Design and implementation of the Our Health Counts (OHC) methodology for First Nations, Inuit, and Metis (FNIM) health assessment and response in urban and related homelands.

OBJECTIVES: Methods for enumeration and population-based health assessment for First Nations, Inuit, and Metis (FNIM) living in Canadian cities are underdeveloped, with resultant gaps in essential demographic, health, and health service access information. Our Health Counts (OHC) was designed to engage FNIM peoples in urban centres in "by community, for community" population health assessment and response. METHODS: The OHC methodology was designed to advance Indigenous self-determination and FNIM data sovereignty in urban contexts through deliberate application of Indigenous principles and linked implementation strategies. Three interwoven principles (good relationships are foundational; research as gift exchange; and research as a vehicle for Indigenous community resurgence) provide the framework for linked implementation strategies which include actively building and maintaining relationships; meaningful Indigenous community guidance, leadership, and participation in all aspects of the project; transparent and equitable sharing of project resources and benefits; and technical innovations, including respondent-driven sampling, customized comprehensive health assessment surveys, and linkage to ICES data holdings to generate measures of health service use. RESULTS: OHC has succeeded across six urban areas in Ontario to advance Indigenous data sovereignty and health assessment capacity; recruit and engage large population-representative cohorts of FNIM living in urban and related homelands; customize comprehensive health surveys and data linkages; generate previously unavailable population-based FNIM demographic, health, and social information; and translate results into enhanced policy, programming, and practice. CONCLUSION: The OHC methodology has been demonstrated as effective, culturally relevant, and scalable across diverse Ontario cities.

RéSUMé: OBJECTIFS: Les méthodes de dénombrement et d'évaluation populationnelle de la santé des personnes des Premières Nations, des Inuits et des Métis (PNIM) vivant dans les villes du Canada sont sous-développées, ce qui laisse des lacunes dans les informations essentielles sur le profil démographique, la santé et l'accès aux services de santé. Le projet Notre santé compte (NSC) vise à collaborer avec les personnes des PNIM dans les centres urbains au moyen d'une évaluation de la santé des populations et d'une intervention « pour nous-mêmes, par nous-mêmes ¼. MéTHODE: La méthode NSC est conçue pour renforcer l'autodétermination autochtone et la souveraineté des données des PNIM vivant en milieu urbain par l'application délibérée de principes autochtones et de stratégies de mise en œuvre connexes. Trois principes imbriqués (« les bonnes relations sont fondamentales ¼; « la recherche en tant qu'échange de cadeaux ¼; et « la recherche comme vecteur de résurgence des communautés autochtones ¼) constituent le cadre de stratégies de mise en œuvre connexes : l'établissement et le maintien actifs de relations; la guidance, la participation et le leadership significatifs des communautés autochtones dans tous les aspects du projet; le partage transparent et équitable des ressources et des avantages du projet; et les innovations techniques, dont l'échantillonnage en fonction des répondants, les enquêtes de santé exhaustives et personnalisées, et les couplages avec les fonds de données de l'Institut de recherche en services de santé (ICES), pour produire des indicateurs d'utilisation des services de santé. RéSULTATS: L'approche NSC a réussi dans six agglomérations urbaines de l'Ontario : à renforcer la souveraineté des données et la capacité d'évaluation de la santé des populations autochtones; à recruter et à mobiliser de vastes cohortes représentatives des PNIM vivant en milieu urbain et sur les territoires connexes; à personnaliser des enquêtes de santé exhaustives et des couplages de données; à générer des informations démographiques, sanitaires et sociales non disponibles auparavant sur les populations des PNIM; et à traduire ces résultats en politiques, en programmes et en pratiques améliorés. CONCLUSION: Il est démontré que la méthode NSC est efficace, culturellement appropriée et modulable dans différentes villes de l'Ontario.

Identifying and validating the components for the development of an information system for health grey literature in Iran: A mixed method approach.

BACKGROUND: Considering the importance and necessity of establishing a nationwide information system for health grey literature in Iran, this study aimed to identify the main dimensions and components needed for developing a health grey literature information system in Iran and validate them according to experts' opinions. MATERIALS AND METHODS: A mixed-method approach with an exploratory sequential design was used in this study. The research was done in following main steps: (1) conducting a systematic literature review to identify the potential components of the health grey literature information system suggested in the literature, (2) Interviewing 19 experts to explore further components required for designing the health grey literature system for Iran and doing a thematic analysis for analyzing the interviews, and (3) validating the identified components by a Delphi panel in two rounds for finalizing the initially-approved dimensions and components. Descriptive statistical analysis was also used for analyzing the Delphi panel's data. RESULTS: Eight dimensions were identified as necessary for developing Iran's health grey literature information system (including 31 components and 111 elements). The main dimensions included goals, data sources, minimum data set, data collection techniques, data content management procedures, quality control approaches, stakeholders, and management and policy-making. CONCLUSION: Using the identified and validated functional components in this study can be helpful In designing a health grey literature system that is of value for health policymakers and medical researchers as well as health information users.

Development of a communication platform for patients with head and neck cancer for effective information delivery and improvement of doctor-patient relationship: application of treatment journey-based service blueprint.

