Managing macromolecular crystallographic data with a laboratory information management system.

Protein crystallography is an established method to study the atomic structures of macromolecules and their complexes. A prerequisite for successful structure determination is diffraction-quality crystals, which may require extensive optimization of both the protein and the conditions, and hence projects can stretch over an extended period, with multiple users being involved. The workflow from crystallization and crystal treatment to deposition and publication is well defined, and therefore an electronic laboratory information management system (LIMS) is well suited to management of the data. Completion of the project requires key information on all the steps being available and this information should also be made available according to the FAIR principles. As crystallized samples are typically shipped between facilities, a key feature to be captured in the LIMS is the exchange of metadata between the crystallization facility of the home laboratory and, for example, synchrotron facilities. On completion, structures are deposited in the Protein Data Bank (PDB) and the LIMS can include the PDB code in its database, completing the chain of custody from crystallization to structure deposition and publication. A LIMS designed for macromolecular crystallography, IceBear, is available as a standalone installation and as a hosted service, and the implementation of key features for the capture of metadata in IceBear is discussed as an example.

Capturing Home Care Information Management and Communication Processes Among Caregivers of Older Adults: Qualitative Study to Inform Technology Design.

BACKGROUND: The demand for complex home care is increasing with the growing aging population and the ongoing COVID-19 pandemic. Family and hired caregivers play a critical role in providing care for individuals with complex home care needs. However, there are significant gaps in research informing the design of complex home care technologies that consider the experiences of family and hired caregivers collectively. OBJECTIVE: The objective of this study was to explore the health documentation and communication experiences of family and hired caregivers to inform the design and adoption of new technologies for complex home care. METHODS: The research involved semistructured interviews with 15 caregivers, including family and hired caregivers, each of whom was caring for an older adult with complex medical needs in their home in Ontario, Canada. Due to COVID-19-related protection measures, the interviews were conducted via Teams (Microsoft Corp). The interview guide was informed by the cognitive work analysis framework, and the interview was conducted using storytelling principles of narrative medicine to enhance knowledge. Inductive thematic analysis was used to code the data and develop themes. RESULTS: Three main themes were developed. The first theme described how participants were continually updating the caregiver team, which captured how health information, including their communication motivations and intentions, was shared among family and hired caregiver participants. The subthemes included binder-based health documentation, digital health documentation, and communication practices beyond the binder. The second theme described how participants were learning to improve care and decision-making, which captured how they acted on information from various sources to provide care. The subthemes included developing expertise as a family caregiver and tailoring expertise as a hired caregiver. The third theme described how participants experienced conflicts within caregiver teams, which captured the different struggles arising from, and the causes of, breakdowns in communication and coordination between family and hired caregiver participants. The subthemes included 2-way communication and trusting the caregiver team. CONCLUSIONS: This study highlights the health information communication and coordination challenges and experiences that family and hired caregivers face in complex home care settings for older adults. Given the challenges of this work domain, there is an opportunity for appropriate digital technology design to improve complex home care. When designing complex home care technologies, it will be critical to include the overlapping and disparate perspectives of family and hired caregivers collectively providing home care for older adults with complex needs to support all caregivers in their vital roles.

The Power of Networking.

This paper explores the critical role of networking, particularly within the oncology data specialist community, in developing and implementing an educational course. Networking, both within and beyond academia, is essential for gathering resources, expertise, and support necessary for designing and delivering an effective curriculum tailored to the demands of oncology data analysis. Networking within this specialized community facilitates collaboration with other educators and professionals, sharing of best practices, innovative teaching methodologies, and assessment strategies specific to oncology data analysis. This paper examines how networking within the oncology data specialist community contributed to the creation of a dynamic and comprehensive course, ultimately enriching the educational experience and preparing students for success.

Deep learning-driven hybrid model for short-term load forecasting and smart grid information management.

Accurate power load forecasting is crucial for the sustainable operation of smart grids. However, the complexity and uncertainty of load, along with the large-scale and high-dimensional energy information, present challenges in handling intricate dynamic features and long-term dependencies. This paper proposes a computational approach to address these challenges in short-term power load forecasting and energy information management, with the goal of accurately predicting future load demand. The study introduces a hybrid method that combines multiple deep learning models, the Gated Recurrent Unit (GRU) is employed to capture long-term dependencies in time series data, while the Temporal Convolutional Network (TCN) efficiently learns patterns and features in load data. Additionally, the attention mechanism is incorporated to automatically focus on the input components most relevant to the load prediction task, further enhancing model performance. According to the experimental evaluation conducted on four public datasets, including GEFCom2014, the proposed algorithm outperforms the baseline models on various metrics such as prediction accuracy, efficiency, and stability. Notably, on the GEFCom2014 dataset, FLOP is reduced by over 48.8%, inference time is shortened by more than 46.7%, and MAPE is improved by 39%. The proposed method significantly enhances the reliability, stability, and cost-effectiveness of smart grids, which facilitates risk assessment optimization and operational planning under the context of information management for smart grid systems.

