A Framework to Develop an Immersive Virtual Reality Simulation Tool for Postpartum Hemorrhage Management Nurse Training.

ABSTRACT: Postpartum hemorrhage (PPH) is the leading cause of maternal mortality and morbidity. Effective nurse training for PPH management can reduce negative health impacts on childbearing women. This article discusses a framework for the development of an innovative immersive virtual reality simulator for PPH management training. The simulator should consist of: 1) a virtual world, including virtual physical and social environments, and simulated patients, and 2) a smart platform, providing automatic instructions, adaptive scenarios, and intelligent performance debriefing and evaluations. This simulator will provide a realistic virtual environment for nurses to practice PPH management and promote women's health.

User-Centered Design for Designing and Evaluating a Prototype of a Data Collection Tool to Submit Information About Incidents of Violence Against Sex Workers: Multiple Methods Approach.

Background: Sex workers face an epidemic of violence in the United States. However, violence against sex workers in the United States is underreported. Sex workers hesitate to report it to the police because they are frequently punished themselves; therefore, an alternative for reporting is needed. Objective: We aim to apply human-centered design methods to create and evaluate the usability of the prototype interface for ReportVASW (violence against sex worker, VASW) and identify opportunities for improvement. Methods: This study explores ways to improve the prototype of ReportVASW, with particular attention to ways to improve the data collection tool. Evaluation methods included cognitive walkthrough, system usability scale, and heuristic evaluation. Results: End users were enthusiastic about the idea of a website to document violence against sex workers. ReportVASW scored 90 on the system usability scale. The tool scored neutral on consistency, and all other responses were positive toward the app, with most being strong. Conclusions: Many opportunities to improve the interface were identified. Multiple methods identified multiple issues to address. Most changes are not overly complex, and the majority were aesthetic or minor. Further development of the ReportVASW data collection tool is worth pursuing.

XML Data and Knowledge-Encoding Structure for a Web-Based and Mobile Antenatal Clinical Decision Support System: Development Study.

BACKGROUND: Displeasure with the functionality of clinical decision support systems (CDSSs) is considered the primary challenge in CDSS development. A major difficulty in CDSS design is matching the functionality to the desired and actual clinical workflow. Computer-interpretable guidelines (CIGs) are used to formalize medical knowledge in clinical practice guidelines (CPGs) in a computable language. However, existing CIG frameworks require a specific interpreter for each CIG language, hindering the ease of implementation and interoperability. OBJECTIVE: This paper aims to describe a different approach to the representation of clinical knowledge and data. We intended to change the clinician's perception of a CDSS with sufficient expressivity of the representation while maintaining a small communication and software footprint for both a web application and a mobile app. This approach was originally intended to create a readable and minimal syntax for a web CDSS and future mobile app for antenatal care guidelines with improved human-computer interaction and enhanced usability by aligning the system behavior with clinical workflow. METHODS: We designed and implemented an architecture design for our CDSS, which uses the model-view-controller (MVC) architecture and a knowledge engine in the MVC architecture based on XML. The knowledge engine design also integrated the requirement of matching clinical care workflow that was desired in the CDSS. For this component of the design task, we used a work ontology analysis of the CPGs for antenatal care in our particular target clinical settings. RESULTS: In comparison to other common CIGs used for CDSSs, our XML approach can be used to take advantage of the flexible format of XML to facilitate the electronic sharing of structured data. More importantly, we can take advantage of its flexibility to standardize CIG structure design in a low-level specification language that is ubiquitous, universal, computationally efficient, integrable with web technologies, and human readable. CONCLUSIONS: Our knowledge representation framework incorporates fundamental elements of other CIGs used in CDSSs in medicine and proved adequate to encode a number of antenatal health care CPGs and their associated clinical workflows. The framework appears general enough to be used with other CPGs in medicine. XML proved to be a language expressive enough to describe planning problems in a computable form and restrictive and expressive enough to implement in a clinical system. It can also be effective for mobile apps, where intermittent communication requires a small footprint and an autonomous app. This approach can be used to incorporate overlapping capabilities of more specialized CIGs in medicine.

