Escore III) em uma amostra de pacientes internado na Unidade de Terapia Intensiva Adulto (UTI) do Hospital de Curicó entre 2011 e 2013. Materiais e métodos Estudo de coorte analítico, observacional e retrospectivo de casos consecutivos desde a admissão na UTI até a alta hospitalar. Um modelo de regressão logística binária foi usado para a análise. Dos 1.042 pacientes admitidos na UTI, foram incluídos 793 pacientes sobreviventes e 249 falecidos, representando 76,1% e 23,9%, respectivamente, do total da amostra. Resultados O escore SAPS III tem melhor capacidade preditiva do que o APACHE II, de acordo com a área sob a curva e a curva de característica de operação do receptor: 0,81 e 0,80, respectivamente. A sensibilidade para o modelo SAPS III foi de 0,95 e para APACHE II foi de 0,93. O índice de especificidade foi de 0,3 para SAPS III e 0,4 para APACHE II, com probabilidade superior a 0,5. Conclusão APACHE II e SAPS III, como indicadores de predição de mortalidade em UTI, apresentam bom poder preditivo, mas baixa especificidade.(AU)

Understanding Monitoring Technologies for Adults With Pain: Systematic Literature Review.

BACKGROUND: Monitoring of patients may decrease treatment costs and improve quality of care. Pain is the most common health problem that people seek help for in hospitals. Therefore, monitoring patients with pain may have significant impact in improving treatment. Several studies have studied factors affecting pain; however, no previous study has reviewed the contextual information that a monitoring system may capture to characterize a patient's situation. OBJECTIVE: The objective of this study was to conduct a systematic review to (1) determine what types of technologies have been used to monitor adults with pain, and (2) construct a model of the context information that may be used to implement apps and devices aimed at monitoring adults with pain. METHODS: A literature search (2005-2015) was conducted in electronic databases pertaining to medical and computer science literature (PubMed, Science Direct, ACM Digital Library, and IEEE Xplore) using a defined search string. Article selection was done through a process of removing duplicates, analyzing title and abstract, and then reviewing the full text of the article. RESULTS: In the final analysis, 87 articles were included and 53 of them (61%) used technologies to collect contextual information. A total of 49 types of context information were found and a five-dimension (activity, identity, wellness, environment, physiological) model of context information to monitor adults with pain was proposed, expanding on a previous model. Most technological interfaces for pain monitoring were wearable, possibly because they can be used in more realistic contexts. Few studies focused on older adults, creating a relevant avenue of research on how to create devices for users that may have impaired cognitive skills or low digital literacy. CONCLUSIONS: The design of monitoring devices and interfaces for adults with pain must deal with the challenge of selecting relevant contextual information to understand the user's situation, and not overburdening or inconveniencing users with information requests. A model of contextual information may be used by researchers to choose possible contextual information that may be monitored during studies on adults with pain.

A Software Framework for Remote Patient Monitoring by Using Multi-Agent Systems Support.

BACKGROUND: Although there have been significant advances in network, hardware, and software technologies, the health care environment has not taken advantage of these developments to solve many of its inherent problems. Research activities in these 3 areas make it possible to apply advanced technologies to address many of these issues such as real-time monitoring of a large number of patients, particularly where a timely response is critical. OBJECTIVE: The objective of this research was to design and develop innovative technological solutions to offer a more proactive and reliable medical care environment. The short-term and primary goal was to construct IoT4Health, a flexible software framework to generate a range of Internet of things (IoT) applications, containing components such as multi-agent systems that are designed to perform Remote Patient Monitoring (RPM) activities autonomously. An investigation into its full potential to conduct such patient monitoring activities in a more proactive way is an expected future step. METHODS: A framework methodology was selected to evaluate whether the RPM domain had the potential to generate customized applications that could achieve the stated goal of being responsive and flexible within the RPM domain. As a proof of concept of the software framework's flexibility, 3 applications were developed with different implementations for each framework hot spot to demonstrate potential. Agents4Health was selected to illustrate the instantiation process and IoT4Health's operation. To develop more concrete indicators of the responsiveness of the simulated care environment, an experiment was conducted while Agents4Health was operating, to measure the number of delays incurred in monitoring the tasks performed by agents. RESULTS: IoT4Health's construction can be highlighted as our contribution to the development of eHealth solutions. As a software framework, IoT4Health offers extensibility points for the generation of applications. Applications can extend the framework in the following ways: identification, collection, storage, recovery, visualization, monitoring, anomalies detection, resource notification, and dynamic reconfiguration. Based on other outcomes involving observation of the resulting applications, it was noted that its design contributed toward more proactive patient monitoring. Through these experimental systems, anomalies were detected in real time, with agents sending notifications instantly to the health providers. CONCLUSIONS: We conclude that the cost-benefit of the construction of a more generic and complex system instead of a custom-made software system demonstrated the worth of the approach, making it possible to generate applications in this domain in a more timely fashion.

