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Introduction: The COVID-19 pandemic has prompted global research efforts to reduce infection impact, highlighting the potential of cross-disciplinary collaboration to enhance research quality and efficiency. Methods: At the FMUSP-HC academic health system, we implemented innovative flow management routines for collecting, organizing and analyzing demographic data, COVID-related data and biological materials from over 4,500 patients with confirmed SARS-CoV-2 infection hospitalized from 2020 to 2022. This strategy was mainly planned in three areas: organizing a database with data from the hospitalizations; setting-up a multidisciplinary taskforce to conduct follow-up assessments after discharge; and organizing a biobank. Additionally, a COVID-19 curated collection was created within the institutional digital library of academic papers to map the research output. Results: Over the course of the experience, the possible benefits and challenges of this type of research support approach were identified and discussed, leading to a set of recommended strategies to enhance collaboration within the research institution. Demographic and clinical data from COVID-19 hospitalizations were compiled in a database including adults and a minority of children and adolescents with laboratory confirmed COVID-19, covering 2020-2022, with approximately 350 fields per patient. To date, this database has been used in 16 published studies. Additionally, we assessed 700 adults 6 to 11 months after hospitalization through comprehensive, multidisciplinary in-person evaluations; this database, comprising around 2000 fields per subject, was used in 15 publications. Furthermore, thousands of blood samples collected during the acute phase and follow-up assessments remain stored for future investigations. To date, more than 3,700 aliquots have been used in ongoing research investigating various aspects of COVID-19. Lastly, the mapping of the overall research output revealed that between 2020 and 2022 our academic system produced 1,394 scientific articles on COVID-19. Discussion: Research is a crucial component of an effective epidemic response, and the preparation process should include a well-defined plan for organizing and sharing resources. The initiatives described in the present paper were successful in our aim to foster large-scale research in our institution. Although a single model may not be appropriate for all contexts, cross-disciplinary collaboration and open data sharing should make health research systems more efficient to generate the best evidence.

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ABSTRACT BACKGROUND: Precisely determining the aspects related to an instrument's validity and reliability measures allows for greater assurance of the quality of the results. OBJECTIVES: To analyze the psychometric properties of The Providers Survey in the Brazilian context of mental health services. DESIGN AND SETTING: The instrument validation study was conducted in Montes Claros, Minas Gerais, Brazil. METHODS: The validation study was conducted using the Consensus-based Standards for the Selection of Health Measurement Instruments checklist to analyze its validity and reliability. RESULTS: A committee of expert judges performed content validation after which the Content Validity Index was calculated. Construct validation took place through Exploratory Factor Analysis using the Kaiser-Meyer-Olkin Test criterion and Bartlett's Sphericity Test. Reliability was verified using test-retest reliability. The significance level adopted for the statistical tests was 5% (P < 0.05). The final instrument comprised 54 questions. The Content Validity Index was 97%. Exploratory Factor Analysis identified a Kaiser-Meyer-Olkin index of 0.901 and Bartlett's Sphericity Test with P < 0.001. We obtained a Cronbach's alpha coefficient of 0.95 and an intraclass correlation coefficient of 0.849. CONCLUSIONS: The Providers Survey, translated and adapted into Portuguese, was named the Work Assessment Instrument for the Recovery of Mental Health. It presented adequate psychometric properties for evaluating work-related practices for the recovery of psychosocial care network users.

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Abstract Background: Alarms alert healthcare professionals of deviations from normal/physiologic status. However, alarm fatigue may occur when their high pitch and diversity overwhelm clinicians, possibly leading to alarms being disabled, paused, and/or ignored. We aimed to determine whether a staff educational program on customizing alarm settings of bedside monitors may decrease inconsistent alarms in the Post-Anesthesia Care Unit (PACU). Methods: This is a prospective, analytic, quantitative, pragmatic, open-label, single-arm study. The outcome was evaluated on PACU admission before (P1) and after (P2) the implementation of the educational program. The heart rate, blood pressure, and oxygen saturation alarms were selected for clinical consistency. Results: A total of 260 patients were included and 344 clinical alarms collected, with 270 (78.4%) before (P1), and 74 (21.6%) after (P2) the intervention. Among the 270 alarms in P1, 45.2% were inconsistent (i.e., false alarms), compared to 9.4% of the 74 in P2. Patients with consistent alarms occurred in 30% in the P1 and 27% in the P2 (p = 0.08). Patients with inconsistent alarms occurred in 25.4% in the P1 and in 3.8% in the P2. Ignored consistent alarms were reduced from 21.5% to 2.6% (p = 0.004) in the P2 group. The educational program was a protective factor for the inconsistent clinical alarm (OR = 0.11 [95% CI 0.04-0.3]; p < 0.001) after adjustments for age, gender, and ASA physical status. Conclusion: Customizing alarm settings on PACU admission proved to be a protective factor against inconsistent alarm notifications of multiparametric monitors.