Percepción de brechas y oportunidades en eSalud de estudiantes de último año de Medicina en Colombia

Introducción: En los últimos años la explosión de dispositivos con acceso a internet en el mundo ha presentado una oportunidad para el desarrollo de intervenciones en salud. Métodos: Se realizó un estudio observacional transversal de tipo descriptivo; se clasificaron las propuestas de innovación presentadas por estudiantes de último año de medicina como trabajo final de un curso de eSalud. Los proyectos se clasificaron en tres dimensiones: grupo poblacional, problema de salud a resolver y tipo de intervención de salud digital. Resultados: Se analizaron 86 proyectos entre los años 2017 y 2020. El 80,2 % se orienta a la población general, seguidos por la gestante (10,4 %), la infantil (8,14 %) y la geriátrica (1,2 %). El 36 % de los proyectos no mencionaban una condición particular de salud; el 12,8 % se dedicó a la salud sexual y reproductiva; el 10,4 % a las enfermedades cardiovasculares; el 9,3 % a la salud mental y el 4,65 % a aspectos de crecimiento y desarrollo. El 59,3 % de los proyectos se dirigía a apoyar las actividades del prestador de servicios de salud; el 34,9 % estaba orientado hacia las necesidades de los usuarios de los sistemas de salud y el 5,9 % se enfocó en los servicios de datos. Conclusiones: La percepción colectiva de los estudiantes refleja la oportunidad de fortalecer la atención primaria en salud mediante el uso de las tecnologías de la información y las comunicaciones, con énfasis en las poblaciones vulnerables. Los estudiantes empiezan a identificar los servicios de datos como oportunidad de intervención.

Introduction: In recent years, the explosion of devices with Internet access in the world has presented an opportunity for the development of health interventions. Methods: A descriptive cross-sectional observational study was carried out. Innovation proposals submitted by last-year medical students were classified as the final project of an eHealth course. The projects were classified into three dimensions: population group, health problem to be solved, and type of digital health intervention. Results: Eighty-six projects were analyzed from 2017 to 2020. 80.2% were aimed at the general population, followed by pregnant women (10.4%), children (8.14%) and geriatrics (1, 2 %). 36% of the projects did not mention a particular health condition; 12.8% was dedicated to sexual and reproductive health; 10.4% to cardiovascular diseases; 9.3% to mental health and 4.65% to aspects of growth and development. 59.3% of the projects were aimed at supporting the activities of the health service provider; 34.9% were oriented towards the needs of users of health systems and 5.9% focused on data services. Conclusions: The collective perception of the students reflects the opportunity to strengthen primary health care through the use of information and communication technologies, with emphasis on vulnerable populations. Students begin to identify data services as an opportunity for intervention.

Caracterización de un corpus extraído de historias clínicas electrónicas de maternas a través de técnicas de procesamiento de lenguaje natural / Characterization of a corpus extracted from maternal electronic health records through natural language processing techniques

Este artículo tuvo como propósito caracterizar el texto libre disponible en una historia clínica electrónica de una institución orientada a la atención de pacientes en embarazo. La historia clínica electrónica, más que ser un repositorio de datos, se ha convertido en un sistema de soporte a la toma de decisiones clínicas. Sin embargo, debido al alto volumen de información y a que parte de la información clave de las historias clínicas electrónicas está en forma de texto libre, utilizar todo el potencial que ofrece la información de la historia clínica electrónica para mejorar la toma de decisiones clínicas requiere el apoyo de métodos de minería de texto y procesamiento de lenguaje natural. Particularmente, en el área de Ginecología y Obstetricia, la implementación de métodos del procesamiento de lenguaje natural podría ayudar a agilizar la identificación de factores asociados al riesgo materno. A pesar de esto, en la literatura no se registran trabajos que integren técnicas de procesamiento de lenguaje natural en las historias clínicas electrónicas asociadas al seguimiento materno en idioma español. En este trabajo se obtuvieron 659 789 tokens mediante los métodos de minería de texto, un diccionario con palabras únicas dado por 7 334 tokens y se estudiaron los n-grams más frecuentes. Se generó una caracterización con una arquitectura de red neuronal CBOW (continuos bag of words) para la incrustación de palabras. Utilizando algoritmos de clustering se obtuvo evidencia que indica que palabras cercanas en el espacio de incrustación de 300 dimensiones pueden llegar a representar asociaciones referentes a tipos de pacientes, o agrupar palabras similares, incluyendo palabras escritas con errores ortográficos. El corpus generado y los resultados encontrados sientan las bases para trabajos futuros en la detección de entidades (síntomas, signos, diagnósticos, tratamientos), la corrección de errores ortográficos y las relaciones semánticas entre palabras para generar resúmenes de historias clínicas o asistir el seguimiento de las maternas mediante la revisión automatizada de la historia clínica electrónica(AU)

