Accurate prediction of all-cause mortality in patients with metabolic dysfunction-associated steatotic liver disease using electronic health records.

INTRODUCTION AND OBJECTIVES: Despite the huge clinical burden of MASLD, validated tools for early risk stratification are lacking, and heterogeneous disease expression and a highly variable rate of progression to clinical outcomes result in prognostic uncertainty. We aimed to investigate longitudinal electronic health record-based outcome prediction in MASLD using a state-of-the-art machine learning model. PATIENTS AND METHODS: n = 940 patients with histologically-defined MASLD were used to develop a deep-learning model for all-cause mortality prediction. Patient timelines, spanning 12 years, were fully-annotated with demographic/clinical characteristics, ICD-9 and -10 codes, blood test results, prescribing data, and secondary care activity. A Transformer neural network (TNN) was trained to output concomitant probabilities of 12-, 24-, and 36-month all-cause mortality. In-sample performance was assessed using 5-fold cross-validation. Out-of-sample performance was assessed in an independent set of n = 528 MASLD patients. RESULTS: In-sample model performance achieved AUROC curve 0.74-0.90 (95 % CI: 0.72-0.94), sensitivity 64 %-82 %, specificity 75 %-92 % and Positive Predictive Value (PPV) 94 %-98 %. Out-of-sample model validation had AUROC 0.70-0.86 (95 % CI: 0.67-0.90), sensitivity 69 %-70 %, specificity 96 %-97 % and PPV 75 %-77 %. Key predictive factors, identified using coefficients of determination, were age, presence of type 2 diabetes, and history of hospital admissions with length of stay >14 days. CONCLUSIONS: A TNN, applied to routinely-collected longitudinal electronic health records, achieved good performance in prediction of 12-, 24-, and 36-month all-cause mortality in patients with MASLD. Extrapolation of our technique to population-level data will enable scalable and accurate risk stratification to identify people most likely to benefit from anticipatory health care and personalized interventions.

An Information Model on Pain Management: Cultural Validation and Refinement.

This study aimed to validate and refine an information model on pain management in a Brazilian hospital, considering the institutional culture, using an expert consensus approach. The first stage took place through a computerized questionnaire and Content Validity Index calculation. Pain management attributes were considered validated with 75% consensus among 19 experts. The second stage validated and refined the information model by three experts via an online meeting. Results showed that out of 11 evaluated attributes, five were validated. In the second stage, the inclusion of new attributes was suggested to address institutional culture. The final information model resulted from 23 sets of revised attributes: 12 validated, seven suggested and four not validated. The resulting Brazilian model has the potential to support the implementation of interventions and propose improvements to the institution's electronic system, which can be reused in other institutions.

EHR-based Case Identification of Pediatric Long COVID: A Report from the RECOVER EHR Cohort.

Objective: Long COVID, marked by persistent, recurring, or new symptoms post-COVID-19 infection, impacts children's well-being yet lacks a unified clinical definition. This study evaluates the performance of an empirically derived Long COVID case identification algorithm, or computable phenotype, with manual chart review in a pediatric sample. This approach aims to facilitate large-scale research efforts to understand this condition better. Methods: The algorithm, composed of diagnostic codes empirically associated with Long COVID, was applied to a cohort of pediatric patients with SARS-CoV-2 infection in the RECOVER PCORnet EHR database. The algorithm classified 31,781 patients with conclusive, probable, or possible Long COVID and 307,686 patients without evidence of Long COVID. A chart review was performed on a subset of patients (n=651) to determine the overlap between the two methods. Instances of discordance were reviewed to understand the reasons for differences. Results: The sample comprised 651 pediatric patients (339 females, M age = 10.10 years) across 16 hospital systems. Results showed moderate overlap between phenotype and chart review Long COVID identification (accuracy = 0.62, PPV = 0.49, NPV = 0.75); however, there were also numerous cases of disagreement. No notable differences were found when the analyses were stratified by age at infection or era of infection. Further examination of the discordant cases revealed that the most common cause of disagreement was the clinician reviewers' tendency to attribute Long COVID-like symptoms to prior medical conditions. The performance of the phenotype improved when prior medical conditions were considered (accuracy = 0.71, PPV = 0.65, NPV = 0.74). Conclusions: Although there was moderate overlap between the two methods, the discrepancies between the two sources are likely attributed to the lack of consensus on a Long COVID clinical definition. It is essential to consider the strengths and limitations of each method when developing Long COVID classification algorithms.

Postpartum hemorrhage in electronic health records: risk factors at admission and in-hospital occurrence.

Objective: Postpartum hemorrhage (PPH) is the leading cause of maternal death globally. Therefore, prevention strategies have been created. The study aimed to evaluate the occurrence of PPH and its risk factors after implementing a risk stratification at admission in a teaching hospital. Methods: A retrospective cohort involving a database of SISMATER® electronic medical record. Classification in low, medium, or high risk for PPH was performed through data filled out by the obstetrician-assistant. PPH frequency was calculated, compared among these groups and associated with the risk factors. Results: The prevalence of PPH was 6.8%, 131 among 1,936 women. Sixty-eight (51.9%) of them occurred in the high-risk group, 30 (22.9%) in the medium-risk and 33 (25.2%) in the low-risk group. The adjusted-odds ratio (OR) for PPH were analyzed using a confidence interval (95% CI) and was significantly higher in who presented multiple pregnancy (OR 2.88, 95% CI 1.28 to 6.49), active bleeding on admission (OR 6.12, 95% CI 1.20 to 4.65), non-cephalic presentation (OR 2.36, 95% CI 1.20 to 4.65), retained placenta (OR 9.39, 95% CI 2.90 to 30.46) and placental abruption (OR 6.95, 95% CI 2.06 to 23.48). Vaginal delivery figured out as a protective factor (OR 0.58, 95% CI 0.34 to 0.98). Conclusion: Prediction of PPH is still a challenge since its unpredictable factor arrangements. The fact that the analysis did not demonstrate a relationship between risk category and frequency of PPH could be attributable to the efficacy of the strategy: Women classified as "high-risk" received adequate medical care, consequently.