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Data quality monitoring plays a crucial role in multicenter prospective registries. By maintaining high data accuracy, completeness, and consistency, researchers can improve the overall quality and reliability of the registry data, enabling meaningful conclusions and supporting evidence-based decisions. The purpose of the present study was to evaluate data quality metrics (completeness, accuracy, and temporal plausibility) of a Multicenter Registry of Cardiac Implantable Electronic Devices (CIEDs) and to perform a direct data audit of a random sample of records to assess the agreement levels with the source documents. The CIED Registry was a prospective, multicenter, real-world observational study carried out from January 2020 to December 2022 in five designated centers across Sao Paulo, Brazil. We assessed the data quality of the CIED Registry by using two distinct approaches:•Dynamic data monitoring using features of the REDCap (Research Electronic Data Capture) software, including data reports and data quality rules•Direct data audit in which information from a random sample of 10 % of cases from the coordinating center was compared with original source documents Our findings suggest that the methodological approach applied to the CIED Registry resulted in high data completeness, accuracy, temporal plausibility, and excellent agreement levels with the source documents.

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Data management "behind the scenes" refers to collection, cleaning, imputation, and demarcation; and despite of being indispensable processes, they are usually neglected and thus, generate erroneous information. During the collection are errors: omission of covariates, deviation from the objective, and insufficient quality. The omission of covariates distorts the result attributed to the main manoeuvre. Deviation from the primary objective commonly occurs when the outcome is rare, delayed, or subjective and promotes substitution by non-equivalent surrogate variables. Moreover, insufficient quality occurs due to inadequate instruments, omission of the measurement procedure, or measurements out of context, such as attribution at the wrong time or equivalent. Furthermore, cleaning implies identifying erroneous, extreme, and missing values, which may or may not be imputed, depending on the percentage. The values of the manoeuvre or the outcome are never imputed, nor are patients eliminated due to a lack of values. Finally, the demarcation of each variable seeks to give it a clinical meaning about the outcome, for which a hierarchical sequence of criteria is followed: 1) previous clinical study, 2) expert agreement, 3) clinical judgment of the investigator/investigators, and 4) statistics. Acting without quality controls in data management frequently causes involuntary lies and confuses instead of clarifying.

El manejo de datos "tras bambalinas" se refiere a los procesos de recopilación, limpieza, imputación y demarcación; los cuales, aun siendo indispensables, usualmente suelen ser descuidados, por lo que generan información errónea. Durante la recopilación son errores: omisión de covariables, desvío del objetivo, y calidad insuficiente. La omisión de covariables distorsiona el resultado atribuido a la maniobra principal. El desvío del objetivo primario es común cuando el desenlace es raro, tardado o subjetivo y promueve la sustitución por variables subrogadas no equivalentes. Además, la calidad insuficiente, sucede por instrumentos inadecuados, omisión del procedimiento de medición, o medición fuera de contexto -como atribución a destiempo o equivalente-. Por otro lado, la limpieza implica identificar valores erróneos, extremos y faltantes, que podrán ser o no imputados, dependiendo del porcentaje se imputará comúnmente por la medida de resumen. Nunca se imputan los valores de la maniobra ni del desenlace, ni se eliminan pacientes por falta de valores. Finalmente, la demarcación de cada variable busca un significado clínico en referencia al desenlace, para ello se sigue una secuencia jerárquica de criterios: 1) estudio clínico previo, 2) acuerdo de expertos, 3) juicio clínico del investigador/investigadores y 4) estadística. Actuar sin controles de calidad en el manejo de datos provoca frecuentemente mentiras involuntarias y confunde en lugar de esclarecer.

