Customer Centricity in Medical Affairs Needs Human-centric Artificial Intelligence.

The evolution of healthcare, together with the changing behaviour of healthcare professionals, means that medical affairs functions of pharmaceutical organisations are constantly reinventing themselves. The emergence of digital ways of working, expedited by the COVID-19 pandemic, means that pharmaceutical-healthcare relationships are evolving to operate in an increasingly virtual world. The value of the pharmaceutical medical affairs function is dependent on understanding customers' needs and providing the right knowledge at the right time to physicians. This requires a human-centric artificial intelligence (AI) approach for medical affairs, which allows the function to query internal and external data sets in a conversational format and receive timely, accurate and concise intelligence on their customers.

Assessment of Strategies and Epidemiological Characteristics of Tuberculosis in Henan Province, China: Observational Study.

BACKGROUND: In 2005, China established an internet-based Tuberculosis Information Management System (TBIMS) to monitor changes in tuberculosis (TB). Many scholars have conducted epidemiological research using TBIMS; however, few studies assessing control strategies have been performed based on this platform data. Henan province is a high TB incidence area in China where, in addition to following the nationwide TB strategies, a series of local intervention combinations have been implemented. OBJECTIVE: Our study aims to evaluate the impact of nationwide TB intervention combinations on epidemiological changes and determine whether Henan province can achieve the World Health Organization's (WHO) goal of reducing TB incidence by 50% and TB mortality by 75% by the year 2025. METHODS: We used descriptive statistical methods to show the spatial and temporal distribution of pulmonary tuberculosis (PTB) reported to the TBIMS database from 2005 to 2018, and logistic regression analysis was performed to identify the risk factors of bacteriological-positive TB. The dynamic compartmental model and Bayesian melding approach was adopted to estimate the burden of TB under the impact of different TB control policies. RESULTS: In total, 976,526 PTB cases were notified to the TBIMS in Henan in a period of 14 years. Although the overall incidence of PTB declined from 91.4/105 to 58.5/105, and the overall incidence of bacteriological-positive PTB declined from 44.5/105 to 14.7/105, the WHO's 2025 goal could not be met. The distribution of high incidence and poverty-stricken counties were basically overlapped. Men, farmers and herdsmen (in rural areas), and subjects aged ≥60 years were more likely to develop bacteriological-positive PTB. The increasing treatment success for drug-susceptible tuberculosis and multidrug-resistant tuberculosis has not provided the desired reduction in incidence and mortality. CONCLUSIONS: To achieve the targeted goal, while improving the cure rate of TB, new active (rather than passive) detection and intervention strategies should be formulated based on epidemiological characteristics in Henan province.

Developing trustworthy recommendations as part of an urgent response (1-2 weeks): a GRADE concept paper.

OBJECTIVES: The aim of this study is to propose an approach for developing trustworthy recommendations as part of urgent responses (1-2 week) in the clinical, public health, and health systems fields. STUDY DESIGN AND SETTING: We conducted a review of the literature, outlined a draft approach, refined the concept through iterative discussions, a workshop by the Grading of Recommendations Assessment, Development and Evaluation Rapid Guidelines project group, and obtained feedback from the larger Grading of Recommendations Assessment, Development and Evaluation working group. RESULTS: A request for developing recommendations within 2 week is the usual trigger for an urgent response. Although the approach builds on the general principles of trustworthy guideline development, we highlight the following steps: (1) assess the level of urgency; (2) assess feasibility; (3) set up the organizational logistics; (4) specify the question(s); (5) collect the information needed; (6) assess the adequacy of identified information; (7) develop the recommendations using one of the 4 potential approaches: adopt existing recommendations, adapt existing recommendations, develop new recommendations using existing adequate systematic review, or develop new recommendations using expert panel input; and (8) consider an updating plan. CONCLUSION: An urgent response for developing recommendations requires building a cohesive, skilled, and highly motivated multidisciplinary team with the necessary clinical, scientific, and methodological expertise; adapting to shifting needs; complying with the principles of transparency; and properly managing conflicts of interest.

Information specialist collaboration in Europe: collaborative methods, processes, and infrastructure through EUnetHTA.

The history of European health technology assessment (HTA) goes back more than 30 years. Almost as old as HTA agencies themselves is the desire to achieve European collaboration. This gained further impetus with the establishment of the European Network of Health Technology Assessment (EUnetHTA) in 2006. In this context, the field of information management faced specific challenges. Although these services are an integral part of HTA and information specialists play a key role here, this field is often not adequately represented in the HTA agencies within EUnetHTA. Furthermore, the organization of HTA production, including the types of HTAs produced, as well as funding, varies considerably. In order to meet these different conditions, information specialists have created various products and defined processes. With the EUnetHTA guideline, a common methodological understanding for the production of rapid Relative Effectiveness Assessments now exists. Furthermore, the Standard Operating Procedures map the complex information retrieval processes within EUnetHTA in a hands-on manner. The newly established Information Specialist Network (ISN) will in future ensure that information specialists are involved in all EUnetHTA assessments and that the methods are applied consistently in all assessments. In addition, the steering committee of the ISN manages enquiries and can be contacted to discuss methodological issues. Major barriers such as heterogeneity in the daily work of the EUnetHTA members can only be overcome through more collaboration and training.