Wearable sensors in patient acuity assessment in critical care.

Acuity assessments are vital for timely interventions and fair resource allocation in critical care settings. Conventional acuity scoring systems heavily depend on subjective patient assessments, leaving room for implicit bias and errors. These assessments are often manual, time-consuming, intermittent, and challenging to interpret accurately, especially for healthcare providers. This risk of bias and error is likely most pronounced in time-constrained and high-stakes environments, such as critical care settings. Furthermore, such scores do not incorporate other information, such as patients' mobility level, which can indicate recovery or deterioration in the intensive care unit (ICU), especially at a granular level. We hypothesized that wearable sensor data could assist in assessing patient acuity granularly, especially in conjunction with clinical data from electronic health records (EHR). In this prospective study, we evaluated the impact of integrating mobility data collected from wrist-worn accelerometers with clinical data obtained from EHR for estimating acuity. Accelerometry data were collected from 87 patients wearing accelerometers on their wrists in an academic hospital setting. The data was evaluated using five deep neural network models: VGG, ResNet, MobileNet, SqueezeNet, and a custom Transformer network. These models outperformed a rule-based clinical score (Sequential Organ Failure Assessment, SOFA) used as a baseline when predicting acuity state (for ground truth we labeled as unstable patients if they needed life-supporting therapies, and as stable otherwise), particularly regarding the precision, sensitivity, and F1 score. The results demonstrate that integrating accelerometer data with demographics and clinical variables improves predictive performance compared to traditional scoring systems in healthcare. Deep learning models consistently outperformed the SOFA score baseline across various scenarios, showing notable enhancements in metrics such as the area under the receiver operating characteristic (ROC) Curve (AUC), precision, sensitivity, specificity, and F1 score. The most comprehensive scenario, leveraging accelerometer, demographics, and clinical data, achieved the highest AUC of 0.73, compared to 0.53 when using SOFA score as the baseline, with significant improvements in precision (0.80 vs. 0.23), specificity (0.79 vs. 0.73), and F1 score (0.77 vs. 0.66). This study demonstrates a novel approach beyond the simplistic differentiation between stable and unstable conditions. By incorporating mobility and comprehensive patient information, we distinguish between these states in critically ill patients and capture essential nuances in physiology and functional status. Unlike rudimentary definitions, such as equating low blood pressure with instability, our methodology delves deeper, offering a more holistic understanding and potentially valuable insights for acuity assessment.

[Digital health in Latin America: current legislation and ethical aspectsSaúde digital na América Latina: legislação atual e aspectos éticos]. / Salud digital en América Latina: legislación actual y aspectos éticos.

Objectives: Describe the current legislation on electronic medical records (EMR) and telehealth in Latin American countries and analyze the treatment of confidentiality and professional secrecy. Methods: Between March and September 2022, a survey of the regulations in force in 21 Latin American countries was conducted at two levels: the existence of legislation on EMR and telehealth, and the treatment of confidentiality and professional secrecy in EMR and telehealth. A data extraction form was prepared for each country. Data were collected from official on-line sources. The information was analyzed qualitatively and synthesized in tables when possible. Results: The use of EMR is legally regulated in 16 countries. Nineteen countries have legislation on telehealth. All the countries analyzed safeguard confidentiality and professional secrecy through regulations. However, confidentiality and professional secrecy are mentioned in 11 countries in the context of telehealth, and in only nine countries in the context of EMR. Conclusions: Since the start of this century, Latin America has made progress in the legislation of digital tools for health care, such as EMR and telehealth. There is also interest in ethical issues related to the use of EMR and telehealth, particularly confidentiality and professional secrecy, aspects that should be strengthened in digital health.

Objetivo: Descrever a legislação vigente sobre prontuários eletrônicos e telessaúde nos países da América Latina e analisar o tratamento da confidencialidade e do sigilo profissional. Métodos: Entre março e setembro de 2022, realizou-se um levantamento sobre a regulamentação vigente nos 21 países latino-americanos incluídos no estudo, em dois níveis: i) existência de legislação sobre prontuários eletrônicos e telessaúde; e ii) tratamento da confidencialidade e do sigilo profissional em prontuários eletrônicos e telessaúde. Uma planilha para extração de dados foi elaborada para cada país. Os dados foram coletados de fontes oficiais disponíveis on-line. Foi realizada uma análise qualitativa das informações, que foram resumidas em tabelas, quando possível. Resultados: O uso dos prontuários eletrônicos é legalmente regulamentado em 16 países. Quanto à telessaúde, 19 países têm legislação sobre essa ferramenta. Todos os países analisados protegem a confidencialidade e o sigilo profissional por meio de regulamentação. No entanto, no contexto da telessaúde, eles são mencionados em 11 países; já no contexto dos prontuários eletrônicos, em apenas 9 países. Conclusões: Desde o início dos anos 2000, a América Latina vem avançando em relação à legislação sobre ferramentas digitais na atenção à saúde, como prontuários eletrônicos e telessaúde. Há também interesse nas questões éticas relacionadas ao uso de prontuários eletrônicos e telessaúde, especialmente em relação à confidencialidade e ao sigilo profissional, embora esses aspectos precisem ser reforçados na saúde digital.