Development of automated metabolite control using mid-infrared probe for bioprocesses and vaccine manufacturing.

Automation of metabolite control in fermenters is fundamental to develop vaccine manufacturing processes more quickly and robustly. We created an end-to-end process analytical technology and quality by design-focused process by replacing manual control of metabolites during the development of fed-batch bioprocesses with a system that is highly adaptable and automation-enabled. Mid-infrared spectroscopy with an attenuated total reflectance probe in-line, and simple linear regression using the Beer-Lambert Law, were developed to quantitate key metabolites (glucose and glutamate) from spectral data that measured complex media during fermentation. This data was digitally connected to a process information management system, to enable continuous control of feed pumps with proportional-integral-derivative controllers that maintained nutrient levels throughout fed-batch stirred-tank fermenter processes. Continuous metabolite data from mid-infrared spectra of cultures in stirred-tank reactors enabled feedback loops and control of the feed pumps in pharmaceutical development laboratories. This improved process control of nutrient levels by 20-fold and the drug substance yield by an order of magnitude. Furthermore, the method is adaptable to other systems and enables soft sensing, such as the consumption rate of metabolites. The ability to develop quantitative metabolite templates quickly and simply for changing bioprocesses was instrumental for project acceleration and heightened process control and automation. ONE-SENTENCE SUMMARY: Intelligent digital control systems using continuous in-line metabolite data enabled end-to-end automation of fed-batch processes in stirred-tank reactors.

What is infodemiology? An overview and its role in public health. / Czym jest infodemiologia? Przeglad i rola w zdrowiu publicznym.

The exponential increase in internet use and the consequent surge in data generation present both opportunities and challenges for public health. Infodemiology, an emerging field at the intersection of information science and public health, seeks to harness the vast amounts of health-related data generated online for public health benefits. This paper provides a comprehensive overview of infodemiology, examining its development, methodologies, and potential to address public health challenges. We discuss the role of infodemiology in identifying and mitigating the spread of misinformation, especially in the context of the COVID-19 pandemic, which underscored the dangers of the "infodemic" - an overabundance of information, both accurate and not, that complicates public health responses. Through both demand and supply-based studies, infodemiology offers unique insights into health trends, misinformation dynamics, and the digital behaviors of health information seekers. Tools such as sentiment analysis are highlighted as essential in navigating the vast digital landscape for real-time health data analysis. Despite the potential of infodemiology, challenges such as data overload or misinformation. The paper concludes by emphasizing the importance of interdisciplinary collaboration, the development of advanced analytical tools, and the need for guidelines to maximize the field's impact on public health policy and practice.

Utilization and efficacy of DotPhrases in the electronic medical record for improving physician documentation.

Clinical documentation of patient visits has changed over the last 20 years, with the increasing use of electronic records causing a seismic shift in how notes are taken. Electronic note-taking aims at reducing the time taken to document a visit, and the introduction of dot phrases, or DotPhrases, in electronic medical records is a step toward reducing the time required to update patients' charts, which might allow doctors to spend more time with their patients. DotPhrases, abbreviated phrases used in the electronic medical record, help in the simplification of note-taking and the standardization of notes. They also allow for a more comprehensive note from physicians and ensure that no information is undocumented. On the contrary, however, excessive usage of DotPhrases can lead to an excessively long and cumbersome note. This can overwhelm physicians and lead to them missing crucial information that is buried somewhere in the notes. Although there is ample research studying the benefits of DotPhrases, adequate research must also be carried out to understand their shortcomings and disadvantages. This article aims to shed some light on use of DotPhrases and to outline their advantages and disadvantages affecting patient management and care.

Impact of narcotics information management system on inappropriate benzodiazepine receptor agonist prescriptions: A quasi-experimental analysis in South Korea.