BACKGROUND: Effective communication and information delivery enhance doctor-patient relationships, improves adherence to treatment, reduces work burden, and supports decision-making. The study developed a head and neck cancer (HNC) communication platform to support effective delivery of information about HNC treatment and improve the doctor-patient relationship. METHODS: This study was structured in three main phases: 1) The requirement elicitation phase sought an understanding of the HNC treatment journey and service failure points (FPs) obtained through patient/medical staff interviews and observations, along with a review of the electronic health record system; 2) The development phase involved core needs analysis, solutions development through a co-creation workshop, and validation of the solutions through focus groups; and 3) the proposed HNC communication platform was integrated with the current treatment system, and the flow and mechanism of the interacting services were structured using a service blueprint (SB). RESULTS: Twenty-two service FPs identified through interviews and observations were consolidated into four core needs, and solutions were proposed to address each need: an HNC treatment journey map, cancer survivor stories, operation consent redesign with surgical illustrations, and a non-verbal communication toolkit. The communication platform was designed through the SB in terms of the stage at which the solution was applied and the actions and interactions of the service providers. CONCLUSIONS: The developed platform has practical significance, reflecting a tangible service improvement for both patients and medical staff, making it applicable in hospital settings.

Pap Smear Cancer Coverage in Brazilian Capitals including the Pandemic Period Caused by the SARS-CoV-2 Virus: Ecological Study.

INTRODUCTION: Cervical cancer develops slowly and may not manifest signs and symptoms at an early stage. It is worth mentioning the factors that can influence the onset of cervical cancer: smoking, early sexual life, multiple sexual partners, use of oral contraceptives, multiparity, low socioeconomic status, among others. An important risk factor for the onset of this disease is HPV infection, a virus associated with most cases of precursor lesions of this type of cancer. It is essential to understand the comprehensiveness of the scope and adherence to the recommended guidelines throughout the national territory. Therefore, health indicators are important management tools that make it possible to evaluate the services offered, measuring the reach of the target population, the supply and access to preventive exams. OBJECTIVE: To analyze the trend of progress in cervical cancer coverage actions in Brazilian capitals from 2016 to 2021. METHOD: This is an ecological study with temporal analysis that used secondary data referring to process indicators for cervical cancer control actions in women aged between 25 and 64 years living in Brazilian capitals between 2016 and 2021. Aspects related to the quality of care in the cervical cancer prevention program were evaluated using databases of the Cancer Information System (SISCAN), available in DATASUS. The indicators used to monitor and evaluate cervical cancer control actions were (i) cervical coverage, (ii) reason for cervical surgery, and (iii) proportion of cervical cancer every 3 years. RESULTS: In 2016, 410,000 tests were performed and notified in the SISCAN system in all Brazilian capitals, with emphasis on Curitiba, with 65,715 tests performed, and Porto Velho, with 174. In 2020, there was a reduction in exams compared to the previous year in all capitals, with the exception of Palmas, which went from 7655 exams to 9604. It was observed that all the capitals studied showed an increase in the annual percentage variation of Pap smear coverage, with the exception of Brasília, Manaus, Porto Alegre and Porto Velho, which did not show a statistically significant increase (APC = 3.01, 2.746, 3.987, 3.69, respectively). When analyzing the performance of oncotic cytology exams in the capitals according to the years 2019 and 2020, it was observed that only Manaus registered an increase in the number of procedures performed, reaching a difference of 56.5% from one year to the next. CONCLUSION: The ecological analysis revealed a worrying drop in the number of tests performed in 2020, reflecting a sharp drop in coverage actions in Brazilian capitals during the pandemic caused by the SARS-CoV-2 virus. The pandemic has exacerbated existing inequalities and highlighted the need for adaptive strategies to maintain essential screening services in times of crisis.

Development of machine-learning models using pharmacy inquiry database for predicting dose-related inquiries in a tertiary teaching hospital.

BACKGROUND: Drug-related problems (DRPs) are a significant concern in healthcare. Pharmacists play a vital role in detecting and resolving DRPs to improve patient safety. A pharmacy inquiry program was established in a tertiary teaching hospital to document inquiries about physicians' orders, aimed at preventing potential DRPs or providing medication information during order reviews. OBJECTIVE: We aimed to develop machine-learning models using a pharmacy inquiry database to predict dose-related inquiries based on prescriptions and patient information. METHODS: This retrospective study analyzed 20,393 pharmacy inquiries collected between January 2018 and February 2023. Data included prescription information (drug ingredient, dose, unit, and frequency), patient characteristics (age, sex, weight, and department), and renal function. The inquiries were categorized into two classes: dose-related inquiries (e.g., wrong dose and inappropriate regimen) and non-dose-related inquiries (e.g., inappropriate drug form and administration route). Six machine-learning models were developed: logistic regression, support vector classifier, decision tree, random forest, extreme gradient boosting, and categorical boosting. To evaluate the performance of the models, the area under the receiver operating characteristic curve and the accuracy were compared. RESULTS: The CatBoost model achieved the highest performance (sensitivity: 0.92; accuracy: 0.79). The SHapley Additive exPlanations values highlighted the importance of features in the model predictions, drug ingredients, units, and renal function, in that order. Notably, lower renal function positively contributed to the prediction of dose-related inquiries. Additionally, the subsequent feature importance among drug ingredients showed that drugs such as acetylsalicylic acid, famotidine, metformin, and spironolactone strongly influenced the prediction of dose-related inquiries. CONCLUSION: Machine-learning models that use pharmacy inquiry data can effectively predict dose-related inquiries. Further external validation and refinement of the models are required for broader applications in healthcare settings. These findings provide valuable guidance for healthcare professionals and highlight the potential of machine learning in pharmacists' decision-making.

Codesign of health technology interventions to support best-practice perioperative care and surgical waitlist management.