Health Policy and Privacy Challenges Associated With Digital Technology.

Importance: Digital technology is part of everyday life. Digital interactions generate large amounts of data that can reveal information about the health of individual consumers (the digital health footprint). Objective: Τo describe health privacy challenges associated with digital technology. Design, Setting, and Participants: For this qualitative study, In-depth, semistructured, qualitative interviews were conducted with 26 key experts from diverse fields in the US between January 1 and July 31, 2018. Open-ended questions and hypothetical scenarios were used to identify sources of digital information that contribute to consumers' health-relevant digital footprints and challenges for health privacy. Participants also completed a survey instrument on which they rated the health relatedness of digital data sources. Main Outcomes and Measures: Health policy challenges associated with digital technology based on qualitative responses to expert interviews. Results: Although experts' ratings of digital data sources suggested a possible distinction between health and nonhealth data, qualitative interviews uniformly indicated that all data can be health data, particularly when aggregated across sources and time. Five key characteristics of the digital health footprint were associated with health privacy policy challenges: invisibility (people are unaware of how their data are tracked), inaccuracy (data in the digital health footprint can be inaccurate), immortality (data have no expiration date and are aggregated over time), marketability (data have immense commercial value and are frequently bought and sold), and identifiability (individuals can be readily reidentified and anonymity is nearly impossible to achieve). There are virtually no regulatory structures in the US to protect health privacy in the context of the digital health footprint. Conclusions and Relevance: The findings suggest that a sector-specific approach to digital technology privacy in the US may be associated with inadequate health privacy protections.

Seminario web compartir-escuchar-actuar, COVID-19: el potencial de la salud digital y los sistemas de información para la salud (IS4H) en la lucha contra la pandemia / Webinar Series: share-listen-act, COVID-19: the potential of digital health and Information Systems for Health (IS4H) in the fight against the pandemic

El 1 de junio del 2020 y con 990 personas registradas, la Organización Panamericana de la Salud (OPS) y el Banco Interamericano de Desarrollo (BID), en colaboración con varios aliados y redes (mencionados al final de este documento), lanzaron la serie de seminarios virtuales CompartirEscuchar-Actuar, COVID-19: El potencial de la salud digital y los sistemas de información para la salud (IS4H) en la lucha contra la pandemia.

On June 1, 2020, in collaboration with several partners and networks (mentioned at the end of this document), and 990 registered attendees, the Pan American Health Organization (PAHO) and the InterAmerican Development Bank (IDB) launched the webinar series Share-Listen-Act, COVID-19: The Potential of Digital Health and Information Systems for Health in the Fight against the Pandemic

Repositorio de investigaciones estudiantiles: tarea necesaria y trascendental / Repository of student research: A necessary and important task

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Conexión de registros sanitarios: base poblacional de salud de Andalucía / Health record linkage: Andalusian health population database

OBJETIVO: Describir el desarrollo de un sistema de información que conecta datos procedentes de múltiples registros, sanitarios y otros, para su uso con fines asistenciales, de administración, gestión, evaluación, inspección, investigación y salud pública. MÉTODO: Conexión determinística de datos pseudonimizados de una población de 8,5 millones de habitantes, procedentes de Base de datos de usuarios, Historia clínica electrónica DIRAYA, Conjunto mínimo básico de datos (hospitalización, cirugía mayor ambulatoria, urgencias hospitalarias y hospital de día médico) y sistemas de información de salud mental, pruebas de imagen, pruebas analíticas, vacunas, pacientes renales y farmacia. Se utilizó un codificador automático para los diagnósticos clínicos y se definieron 80 enfermedades crónicas para su seguimiento. La arquitectura del sistema de información constó de tres capas: datos (base de datos Oracle 11g), aplicaciones (MicroStrategy BI) y presentación (MicroStrategy Web, librerías JavaScript, HTML 5 y hojas de estilo CSS). Se implantaron medidas para la gobernanza del sistema. RESULTADOS: Se incluyeron datos de 12,5 millones de personas que fueron usuarias entre los años 2001 y 2017, con 435,5 millones de diagnósticos. El 88,7% de estos diagnósticos fueron generados por el codificador automático. Los datos se presentan mediante informes predefinidos o consultas dinámicas, ambos exportables a ficheros CSV para su tratamiento fuera del sistema. Analistas expertos pueden acceder directamente a las bases de datos y realizar extracciones mediante SQL o tratar directamente los datos con herramientas externas. CONCLUSIÓN: El trabajo ha mostrado cómo la conexión de registros sanitarios abre nuevas posibilidades en el análisis de datos