Using interoperable nursing care data to improve outcomes for multiple traumas patients with Impaired Physical Mobility.

AIM(S): To demonstrate how interoperable nursing care data can be used by nurses to create a more holistic understanding of the healthcare needs of multiple traumas patients with Impaired Physical Mobility. By proposing and validating linkages for the nursing diagnosis of Impaired Physical Mobility in multiple trauma patients by mapping to the Nursing Outcomes Classification (NOC) and Nursing Interventions Classification (NIC) equivalent terms using free-text nursing documentation. DESIGN: A descriptive cross-sectional design, combining quantitative analysis of interoperable data sets and the Kappa's coefficient score with qualitative insights from cross-mapping methodology and nursing professionals' consensus. METHODS: Cross-mapping methodology was conducted in a Brazilian Level 1 Trauma Center using de-identified records of adult patients with a confirmed medical diagnosis of multiple traumas and Impaired Physical Mobility (a nursing diagnosis). The hospital nursing free-text records were mapped to NANDA-I, NIC, NOC and NNN linkages were identified. The data records were retrieved for admissions from September to October 2020 and involved medical and nursing records. Three expert nurses evaluated the cross-mapping and linkage results using a 4-point Likert-type scale and Kappa's coefficient. RESULTS: The de-identified records of 44 patients were evaluated and then were mapped to three NOCs related to nurses care planning: (0001) Endurance; (0204) Immobility Consequences: Physiological, and (0208) Mobility and 13 interventions and 32 interrelated activities: (6486) Environmental Management: Safety; (0840) Positioning; (3200) Aspiration Precautions; (1400) Pain Management; (0940) Traction/Immobilization Care; (3540) Pressure Ulcer Prevention; (3584) Skincare: Topical Treatment; (1100) Nutrition Management; (3660) Wound Care; (1804) Self-Care Assistance: Toileting; (1801) Self-Care Assistance: Bathing/Hygiene; (4130) Fluid Monitoring; and (4200) Intravenous Therapy. The final version of the constructed NNN Linkages identified 37 NOCs and 41 NICs. CONCLUSION: These valid NNN linkages for patients with multiple traumas can serve as a valuable resource that enables nurses, who face multiple time constraints, to make informed decisions efficiently. This approach of using evidence-based linkages like the one developed in this research holds high potential for improving patient's safety and outcomes. NO PATIENT OR PUBLIC CONTRIBUTION: In this study, there was no direct involvement of patients, service users, caregivers or public members in the design, conduct, analysis and interpretation of data or preparation of the manuscript. The study focused solely on analysing existing de-identified medical and nursing records to propose and validate linkages for nursing diagnoses.

Making causal inferences from transactional data: A narrative review of opportunities and challenges when implementing the target trial framework.

The target trial framework has emerged as a powerful tool for addressing causal questions in clinical practice and in public health. In the healthcare sector, where decision-making is increasingly data-driven, transactional databases, such as electronic health records (EHR) and insurance claims, present an untapped potential for answering complex causal questions. This narrative review explores the potential of the integration of the target trial framework with real-world data to enhance healthcare decision-making processes. We outline essential elements of the target trial framework, and identify pertinent challenges in data quality, privacy concerns, and methodological limitations, proposing solutions to overcome these obstacles and optimize the framework's application.

Comparison of Clinical Decision Support Tools to Improve Pediatric Lipid Screening.

OBJECTIVE: To test whether different clinical decision support tools increase clinician orders and patient completions relative to standard practice and each other. STUDY DESIGN: A pragmatic, patient-randomized clinical trial in the electronic health record was conducted between October 2019 and April 2020 at Geisinger Health System in Pennsylvania, with 4 arms: care gap-a passive listing recommending screening; alert-a panel promoting and enabling lipid screen orders; both; and a standard practice-no guideline-based notification-control arm. Data were analyzed for 13 346 9- to 11-year-old patients seen within Geisinger primary care, cardiology, urgent care, or nutrition clinics, or who had an endocrinology visit. Principal outcomes were lipid screening orders by clinicians and completions by patients within 1 week of orders. RESULTS: Active (care gap and/or alert) vs control arm patients were significantly more likely (P < .05) to have lipid screening tests ordered and completed, with ORs ranging from 1.67 (95% CI 1.28-2.19) to 5.73 (95% CI 4.46-7.36) for orders and 1.54 (95% CI 1.04-2.27) to 2.90 (95% CI 2.02-4.15) for completions. Alerts, with or without care gaps listed, outperformed care gaps alone on orders, with odds ratios ranging from 2.92 (95% CI 2.32-3.66) to 3.43 (95% CI 2.73-4.29). CONCLUSIONS: Electronic alerts can increase lipid screening orders and completions, suggesting clinical decision support can improve guideline-concordant screening. The study also highlights electronic record-based patient randomization as a way to determine relative effectiveness of support tools. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04118348.

Automatic Speech Recognition System to Record Progress Notes in a Mobile EHR: A Pilot Study.

Creating notes in the EHR is one of the most problematic aspects for health professionals. The main challenges are the time spent on this task and the quality of the records. Automatic speech recognition technologies aim to facilitate clinical documentation for users, optimizing their workflow. In our hospital, we internally developed an automatic speech recognition system (ASR) to record progress notes in a mobile EHR. The objective of this article is to describe the pilot study carried out to evaluate the implementation of ASR to record progress notes in a mobile EHR application. As a result, the specialty that used ASR the most was Home Medicine. The lack of access to a computer at the time of care and the need to perform short and fast evolutions were the main reasons for users to use the system.