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BACKGROUND: Alarms alert healthcare professionals of deviations from normal/physiologic status. However, alarm fatigue may occur when their high pitch and diversity overwhelm clinicians, possibly leading to alarms being disabled, paused, and/or ignored. We aimed to determine whether a staff educational program on customizing alarm settings of bedside monitors may decrease inconsistent alarms in the Post-Anesthesia Care Unit (PACU). METHODS: This is a prospective, analytic, quantitative, pragmatic, open-label, single-arm study. The outcome was evaluated on PACU admission before (P1) and after (P2) the implementation of the educational program. The heart rate, blood pressure, and oxygen saturation alarms were selected for clinical consistency. RESULTS: A total of 260 patients were included and 344 clinical alarms collected, with 270 (78.4%) before (P1), and 74 (21.6%) after (P2) the intervention. Among the 270 alarms in P1, 45.2% were inconsistent (i.e., false alarms), compared to 9.4% of the 74 in P2. Patients with consistent alarms occurred in 30% in the P1 and 27% in the P2 (p = 0.08). Patients with inconsistent alarms occurred in 25.4% in the P1 and in 3.8% in the P2. Ignored consistent alarms were reduced from 21.5% to 2.6% (p = 0.004) in the P2 group. The educational program was a protective factor for the inconsistent clinical alarm (OR = 0.11 [95% CI 0.04-0.3]; p < 0.001) after adjustments for age, gender, and ASA physical status. CONCLUSION: Customizing alarm settings on PACU admission proved to be a protective factor against inconsistent alarm notifications of multiparametric monitors.

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AIMS: This article aims to perform a Systematic Literature Review (SLR) to better understand the structures of different methods, techniques, models, methodologies, and technologies related to provenance data management in health information systems (HISs). The SLR developed here seeks to answer the questions that contribute to describing the results. METHOD: An SLR was performed on six databases using a search string. The backward and forward snowballing technique was also used. Eligible studies were all articles in English that presented on the use of different methods, techniques, models, methodologies, and technologies related to provenance data management in HISs. The quality of the included articles was assessed to obtain a better connection to the topic studied. RESULTS: Of the 239 studies retrieved, 14 met the inclusion criteria described in this SLR. In order to complement the retrieved studies, 3 studies were included using the backward and forward snowballing technique, totaling 17 studies dedicated to the construction of this research. Most of the selected studies were published as conference papers, which is common when involving computer science in HISs. There was a more frequent use of data provenance models from the PROV family in different HISs combined with different technologies, among which blockchain and middleware stand out. Despite the advantages found, the lack of technological structure, data interoperability problems, and the technical unpreparedness of working professionals are still challenges encountered in the management of provenance data in HISs. CONCLUSION: It was possible to conclude the existence of different methods, techniques, models, and combined technologies, which are presented in the proposal of a taxonomy that provides researchers with a new understanding about the management of provenance data in HISs.

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The aim of this study was to predict production indicators and to determine their potential economic impact on a poultry integration system using artificial neural networks (ANN) models. Forty zootechnical and production parameters from broiler breeder farms, one hatchery, broiler production flocks, and one slaughterhouse were selected as variables. The ANN models were established for four output variables: "saleable hatching", "weight at the end of week 5," "partial condemnation," and "total condemnation" and were analyzed in relation to the coefficient of multiple determination (R2), correlation coefficient (R), mean error (E), mean squared error (MSE), and root mean square error (RMSE). The production scenarios were simulated and the economic impacts were estimated. The ANN models were suitable for simulating production scenarios after validation. For "saleable hatching", incubator and egg storage period are likely to increase the financial gains. For "weight at the end of the week 5" the lineage (A) is important to increase revenues. However, broiler weight at the end of the first week may not have a significant influence. Flock sex (female) may influence the "partial condemnation" rates, while chick weight at first day may not. For "total condemnation", flock sex and type of chick may not influence condemnation rates, but mortality rates and broiler weight may have a significant impact.

O objetivo deste trabalho foi predizer os indicadores de produção e determinar o seu potencial impacto econômico em um sistema de integração utilizando as redes neurais artificiais (RNA). Quarenta parâmetros zootécnicos e de produção de granjas de matrizes e de frango de corte, um incubatório e um abatedouro foram selecionados como variáveis. Os modelos de RNA foram estabelecidos para quatro variáveis de saída ("eclosão vendável", "peso ao final da quinta semana", "condenações parciais" e "condenações totais") e foram analisados em relação ao coeficiente de determinação múltipla (R2), coeficiente de correlação (R), erro médio (E), erro quadrático médio (EQM) e raiz do erro quadrático médio (REQM). Os cenários produtivos foram simulados e os impactos foram estimados. Os modelos de RNA gerados foram adequados para simular diferentes cenários produtivos após o treinamento. Para "eclosão vendável", o modelo de incubadora e o período de incubação aumentaram os ganhos financeiros. Para "peso ao final da quinta semana", a linhagem também demonstrou influencia no retorno financeiro, o que não aconteceu com o peso ao final da primeira semana. O sexo do lote possui influência nas taxas de "condenação parcial", ao contrário do peso do frango no primeiro dia. As taxas de mortalidade e o peso do frango apresentaram influência na "condenação total", mas o sexo do lote e o tipo de pinto não tiverem influência.