OBJECTIVES: This project aimed to determine where health technology can support best-practice perioperative care for patients waiting for surgery. METHODS: An exploratory codesign process used personas and journey mapping in three interprofessional workshops to identify key challenges in perioperative care across four health districts in Sydney, Australia. Through participatory methodology, the research inquiry directly involved perioperative clinicians. In three facilitated workshops, clinician and patient participants codesigned potential digital interventions to support perioperative pathways. Workshop output was coded and thematically analysed, using design principles. RESULTS: Codesign workshops, involving 51 participants, were conducted October to November 2022. Participants designed seven patient personas, with consumer representatives confirming acceptability and diversity. Interprofessional team members and consumers mapped key clinical moments, feelings and barriers for each persona during a hypothetical perioperative journey. Six key themes were identified: 'preventative care', 'personalised care', 'integrated communication', 'shared decision-making', 'care transitions' and 'partnership'. Twenty potential solutions were proposed, with top priorities a digital dashboard and virtual care coordination. DISCUSSION: Our findings emphasise the importance of interprofessional collaboration, patient and family engagement and supporting health technology infrastructure. Through user-based codesign, participants identified potential opportunities where health technology could improve system efficiencies and enhance care quality for patients waiting for surgical procedures. The codesign approach embedded users in the development of locally-driven, contextually oriented policies to address current perioperative service challenges, such as prolonged waiting times and care fragmentation. CONCLUSION: Health technology innovation provides opportunities to improve perioperative care and integrate clinical information. Future research will prototype priority solutions for further implementation and evaluation.

Real world performance of the 21st Century Cures Act population-level application programming interface.

OBJECTIVE: To evaluate the real-world performance of the SMART/HL7 Bulk Fast Health Interoperability Resources (FHIR) Access Application Programming Interface (API), developed to enable push button access to electronic health record data on large populations, and required under the 21st Century Cures Act Rule. MATERIALS AND METHODS: We used an open-source Bulk FHIR Testing Suite at 5 healthcare sites from April to September 2023, including 4 hospitals using electronic health records (EHRs) certified for interoperability, and 1 Health Information Exchange (HIE) using a custom, standards-compliant API build. We measured export speeds, data sizes, and completeness across 6 types of FHIR. RESULTS: Among the certified platforms, Oracle Cerner led in speed, managing 5-16 million resources at over 8000 resources/min. Three Epic sites exported a FHIR data subset, achieving 1-12 million resources at 1555-2500 resources/min. Notably, the HIE's custom API outperformed, generating over 141 million resources at 12 000 resources/min. DISCUSSION: The HIE's custom API showcased superior performance, endorsing the effectiveness of SMART/HL7 Bulk FHIR in enabling large-scale data exchange while underlining the need for optimization in existing EHR platforms. Agility and scalability are essential for diverse health, research, and public health use cases. CONCLUSION: To fully realize the interoperability goals of the 21st Century Cures Act, addressing the performance limitations of Bulk FHIR API is critical. It would be beneficial to include performance metrics in both certification and reporting processes.

Researching big IT in the UK National Health Service: A systematic review of theory-based studies.

OBJECTIVE: To identify and discuss theory-based studies of large-scale health information technology programs in the UK National Health Service. MATERIALS AND METHODS: Using the PRISMA systematic review framework, we searched Scopus, PubMed and CINAHL databases from inception to March 2022 for theory-based studies of large-scale health IT implementations. We undertook detailed full-text analyses of papers meeting our inclusion criteria. RESULTS: Forty-six studies were included after assessment for eligibility, of which twenty-five applied theories from the information systems arena (socio-technical approaches, normalization process theory, user acceptance theories, diffusion of innovation), twelve from sociology (structuration theory, actor-network theory, institutional theory), while nine adopted other theories. Most investigated England's National Program for IT (2002-2011), exploring various technologies among which electronic records predominated. Research themes were categorized into user factors, program factors, process outcomes, clinical impact, technology, and organizational factors. Most research was qualitative, often using a case study strategy with a longitudinal or cross-sectional approach. Data were typically collected through interviews, observation, and document analysis; sampling was generally purposive; and most studies used thematic or related analyses. Theories were generally applied in a superficial or fragmentary manner; and articles frequently lacked detail on how theoretical constructs and relationships aided organization, analysis, and interpretation of data. CONCLUSION: Theory-based studies of large NHS IT programs are relatively uncommon. As large healthcare programs evolve over a long timeframe in complex and dynamic environments, wider adoption of theory-based methods could strengthen the explanatory and predictive utility of research findings across multiple evaluation studies. Our review has confirmed earlier suggestions for theory selection, and we suggest there is scope for more explicit use of such theoretical constructs to strengthen the conceptual foundations of health informatics research. Additionally, the challenges of large national health informatics programs afford wide-ranging opportunities to test, refine, and adapt sociological and information systems theories.

Review of Qualitative Research Methods in Health Information System Studies.

