Building consensus on common features and interoperability use cases for community health information systems: a Delphi study.

INTRODUCTION: Information systems for community health have become increasingly sophisticated and evidence-based in the last decade and they are now the most widely used health information systems in many low-income and middle-income countries. This study aimed to establish consensus regarding key features and interoperability priorities for community health information systems (CHISs). METHODS: A Delphi study was conducted among a systematically selected panel of CHIS experts. This impressive pool of experts represented a range of leading global health institutions, with gender and regional balance as well as diversity in their areas of expertise. Through five rounds of iterative surveys and follow-up interviews, the experts established a high degree of consensus. We supplemented the Delphi study findings with a series of focus group discussions with 10 community health worker (CHW) leaders. RESULTS: CHISs today are expected to adapt to a wide range of local contextual requirements and to support and improve care delivery. While once associated with a single role type (CHWs), these systems are now expected to engage other end users, including patients, supervisors, clinicians and data managers. Of 30 WHO-classified digital health interventions for care providers, experts identified 23 (77%) as being important for CHISs. Case management and care coordination features accounted for more than one-third (14 of 37, 38%) of the core features expected of CHISs today, a higher proportion than any other category. The highest priority use cases for interoperability include CHIS to health management information system monthly reporting and CHIS to electronic medical record referrals. CONCLUSION: CHISs today are expected to be feature-rich, to support a range of user roles in community health systems, and to be highly adaptable to local contextual requirements. Future interoperability efforts, such as CHISs in general, are expected not only to move data efficiently but to strengthen community health systems in ways that measurably improve care.

A cross-sectional survey on awareness of cancer risk factors, information sources and health behaviors for cancer prevention in Japan.

Due to recent increases in cancer burden worldwide, we investigated current awareness of cancer risk factors and the association between information sources and health behaviors for cancer prevention in Japan. A nationwide representative sample aged 20 years or older (563 men and 653 women) responded to a questionnaire as part of a population-based survey in December 2018. Tobacco smoking (55.7% of the mean attributable fraction of cancer risk overall) and cancer-causing infection (52.0%) were regarded more highly than other lifestyle factors as causes of cancer (obesity [36.6%], physical inactivity [31.9%], unbalanced diet [30.9%], and alcohol consumption [26.2%]). The association between information sources and health behaviors for cancer prevention was evaluated using a logistic regression model. The websites of public institutions, and health professionals were associated with a broad range of health behaviors including improving diet, exercise, cancer screening/health check-up, and abstinence from smoking/drinking. Among sources of print media, positive associations were observed between books and improving diet/exercise, brochures and cancer screening/health check-up, and advertisements and abstinence from smoking/drinking. A strategic health communication approach that utilizes various information sources and delivery channels is needed to inform the public about cancer prevention and to motivate risk-reducing behaviors in the population.

Maturity assessment of Kenya's health information system interoperability readiness.

BACKGROUND: The use of digital technology in healthcare promises to improve quality of care and reduce costs over time. This promise will be difficult to attain without interoperability: facilitating seamless health information exchange between the deployed digital health information systems (HIS). OBJECTIVE: To determine the maturity readiness of the interoperability capacity of Kenya's HIS. METHODS: We used the HIS Interoperability Maturity Toolkit, developed by MEASURE Evaluation and the Health Data Collaborative's Digital Health and Interoperability Working Group. The assessment was undertaken by eHealth stakeholder representatives primarily from the Ministry of Health's Digital Health Technical Working Group. The toolkit focused on three major domains: leadership and governance, human resources and technology. RESULTS: Most domains are at the lowest two levels of maturity: nascent or emerging. At the nascent level, HIS activities happen by chance or represent isolated, ad hoc efforts. An emerging maturity level characterises a system with defined HIS processes and structures. However, such processes are not systematically documented and lack ongoing monitoring mechanisms. CONCLUSION: None of the domains had a maturity level greater than level 2 (emerging). The subdomains of governance structures for HIS, defined national enterprise architecture for HIS, defined technical standards for data exchange, nationwide communication network infrastructure, and capacity for operations and maintenance of hardware attained higher maturity levels. These findings are similar to those from interoperability maturity assessments done in Ghana and Uganda.