Integrating Social Networks and Remote Patient Monitoring Systems to Disseminate Notifications.

Healthcare workforce shortage can be compensated by using information and communication technologies. Remote patient monitoring systems allow us to identify and communicate complications and anomalies. Integrating social networking services into remote patient monitoring systems enables users to manage their relationships. User defined relationships may be used to disseminate healthcare related notifications. Hence this integration leads to quicker interventions and may reduce hospital readmission rate. As a proof of concept, a module was integrated to a remote patient monitoring platform. A mobile application to manage relationships and receive notifications was also developed.

Scaling-up health information systems to improve HIV treatment: An assessment of initial patient monitoring systems in Mozambique

Introduction­The rapid scale-up of HIV care and treatment in resource-limited countries requires concurrent, rapid development of health information systems to support quality service delivery. Mozambique, a country with an 11.5% prevalence of HIV, has developed nation-wide patient monitoring systems (PMS) with standardized reporting tools, utilized by all HIV treatment providers in paper or electronic form. Evaluation of the initial implementation of PMS can inform and strengthen future development as the country moves towards a harmonized, sustainable health information system. Objective­This assessment was conducted in order to 1) characterize data collection and reporting processes and PMS resources available and 2) provide evidence-based recommendations for harmonization and sustainability of PMS. Methods­This baseline assessment of PMS was conducted with eight non-governmental organizations that supported the Ministry of Health to provide 90% of HIV care and treatment in Mozambique. The study team conducted structured and semi-structured surveys at 18 health facilities located in all 11 provinces. Seventy-nine staff were interviewed. Deductive a priori analytic categories guided analysis. Results­Health facilities have implemented paper and electronic monitoring systems with varying success. Where in use, robust electronic PMS facilitate facility-level reporting of required indicators; improve ability to identify patients lost to follow-up; and support facility and patient management. Challenges to implementation of monitoring systems include a lack of national guidelines and norms for patient level HIS, variable system implementation and functionality, and limited human and infrastructure resources to maximize system functionality and information use. Conclusions­This initial assessment supports the need for national guidelines to harmonize, expand, and strengthen HIV-related health information systems. Recommendations may benefit other countries with similar epidemiologic and resource-constrained environments seeking to improve PMS implementation.

Cystic Fibrosis Cloud database: Un sistema informático para el almacenamiento y manejo de datos clínicos y microbiológicos del paciente con fibrosis quística / Cystic Fibrosis Cloud database: An information system for storage and management of clinical and microbiological data of cystic fibrosis patients

El manejo clínico y epidemiológico de los pacientes con fibrosis quística (FQ) con exacerbaciones pulmonares agudas o infecciones pulmonares crónicas demanda una actualización permanente de procedimientos médicos y microbiológicos, estos se asocian con la constante evolución de los agentes patógenos durante la colonización de su hospedador. Para poder monitorear la dinámica de estos procesos es fundamental disponer de sistemas expertos que permitan almacenar, extraer y utilizar la información generada a partir de estudios realizados sobre el paciente y los microorganismos aislados de aquel. En este trabajo hemos diseñado y desarrollado una base de datos on-line basada en un sistema informático que permite el almacenamiento, el manejo y la visualización de la información proveniente de estudios clínicos y de análisis microbiológicos de bacterias obtenidas del tracto respiratorio del paciente con FQ. Este sistema informático fue designado como Cystic Fibrosis Cloud database (CFC database) y está disponible en el sitio http://servoy.infocomsa.com/cfc_database. Está compuesto por una base de datos principal y una interfaz on-line, la cual emplea la arquitectura de productos Servoy basada en tecnología Java. Si bien el sistema CFC database puede ser implementado como un programa local de uso privado en los centros de asistencia a pacientes con FQ, admite también la posibilidad de ser empleado, actualizado y compartido por diferentes usuarios, quienes pueden acceder a la información almacenada de manera ordenada, práctica y segura. La implementación del CFC database podría tener una gran impacto en la monitorización de las infecciones respiratorias, la prevención de exacerbaciones, la detección de organismos emergentes y la adecuación de las estrategias de control de infecciones pulmonares en pacientes con FQ