OBJECTIVES: The aim of this study was to review hospital-based health information system (HIS) studies that used qualitative research methods and evaluate their methodological contexts and implications. In addition, we propose practical guidelines for HIS researchers who plan to use qualitative research methods. METHODS: We collected papers published from 2012 to 2022 by searching the PubMed and CINAHL databases. As search keywords, we used specific system terms related to HISs, such as "electronic medical records" and "clinical decision support systems," linked with their operational terms, such as "implementation" and "adaptation," and qualitative methodological terms such as "observation" and "in-depth interview." We finally selected 74 studies that met this review's inclusion criteria and conducted an analytical review of the selected studies. RESULTS: We analyzed the selected articles according to the following four points: the general characteristics of the selected articles; research design; participant sampling, identification, and recruitment; and data collection, processing, and analysis. This review found methodologically problematic issues regarding researchers' reflections, participant sampling methods and research accessibility, and data management. CONCLUSIONS: Reports on the qualitative research process should include descriptions of researchers' reflections and ethical considerations, which are meaningful for strengthening the rigor and credibility of qualitative research. Based on these discussions, we suggest guidance for conducting ethical, feasible, and reliable qualitative research on HISs in hospital settings.

esafíos en la vigilancia de todos los casos de cáncer en Chile: Registro Nacional de Cáncer / Challenges in surveillance of all cancer cases: The Chilean National Cancer Registry

El cáncer causa millones de muertes a nivel mundial por lo que su registro es fundamental, existiendo registros clínicos, hospitalarios y poblacionales. Estos últimos son el estándar de oro para la información sobre incidencia y supervivencia de cáncer en una región definida. En Chile se cuenta con cinco registros poblacionales ubicados en ciertas zonas del país. El Registro Nacional del Cáncer chileno surge como un desafío para conformar una herramienta transversal a los tres tipos de registro con la finalidad de, al menos, conocer la cantidad de casos por tipo de cáncer. Su diseño implicó un despliegue de acciones orientadas a lograr consensos entre diversos actores respecto de la información, validación y eventos necesarios de registrar. Se identificaron cuatro etapas en el proceso de atención y el registro: sospecha de diagnóstico, confirmación morfológica (biopsia), resolución clínica (comité oncológico incluyendo la indicación de tratamiento), tratamiento y seguimiento oncológico. A su vez, el desarrollo de la plataforma (años 2018 a 2021) implicó levantamiento de información y acuerdos sobre los requerimientos para el co-diseño del registro, incluyendo un exitoso pilotaje con más de 20 establecimientos de salud del sector público y privado con registro de cerca de 7500 casos de cáncer. El despliegue y uso del Registro Nacional de Cáncer a nivel nacional depende de la autoridad sanitaria. Se trata de un sistema de información que recolecta, almacena, procesa y analiza de forma continua y sistemática datos sobre todos los casos y tipos de cánceres que ocurren en el país. En este trabajo se presenta el diseño y desarrollo de la herramienta, los desafíos abordados, sus fortalezas y debilidades.

Cancer causes millions of deaths worldwide, making its registration essential. There are clinical, hospital, and population-based registries in place. The latter is the gold standard for information on cancer incidence and survival in a defined region. Chile has five population-based registries located in specific areas of the country. The Chilean National Cancer Registry emerged with the challenge of creating a tool encompassing all three types of registries to identify the number of cancer cases by type. Its design involved a series of actions to achieve consensus among various actors regarding information, validation, and events to be registered. Four stages were identified in the care and registration process: suspected diagnosis, morphological confirmation (biopsy), clinical resolution (oncology committee, including treatment recommendations), treatment, and oncological follow-up. The platform's development (from 2018 to 2021) involved gathering information and agreements on the requirements for co-designing the registry, including a successful pilot program with over 20 public and private healthcare facilities that recorded nearly 7500 cancer cases. The deployment and use of the National Cancer Registry at a national level depends on the healthcare authority. It is an information system that continuously and systematically collects, stores, processes, and analyzes data on all cancer cases and types occurring in the country. This work presents the design and development of the tool, the challenges addressed, as well as its strengths and weaknesses.

Challenges in surveillance of all cancer cases: The Chilean National Cancer Registry. / Desafíos en la vigilancia de todos los casos de cáncer en Chile: Registro Nacional de Cáncer.

Cancer causes millions of deaths worldwide, making its registration essential. There are clinical, hospital, and population-based registries in place. The latter is the gold standard for information on cancer incidence and survival in a defined region. Chile has five population-based registries located in specific areas of the country. The Chilean National Cancer Registry emerged with the challenge of creating a tool encompassing all three types of registries to identify the number of cancer cases by type. Its design involved a series of actions to achieve consensus among various actors regarding information, validation, and events to be registered. Four stages were identified in the care and registration process: suspected diagnosis, morphological confirmation (biopsy), clinical resolution (oncology committee, including treatment recommendations), treatment, and oncological follow-up. The platform's development (from 2018 to 2021) involved gathering information and agreements on the requirements for co-designing the registry, including a successful pilot program with over 20 public and private healthcare facilities that recorded nearly 7500 cancer cases. The deployment and use of the National Cancer Registry at a national level depends on the healthcare authority. It is an information system that continuously and systematically collects, stores, processes, and analyzes data on all cancer cases and types occurring in the country. This work presents the design and development of the tool, the challenges addressed, as well as its strengths and weaknesses.