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ABSTRACT Objectives: to analyze the accuracy of the clinical indicators of ineffective airway clearance in adult intensive care unit patients. Methods: diagnostic accuracy study, performed in the intensive care unit of a university hospital in northeastern Brazil. The sample consisted of 104 patients hospitalized between June and October 2019. Results: the prevalence of ineffective airway clearance was 36.54%. The indicators with high specificity included absence of cough (0.8326), orthopnea (0.6817), adventitious breath sounds (0.8175), and diminished breath sounds (0.8326). The clinical indicators with high sensitivity and specificity were alteration in respiratory rate (0.9999) and alteration in respiratory pattern (0.9999). Conclusions: six clinical indicators provided an accurate identification of ineffective airway clearance. The clinical indicators alteration in respiratory rate and alteration in respiratory pattern were the most accurate for critical adult patients. The findings of this study contribute to accurate diagnostic inferences and to prevention of respiratory complications in these patients.

RESUMO Objetivos: analisar a acurácia dos indicadores clínicos de desobstrução ineficaz de vias aéreas em pacientes de unidade de terapia intensiva adulto. Métodos: estudo de acurácia diagnóstica em unidade de terapia intensiva de um hospital universitário do nordeste do Brasil. Amostra de 104 pacientes internados entre junho e outubro de 2019. Resultados: a prevalência de desobstrução ineficaz de vias aéreas foi de 36,54%. Os indicadores com alta especificidade foram ausência de tosse (0,8326), ortopneia (0,6817), sons respiratórios adventícios (0,8175) e sons respiratórios diminuídos (0,8326). Os indicadores clínicos com alta sensibilidade e especificidade foram alteração na frequência respiratória (0,9999) e alteração no padrão respiratório (0,9999). Conclusões: seis indicadores clínicos forneceram identificação precisa da desobstrução ineficaz de vias aéreas. Os indicadores clínicos alteração na frequência respiratória e alteração no padrão respiratório foram os mais precisos para pacientes críticos. Os achados contribuem para inferências diagnósticas precisas e para prevenção de complicações respiratórias nesses pacientes.

RESUMEN Objetivos: analizar la precisión de indicadores clínicos de limpieza ineficaz de las vías aéreas en pacientes de unidades de cuidados intensivos adulto. Métodos: estudio de precisión diagnóstica en unidad de cuidados intensivos de hospital universitario en noreste brasileño. Muestra de 104 pacientes hospitalizados entre junio y octubre de 2019. Resultados: prevalencia de limpieza ineficaz de las vías aéreas del 36,54%. Indicadores con alta especificidad; ausencia de tos (0,8326), ortopnea (0,6817), ruidos respiratorios adventicios (0,8175) y ruidos respiratorios disminuidos (0,8326). Indicadores clínicos con alta sensibilidad y especificidad; cambio en la frecuencia respiratoria (0,9999) y cambio en el patrón de respiración (0,9999). Conclusiones: seis indicadores clínicos proporcionaron identificación precisa de la limpieza ineficaz de las vías aéreas; cambio en la frecuencia respiratoria y cambio en el patrón de respiración fueron los más precisos para pacientes críticos. Nuestros hallazgos contribuyen a inferencias diagnósticas precisas y la prevención de complicaciones respiratorias en estos pacientes.

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INTRODUCTION: CHDs are the most common type of birth defect. One in four newborns with a heart defect has a critical CHD. In Mexico, there is a lack of data available to determine its prevalence. Pulse oximetry screening programmes have been implemented worldwide, reporting opportunity areas in algorithm interpretation and data management. Our study aims to share preliminary results of a 3-year experience of a multicentre pulse oximetry screening programme that addresses critical challenges. MATERIALS AND METHODS: This retrospective study examined the reports of newborns screened from February 2016 to July 2019 from five hospitals. Two algorithms -the New Jersey and the American Academy of Pediatrics- were implemented over consecutive periods. The algorithms' impact was assessed through the calculation of the false-positive rate in an eligible population. RESULTS: A total of 8960 newborns were eligible for the study; from it, 32.27% were screened under the New Jersey and 67.72% under the American Academy of Pediatrics algorithm - false-positive rate: 1% (CI 95: ± 0.36%) and 0.71% (CI 95: ± 0.21%), respectively. Seventy-nine newborns were referred, six were diagnosed with critical CHD, and six with CHD. The critical CHD estimated prevalence was 6.69:10,000 newborns (CI 95: ± 5.36). Our results showed that the algorithm was not related to the observable false-positive rate reduction. DISCUSSION: Other factors may play a role in decreasing the false-positive rate. Our experience implementing this programme was that a systematic screening process led to more confident results, newborn's report interpretation, and follow-up.