The purpose of this article was to characterize the free text available in an electronic health record of an institution, directed at the care of patients in pregnancy. More than being a data repository, the electronic health record (HCE) has become a clinical decision support system (CDSS). However, due to the high volume of information, as some of the key information in EHR is in free text form, using the full potential that EHR information offers to improve clinical decision-making requires the support of methods of text mining and natural language processing (PLN). Particularly in the area of gynecology and obstetrics, the implementation of PLN methods could help speed up the identification of factors associated with maternal risk. Despite this, in the literature there are no papers that integrate PLN techniques in EHR associated with maternal follow-up in Spanish. Taking into account this knowledge gap, in this work a corpus was generated and characterized from the EHRs of a gynecology and obstetrics service characterized by treating high-risk maternal patients. PLN and text mining methods were implemented on the data, obtaining 659 789 tokens and a dictionary with unique words given by 7 334 tokens. The characterization of the data was developed from the identification of the most frequent words and n-grams and a vector representation of embedding words in a 300-dimensional space was performed using a CBOW (Continuous Bag of Words) neural network architecture. The embedding of words allowed to verify by means of Clustering algorithms, that the words associated to the same group can come to represent associations referring to types of patients, or group similar words, including words written with spelling errors. The corpus generated and the results found lay the foundations for future work in the detection of entities (symptoms, signs, diagnoses, treatments), correction of spelling errors and semantic relationships between words to generate summaries of medical records or assist the follow-up of mothers through the automated review of the electronic health record(AU)

Arquetipos, terminologías e interoperabilidad semántica en salud / Archetypes, terminologies and semantic interoperability in health

La falta de aplicación de estándares repercute en lo negativo en la calidad de la prestación de servicios de salud, lo cual se ve reflejado en un alto porcentaje de errores médicos prevenibles, que son causados por la falta de acceso inmediato a la información de salud. Es por esto que en la actualidad, existe una necesidad hacia sistemas distribuidos e interconectados, que favorezcan la representación y comunicación de los sistemas de historia clínica electrónica, de tal forma que permitan la interoperabilidad. Es aquí donde la arquitectura de modelo dual surge como una solución a los problemas clásicos de evolución y mantenimiento de los sistemas de información y por consiguiente, como la piedra angular para alcanzar la llamada interoperabilidad semántica. La interoperabilidad es la clave para la atención efectiva en el ámbito de la salud ya que aumenta la calidad de la atención, reduce los costos, y mejora los servicios, lo que se traduce en una atención más segura y eficiente. En la presente revisión, se pretende como objetivo, describir los elementos más importantes a la hora de expresar la información clínica, como son las terminologías para codificar la información, un modelo de referencia para expresar las características generales de los componentes de un registro clínico, y de unos arquetipos que definen los conceptos clínicos presentes; todos estos como componentes indispensables para alcanzar dicha interoperabilidad.

The lack of application of standards has a negative effect on the quality of health service provision which is shown in the high percentage of preventable medical errors that are caused by lack of immediate access to health information. That is the reason why it is necessary today to move towards distributed and interconnected systems favoring representation and communication of electronic health record systems so that they allow interoperability. This is the moment when the dual model architecture emerges as a solution to the clasic problems of evolution and maintenance of the information systems and consequently, as a milestone to reach the so called semantic interoperability. Interoperability is the key to effective care in health since it increases the quality of care, reduces costs and improves services. All the above-mentioned brings more efficient and safer care. The present literature review was aimed at describing the most important elements to express clinical information such as terminologies to coding information, a reference model to express the general characteristics of the clinical register components and those of archetypes that define the present clinical concepts. All of them are indispensable elements to reach interoperability.

Terminologies and classification systems in biomedical sciences

Standards terminologies emerged as an attempt to reduce the diversity terminology in scientific languages, facilitating good communication, which is the basis of all scientific research. This review explains principles and applications associated with terminologies and classification systems focusing mainly on the field of biomedical sciences. The research was conducted on scientific databases, books and network using the keywords: Terminologies, Classification systems, Medical Informatics, Electronic Health Records systems, Interoperability, Ontologies and Bio-ontologies. This review is intended to explain that terminologies facilitate good communication, reducing terminology diversity and they are not static systems. They can "evolve" to more complex structures like biomedical ontologies, with the aim of being used with multiple purposes beginning with the efficient transfer of information, to the processing of information as a result of biological research for its understanding(AU)

Las terminologías surgieron como un intento de reducir la diversidad terminológica en el lenguaje científico, facilitando una buena comunicación, que es la base de toda investigación científica. Esta revisión explica los principios y las aplicaciones asociadas con las terminologías y los sistemas de clasificación, centrándose en el campo de las ciencias biomédicas. La investigación fue realizada en bases de datos científicas, libros e internet, utilizando las palabras clave: Terminología, sistemas de clasificación, interoperabilidad, ontologías y Bio-ontologías. Esta revisión tiene por objeto explicar que las terminologías facilitan una buena comunicación, reduciendo la diversidad terminológica y además explicando que no son sistemas estáticos. Ellas pueden evolucionar para formar estructuras complejas como ontologías biomédicas, con el objetivo de ser utilizadas con múltiples propósitos que comienzan con la transferencia eficiente de la información, hasta el procesamiento de información obtenida de la investigación biológica para su comprensión(AU)