El cáncer causa millones de muertes a nivel mundial por lo que su registro es fundamental, existiendo registros clínicos, hospitalarios y poblacionales. Estos últimos son el estándar de oro para la información sobre incidencia y supervivencia de cáncer en una región definida. En Chile se cuenta con cinco registros poblacionales ubicados en ciertas zonas del país. El Registro Nacional del Cáncer chileno surge como un desafío para conformar una herramienta transversal a los tres tipos de registro con la finalidad de, al menos, conocer la cantidad de casos por tipo de cáncer. Su diseño implicó un despliegue de acciones orientadas a lograr consensos entre diversos actores respecto de la información, validación y eventos necesarios de registrar. Se identificaron cuatro etapas en el proceso de atención y el registro: sospecha de diagnóstico, confirmación morfológica (biopsia), resolución clínica (comité oncológico incluyendo la indicación de tratamiento), tratamiento y seguimiento oncológico. A su vez, el desarrollo de la plataforma (años 2018 a 2021) implicó levantamiento de información y acuerdos sobre los requerimientos para el co-diseño del registro, incluyendo un exitoso pilotaje con más de 20 establecimientos de salud del sector público y privado con registro de cerca de 7500 casos de cáncer. El despliegue y uso del Registro Nacional de Cáncer a nivel nacional depende de la autoridad sanitaria. Se trata de un sistema de información que recolecta, almacena, procesa y analiza de forma continua y sistemática datos sobre todos los casos y tipos de cánceres que ocurren en el país. En este trabajo se presenta el diseño y desarrollo de la herramienta, los desafíos abordados, sus fortalezas y debilidades.

Health Data Sharing with the Goal of Value Creation; Trying to Develop a Framework Using Qualitative Content Analysis.

Introduction: Within the field of data sharing, discussions surrounding privacy concerns and big data management are extensive. This study aimed to provide a comprehensive framework for health data sharing with the objective of creating value. Methods: This study is a qualitative content analysis, which was conducted using a combination of written sources through a systematic review method, in conjunction with content derived from interviews with experts in information technology and healthcare within hospital and emergency settings. Grounded theory serves as the qualitative methodology, involving three coding phases: open, axial, and selective, facilitated by MAXQDA software. Results: Qualitative content analysis of the interviews revealed seven main (core) categories and 44 subcategories as driving factors in promoting healthcare data sharing. Simultaneously, inhibiting factors resulted in six main categories and 36 subcategories. The driving factors encompassed technology, education, patient management improvement, data utilization for various purposes, data-related considerations, legal and regulatory aspects, and health-related factors. Conversely, inhibiting factors encompassed security and privacy concerns, legal issues, external organizational influences, monitoring and control activities, financial considerations, and inter-organizational challenges. Conclusion: This study has identified key driving and inhibiting factors that influence the sharing of healthcare data. These factors contribute to a more comprehensive understanding of the dynamics surrounding data sharing within the healthcare information system.

Patients' Use of Telemedicine Mobile Application During COVID-19 Restrictions.

Telemedicine is being used in an increasing number of countries as an alternative to face-to-face traditional healthcare, to reduce the chances of spreading COVID-19. Although the use and benefits of telemedicine have been increasingly demonstrated for a long time, we do not know much about its adoption and use during the COVID-19 pandemic, when the community is confined by the social distancing restrictions. The main aim of this research is to study the factors affecting the adoption and use of telemedicine in patients during the period of COVID-19 restrictions. We also want to investigate the benefits of telemedicine for patients. We used a qualitative approach in this study. We interviewed six patients who used telemedicine during the COVID-19 restrictions. We find that telemedicine applications offered an overall positive experience for patients as a viable alternative way of medical care when physical attendance was restricted.

Coding undiagnosed rare disease patients in health information systems: recommendations from the RD-CODE project.

BACKGROUND: In European Union countries, any disease affecting less than 5 people in 10,000 is considered rare. As expertise is scarce and rare diseases (RD) are complex, RD patients can remain undiagnosed for many years. The period of searching for a diagnosis, called diagnostic delay, sometimes leads to a diagnostic dead end when the patient's disease is impossible to diagnose after undergoing all available investigations. In recent years, extensive efforts have been made to support the implementation of ORPHA nomenclature in health information systems (HIS) so as to allow RD coding. Until recently, the nomenclature only encompassed codes for specific RD. Persons suffering from a suspected RD who could not be diagnosed even after full investigation, could not be coded with ORPHAcodes. The recognition of the RD status is necessary for patients, even if they do not have a precise diagnosis. It can facilitate reimbursement of care, be socially and psychologically empowering, and grant them access to scientific advances. RESULTS: The RD-CODE project aimed at making those patients identifiable in HIS in order to produce crucial epidemiological data. Undiagnosed patients were defined as patients for whom no clinically-known disorder could be confirmed by an expert center after all reasonable efforts to obtain a diagnosis according to the state-of-the-art and diagnostic capabilities available. Three recommendations for the coding of undiagnosed RD patients were produced by a multi-stakeholder panel of experts: 1/ Capture the diagnostic ascertainment for all rare disease cases; 2/ Use the newly created ORPHAcode (ORPHA:616874 "Rare disorder without a determined diagnosis after full investigation"), available in the Orphanet nomenclature: as the code is new, guidelines are essential to ensure its correct and homogeneous use for undiagnosed patients' identification in Europe and beyond; 3/ Use additional descriptors in registries. CONCLUSIONS: The recommendations can now be implemented in HIS (electronic health records and/or registries) and could be a game-changer for patients, clinicians and researchers in the field, enabling assessment of the RD population, including undiagnosed patients, adaptation of policy measures including financing for care and research programs, and to improved access of undiagnosed patients to research programs.

Designing a comprehensive minimum dataset for patients with COVID-19 in Iranian hospital information systems.