Importancia del uso de sistemas de información en la automatización de historiales clínicos, una revisión sistemática / Importance of Use of Information Systems in the Automation of Medical Records, a Systematic Review

Los sistemas de información en los servicios de salud han contribuido en los procesos de automatización de historiales clínicos, desempeñando un papel importante en la atención médica. El objetivo de esta revisión ha sido identificar la importancia de los sistemas de información para la automatización de historiales clínicos y las herramientas usadas para su implementación. Se revisaron artículos de revistas indexadas en base de datos bibligráficas como: IEEE Digital Library, ScienceDirect, Scielo, Google Scholar con la finalidad de tener una mejor clasificación de información que aportara al desarrollo del contenido estudiado. Se identificó que los sistemas de información mejoran la comunicación médico-paciente, aceleran procesos de atención médica, reducen costos y tiempo. Los sistemas de información son importantes para la automatización de historiales clínicas, garantizado mejoras en el proceso de atención al paciente en los establecimientos de salud(AU)

Information systems in health services have contributed to the automation of medical records, playing an important role in medical care. The objective of this review was to identify the importance of information systems for the automation of medical records and the tools used for their implementation. Articles from journals indexed in bibliographic databases such as: IEEE Digital Library, ScienceDirect, Scielo, Google Scholar have been reviewed in order to have a better classification of information that contributes to the improvement of our interest topic. It has been identified that these information systems increase doctor-patient communication, speed up medical care processes, reduce costs and time. Information systems are important for the automation of medical records, guaranteeing advances in the patient care process in health establishments(AU)

Intelligent machines and mental health in the era of COVID-19.

The idea of a network of small devices that would be able to connect each other, appeared in the early 80s. In a prophetic article, Mark Weiser,1 described such a connection, that it is now known under the term of Internet of Things (IoT). In a broadest sense, the term IoT encompasses everything connected to the internet, but it is increasingly being used to define objects that "talk" to each other, creating a network from simple sensors to smartphones and wearables connected. During the recent years this network of communicating devices has been combined with other technological achievements, and particularly with the Virtual Reality (VR)2 and the Artificial Intelligence (AI).3 The emerge of COVID-19 pandemic in 2019, resulted to the poor response and healthcare failures of many countries globally.4 One of the main reasons for such a failure, was the inability of accurate data collection from different sources. Apparently, it was the first time, humanity realized the need for massive amounts of heterogeneous data to be collected, interpreted, and shared. Amid the ongoing COVID-19 pandemic, several innovators and public authorities are looking to leverage IoT tools to reduce the burden on the healthcare systems.5 Mental health is one of the areas that seems to benefit the most of such technologies. A significant decrease of the total amount of ER visits and a dramatic increase of internet access from the patients and care givers along to the development of applications for mental health issues, followed the outbreak of SARS-CoV-2.6 Such technologies proved to be efficient to help mentally ill patients and pioneer the path in the future. Probably the most obvious use of these emerged technologies is the improvement of the telehealth options. Patients who suffer from mental illness face significant problems towards the continuity of care during the crisis.7 Nonetheless, they usually have other health problems, that deprive them from an equitable health care provision. Improved telehealth platforms can give them a single point access to address all their problems. The use of electronic health records can reduce the fragmentary health services and improve the outcome.8 However, this is only the beginning. The COVID-19 crisis and the subsequent social isolation, to reduce both the contamination and the spread of the disease, highlighted the necessity for providing accurate and secure diagnoses and treatments from a safe distance. Virtual reality combined with IoT and AI technologies seem to be a reliable alternative to the classic physical and mental examination and treatment in many areas of mental and neurological diseases.2 These novel techniques can spot the early signs and detect mental illnesses with high accuracy. However, caution and more work are required to bridge the space between these recently thrived technologies and mental health care.7 It is worth mentioning, that internet-oriented health care procedures can also help to reduce the gaps caused by the stigma of mental illness. For example, the development of AI chatbots (an application used to chat directly with a human) can alleviate the fears of judgment of the help seeking persons and provide the professionals with a supplemental support toward improved services to their patients.9 A final remark for conclusion. Humanity is more and more depended to the "intelligent" machines. However, we must not forget that we humans are responsible to set the rules of such co-existence.