Ten years of the Citizen's Electronic Health Record e-SUS Primary Healthcare: in search of an electronic Unified Health System / Dez anos do Prontuário Eletrônico do Cidadão e-SUS APS: em busca de um Sistema Único de Saúde eletrônico

ABSTRACT OBJECTIVE: Contextualize the adherence to the Prontuário Eletrônico do Cidadão (PEC - Citizen's Electronic Health Record) by Brazilian municipalities and the evolution of the electronic strategy of the Unified Health System (e-SUS) for Primary Healthcare (PHC) during its 10 years. METHODS: This descriptive study added information on adherence to the use of medical records extracted from the database of the Secretaria de Atenção Primária à Saúde (SAPS- Primary Healthcare Secretary) of the Federal Government between 2017 and 2022. We analized the number of computerized basic healthcare units that used some electronic medical records, the number of those that used simplified data collection (SDC), and those that implemented the citizen's electronic health record (PEC) in the same period. A descriptive synthesis of the functionalities and modules implemented in the system during its 10 years of development was also carried out. RESULTS: The adherence of Brazilian municipalities to the PEC has grown exponentially in the last five years, going from 8,930 healthcare units in 2017 to 26,091 in 2022. As expected, while the main functionalities and improvements developed in this decade sought to implement new flows and modules of administrative, clinical care, and care management processes and health service administration, improving aspects of usability and technological infrastructure of the application architecture was also crucial for the success of the system. CONCLUSIONS: In 2023, the milestone of a decade will be celebrated since the beginning of health records implementation by Brazilian municipalities, marked by technological and infrastructure challenges and improvements and new functionalities that highlight the technological evolution of the e-SUS PHC system and strategy. Despite many other tools, the PEC is arguably Brazil's leading electronic medical record today, as it has always invested in evolution, updating itself in technological and usability opportunities.

RESUMO OBJETIVO: Contextualizar a adesão ao Prontuário Eletrônico do Cidadão (PEC) pelos municípios brasileiros e a evolução da estratégia eletrônica do Sistema Único de Saúde (e-SUS) da Atenção Primária (APS) durante seus 10 anos. MÉTODOS: Trata-se de um estudo de cunho descritivo, que agregou informações de adesão ao uso do prontuário, extraídas da base de dados da Secretaria de Atenção Primária à Saúde (SAPS) do Governo Federal, entre os anos de 2017 e 2022. Foram analisados o quantitativo de unidades básicas de saúde informatizadas que utilizavam algum prontuário eletrônico e o número das que utilizavam a Coleta de Dados Simplificada (CDS) e das que implementaram o Prontuário Eletrônico do Cidadão (PEC), no mesmo período. Também foi realizada uma síntese descritiva das funcionalidades e módulos que foram implementados no sistema durante seus 10 anos de desenvolvimento. RESULTADOS: A adesão dos municípios brasileiros ao PEC cresceu exponencialmente nos últimos cinco anos, passando de 8.930 unidades de saúde em 2017 para 26.091 em 2022. Como era de se esperar, as principais funcionalidades e melhorias desenvolvidas nessa década buscaram implementar novos fluxos e módulos de processos administrativos, de atendimento clínico e de gestão do cuidado e administração do serviço de saúde, mas também foram importantes para o sucesso do sistema aprimorar aspectos de usabilidade e de infraestrutura tecnológica da arquitetura da aplicação. CONCLUSÕES: Em 2023, celebra-se o marco de uma década do início da implantação do prontuário pelos municípios brasileiros, marcado por desafios de ordem tecnológica e de infraestrutura, bem como de melhorias e novas funcionalidades que evidenciaram a evolução tecnológica do sistema e da estratégia e-SUS APS. Mesmo que muitas outras existam, pode-se dizer que o PEC é hoje a principal ferramenta de prontuário eletrônico no Brasil, pois sempre investiu em evolução, vindo a se atualizar nas oportunidades tecnológicas e de usabilidade.

PEP acadêmico: plataforma web para registro eletrônico no cenário da atenção primária à saúde / Academic PEP: educational web platform for electronic registration in the primary health care scenario

Aproximar os estudantes das funcionalidades, potencialidades e das limitações das tecnologias para o registro eletrônico em saúde (RES) é necessário e urgente, a fim de prepará-los para futura atuação profissional. Os registros constituem memória valiosa para o profissional, instituição de saúde e paciente, sendo importante ferramenta na integralidade e longitudinalidade das informações para a tomada de decisão. Neste sentido, este estudo tem por objetivo desenvolver e avaliar uma plataforma web para o ensino e aprendizagem de registros eletrônicos, no cenário da Atenção Primária em Saúde (APS). Como percurso metodológico esta pesquisa foi conduzida em três etapas, sendo a 1° etapa o Planejamento; a 2° etapa o Desenvolvimento da plataforma utilizando-se do referencial metodológico do desenvolvimento ágil de software, na modalidade Scrum. E por fim, na 3° etapa, a Avaliação pelos estudantes de Enfermagem e Medicina, professores e especialistas em Tecnologias da Informação e Comunicação (TIC), por meio de questionários: Teste de Aceitação; escala System Usability Scale (SUS); recomendação do produto pelo escore Net Promoter e avaliação da inter-relação das funcionalidades do registro eletrônico e competências-chave, pautadas na Taxonomia de Bloom. A análise dos dados foi realizada por meio de estatística descritiva. Participaram da etapa de avaliação um total de 34 estudantes, 14 professores e 9 especialistas em TIC. Foram pontuadas oportunidades de melhorias na tela de agendamento e nas telas de atendimento do paciente, nos itens referentes ao registro de dados objetivos, avaliação e plano de cuidados. Por meio da SUS observou-se que a plataforma apresenta usabilidade adequada aos objetivos propostos. No Net Promoter Score é possível observar que a maioria dos avaliadores classificaram a plataforma na zona de excelência. Em relação à avaliação dos professores acerca da interrelação das funcionalidades do registro eletrônico para APS e competências-chave, conforme o ano de curso, é possível inferir a possibilidade de contribuição com o desenvolvimento de competências no processo de aprendizado em registros eletrônicos em saúde. Conclui-se que, por meio da plataforma, é possível que o estudante vivencie a experiência imersiva ao realizar as mesmas tarefas de um registro eletrônico no cenário da APS, utilizando banco de dados de pacientes simulados. Destaca-se que a construção e avaliação da plataforma corrobora com a necessidade de desenvolver competências em RES, buscando preparar os estudantes de Enfermagem e Medicina para a documentação adequada das informações inerentes ao cuidado em saúde, aspecto fundamental para a prática clínica.