AIMS: The South Korean government implemented the narcotics information management system (NIMS) on 18 May 2018 to manage benzodiazepine receptor agonists (BzRAs) and narcotics effectively and establish a reporting mechanism for these drugs. This study assessed the effects of NIMS on inappropriate use of BzRAs. METHODS: Using national patient sample data from 2016 to 2020, we analysed adult outpatients who were prescribed oral BzRAs. We conducted a time series and segmented regression analysis using selected indicators to analyse the monthly variations related to the inappropriate use of these medications. RESULTS: The study revealed no significant changes in the indicators of inappropriate BzRA use following the NIMS implementation. Contrary to expectations, there was a significant increase in the proportion of patients exceeding defined daily dose (DDD) and in those receiving concurrent prescriptions of multiple BzRAs, following the implementation of NIMS. The immediate impact of the COVID-19 pandemic was an increase in DDD exceedance; however, overall, this did not significantly affect BzRA use. CONCLUSIONS: The introduction of NIMS did not significantly enhance the management of BzRA misuse. Additional measures, including continuous monitoring, system improvements and comprehensive education for prescribers and patients, are recommended to ensure the appropriate use of psychotropic medications.

[Design and Application of an IVD Reagent Management Information Systems Based on Unique Code].

The management of in vitro diagnostic (IVD) reagents in hospitals often faces issues such as the lack of a unified coding system, unclear consumption patterns, and unknown cost-to-income ratios. It is necessary to employ information systems to achieve comprehensive, detailed, and traceable management of IVD reagents. An information management system for IVD reagents based on unique coding is introduced, which integrates admission, acceptance, and consumption processes through unique codes. The system calculates the income per experimental item based on the consumption of IVD reagents and the charge for each experimental item. The system enhances the efficiency of the IVD reagent supply chain management and promotes detailed oversight of IVD reagent usage.

A Nationwide Online Tracking System of pediatric ICU demand and capacity during a respiratory epidemic in Uruguay / Desarrollo de un Sistema Nacional de Monitoreo En Línea de Capacidad y Demanda de las Unidades de Cuidados Intensivos Pediátricas Durante Una Epidemia Respiratoria

Monitoring national capacity of pediatric intensive care (PICU) beds is important for resource allocation. We describe the development and application of an online tool for bed occupancy monitoring during the respiratory epidemic of 2023 in Uruguay. A 5-minute survey was sent out daily to each PICU designated staff utilizing an instant messaging application, throughout the 12-week of 2023 winter season. The survey gathered information on staffed bed capacity, occupancy rates, invasive mechanical ventilation (IMV) demand and number of children admitted for lower respiratory tract infections (LRTIs). Data was manually entered using the REDcap Software platform. A comparison between PICUs from the capital city Montevideo (MVD) and the inland region (INN) was performed. Participating PICUs had access to a daily dashboard with nationwide data. We collected data from 100% (n=20) of Uruguayan PICUs, 68% in MVD (2.72 PICU beds per-10,000 <18 years) and 32% in the INN (0.86 PICU beds per-10,000 <18 years). National average bed occupancy rate was 55.5%, without differences between MVD and INN. However, LRTI admissions and IMV incidence were notably higher among INN PICUs compared with MVD PICUs, 83.0% vs. 71% (P<0.01) and 19.9% vs. 14.7% (P<0.01) respectively. During one week occupancy exceeded 80% without differences between MVD and INN. The implementation of a nationwide PICU bed monitoring tool was possible. Although occupancy rates did not reach critical levels at a national grade, regional differences were found that merit further study to improve vital PICUs resource allocation.

Monitorear la capacidad nacional de camas de cuidados intensivos pediátricos (UCIP) es importante para la asignación de recursos. Describimos el desarrollo y aplicación de una herramienta online para el seguimiento de la ocupación de camas durante la epidemia respiratoria de 2023 en Uruguay. Se envió diariamente una encuesta de 5 minutos a cada personal designado de la UCIP mediante una aplicación de mensajería instantánea, durante las 12 semanas de la temporada de invierno de 2023. La encuesta recopiló información sobre la capacidad de camas con personal, las tasas de ocupación, la demanda de ventilación mecánica invasiva (IMV) y el número de niños admitidos por infecciones del tracto respiratorio inferior (LRTI). Los datos se ingresaron manualmente utilizando la plataforma del software REDcap. Se realizó una comparación entre UCIP de la capital Montevideo (MVD) y del interior (INN). Las UCIP participantes tuvieron acceso a un panel diario con datos a nivel nacional. Se recolectaron datos del 100% (n=20) de las UCIP uruguayas, el 68% en MVD (2,72 camas UCIP por 10.000 <18 años) y el 32% en el INN (0,86 camas UCIP por 10.000 <18 años). La tasa de ocupación de camas promedio nacional fue del 55,5%, sin diferencias entre MVD e INN. Sin embargo, los ingresos por LRTI y la incidencia de IMV fueron notablemente mayores entre las UCIP INN en comparación con las UCIP MVD, 83,0% frente a 71% (P<0,01) y 19,9% frente a 14,7% (P<0,01), respectivamente. Durante una semana la ocupación superó el 80% sin diferencias entre MVD y INN. Fue posible implementar una herramienta de monitoreo de camas UCIP a nivel nacional. Aunque las tasas de ocupación no alcanzaron niveles críticos a nivel nacional, se encontraron diferencias regionales que merecen más estudios para mejorar la asignación de recursos vitales de las UCIP.