The epidemiological and clinical management of cystic fibrosis (CF) patients suffering from acute pulmonary exacerbations or chronic lung infections demands continuous updating of medical and microbiological processes associated with the constant evolution of pathogens during host colonization. In order to monitor the dynamics of these processes, it is essential to have expert systems capable of storing and subsequently extracting the information generated from different studies of the patients and microorganisms isolated from them. In this work we have designed and developed an on-line database based on an information system that allows to store, manage and visualize data from clinical studies and microbiological analysis of bacteria obtained from the respiratory tract of patients suffering from cystic fibrosis. The information system, named Cystic Fibrosis Cloud database is available on the http://servoy.infocomsa.com/cfc_database site and is composed of a main database and a web-based interface, which uses Servoy's product architecture based on Java technology. Although the CFC database system can be implemented as a local program for private use in CF centers, it can also be used, updated and shared by different users who can access the stored information in a systematic, practical and safe manner. The implementation of the CFC database could have a significant impact on the monitoring of respiratory infections, the prevention of exacerbations, the detection of emerging organisms, and the adequacy of control strategies for lung infections in CF patients

[Cystic Fibrosis Cloud database: An information system for storage and management of clinical and microbiological data of cystic fibrosis patients]. / Cystic Fibrosis Cloud database: Un sistema informático para el almacenamiento y manejo de datos clínicos y microbiológicos del paciente con fibrosis quística.

The epidemiological and clinical management of cystic fibrosis (CF) patients suffering from acute pulmonary exacerbations or chronic lung infections demands continuous updating of medical and microbiological processes associated with the constant evolution of pathogens during host colonization. In order to monitor the dynamics of these processes, it is essential to have expert systems capable of storing and subsequently extracting the information generated from different studies of the patients and microorganisms isolated from them. In this work we have designed and developed an on-line database based on an information system that allows to store, manage and visualize data from clinical studies and microbiological analysis of bacteria obtained from the respiratory tract of patients suffering from cystic fibrosis. The information system, named Cystic Fibrosis Cloud database is available on the http://servoy.infocomsa.com/cfc_database site and is composed of a main database and a web-based interface, which uses Servoy's product architecture based on Java technology. Although the CFC database system can be implemented as a local program for private use in CF centers, it can also be used, updated and shared by different users who can access the stored information in a systematic, practical and safe manner. The implementation of the CFC database could have a significant impact on the monitoring of respiratory infections, the prevention of exacerbations, the detection of emerging organisms, and the adequacy of control strategies for lung infections in CF patients.

Prevalence of Ventilatory Conditions for Dynamic Fluid Responsiveness Prediction in 2 Tertiary Intensive Care Units.

BACKGROUND: Dynamic parameters for fluid responsiveness obtained from heart-lung interaction during invasive mechanical ventilation require specific conditions not always present in intensive care unit (ICU) patients. The aim of this study was to examine the prevalence of these conditions in critically ill patients. METHODS: We conducted a prospective observational study in 2 medical-surgical ICUs. We evaluated whether it would be possible to measure dynamic indices of fluid responsiveness when fluid expansion was administered. We recorded whether the patients were in controlled invasive mechanical ventilation with tidal volume >8 mL/kg and without arrhythmias. The proportion of patients who fulfilled these conditions was recorded. A post hoc subgroup analyses by terciles of Simplified Acute Physiology Score 3 (SAPS3) were performed. RESULTS: A total of 826 fluid challenges were undertaken in 424 patients during the study. The use of controlled mechanical ventilation with tidal volume > 8 mL/kg and without arrhythmias occurred in only 2.9% of the patients at the time of fluid challenge episodes. There was an increase in the prevalence of these conditions as the severity of the patients also increased: lower tercile of SAPS3 (0%), intermediate tercile (2%), and higher tercile (6.9%; P < .01 Pearson chi-square test). CONCLUSIONS: Respiratory-dependent dynamic parameters for predicting fluid responsiveness in ICU may have restricted applicability in daily practice, even in more severe patients, due to low prevalence of required conditions.