Aproximar os estudantes das funcionalidades, potencialidades e das limitações das tecnologias para o registro eletrônico em saúde (RES) é necessário e urgente, a fim de prepará-los para futura atuação profissional. Os registros constituem memória valiosa para o profissional, instituição de saúde e paciente, sendo importante ferramenta na integralidade e longitudinalidade das informações para a tomada de decisão. Neste sentido, este estudo tem por objetivo desenvolver e avaliar uma plataforma web para o ensino e aprendizagem de registros eletrônicos, no cenário da Atenção Primária em Saúde (APS). Como percurso metodológico esta pesquisa foi conduzida em três etapas, sendo a 1° etapa o Planejamento; a 2° etapa o Desenvolvimento da plataforma utilizando-se do referencial metodológico do desenvolvimento ágil de software, na modalidade Scrum. E por fim, na 3° etapa, a Avaliação pelos estudantes de Enfermagem e Medicina, professores e especialistas em Tecnologias da Informação e Comunicação (TIC), por meio de questionários: Teste de Aceitação; escala System Usability Scale (SUS); recomendação do produto pelo escore Net Promoter e avaliação da inter-relação das funcionalidades do registro eletrônico e competências-chave, pautadas na Taxonomia de Bloom. A análise dos dados foi realizada por meio de estatística descritiva. Participaram da etapa de avaliação um total de 34 estudantes, 14 professores e 9 especialistas em TIC. Foram pontuadas oportunidades de melhorias na tela de agendamento e nas telas de atendimento do paciente, nos itens referentes ao registro de dados objetivos, avaliação e plano de cuidados. Por meio da SUS observou-se que a plataforma apresenta usabilidade adequada aos objetivos propostos. No Net Promoter Score é possível observar que a maioria dos avaliadores classificaram a plataforma na zona de excelência. Em relação à avaliação dos professores acerca da interrelação das funcionalidades do registro eletrônico para APS e competências-chave, conforme o ano de curso, é possível inferir a possibilidade de contribuição com o desenvolvimento de competências no processo de aprendizado em registros eletrônicos em saúde. Conclui-se que, por meio da plataforma, é possível que o estudante vivencie a experiência imersiva ao realizar as mesmas tarefas de um registro eletrônico no cenário da APS, utilizando banco de dados de pacientes simulados. Destaca-se que a construção e avaliação da plataforma corrobora com a necessidade de desenvolver competências em RES, buscando preparar os estudantes de Enfermagem e Medicina para a documentação adequada das informações inerentes ao cuidado em saúde, aspecto fundamental para a prática clínica.

Prevalence and reasons for referrals to the Endodontics Specialty Clinic at the Piracicaba Dental School

Abstract Dental referrals to the Endodontics Specialty Clinic (ESC) are routine owing to the complexity of endodontic treatments. To obtain a better prognosis for treatment, students/dentists must perceive their technical limits. This study sought to investigate the referrals of patients to the ESC from different clinics of the Piracicaba Dental School, State University of Campinas - SP, Brazil, and check: a) the demographic profile of patients and the most commonly affected tooth; b) the clinic with the largest number of referrals; c) the reasons for referrals; d) the complexity of the cases; e) and the difficulty in assessing the referred cases based on the classification provided by the American Association of Endodontists (AAE) and Souza-Filho. The study sample consisted of patients' electronic dental referral records from February 2015 to June 2019. A total of 1,707 patients were referred to the ESC during the study period, and 62.4% were female. Lower molars were the most frequently involved teeth (34.8%), and 60.7% of the cases were referred due to the presence of root curvature. The AAE classification showed prevalence of highly difficult cases (71.3%), whereas Souza-Filho classification demonstrated a high rate of class III cases (85.8%). This study highlights the difficulties encountered by undergraduate students before or during endodontic treatments, reinforcing the need for clear criteria for selecting cases appropriate for each education level, thus improving endodontic treatment prognosis.

Uso de prontuário eletrônico e parâmetros de acesso e acolhimento segundo dados do terceiro ciclo do PMAQ-AB / Use of electronic health records and primary health care accessibility according to data from the third cycle of the PMAQ-AB

Resumo O uso de prontuários eletrônicos (PE) na atenção primária em saúde (APS) visa maior integração e qualidade dos serviços. Um dos pontos mais críticos da APS brasileira segue sendo o acesso. O objetivo deste artigo é analisar através dos dados do terceiro ciclo avaliativo do Programa de Melhoria do Acesso e Qualidade da Atenção Básica (PMAQ-AB) a relação entre o uso de prontuário eletrônico e os parâmetros de acesso e acolhimento das unidades participantes. Estudo transversal analítico com dados secundários. Foram avaliados dados provenientes de 38.865 equipes de atenção primária, 30.346 unidades de saúde e 140.444 usuários entrevistados. O uso de PE esteve associado a maior realização de atendimento à demanda espontânea (OR 1,664; IC95% 1,485-1,866), avaliação de risco e vulnerabilidade (OR 1,329; IC95% 1,122-1,574) e utilização de protocolos de conduta (OR 1,656; IC95% 1,530-1,793), além de maior possibilidade de agendamento por telefone (OR 3,179; IC95% 3,030-3,335). Serviços que utilizam PE tem maior chance de ser o primeiro contato dos pacientes (OR 1,226; IC95% 1,171-1,283) e de serem buscados quando o usuário tem problemas de urgência (OR 1,198; IC95% 1,161-1,236). Há uma possibilidade concreta de melhoria do acesso através da informatização.