Social network analysis for medical narcotics in South Korea: focusing on patients and healthcare organizations.

BACKGROUND: Medical narcotics must be administered under medical supervision because of their potential for misuse and abuse, leading to more dangerous and addictive substances. The control of medical narcotics requires close monitoring to ensure that they remain safe and effective. This study proposes a methodology that can effectively identify the overprescription of medical narcotics in hospitals and patients. METHODS: Social network analysis (SNA) was applied to prescription networks for medical narcotics. Prescription data were obtained from the Narcotics Information Management System in South Korea, which contains all data on narcotic usage nationwide. Two-mode networks comprising hospitals and patients were constructed based on prescription data from 2019 to 2021 for the three most significant narcotics: appetite suppressants, zolpidem, and propofol. Two-mode networks were then converted into one-mode networks for hospitals. Network structures and characteristics were analyzed to identify hospitals suspected of overprescribing. RESULTS: The SNA identified hospitals that overprescribed medical narcotics. Patients suspected of experiencing narcotic addiction seek treatment in such hospitals. The structure of the network was different for the three narcotics. While appetite suppressants and propofol networks had a more centralized structure, zolpidem networks showed a less centralized but more fragmented structure. During the analysis, two types of hospitals caught our attention: one with a high degree, meaning that potential abusers have frequently visited the hospital, and the other with a high weighted degree, meaning that the hospital may overprescribe. For appetite suppressants, these two types of hospitals matched 84.6%, compared with 30.0% for propofol. In all three narcotics, clinics accounted for the largest share of the network. Patients using appetite suppressants were most likely to visit multiple locations, whereas those using zolpidem and propofol tended to form communities around their neighborhoods. CONCLUSIONS: The significance of this study lies in its analysis of nationwide narcotic use reports and the differences observed across different types of narcotics. The social network structure between hospitals and patients varies depending on the composition of the medical narcotics. Therefore, these characteristics should be considered when controlling medication with narcotics. The results of this study provide guidelines for controlling narcotic use in other countries.

[Use of social networks as a source of information on health and digital health literacy in the Spanish general population]. / Uso de redes sociales como fuente de información sobre salud y alfabetización digital en salud en población general española.

OBJECTIVE: Social media allows individuals to access a vast amount of health-related information immediately and anonymously, a fact that is turning these platforms into one of the primary sources of reference in this area, especially for younger generations. Given this reality, the objective of determining the impact of social media on digital health literacy in the general Spanish population was proposed. METHODS: A cross-sectional descriptive study was carried out in 2023. Using a non-probabilistic sampling, the population residing in Spain, over eighteen years old, and users of social networks were included, obtaining a sample of 1,307 participants. An adaptation of the validated eHEALS questionnaire on digital health literacy was used. This questionnaire, created in Microsoft Forms, was disseminated through an anonymous link via the research team's social networks and collaborators. A descriptive and inferential statistical analysis was performed using SPSS 22.0, assuming a significance level with a value of p<0.05. RESULTS: All participants affirmed having consumed health information through social networks, but 72.1% stated they had actively used these platforms to search for this health information. Regarding digital health literacy, a median score of 24 out of 40 points was obtained on the questionnaire, being significantly higher among those who claimed to use social networks as a source of health information (p=0.0001). CONCLUSIONS: Actively employing social media as a source of health information is associated with a higher level of digital health literacy.