Wi-Bio: management policy aimed at the establishment of networks for patient monitoring using IEEE 802.11

INTRODUCTION: Patient monitoring will tend to decline in the coming years due to a shortage of physical and human resources in hospitals. Therefore, several studies define alternatives to improve patient monitoring using wireless networks. In these studies, a wireless network is used to transfer data generated by medical sensors without interacting with the traffic in the data network of the hospital. However, this approach should be avoided because there are demands for integration between user applications and patient monitoring. Therefore, this paper defines a patient monitoring system, called Wi-Bio, directed to the establishment of IEEE 802.11 networks that allows traffic generated by user applications. METHODS: The formal validation of Wi-Bio was made through the design of Petri nets, and performance analysis was performed through simulations of the Network Simulator 2 tool. The adoption of this approach is justified by the fact that Petri nets allow verification of logical correctness of the designed systems, while simulations allow behavioral analysis of Wi-Bio in overload scenarios where many patients are monitored. RESULTS: The results confirmed the validity of the designed Petri nets and showed that Wi-Bio is able to accomplish the temporal goals imposed by medical sensors, thereby promoting efficient integration of traffic present in the data network and the patient monitoring network. CONCLUSION: As described, Wi-Bio fulfilled its objectives and motivates future studies aimed at complementing the obtained results.

Um anjo para ELA: arquitetura baseada em visão computacional aplicada ao monitoramento on-line de parâmetros respiratórios de pacientes com Esclerose Lateral Amiotrófica (ELA) em ambiente hospitalar / An angel for ALS: architecture based on computer vision applied for on-line monitoring respiratory parameters of patients with Amyotrophic Lateral Sclerosis (ALS) in hospital environment

INTRODUÇÃO: A Esclerose Lateral Amiotrófica (ELA) é uma doença neurodegenerativa, caracterizada por uma progressiva e fatal perda de neurônios motores do córtex cerebral, tronco encefálico e medula espinhal, mas que mantém preservada a atividade intelectual e cognitiva do paciente. Pacientes acometidos por essa doença irão invariavelmente necessitar do auxílio de ventiladores mecânicos. MÉTODOS: Foi utilizado um conjunto de hardware e software para realizar o monitoramento dos parâmetros respiratórios dos pacientes em leitos hospitalares como forma de auxiliar à equipe de saúde. O monitoramento desses parâmetros deu-se por meio de uma webcam, que capturava os valores exibidos na tela do ventilador mecânico, e do emprego de técnicas de visão computacional e Optical Character Recognition (OCR). Neste sentido, o sistema foi testado sob três condições de luminosidade diferentes para verificar a eficácia do mesmo. RESULTADOS: O sistema apresentou uma média geral de acertos de 94.90%. Além disso, quando a interferência luminosa foi mínima, o sistema obteve uma média geral de acertos de 97,76%. CONCLUSÃO: A adoção de um sistema computacional baseado em visão computacional para auxílio da equipe de saúde no monitoramento hospitalar de pacientes com ELA mostrou-se satisfatória. No entanto, a pesquisa mostrou que a adoção de um sistema com maior imunidade à interferências luminosas externas tende a apresentar melhores resultados.

INTRODUCTION: Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by a progressive and fatal loss of motor neurons in the cerebral cortex, brainstem and spinal cord. In spite of that, the patient's intellectual and cognitive activity remains preserved. Patients affected by this disease will invariably need the help of mechanical ventilators. METHODS: A set of hardware and software was used to perform the monitoring of respiratory parameters of patients in hospital beds as a means of assisting the healthcare team. The monitoring of these parameters was performed by a webcam that captured the values displayed on the screen of the ventilator, and the employment of computer vision techniques and Optical Character Recognition (OCR). In this sense, the system was tested under three different lighting conditions to verify its effectiveness. RESULTS:The system presented an overall average of 94.90% of correct answers. Furthermore, when the luminous interference was minimum, it achieved an overall average of success of 97.76%. CONCLUSION: The adoption of a computational system based on computer vision to aid the healthcare team in hospital monitoring of patients with ALS was satisfactory. However, the research has shown that the adoption of a system with greater immunity to external light interference tends to achieve better results.