Abstract The use of electronic health records (EHR) in primary healthcare (PHC) aims for better integration of services and care quality. One of most the critical points of Brazilian PHC is access. This article aims to analyze, through data from the third evaluation cycle of the Brazilian Program for Improving Access and Quality of Primary Care (PMAQ-AB), the relationship between the use of electronic health records and the parameters of access of the participant teams. Cross-sectional analytical study with secondary data. Data from 38,865 primary care teams, 30,346 health units and 140,444 interviewed users were evaluated. The use of EHR was associated with greater care for non-programmed demands (OR 1.664; 95%CI 1.485-1.866), risk and vulnerability assessment (OR 1.329; 95%CI 1.122-1.574) and use of protocols for clinical conducts (OR 1.656; 95%CI 1.530-1.793), in addition to a greater possibility of scheduling consultation by telephone (OR 3.179; 95%CI 3.030-3.335). Services using EHR are more likely to be the patients first contact (OR 1.226; 95%CI 1.171-1.283) and to be sought when facing urgent health problem (OR 1.198; 95%CI 1.161-1.236). The results point to a concrete possibility of improving access through computerization.

Contributions of representing the elements of nursing practice in the ISO 18.104:2023 standard: a theoretical study / Contribuições da representação dos elementos da prática de enfermagem na norma ISO 18.104:2023: estudo teórico / Aportes de la representación de los elementos de la práctica de enfermería en la norma ISO 18.104:2023: estudio teórico

ABSTRACT Objective: To reflect on the contributions of representing nursing practice elements in the ISO 18.104:2023 standard. Method: This is a theoretical study with standard analysis. Categorical structures were described to represent nursing practice in terminological systems and contributions identified in the parts of the version were analyzed. Results: There is innovation in the inclusion of nurse sensitive outcomes, nursing action, nursing diagnosis explanation as an indicator of nursing service demand and complexity of care, representation of concepts through mental maps and suggestion of use of restriction models for nursing actions. It describes that the Nursing Process is constituted by nursing diagnosis, nursing action and nurse sensitive outcomes. Final considerations: Indicating a nursing diagnosis as an indicator will bring benefits for knowledge production and decision-making. Although care outcomes are not exclusive responses to nursing action, the modifiable attributes of a nursing diagnosis generate knowledge about clinical practice, nursing action effectiveness and subjects of care' health state. There is coherence in understanding the Nursing Process concept evolution.

RESUMO Objetivo: Refletir sobre as contribuições da representação dos elementos da prática de enfermagem na norma ISO 18.104:2023. Método: Estudo teórico com análise da norma. Foram descritas estruturas categoriais para representação da prática da enfermagem nos sistemas terminológicos e analisadas as contribuições identificadas nas partes da versão. Resultados: Há inovação na inclusão do resultado sensível à ação da enfermeira, explicitação do diagnóstico de enfermagem como indicador da demanda de serviços e complexidade de assistência, representação dos conceitos por mapas mentais e sugestão do uso de modelos de restrição para ações de enfermagem. Descreve que o Processo de Enfermagem é constituído pelo diagnóstico, ação e resultado sensível à ação da enfermeira. Considerações finais: A indicação do diagnóstico de enfermagem como um indicador trará benefícios para produção de conhecimento e tomada de decisão. Embora os resultados do cuidado não sejam respostas exclusivas a uma ação da enfermeira, os atributos modificáveis de um diagnóstico de enfermagem geram conhecimentos sobre a prática clínica, a eficácia das ações de enfermagem e o estado de saúde dos sujeitos de cuidado. Há coerência na compreensão da evolução do conceito de Processo de Enfermagem.

RESUMEN Objetivo: Reflexionar sobre los aportes de representar los elementos de la práctica de enfermería en la norma ISO 18.104:2023. Método: Estudio teórico con análisis de la norma. Se describieron estructuras categóricas para representar la práctica de enfermería en sistemas terminológicos y se analizaron las contribuciones identificadas en las partes de la versión. Resultados: Hay innovación en la inclusión del resultado sensible a la acción del enfermero, explicación del diagnóstico de enfermería como indicador de demanda de servicios y complejidad del cuidado, representación de conceptos a través de mapas mentales y sugerencia del uso de modelos de restricción para las acciones de enfermería. Describe que el Proceso de Enfermería está constituido por el diagnóstico, la acción y el resultado sensible a la acción del enfermero. Consideraciones finales: La indicación del diagnóstico de enfermería como indicador traerá beneficios para la producción de conocimiento y la toma de decisiones. Aunque los resultados del cuidado no son respuestas exclusivas a la acción del enfermero, los atributos modificables de un diagnóstico de enfermería generan conocimiento sobre la práctica clínica, la efectividad de las acciones de enfermería y el estado de salud de los sujetos del cuidado. Hay coherencia en la comprensión de la evolución del concepto de Proceso de Enfermería.