OBJECTIVE: Las redes sociales permiten a las personas acceder de manera inmediata y anónima a una cantidad ingente de información sobre aspectos de salud, hecho que está provocando que se estén convirtiendo en una de las fuentes de referencia en este ámbito, sobre todo para las generaciones más jóvenes. Atendiendo a esta realidad se planteó el objetivo de determinar el impacto de las redes sociales en la alfabetización digital en salud en la población general española. METHODS: Se realizó un estudio descriptivo transversal en el año 2023. Mediante un muestreo no probabilístico, se incluyó población residente en España, mayor de dieciocho años y usuaria de redes sociales, obteniendo una muestra de 1.307 participantes. Se utilizó una adaptación del cuestionario validado eHEALS sobre alfabetización digital en salud. Dicho cuestionario, elaborado en Microsoft Forms, fue difundido mediante un enlace anónimo a través de las redes sociales del equipo investigador y colaboradores. Se realizó un análisis estadístico descriptivo e inferencial mediante SPSS 22.0, asumiendo un nivel de significación con un valor de p<0,05. RESULTS: La totalidad de los participantes afirmaron haber consumido información sobre salud a través de redes sociales, pero fue el 72,1% el que afirmó haber usado estas plataformas activamente para buscar esta información sobre salud. Con respecto a la alfabetización digital en salud, se obtuvo una puntuación mediana en el cuestionario de 24 sobre 40 puntos, siendo significativamente mayor entre los que afirmaron usar las redes sociales como fuente de información sobre salud (p=0,0001). CONCLUSIONS: Emplear de manera activa las redes sociales como fuente de información sobre salud parece tener relación con un mayor nivel de alfabetización digital en salud.

Taipei Medical University Clinical Research Database: a collaborative hospital EHR database aligned with international common data standards.

OBJECTIVE: The objective of this paper is to provide a comprehensive overview of the development and features of the Taipei Medical University Clinical Research Database (TMUCRD), a repository of real-world data (RWD) derived from electronic health records (EHRs) and other sources. METHODS: TMUCRD was developed by integrating EHRs from three affiliated hospitals, including Taipei Medical University Hospital, Wan-Fang Hospital and Shuang-Ho Hospital. The data cover over 15 years and include diverse patient care information. The database was converted to the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) for standardisation. RESULTS: TMUCRD comprises 89 tables (eg, 29 tables for each hospital and 2 linked tables), including demographics, diagnoses, medications, procedures and measurements, among others. It encompasses data from more than 4.15 million patients with various medical records, spanning from the year 2004 to 2021. The dataset offers insights into disease prevalence, medication usage, laboratory tests and patient characteristics. DISCUSSION: TMUCRD stands out due to its unique advantages, including diverse data types, comprehensive patient information, linked mortality and cancer registry data, regular updates and a swift application process. Its compatibility with the OMOP CDM enhances its usability and interoperability. CONCLUSION: TMUCRD serves as a valuable resource for researchers and scholars interested in leveraging RWD for clinical research. Its availability and integration of diverse healthcare data contribute to a collaborative and data-driven approach to advancing medical knowledge and practice.

Gerenciamento do protocolo de prevenção de lesão por pressão: construção de painel de bordo informatizado / Management of the pressure injury prevention protocol: construction of a computerized dashboard / Gestión del protocolo de prevención de lesiones por presión: construcción de panel informatizado

Objetivo: Relatar a construção e implantação de painel de bordo, desenvolvido por enfermeiros e profissionais da tecnologia da informação, para gerenciamento do Protocolo de Prevenção de Lesão por Pressão. Métodos: Trata-se de um relato de experiência sobre a construção e implantação de painel de bordo informatizado para gerenciamento de protocolo em um hospital privado universitário, localizado no interior do estado de São Paulo. Resultados: A construção do painel de bordo foi dividida nas seguintes etapas: revisão e atualização do protocolo, construção do modelo eletrônico e implementação. A divulgação foi realizada pela Comissão de Prevenção de Lesão por Pressão. Conclusão: O painel de bordo possibilitou a visualização rápida e em tempo real dos riscos dos pacientes, intervenções propostas e efetividade das medidas de prevenção, além de promover a integração e empoderamento dos profissionais na gestão do cuidado. (AU)

Objective: To report the construction and implementation of a dashboard, developed by nurses and information technology professionals, to manage the Pressure Injury Prevention Protocol. Methods: This is an experience report on the construction and implementation of a computerized dashboard for protocol management in a private university hospital, located in the interior of the state of São Paulo. Results: The construction of the dashboard was divided into the following steps: review and update of the protocol, construction of the electronic model and implementation. The Pressure Injury Prevention Commission disclosed the tool. Conclusion: The dashboard enabled the quick and real-time visualization of patient risks, proposed interventions and effectiveness of prevention measures, in addition to promoting the integration and empowerment of professionals in the management of care. (AU)