BACKGROUND: The Minimum Data Set (MDS) plays a vital role in data exchange, collection and quality improvement. In the context of the COVID-19 pandemic, there is a need for a tailored MDS that aligns with the specific information needs of the Iranian community and integrates seamlessly into the country's Hospital Information Systems (HIS). OBJECTIVE: The study aimed to develop a comprehensive MDS for COVID-19 patients in Iran, with objectives to identify essential data elements and integrate the MDS into HIS, enhancing data exchange and supporting decision-making. METHOD: This study employed a comparative-descriptive approach to design COVID-19 patient data elements based on World Health Organisation and Centers for Disease Control and Prevention guidelines. The Delphi technique involved 35 experts in two rounds for checklist refinement. The finalised MDS consisted of 9 main terms and 80 sub-terms, analysed using descriptive statistics and IBM SPSS software. RESULTS: Of 35 experts involved with the study, 69% were male and 31% female, and Health Information Management experts were the majority (34%). The refined MDS for COVID-19 in Iran comprises 50 data elements, while 30 elements were excluded. The MDS includes 8 main terms and 80 sub-terms, with unanimous approval for identity, underlying disease, and treatment sections. CONCLUSION: The customised MDS for COVID-19 patients in Iran addresses data collection challenges and supports effective disease prevention and management. By providing comprehensive and reliable information, the MDS enhances healthcare quality, facilitates timely access to medical records, and fosters integrated health services.

Challenges and successes in implementing an integrated electronic patient record (HIVE) at the Manchester University National Health Service Foundation Trust, England: 1000+ legacy systems, 10 hospitals, one electronic patient record.

BACKGROUND: The Manchester University National Health Service (NHS) Foundation Trust (MFT) is one of the largest NHS Trusts in England. Historically, the Trust has had very mixed clinical record keeping, including over 1000 individual information systems. None of these health information technology systems had the full functionality of an integrated electronic patient record (EPR). MFT evolved to its current size and complexity with a vision to improve patient care in Greater Manchester by adopting a Trust-wide EPR. The EPR "Go Live" occurred in September 2022. AIM: To describe the process of EPR integration as it reflected and impacted upon MFT's health information management (HIM) teams. METHOD: MFT worked through a 2-year readiness program of work. This included technical readiness, software development and migration planning. Migration of data from the approximately 1000 systems was a major undertaking, during which access to the clinical history and ongoing operational reporting needed to be maintained. Pre-implementation requirements were outlined, a change management program was implemented, and the overall implementation was managed to tight timelines. DISCUSSION: "Go Live" was achieved for the EPIC EPR product (HIVE) within MFT. Legacy systems are still in the process of being decommissioned and staff are transacting within HIVE. Significant changes in processes and reporting continue to be made, despite some challenges. CONCLUSION: The Trust delivered the single largest EPIC European "Go live." Lessons learnt continue to be identified. The impact of what the EPR means for the HIM function is described.

Trends in caesarean section rates in Europe from 2015 to 2019 using Robson's Ten Group Classification System: A Euro-Peristat study.

OBJECTIVE: To assess changes in caesarean section (CS) rates in Europe from 2015 to 2019 and utilise the Robson Ten Group Classification System (TGCS) to evaluate the contribution of different obstetric populations to overall CS rates and trends. DESIGN: Observational study utilising routine birth registry data. SETTING: A total of 28 European countries. POPULATION: Births at ≥22 weeks of gestation in 2015 and 2019. METHODS: Using a federated model, individual-level data from routine sources in each country were formatted to a common data model and transformed into anonymised, aggregated data. MAIN OUTCOME MEASURES: By country: overall CS rate. For TGCS groups (by country): CS rate, relative size, relative and absolute contribution to overall CS rate. RESULTS: Among the 28 European countries, both the CS rates (2015, 16.0%-55.9%; 2019, 16.0%-52.2%) and the trends varied (from -3.7% to +4.7%, with decreased rates in nine countries, maintained rates in seven countries (≤ ± 0.2) and with increasing rates in 12 countries). Using the TGCS (for 17 countries), in most countries labour induction increased (groups 2a and 4a), whereas multiple pregnancies (group 8) decreased. In countries with decreasing overall CS rates, CS tended to decrease across all TGCS groups, whereas in countries with increasing rates, CS tended to increase in most groups. In countries with the greatest increase in CS rates (>1%), the absolute contributions of groups 1 (nulliparous term cephalic singletons, spontaneous labour), 2a and 4a (induction of labour), 2b and 4b (prelabour CS) and 10 (preterm cephalic singletons) to the overall CS rate tended to increase. CONCLUSIONS: The TGCS shows varying CS trends and rates among countries of Europe. Comparisons between European countries, particularly those with differing trends, could provide insight into strategies to reduce CS without clinical indication.

Prevalência e fatores pessoais associados à violência autoprovocada em adolescentes / Prevalence and personal factors associated with self-harm in adolescents / Prevalencia y factores personales asociados a la violencia autoinflingida en adolescentes

RESUMO Objetivo: identificar a prevalência e os fatores pessoais associados à violência autoprovocada em adolescentes. Método: estudo observacional analítico, do tipo transversal. A população foi composta pelas notificações de violência interpessoal ou autoprovocada em adolescentes no Brasil, oriundas do Sistema de Informação de Agravos de Notificação. Foram incluídas as notificações ocorridas entre 2009 e 2021 no Brasil, em adolescentes de 10 a 19 anos. Os dados foram analisados com estatística descritiva e inferencial. Resultados: a prevalência de violência autoprovocada foi de 27,39% no Brasil. Adolescentes pretos aumentam a prevalência de violência autoprovocada em 3%, e os pardos e indígenas em 2%; mais de 8 anos de escolaridade constitui fator de proteção em relação à violência autoprovocada, reduzindo em 12% a prevalência de violência autoinfligida. Conclusão: os resultados indicam a necessidade de que sejam traçadas políticas e estratégias eficazes que auxiliem no cuidado a esse público.