Postpartum hemorrhage in electronic health records: risk factors at admission and in-hospital occurrence

Abstract Objective: Postpartum hemorrhage (PPH) is the leading cause of maternal death globally. Therefore, prevention strategies have been created. The study aimed to evaluate the occurrence of PPH and its risk factors after implementing a risk stratification at admission in a teaching hospital. Methods: A retrospective cohort involving a database of SISMATER® electronic medical record. Classification in low, medium, or high risk for PPH was performed through data filled out by the obstetrician-assistant. PPH frequency was calculated, compared among these groups and associated with the risk factors. Results: The prevalence of PPH was 6.8%, 131 among 1,936 women. Sixty-eight (51.9%) of them occurred in the high-risk group, 30 (22.9%) in the medium-risk and 33 (25.2%) in the low-risk group. The adjusted-odds ratio (OR) for PPH were analyzed using a confidence interval (95% CI) and was significantly higher in who presented multiple pregnancy (OR 2.88, 95% CI 1.28 to 6.49), active bleeding on admission (OR 6.12, 95% CI 1.20 to 4.65), non-cephalic presentation (OR 2.36, 95% CI 1.20 to 4.65), retained placenta (OR 9.39, 95% CI 2.90 to 30.46) and placental abruption (OR 6.95, 95% CI 2.06 to 23.48). Vaginal delivery figured out as a protective factor (OR 0.58, 95% CI 0.34 to 0.98). Conclusion: Prediction of PPH is still a challenge since its unpredictable factor arrangements. The fact that the analysis did not demonstrate a relationship between risk category and frequency of PPH could be attributable to the efficacy of the strategy: Women classified as "high-risk" received adequate medical care, consequently.

Nursing workload: use of artificial intelligence to develop a classifier model / Carga de trabajo de enfermería: uso de inteligencia artificial para el desarrollo de modelo clasificador / Carga de trabalho de enfermagem: uso de inteligência artificial para o desenvolvimento de modelo classificador

Objective: to describe the development of a predictive nursing workload classifier model, using artificial intelligence. Method: retrospective observational study, using secondary sources of electronic patient records, using machine learning. The convenience sample consisted of 43,871 assessments carried out by clinical nurses using the Perroca Patient Classification System, which served as the gold standard, and clinical data from the electronic medical records of 11,774 patients, which constituted the variables. In order to organize the data and carry out the analysis, the Dataiku® data science platform was used. Data analysis occurred in an exploratory, descriptive and predictive manner. The study was approved by the Ethics and Research Committee of the institution where the study was carried out. Results: the use of artificial intelligence enabled the development of the nursing workload assessment classifier model, identifying the variables that most contributed to its prediction. The algorithm correctly classified 72% of the variables and the area under the Receiver Operating Characteristic curve was 82%. Conclusion: a predictive model was developed, demonstrating that it is possible to train algorithms with data from the patient's electronic medical record to predict the nursing workload and that artificial intelligence tools can be effective in automating this activity.

Objetivo: describir el desarrollo de un modelo clasificador predictivo de la carga de trabajo de enfermería, utilizando inteligencia artificial. Método: estudio observacional retrospectivo, en fuentes secundarias de registros electrónicos de pacientes, con uso de aprendizaje automático. La muestra por conveniencia se constituyó de 43.871 evaluaciones realizadas por enfermeras asistenciales con el Sistema de Clasificación de Pacientes de Perroca, que sirvieron como patrón oro, y datos clínicos del expediente electrónico de 11.774 pacientes, que constituyeron las variables. Para la organización de los datos y la realización de los análisis se utilizó la plataforma de ciencia de datos Dataiku ® . El análisis de los datos ocurrió de forma exploratoria, descriptiva y predictiva. Estudio aprobado por el Comité de Ética e Investigación de la institución campo del estudio. Resultados: el uso de inteligencia artificial posibilitó el desarrollo del modelo clasificador de evaluación de la carga de trabajo de enfermería, identificando las variables que más contribuyeron para su predicción. El algoritmo clasificó correctamente el 72% de las variables y el área bajo la curva Receiver Operating Characteristic fue del 82%. Conclusión: hubo el desarrollo de un modelo predictivo, demostrando que es posible entrenar algoritmos con datos del expediente electrónico del paciente para predecir la carga de trabajo de enfermería y que las herramientas de inteligencia artificial pueden ser efectivas para la automatización de esta actividad.

Objetivo: descrever o desenvolvimento de um modelo classificador preditivo da carga de trabalho de enfermagem, utilizando inteligência artificial. Método: estudo observacional retrospectivo, em fontes secundárias de registros eletrônicos de pacientes, com uso de aprendizado de máquina. A amostra por conveniência constituiu-se de 43.871 avaliações realizadas por enfermeiras assistenciais com o Sistema de Classificação de Pacientes de Perroca, as quais serviram como padrão ouro, e os dados clínicos do prontuário eletrônico de 11.774 pacientes, que constituíram as variáveis. Para a organização dos dados e a realização das análises, utilizou-se a plataforma de ciência de dados Dataiku ® . A análise dos dados ocorreu de forma exploratória, descritiva e preditiva. Estudo aprovado pelo Comitê de Ética e Pesquisa da instituição campo do estudo. Resultados: o uso de inteligência artificial possibilitou o desenvolvimento do modelo classificador de avaliação da carga de trabalho de enfermagem, identificando as variáveis que mais contribuíram para a sua predição. O algoritmo classificou corretamente 72% das variáveis e a área sob a curva Receiver Operating Characteristic foi de 82%. Conclusão: houve o desenvolvimento de um modelo preditivo, demonstrando que é possível treinar algoritmos com dados do prontuário eletrônico do paciente para predizer a carga de trabalho de enfermagem e que as ferramentas da inteligência artificial podem ser efetivas para a automatização desta atividade.