OBJECTIVE: To describe the development of an information system that connects data from multiple health records to improve assistance to patients, health services administration, management, evaluation, and inspection, as well as public health and research. METHOD: Deterministic connection of pseudonymized data from a population of 8.5 million inhabitants provided by: a users database, DIRAYA electronic medical records, minimum basic data sets (inpatients, outpatient mayor surgery, hospital emergencies and medical day hospital), mental health information systems, analytical and image tests, vaccines, renal patients, and pharmacy. An automatic coder was used to code clinical diagnoses and 80 chronic pathologies were identified to follow-up. The architecture of the information system consisted of three layers: data (Oracle Database 11g), applications (MicroStrategy BI) and presentation (MicroStrategy Web, JavaScript libraries, HTML 5 and CSS style sheets). Measures for the governance of the system were implemented. RESULTS: Data from 12.5 million health system users between 2001 and 2017 were gathered, including 435.5 million diagnoses, 88.7% of which were generated by the automatic coder. Data can be accessed through predefined reports or dynamic queries, both exportable to CSV files for processing outside the system. Expert analysts can directly access the databases and perform queries using SQL or directly treat the data with external tools. CONCLUSION: The work has shown that the connection of health records opens new possibilities for data analysis

Comunicación para la salud laboral / Communication for occupational health

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OntoSIDES: Ontology-based student progress monitoring on the national evaluation system of French Medical Schools.

We introduce OntoSIDES, the core of an ontology-based learning management system in Medicine, in which the educational content, the traces of students' activities and the correction of exams are linked and related to items of an official reference program in a unified RDF data model. OntoSIDES is an RDF knowledge base comprised of a lightweight domain ontology that serves as a pivot high-level vocabulary of the query interface with users, and of a dataset made of factual statements relating individual entities to classes and properties of the ontology. Thanks to an automatic mapping-based data materialization and rule-based data saturation, OntoSIDES contains around 8 millions triples to date, and provides an integrated access to useful information for student progress monitoring, using a powerful query language (namely SPARQL) allowing users to express their specific needs of data exploration and analysis. Since we do not expect end-users to master the raw syntax of SPARQL and to express directly complex queries in SPARQL, we have designed a set of parametrized queries that users can instantiate through a user-friendly interface.

Maturity Assessment Methodology for HISMM - Hospital Information System Maturity Model.

Maturity models have been adopted in organizations from different sectors of activity, as guides and references for information system (IS) management. In the healthcare field, maturity models have also been used to deal with the enormous complexity and demands of hospital information systems (HIS). This article presents a research project that aimed to develop a new comprehensive model of maturity for a health area. HISMM (hospital information system maturity model) was developed to address the complexity of HIS and intends to offer a useful tool to meet the demands of its management. The HISMM has the peculiarity of combining a set of key maturity influence factors and their respective characteristics, enabling not only the assessment of the global maturity of an HIS but also of the individual maturities of its various dimensions. In this article, we present a methodology for the application and implementation of this model in HIS, thus contributing to its widespread practical application and acceptance.

Twelve tips for medical students to conduct a systematic review.

Background: Medical students engaged in research develop general skills that are instrumental to clinical practice. The systematic review, a cornerstone of evidence-based medicine, represents an ideal starting point for student researchers. Aim and methods: To outline twelve tips on conducting a systematic review for medical students with limited research experience. Results: The tips in this article are practical, comprehensive, and informed by the authors experience as medical students. Conclusion: The twelve tips can help medical students contribute to the literature and build a valuable skillset for future research and clinical practice.

Indexing the Event Calculus: Towards practical human-readable Personal Health Systems.