Maternal and neonatal data collection systems in low- and middle-income countries for maternal vaccines active safety surveillance systems: A scoping review.

BACKGROUND: Most post-licensure vaccine pharmacovigilance in low- and middle-income countries (LMICs) are passive reporting systems. These have limited utility for maternal immunization pharmacovigilance in LMIC settings and need to be supplemented with active surveillance. Our study's main objective was to identify existing perinatal data collection systems in LMICs that collect individual information on maternal and neonatal health outcomes and could be developed to inform active safety surveillance of novel vaccines for use during pregnancy. METHODS: A scoping review was performed following the Arksey and O'Malley six-stage approach. We included studies describing electronic or mixed paper-electronic data collection systems in LMICs, including research networks, electronic medical records, and custom software platforms for health information systems. Medline PubMed, EMBASE, Global Health, Cochrane Library, LILACS, Bibliography of Asian Studies (BAS), and CINAHL were searched through August 2019. We also searched grey literature including through Google and websites of existing relevant perinatal data collection systems, as well as contacted authors of key studies and experts in the field to validate the information and identify additional sources of relevant unpublished information. RESULTS: A total of 11,817 records were identified. The full texts of 264 records describing 96 data collection systems were assessed for eligibility. Eight perinatal data collection systems met our inclusion criteria: Global Network's Maternal Newborn Health Registry, International Network for the Demographic Evaluation of Populations and their Health; Perinatal Informatic System; Pregnancy Exposure Registry & Birth Defects Surveillance; SmartCare; Open Medical Record System; Open Smart Register Platform and District Health Information Software 2. These selected systems were qualitatively characterized according to seven different domains: governance; system design; system management; data management; data sources, outcomes and data quality. CONCLUSION: This review provides a list of active maternal and neonatal data collection systems in LMICs and their characteristics as well as their outreach, strengths, and limitations. Findings could potentially help further understand where to obtain population-based high-quality information on outcomes to inform the conduct of maternal immunization active vaccine safety surveillance activities and research in LMICs.

[Health Data Hub: Why and how?] / Le Health Data Hub (suite) - Pourquoi ? Comment ?

TITLE: Le Health Data Hub (suite) - Pourquoi ? Comment ? ABSTRACT: Dans le monde de la recherche et de la santé publique, un consensus existe pour considérer que les données de santé constituent une ressource extrêmement précieuse pour de multiples usages, et qu'il convient d'en faciliter l'accès et le partage. Dans ce domaine, la France dispose de nombreux atouts, notamment de bases de données d'ampleur et de richesse sans doute uniques. Depuis quelques années, les pouvoirs publics ont pris conscience des enjeux autour de ces données et ont mis en place un dispositif technique, légal et réglementaire pour y faire face : le Système national des données de santé (SNDS) accompagné de la Plateforme des données de santé (PDS), plus communément appelée Health Data Hub (HDH). Cette plateforme est une infrastructure officiellement créée par un arrêté ministériel du 30 novembre 2019, destinée à faciliter l'accès et l'utilisation des données de santé afin de favoriser la recherche. On ne peut qu'applaudir une telle initiative qui constitue un progrès majeur et ouvre de nombreuses perspectives pour la recherche et la santé publique. Cependant, tel qu'il est conçu, le HDH pose divers problèmes qui amènent à questionner ses orientations actuelles.

An Education Framework for Effective Implementation of a Health Information System: Scoping Review.