ABSTRACT Objective: To identify the prevalence and personal factors associated with self-harm in adolescents. Method: A cross-sectional analytical observational study. The population consisted of notifications of interpersonal or self-harm violence in adolescents in Brazil from the Notifiable Diseases Information System. Notifications between 2009 and 2021 in Brazil were included in adolescents aged 10 to 19. The data was analyzed using descriptive and inferential statistics. Results: The prevalence of self-harm was 27.39% in Brazil. Black adolescents increase the prevalence of self-harm violence by 3% and brown and indigenous adolescents by 2%; more than eight years of schooling is a protective factor in relation to self-harm violence, reducing the prevalence of self-inflicted violence by 12%. Conclusion: The results indicate the need for effective policies and strategies to help care for this public.

RESUMEN Objetivo: identificar la prevalencia y los factores personales asociados a la violencia autoinfligida en adolescentes. Método: estudio observacional, analítico, transversal. La población estuvo constituida por notificaciones de violencia interpersonal o autoinfligida entre adolescentes de Brasil, provenientes del Sistema de Información de Enfermedades De Declaración Obligatoria. Se incluyeron las notificaciones ocurridas entre 2009 y 2021 en Brasil, en adolescentes de 10 a 19 años. Los datos fueron analizados con estadística descriptiva e inferencial. Resultados: la prevalencia de violencia autoinfligida fue del 27,39% en Brasil. Los adolescentes negros aumentan la prevalencia de la violencia autoinfligida en un 3%, y los pardos e indígenas en un 2%; más de 8 años de escolaridad constituye un factor protector en relación a la violencia autoinfligida, reduciendo en un 12% la prevalencia de la violencia autoinfligida. Conclusión: los resultados indican la necesidad de diseñar políticas y estrategias efectivas para ayudar a la atención de esta población.

Avaliação do impacto da implantação do novo sistema de informações da atenção primária à saúde nos registros de atendimentos e visitas domiciliares no Brasil / Evaluation of the impact of the implementation of the new primary health care information system on records of patient care and home visits in Brazil / Evaluación del impacto de la implantación del nuevo sistema de informaciones de la atención primaria de salud en los registros de atención y visitas domiciliarias en Brasil

Resumo: A substituição do Sistema de Informação da Atenção Básica (SIAB, 1998-2015), a partir de janeiro de 2016, pelo novo Sistema de Informação em Saúde para a Atenção Básica (SISAB) determinou novas formas de coleta, processamento e uso das informações, com possível impacto nos registros das atividades desenvolvidas na atenção primária à saúde no Brasil. O objetivo deste estudo foi avaliar o impacto da implantação do novo sistema de informação sobre registros de atendimentos de médicos e enfermeiros, e de visitas domiciliares de agentes comunitários de saúde (ACS) brasileiros entre 2007 e 2019. Para tal, utilizou-se uma abordagem bayesiana de modelo estrutural para séries temporais, com base em uma regressão difusa de espaço-estado. Ao longo do período de 2016 a 2019, foram registrados 463,47 milhões de atendimentos médicos, 210,61 milhões de atendimentos de enfermagem e 1,28 bilhão de visitas de ACS. Seguindo a tendência registrada antes da implantação, seriam esperados 598,86 milhões, 430,46 milhões e 1,5 bilhão de atendimentos de médicos, enfermeiros e visitas de ACS, respectivamente. Em termos relativos, houve um decréscimo de 25% nos atendimentos médicos, 51% nos atendimentos de enfermagem e 15% nas visitas de ACS quando comparado com o valor esperado pelo método bayesiano. O impacto negativo no registro de atendimentos e de visitas domiciliares identificado neste estudo, seja por dificuldade de adaptação ao novo sistema, seja por diminuição de registros indevidos, merece ser alvo de investigação para que se possa, de forma planejada, compreender e superar o desafio da melhoria do sistema de informação da atenção primária.

Abstract: The replacement of the Primary Care Information System (SIAB, 1998-2015), as of January 2016, by the new Health Information System for Primary Care (SISAB) determined new forms of collecting, processing, and using information, with a possible impact on the records of activities carried out in primary health care in Brazil. This study aimed to evaluate the implementation impact of the new information system on records of physicians' and nurses' patient care and home visits of community health workers (CHW) in Brazil from 2007 to 2019. To this end, a Bayesian structural time-series model approach was used, based on a diffuse state-space regression. From 2016 to 2019, 463.47 million physician care, 210.61 million nursing care, and 1.28 billion CHW visits were recorded. Following the trend recorded before the implementation, 598.86 million, 430.46 million, and 1.5 billion physician and nursing appointments and CHW visits would be expected, respectively. In relative terms, there was a decrease of 25% in physician care, 51% in nursing care, and 15% in CHW visits when compared to the value expected by the Bayesian method. The negative impact on the records of patient care and home visits identified in this study, whether due to difficulties in adapting to the new system or a reduction in improper records, must be investigated so that the challenge of improving the primary care information system can be understood and overcome in a planned way.