Implementation and use of electronic patient records in the Brazilian Air Force: a cross-sectional study1

SUMMARY OBJECTIVE: The objective was to analyze the implementation and use of the electronic patient record in the health services of the Brazilian Air Force. METHODS: This is a cross-sectional study carried out with 234 physicians, between March and May 2021. The data collection instrument was sent by email. The electronic patient record was implemented in the Air Force approximately 3 years ago (64.5%), and about 81% of the physicians received training to operate it. RESULTS: The most common records involve data related to consultations (90.1%) and interviews with physical examination (67.1%). Physicians cited that information storage (75.6%), agility, and feasibility of recording (55.1%) were the main advantages of the electronic patient record. As disadvantages, problems in electronic equipment (69.7%) and system errors (65%) were reported. Most participants considered that the implementation had a positive impact on work dynamics (75.6%) and productivity (66.7%), mainly regarding the components "Work processes" (57.3%) and "Amount of carried out activities" (21.4%). Keeping records was significantly associated with the job position (p<0.001), type of unit (p=0.008), time of implementation (p<0.001), and participation in training (p=0.028). CONCLUSION: The implementation of the electronic patient record in the Air Force was recently done, and just over half of the physicians were trained prior to the implementation. The tool is considered compatible with work processes and has a positive effect on productivity.

Salud digital en América Latina: legislación actual y aspectos éticos / Digital health in Latin America: current legislation and ethical aspects / Saúde digital na América Latina: legislação atual e aspectos éticos

RESUMEN Objetivo. Describir la legislación vigente respecto a historia clínica electrónica (HCE) y telesalud de los países latinoamericanos y analizar el tratamiento de la confidencialidad y el secreto profesional. Métodos. Entre marzo y septiembre de 2022, se realizó un relevamiento de la reglamentación vigente en los 21 países latinoamericanos en estudio, en dos niveles: i) la existencia de legislación respecto a la HCE y la telesalud, y ii) el tratamiento de la confidencialidad y el secreto profesional en la HCE y la telesalud. Se confeccionó una ficha de extracción de datos por país. Se recolectaron datos a partir de fuentes on-line oficiales. Se analizó cualitativamente la información y se sintetizó en forma de tablas cuando fue posible. Resultados. El uso de la HCE está reglamentado legalmente en 16 países. Para el caso de telesalud, son 19 países los que cuentan con legislación en referencia a esta herramienta. Todos los países analizados resguardan la confidencialidad y el secreto profesional a través de reglamentaciones. Sin embargo, en el contexto de telesalud se mencionan en 11 países, en tanto en el contexto de la HCE, solo en 9 países. Conclusiones. Desde el inicio del segundo milenio América Latina ha avanzado respecto a la legislación de herramientas digitales en la atención en salud como la HCE y la telesalud. Se observa a su vez un interés por las cuestiones éticas relacionadas con el uso de la HCE y la telesalud, en particular de la confidencialidad y secreto profesional, aunque dichos aspectos deben ser fortalecidos en la salud digital.

ABSTRACT Objectives. Describe the current legislation on electronic medical records (EMR) and telehealth in Latin American countries and analyze the treatment of confidentiality and professional secrecy. Methods. Between March and September 2022, a survey of the regulations in force in 21 Latin American countries was conducted at two levels: the existence of legislation on EMR and telehealth, and the treatment of confidentiality and professional secrecy in EMR and telehealth. A data extraction form was prepared for each country. Data were collected from official on-line sources. The information was analyzed qualitatively and synthesized in tables when possible. Results. The use of EMR is legally regulated in 16 countries. Nineteen countries have legislation on telehealth. All the countries analyzed safeguard confidentiality and professional secrecy through regulations. However, confidentiality and professional secrecy are mentioned in 11 countries in the context of telehealth, and in only nine countries in the context of EMR. Conclusions. Since the start of this century, Latin America has made progress in the legislation of digital tools for health care, such as EMR and telehealth. There is also interest in ethical issues related to the use of EMR and telehealth, particularly confidentiality and professional secrecy, aspects that should be strengthened in digital health.

RESUMO Objetivo. Descrever a legislação vigente sobre prontuários eletrônicos e telessaúde nos países da América Latina e analisar o tratamento da confidencialidade e do sigilo profissional. Métodos. Entre março e setembro de 2022, realizou-se um levantamento sobre a regulamentação vigente nos 21 países latino-americanos incluídos no estudo, em dois níveis: i) existência de legislação sobre prontuários eletrônicos e telessaúde; e ii) tratamento da confidencialidade e do sigilo profissional em prontuários eletrônicos e telessaúde. Uma planilha para extração de dados foi elaborada para cada país. Os dados foram coletados de fontes oficiais disponíveis on-line. Foi realizada uma análise qualitativa das informações, que foram resumidas em tabelas, quando possível. Resultados. O uso dos prontuários eletrônicos é legalmente regulamentado em 16 países. Quanto à telessaúde, 19 países têm legislação sobre essa ferramenta. Todos os países analisados protegem a confidencialidade e o sigilo profissional por meio de regulamentação. No entanto, no contexto da telessaúde, eles são mencionados em 11 países; já no contexto dos prontuários eletrônicos, em apenas 9 países. Conclusões. Desde o início dos anos 2000, a América Latina vem avançando em relação à legislação sobre ferramentas digitais na atenção à saúde, como prontuários eletrônicos e telessaúde. Há também interesse nas questões éticas relacionadas ao uso de prontuários eletrônicos e telessaúde, especialmente em relação à confidencialidade e ao sigilo profissional, embora esses aspectos precisem ser reforçados na saúde digital.