BACKGROUND: To optimize their use of a new Health Information System (HIS), supporting health care providers require effective HIS education. Failure to provide this education can significantly hinder an organization's HIS implementation and sustainability efforts. OBJECTIVE: The aim of this review is to understand the most effective educational strategies and approaches to enable health care providers to optimally use an HIS. METHODS: Ovid MEDLINE, Ovid Embase, EBSCO Cumulative Index to Nursing and Allied Health Literature, and EBSCO Education Resources Information Center were searched to identify relevant papers. Relevant studies were systematically reviewed and analyzed using a qualitative thematic analysis approach. RESULTS: Of the 3539 studies screened, 17 were included for data extraction. The literature on the most effective approaches to enable health care providers to optimally use an HIS emphasized the importance of investing in engaging and understanding learners in the clinical context, maximizing the transfer of learning to care, and designing continuous and agile evaluation to meet the emerging demands of the clinical environment. CONCLUSIONS: This review supports the advancement of a new HIS learning framework that organizational leaders and educators can use to guide HIS education design and development. Future research should examine how this framework can be translated into practice.

Estudo da qualidade dos Dados do Painel COVID-19 para crianças, adolescente e jovens, Espírito Santo ­ Brasil, 2020 / A study assessing the quality of the COVID-19 Panel Data for children, adolescents and young individuals, Espírito Santo ­ Brazil, 2020 / Estudio de calidad de datos del Panel COVID-19 para niños, adolescentes y jóvenes, Espírito Santo ­ Brasil, 2020

Objetivo: descrever a completude dos dados e avaliar a qualidade do Banco de dados do Painel COVID-19 no Espírito Santo em 2020, quanto à completude de suas variáveis, bem como analisar a confirmação da doença e sua evolução por crianças, adolescentes e jovens. Métodos: estudo descritivo exploratório. A completude no preenchimento da ficha no Painel COVID-19 foi classificada como excelente (menos de 5% de preenchimento incompleto), bom (5% a 10%), regular (10% a 20%), ruim (20% a 50%) ou muito ruim (50% ou mais). Resultados: observou-se qualidade regular para o critério de confirmação (16%), ruim para a classificação da doença (44%) e status de notificação (30%) e muito ruim para a evolução (79%). Quanto às variáveis epidemiológicas, destaca-se a variável raça/cor da pele com completude regular (17%). Conclusão e implicações para a prática: é necessário educação permanente dos profissionais para o preenchimento dos dados de forma correta. Tratando-se de uma pandemia por um vírus novo, esses dados devem estar disponíveis imediatamente, e com qualidade para que medidas de controle possam ser adotadas

Objective: to describe the completeness of the data and evaluate the quality of the COVID-19 Panel Database in Espírito Santo in 2020, as to the completeness of its variables, as well as to analyze the confirmation of the disease and its evolution by children, adolescents and young people. Methods: exploratory descriptive study. Completeness of filling in the form on the COVID-19 Panel was classified as excellent (less than 5% incomplete), good (5% to 10%), fair (10% to 20%), poor (20% to 50%) or very bad (50% or more). Results: regular quality was observed for the confirmation criterion (16%), poor for the classification of the disease (44%) and notification status (30%) and very poor for the evolution (79%). Regarding the epidemiological variables, the race-skin color variable with regular completeness (17%) stands out. Conclusion and implications for the practice: permanent education of professionals is necessary to fill in the data correctly. in the case of a pandemic due to a new virus, these data must be available immediately, and with quality so that control measures can be adopted

Objetivo: describir la exhaustividad de los datos y evaluar la calidad de la Base de Datos Panel COVID-19 en Espírito Santo en 2020, en cuanto a la exhaustividad de sus variables, así como analizar la confirmación de la enfermedad y su evolución en niños, adolescentes y jóvenes. Métodos: estudio descriptivo exploratorio. La exhaustividad al completar el formulario en el Panel COVID-19 se clasificó como excelente (menos del 5% incompleto), buena (5% a 10%), regular (10% a 20%), deficiente (20% a 50%) o muy mala (50% o más). Resultados: se observó calidad regular para el criterio de confirmación (16%), mala para la clasificación de la enfermedad (44%) y estado de notificación (30%) y muy mala para la evolución (79%). En cuanto a las variables epidemiológicas, se destaca la variable raza-color de piel con exhaustividad regular (17%). Conclusión e implicaciones para la práctica: es necesaria la formación permanente de los profesionales para completar correctamente los datos. En el caso de una pandemia por un nuevo virus, estos datos deben estar disponibles de manera inmediata y con calidad para que se puedan adoptar medidas de control

Improving quality and use of routine health information system data in low- and middle-income countries: A scoping review.