Personal Health Systems (PHS) are mobile solutions tailored to monitoring patients affected by chronic non communicable diseases. In general, a patient affected by a chronic disease can generate large amounts of events: for example, in Type 1 Diabetic patients generate several glucose events per day, ranging from at least 6 events per day (under normal monitoring) to 288 per day when wearing a continuous glucose monitor (CGM) that samples the blood every 5 minutes for several days. Just by itself, without considering other physiological parameters, it would be impossible for medical doctors to individually and accurately follow every patient, highlighting the need of simple approaches towards querying physiological time series. Achieving this with current technology is not an easy task, as on one hand it cannot be expected that medical doctors have the technical knowledge to query databases and on the other hand these time series include thousands of events, which requires to re-think the way data is indexed. Anyhow, handling data streams efficiently is not enough. Domain experts' knowledge must be explicitly included into PHSs in a way that it can be easily readed and modified by medical staffs. Logic programming represents the perfect programming paradygm to accomplish this task. In this work, an Event Calculus-based reasoning framework to standardize and express domain-knowledge in the form of monitoring rules is suggested, and applied to three different use cases. However, if online monitoring has to be achieved, the reasoning performance must improve dramatically. For this reason, three promising mechanisms to index the Event Calculus Knowledge Base are proposed. All of them are based on different types of tree indexing structures: k-d trees, interval trees and red-black trees. The paper then compares and analyzes the performance of the three indexing techniques, by computing the time needed to check different type of rules (and eventually generating alerts), when the number of recorded events (e.g. values of physiological parameters) increases. The results show that customized jREC performs much better when the event average inter-arrival time is little compared to the checked rule time-window. Instead, where the events are more sparse, the use of k-d trees with standard EC is advisable. Finally, the Multi-Agent paradigm helps to wrap the various components of the system: the reasoning engines represent the agent minds, and the sensors are its body. The said agents have been developed in MAGPIE, a mobile event based Java agent platform.

Algunas reflexiones sobre los datos abiertos enlazados en Cuba / Some Reflections on Linked Open Data in Cuba

Cuba está realizando una introducción intensiva de las tecnologías de la información y la comunicación en la sociedad, con el desarrollo y el despliegue de sistemas de información para aumentar la eficiencia de varios sectores económicos y sociales. En este contexto, varias instituciones gubernamentales están publicando datos; sin embargo, estos datos se publican utilizando diversos formatos y estándares, sin relaciones explícitas entre ellos, con alta dispersión y baja capacidad de integración de datos. En este artículo presentamos algunas reflexiones sobre la necesidad del uso de los datos abiertos enlazados en Cuba y algunos desafíos que afectan la adopción masiva de ellos en el país. Señalamos que la apertura de los datos abiertos enlazados en Cuba requiere el uso de mecanismos adecuados relacionados con una infraestructura tecnológica actualizada, un marco legal adecuado y una sinergia adecuada entre los productores y los consumidores de los datos abiertos enlazados en el país(AU)

Cuba is carrying out an intensive introduction of the ICT in the society, developing and deploying information systems to increase the efficiency of several economic and social sectors. In this context, several government institutions are publishing open data; however, these data are published using diverse formats and standards, without explicit relations between them, with high dispersion and low data integration capabilities. In this paper, we state some reflections about the use of the linked open data in Cuba and some challenges affecting the massive adoption of them in the country. We point out that the openness of the linked open data in Cuba requires the use of adequate mechanisms related to an updated technological infrastructure, an adequate legal framework and an adequate synergy between the producers and consumers of the linked open data in the country(AU)

The project vita: A dynamic knowledge management tool.

A project vita is a comprehensive index of factual information about a project's activities and achievements. Like an individual's professional curriculum vita or resume, it serves as evidence of past performance and capacity for future endeavors. This article situates the project vita as a knowledge management tool for use by large-scale research and development projects or coalitions. In such complex endeavors, the variety and scope of the knowledge generated can quickly outpace project staff attempts to collect, classify, disseminate, and support the effective use of the constant stream of information being produced. We describe how to develop a project vita and utilize it to support several essential project functions, including communication, evaluation, management, and as a portal to products.

Implementation of a Research Information Management System in a Pediatric Hospital.

Faculty publications have been collected in universities, health, and medical institutions for many years, and Cincinnati Children's is no exception. Since 1949, a yearly list of faculty publications was manually compiled using multiple data sources and disseminated by the Edward L. Pratt Research Library. Products to centralize faculty publication collection and analysis with bibliometric tools are growing in popularity. This article will review the collaborative decision to choose a Research Information Management System and the implementation process including successes, challenges, and future opportunities.

Recursive partitioning methods for data imputation in the context of item response theory: a Monte Carlo simulation

Missing data is a common problem faced by psychometricians and measurement professionals. To address this issue, there are a number of techniques that have been proposed to handle missing data regarding Item Response Theory. These methods include several types of data imputation methods - corrected item mean substitution imputation, response function imputation, multiple imputation, and the EM algorithm, as well as approaches that do not rely on the imputation of missing values - treating the item as not presented, coding missing responses as incorrect, or as fractionally correct. Of these methods, even though multiple imputation has demonstrated the best performance in prior research, higher MAE was still present. Given this higher model parameter estimation MAE for even the best performing missing data methods, this simulation study's goal was to explore the performance of a set of potentially promising data imputation methods based on recursive partitioning. Results of this study demonstrated that approaches that combine multivariate imputation by chained equations and recursive partitioning algorithms yield data with relatively low estimation MAE for both item difficulty and item discrimination. Implications of these findings are discussed

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