Resumen: La sustitución del Sistema de Información de la Atención Básica (SIAB, 1998-2015), desde enero de 2016, por el nuevo Sistema de Información en Salud para la Atención Básica (SISAB) estableció nuevas maneras para recolectar, procesar y utilizar las informaciones, con posibles impactos en los registros de las actividades desarrolladas en la atención primaria de salud en Brasil. El objetivo de este estudio fue evaluar el impacto de la implantación del nuevo sistema de información sobre los registros de atención de médicos y enfermeros y de visitas domiciliarias de agentes comunitarios de salud (ACS) en Brasil entre 2007 y 2019. Para eso, se utilizó un enfoque bayesiano de modelo estructural para series temporales basadas en una regresión difusa de espacio de estado. Entre los años 2016 y 2019, se registraron 463,47 millones de consultas médicas, 210,61 millones de consultas de enfermería y 1,28 mil millones de visitas de ACS. Siguiendo la tendencia registrada antes de la implantación, se esperarían 598,86 millones, 430,46 millones y 1,5 mil millones de consultas médicas y de enfermería y visitas de ACS respectivamente. En términos relativos, hubo una disminución del 25% en las consultas médicas, del 51% en las consultas de enfermería y del 15% en las visitas de ACS en comparación con el valor esperado por el método bayesiano. El impacto negativo en el registro de consultas y visitas domiciliarias identificado en este estudio, ya sea por dificultades en la adaptación al nuevo sistema o por la disminución de los registros indebidos, merece ser objeto de investigación para que se pueda, de manera planificada, comprender y superar el desafío continuo de mejorar el sistema de información de la atención primaria.

Avaliação da efetividade da intervenção para aprimoramento do Sistema de Informações sobre Mortalidade em Pernambuco, Brasil: um estudo quase-experimental / Evaluation of the effectiveness of the intervention to improve the Brazilian Mortality Information System in Pernambuco, Brazil: a quasi-experimental study / Evaluación de la efectividad de la intervención para mejorar el Sistema de Informaciones sobre la Mortalidad en Pernambuco, Brasil: un estudio cuasiexperimental

Resumo: Avaliou-se a influência da variação da implantação do Sistema de Informações sobre Mortalidade (SIM) nos resultados antes e depois da intervenção para aprimoramento do sistema em Pernambuco, Brasil. Foram explicitados o modelo lógico e a matriz de indicadores e julgamento do SIM. Coletaram-se dados primários nos 184 municípios e dados secundários na base do sistema. Obteve-se o grau de implantação (GI) a partir de indicadores de estrutura e processo, posteriormente relacionado aos de resultado, com base no modelo. A intervenção foi direcionada às falhas identificadas e se desenvolveu mediante etapas estratégicas. Foi calculado o percentual de variação anual do GI e dos resultados antes e depois da intervenção. Classificou-se o SIM como parcialmente implantado nas avaliações pré (70,6%) e pós-intervenção (73,1%), com incrementos em todos os componentes. As Regiões de Saúde seguiram a mesma classificação do âmbito estadual, excetuando-se a XII (80,3%), com escore implantado, após a intervenção. Cobertura do sistema, óbitos com causa básica definida, transferência mensal e envio oportuno de dados situaram-se acima de 90% nas duas avaliações. Houve melhora na completude das Declarações de Óbito infantil e no registro oportuno de eventos notificáveis. O fortalecimento da gestão e operacionalização do SIM por meio de intervenções aplicadas no contexto de produção dos dados pode aprimorar os resultados do sistema.

Abstract: This study evaluated the influence of the variation in the implementation of the Brazilian Mortality Information System (SIM) on the results, before and after the intervention to improve the system in Pernambuco, Brazil. The SIM logical model and matrix of indicators and assessment were described, primary data were collected from the 184 municipalities and secondary data were collected from the system database. The degree of implementation (DI) was obtained from the indicators of structure and process, and then related to result indicators, based on the model. The intervention was directed at the shortcomings identified, and developed using strategic stages. The percentage of annual variation of the DI and the results before and after the intervention were calculated. The SIM was classified as partially implemented in the pre- (70.6%) and post-intervention (73.1%) evaluations, with increments in all components. The Health Regions followed the same classification of the state level, except for XII (80.3%), regarding implemented score after the intervention. The coverage of the system; deaths with a defined underlying cause; monthly transfer; and timely submission of data were above 90% in both evaluations. There was an improvement in the completeness of infant Death Certificates and in the timely recording of notifiable events. Strengthening the management and operationalization of the SIM with interventions applied to data registration can improve the system's results.

Resumen: Se evaluó la influencia de la variación de la implantación del Sistema de Informaciones sobre la Mortalidad (SIM) en los resultados, antes y después de la intervención para mejorar el sistema en Pernambuco, Brasil. Se explicitaron el modelo lógico y la matriz de indicadores y juicio del SIM, recolectando datos primarios en los 184 municipios y datos secundarios en la base del sistema. Se obtuvo el grado de implantación (GI) a partir de indicadores de estructura y proceso, posteriormente, relacionado con los indicadores de resultado, basado en el modelo. La intervención se dirigió a los fallos identificados y se desarrolló a través de etapas estratégicas. Se calcularon el porcentaje de variación anual del GI y de los resultados antes y después de la intervención. El SIM se clasificó como parcialmente implantado en las evaluaciones previas (70,6%) y posteriores a la intervención (73,1%) con aumento en todos los componentes. Las Regiones de Salud han seguido la misma clasificación del ámbito estatal, salvo la XII (80,3%), con puntaje implantado, después de la intervención. La cobertura del sistema; óbitos debido a causa básica definida; transferencia mensual y envío oportuno de datos, estuvieron por encima del 90% en ambas evaluaciones. Hubo una mejora en la exhaustividad de los Certificados de Muerte infantiles y en el registro oportuno de eventos notificables. Fortalecer la gestión y la implementación del SIM a través de intervenciones aplicadas en el contexto de producción de datos puede mejorar los resultados del sistema.