BACKGROUND: A routine health information system is one of the essential components of a health system. Interventions to improve routine health information system data quality and use for decision-making in low- and middle-income countries differ in design, methods, and scope. There have been limited efforts to synthesise the knowledge across the currently available intervention studies. Thus, this scoping review synthesised published results from interventions that aimed at improving data quality and use in routine health information systems in low- and middle-income countries. METHOD: We included articles on intervention studies that aimed to improve data quality and use within routine health information systems in low- and middle-income countries, published in English from January 2008 to February 2020. We searched the literature in the databases Medline/PubMed, Web of Science, Embase, and Global Health. After a meticulous screening, we identified 20 articles on data quality and 16 on data use. We prepared and presented the results as a narrative. RESULTS: Most of the studies were from Sub-Saharan Africa and designed as case studies. Interventions enhancing the quality of data targeted health facilities and staff within districts, and district health managers for improved data use. Combinations of technology enhancement along with capacity building activities, and data quality assessment and feedback system were found useful in improving data quality. Interventions facilitating data availability combined with technology enhancement increased the use of data for planning. CONCLUSION: The studies in this scoping review showed that a combination of interventions, addressing both behavioural and technical factors, improved data quality and use. Interventions addressing organisational factors were non-existent, but these factors were reported to pose challenges to the implementation and performance of reported interventions.

Routine Health Information System (RHIS) improvements for strengthened health system management.

BACKGROUND: A well-functioning routine health information system (RHIS) can provide the information needed for health system management, for governance, accountability, planning, policy making, surveillance and quality improvement, but poor information support has been identified as a major obstacle for improving health system management. OBJECTIVES: To assess the effects of interventions to improve routine health information systems in terms of RHIS performance, and also, in terms of improved health system management performance, and improved patient and population health outcomes. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library, MEDLINE Ovid and Embase Ovid in May 2019. We searched Global Health, Ovid and PsycInfo in April 2016. In January 2020 we searched for grey literature in the Grey Literature Report and in OpenGrey, and for ongoing trials using the International Clinical Trials Registry Platform (ICTRP) and ClinicalTrials.gov. In October 2019 we also did a cited reference search using Web of Science, and a 'similar articles' search in PubMed. SELECTION CRITERIA: Randomised and non-randomised trials, controlled before-after studies and time-series studies comparing routine health information system interventions, with controls, in primary, hospital or community health care settings. Participants included clinical staff and management, district management and community health workers using routine information systems. DATA COLLECTION AND ANALYSIS: Two authors independently reviewed records to identify studies for inclusion, extracted data from the included studies and assessed the risk of bias. Interventions and outcomes were too varied across studies to allow for pooled risk analysis. We present a 'Summary of findings' table for each intervention comparisons broadly categorised into Technical and Organisational (or a combination), and report outcomes on data quality and service quality. We used the GRADE approach to assess the certainty of the evidence. MAIN RESULTS: We included six studies: four cluster randomised trials and two controlled before-after studies, from Africa and South America. Three studies evaluated technical interventions, one study evaluated an organisational intervention, and two studies evaluated a combination of technical and organisational interventions. Four studies reported on data quality and six studies reported on service quality. In terms of data quality, a web-based electronic TB laboratory information system probably reduces the length of time to reporting of TB test results, and probably reduces the overall rate of recording errors of TB test results, compared to a paper-based system (moderate certainty evidence). We are uncertain about the effect of the electronic laboratory information system on the recording rate of serious (misidentification) errors for TB test results compared to a paper-based system (very low certainty evidence). Misidentification errors are inaccuracies in transferring test results between an electronic register and patients' clinical charts. We are also uncertain about the effect of the intervention on service quality (timeliness of starting or changing a patient's TB treatment) (very low certainty evidence). A hand-held electronic device probably improves the length of time to report TB test results, and probably reduces the total frequency of recording errors in TB test results between the laboratory notebook and the electronic information record system, compared to a paper-based system (moderate-certainty evidence). We are, however, uncertain about the effect of the intervention on the frequency of serious (misidentification) errors in recording between the laboratory notebook and the electronic information record, compared to a paper-based system (very low certainty evidence). We are uncertain about the effect of a hospital electronic health information system on service quality (length of time outpatients spend at hospital, length of hospital stay, and hospital revenue collection), compared to a paper-based system (very low certainty evidence). High-intensity brief text messaging (SMS) may make little or no difference to data quality (in terms of completeness of documentation of pregnancy outcomes), compared to low-intensity brief text messaging (low-certainty evidence). We are uncertain about the effect of electronic drug stock notification (with either data management support or product transfer support) on service quality (in terms of transporting stock and stock levels), compared to paper-based stock notification (very low certainty evidence). We are uncertain about the effect of health information strengthening (where it is part of comprehensive service quality improvement intervention) on service quality (health worker motivation, receipt of training by health workers, health information index scores, quality of clinical observation of children and adults) (very low certainty evidence). AUTHORS' CONCLUSIONS: The review indicates mixed effects of mainly technical interventions to improve data quality, with gaps in evidence on interventions aimed at enhancing data-informed health system management. There is a gap in interventions studying information support beyond clinical management, such as for human resources, finances, drug supply and governance. We need to have a better understanding of the causal mechanisms by which information support may affect change in management decision-making, to inform robust intervention design and evaluation methods.