Objetivo: Informar la construcción e implementación de un panel, desarrollado por enfermeras y profesionales de tecnologías de la información, para gestionar el Protocolo de Prevención de Lesiones por Presión. Métodos: Se trata de un informe de experiencia sobre la construcción e implementación de un panel computarizado para la gestión del protocolo en un hospital universitario privado, en el interior del estado de São Paulo. Resultados: La construcción del panel se dividió en los siguientes pasos: revisión y actualización del protocolo, construcción del modelo electrónico e implementación. La divulgación fue realizada por la Comisión de Prevención de Lesiones por Presión. Conclusión: El panel permitió la visualización rápida y en tiempo real de los riesgos del paciente, las intervenciones propuestas y la efectividad de las medidas de prevención, además de promover la integración y el empoderamiento de los profesionales en la gestión del cuidado. (AU)

Can proactive support prevent unscheduled care? A controlled observational retrospective cohort study in cancer patients in Scotland.

INTRODUCTION: Preventative spend is a global health and social care strategy. Improving Cancer Journeys (ICJ) is a proactive, holistic, multidisciplinary project consistent with this agenda, currently being rolled out across Scotland and parts of UK. ICJ helps people with cancer access whatever support they need to mitigate their most pressing concerns. This study hypothesised that ICJ service users should subsequently use less unscheduled care than matched cohorts not using ICJ. METHODS: Retrospective observational cohort study using linked national datasets. N = 1,214 ICJ users in Glasgow were matched for age, sex, deprivation, cancer type, stage, and diagnosis year to two control groups: 1. Cancer patients from Glasgow before ICJ (pre-2014), 2. Cancer patients from rest of Scotland during study period (2014-2018). Cancer registrations were linked for 12-month baseline and study periods to: NHS24 calls, A&E admissions, inpatient hospital admissions, unscheduled care, number & cost of psychotropic prescriptions. Per-person mean service uses were compared between groups. RESULTS: There was a significant increase in NHS24 calls in the ICJ group (0.36 per person vs. -0.03 or 0.35), more and longer A&E attendances in ICJ (0.37 per person vs. 0.19 or 0.26; 2.19 h per person vs. 0.81-0.92 h), more and longer hospital admissions in ICJ (4.25 vs. 2.59 or 2.53; 12.05 days vs. 8.37 or 8.64), more care pathways involving more steps in ICJ (0.77 spells vs. 0.39 or 0.57; 1.88 steps vs. 1.56 or 1.21), more psychotropic drug prescriptions and higher costs in ICJ (1.88 prescription vs. 1.56 or 1.21; £9.51 vs. £9.57 or £6.95) in comparison to both control groups. DISCUSSION: ICJ users sourced significantly more unscheduled care than matched cohorts. These findings were consistent with much of the comparable literature examining the impact of non-health interventions on subsequent health spend. They also add to the growing evidence showing that ICJ reached its intended target, those with the greatest need. Together these findings raise the possibility that those choosing to use ICJ may also be self-identifying as a cohort of people more likely to use unscheduled care in future. This needs to be tested prospectively, because this understanding would be very helpful for health and social care planners in all countries where proactive holistic services exist.

Deductive Care Methodology: Describing and testing modes of care research.

OBJECTIVE: Define the modes of procedure of the Deductive Care Methodology (DCM) in the generation of knowledge about person's health care. METHODOLOGY: Design and test of the DCM modes based on three phases: mapping of the DCM, generation of models from this methodology and testing of the models through studies in a clinical context. RESULTS: The DCM presents five levels of abstraction with three modes broken down to 16 types. The modes are: Philosophical Mode to conceptualize and obtain generalities about reality, Mathematical Mode to operate with generalities, and Physical Mode to operationally verify, validating the results and the predictive capacity of the model. This MDC allows the creation of three models: Knowledge Model about Person Care, an ontology of care, Vulnerability Model about the person and Taxonomic Triangulation Model for knowledge management. All models generate products for computational knowledge management. In addition, the models are applied in teaching and generate research with more than a hundred participations in conferences and journals, of which five impact publications (from 2008 to 2022) classified in the categories of Nursing and Informatics are analysed. CONCLUSIONS: The DCM collects prior knowledge to work with certainties, evidence and applying inferences that do not depend on the number of cases or inductive designs. This research presents a formal structure of the DCM with an interdisciplinary orientation between Health Sciences and Computer Sciences.