Public health reporting and outbreak response: synergies with evolving clinical standards for interoperability.

Public health needs up-to-date information for surveillance and response. As healthcare application programming interfaces become widely available, a novel data gathering mechanism could provide public health with critical information in a timely fashion to respond to a fast-moving epidemic. In this article, we extrapolate from our experiences using a Fast Healthcare Interoperability Resource-based architecture for infectious disease surveillance for sexually transmitted diseases to its application to gather case information for an outbreak. One of the challenges with a fast-moving outbreak is to accurately assess its demand on healthcare resources, since information specific to comorbidities is often not available. These comorbidities are often associated with poor prognosis and higher resource utilization. If the comorbidity data and other clinical information were readily available to public health workers, they could better address community disruption and manage healthcare resources. The use of FHIR resources available through application programming and filtered through tools such as described herein will give public health the flexibility needed to investigate rapidly emerging disease while protecting patient privacy.

Effect and feasibility of district level scale up of maternal, newborn and child health interventions in Pakistan: a quasi-experimental study.

INTRODUCTION: Pakistan has a high burden of maternal, newborn and child morbidity and mortality. Several factors including weak scale-up of evidence-based interventions within the existing health system; lack of community awareness regarding health conditions; and poverty contribute to poor outcomes. Deaths and morbidity are largely preventable if a combination of community and facility-based interventions are rolled out at scale. METHODS AND ANALYSIS: Umeed-e-Nau (UeN) (New Hope) project aims is to improve maternal, newborn and child health (MNCH) in eight high-burden districts of Pakistan by scaling up of evidence-based interventions. The project will assess interventions focused on, first, improving the quality of MNCH care at primary level and secondary level. Second, interventions targeting demand generation such as community mobilisation, creating awareness of healthy practices and expanding coverage of outreach services will be evaluated. Third, we will also evaluate interventions targeting the improvement in quality of routine health information and promotion of use of the data for decision-making. Hypothesis of the project is that roll out of evidence-based interventions at scale will lead to at least 20% reduction in perinatal mortality and 30% decrease in diarrhoea and pneumonia case fatality in the target districts whereas two intervention groups will serve as internal controls. Monitoring and evaluation of the programme will be undertaken through conducting periodical population level surveys and quality of care assessments. Descriptive and multivariate analytical methods will be used for assessing the association between different factors, and difference in difference estimates will be used to assess the impact of the intervention on outcomes. ETHICS AND DISSEMINATION: The ethics approval was obtained from the Aga Khan University Ethics Review Committee. The findings of the project will be shared with relevant stakeholders and disseminated through open access peer-reviewed journal articles. TRIAL REGISTRATION NUMBER: NCT04184544; Pre-results.

Cultural Considerations for Conducting the Health Information National Trends Survey with Micronesian Communities: Lessons from a Qualitative Study.

A critical barrier to addressing health disparities among minorities is the lack of data, particularly on Pacific Islanders. Typically, national health surveillance systems do not have the resources to ensure proper representation of these small population groups. This study reports factors that guided the cultural adaptation and administration of the National Cancer Institute's Health Information Trends National Survey (HINTS) for a United States-dwelling Pacific Islander population in Hawai'i. To adapt the survey, four focus groups were conducted with 32 purposively-selected Micronesian migrants. Themes on health, healthcare barriers, cancer and methods to implement the survey were extracted from the analyses of the focus group narratives. Key cultural factors were identified that impact health practices, including religious and cancer fatalism, racism, health locus of control and other barriers. Using information from the focus group participants, the HINTS questionnaire was modified and the survey was implemented. The survey data provided will inform the future delivery of health promotion strategies for this unique medically underserved population.

Estrategia metodológica para el Cálculo Diferencial e Integral en la carrera Sistemas de Información en Salud / Methodological Strategy for the Differential and Integral Calculus in the career Health Information Systems

Introducción: El Cálculo Diferencial e Integral ha sido tradicionalmente de difícil comprensión por los estudiantes. La introducción de las TIC en la enseñanza de las Matemáticas constituye uno de los lineamientos de esta asignatura. El proceso de enseñanza-aprendizaje de las Matemáticas requiere de la introducción de métodos novedosos como pueden ser los asistentes matemáticos, que desarrollan el aprendizaje a partir de potenciar el rol del estudiante como sujeto central, convirtiéndolo en constructor del conocimiento. Objetivo: Diseñar una Estrategia Metodológica para el desarrollo del Proceso de Enseñanza - Aprendizaje del Cálculo Diferencial e Integral, en la carrera Sistemas de Información en Salud. Material y Método: Se realizó un estudio experimental con los 32 estudiantes de primer año de la carrera de Sistemas de Información en Salud en la Facultad Salvador Allende en el año académico 2018-19. El Grupo de Control recibió las clases a través de la forma tradicional y el Grupo Experimental utilizó el asistente GeoGebra. Resultados: La introducción del GeoGebra, permitió realizar movimientos, transformaciones y cambios en las funciones matemáticas, para contribuir a que los alumnos pudieran llegar a conclusiones válidas y asimilar los nuevos contenidos con mayor facilidad. Conclusiones: La aplicación de esta estrategia contribuye a la obtención de mejores resultados docentes, permite optimizar el tiempo de realización de los problemas, aumentar el número de ejercicios a desarrollar y combinar el trabajo independiente del alumno utilizando las tecnologías(AU)

Introduction: Diferential and Integral Calculus has traditionally been difficult for students to understand. The introduction of ICT in the teaching of Mathematics constitutes one of the guidelines of this subject. The teaching-learning process of Mathematics requires the introduction of novel methods such as mathematical assistants, who develop learning by enhancing the role of the student as a central subject, turning him into a constructor of knowledge. Objective: To design a Methodological Strategy to improve the learning process of Differential and Integral Calculus in Health Information Systems career. Method: An experimental study was carried out with the 32 first-year students of the Health Information Systems degree at the "Salvador Allende" Faculty in the 2018-19 academic year. The Control Group received the classes through the traditional way and the Experimental Group used the GeoGebra assistant. Results: The introduction of GeoGebra allowed movements, transformations and changes in mathematical functions to be made, so that students could reach valid conclusions and assimilate new content more easily. Conclusions: The application of this strategy by means of using technology, contributes to obtain better results, allows optimizing the time of realization of the exercises, increasing the number of them and the independent work of the student(AU)