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Sentinel surveillance networks are sophisticated health information systems that warn about outbreaks and spread of infectious diseases with epidemic or pandemic potential, the effectiveness of countermeasures and pressures on health systems. They are underpinned by their ability to turn data into information and knowledge in a timely way. The Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) is one of Europe's oldest. We report its progressive use of technology to improve the scope of sentinel surveillance, with a focus on genomic surveillance. The technologies include terminologies, phenotypes, compute capability, virology including virial genome sequencing, and serology. The RSC's data collection developed from partial, then full extraction of computerised medical record (CMR) data. with increasing sophistication in its creation of phenotypes. The scope of surveillance in 1967 was clinical diagnosis, influenzalike-illness (ILI) was its focus. In the 1992-1993 winter virology sampling started, with progressively more sophisticated sequencing of the viral genome. From 2008 viral sequencing was comprehensive with the Global Initiative on Sharing All Influenza Data (GISAID) the primary repository, supplemented by the COVID-19 Genomics UK (COG-UK) consortium in-pandemic. High quality primary care data captures sociodemographic features, risk group status, and vaccine exposure; linked hospital and death data informs about severe outcomes; virology identified the causative organism and genomic surveillance the variant. Timely data access and analysis will enable identification of new variants resistant to vaccination or other countermeasures and enable new interventions to be developed. [ABSTRACT FROM AUTHOR]

Introduction: Process Mining (PM) has emerged as a transformative tool in healthcare, facilitating the enhancement of process models and predicting potential anomalies. However, the widespread application of PM in healthcare is hindered by the lack of structured event logs and specific data privacy regulations. Concept: This paper introduces a pipeline that converts routine healthcare data into PM-compatible event logs, leveraging the newly available permissions under the Health Data Utilization Act to use healthcare data. Implementation: Our system exploits the Core Data Sets (CDS) provided by Data Integration Centers (DICs). It involves converting routine data into Fast Healthcare Interoperable Resources (FHIR), storing it locally, and subsequently transforming it into standardized PM event logs through FHIR queries applicable on any DIC. This facilitates the extraction of detailed, actionable insights across various healthcare settings without altering existing DIC infrastructures. Lessons Learned: Challenges encountered include handling the variability and quality of data, and overcoming network and computational constraints. Our pipeline demonstrates how PM can be applied even in complex systems like healthcare, by allowing for a standardized yet flexible analysis pipeline which is widely applicable.The successful application emphasize the critical role of tailored event log generation and data querying capabilities in enabling effective PM applications, thus enabling evidence-based improvements in healthcare processes. [ABSTRACT FROM AUTHOR]

The design of digital health information systems around a conflated gender/sex binary contributes to health inequities. Lack of specific information that supports affirming communication lead to inappropriate care, disrespectful encounters with healthcare staff, and avoidance of health services by clients who have been harmed by misgendering, deadnaming and being outed. The HL7 International Gender Harmony Model (HL7 GHM) supports the design, implementation and use of DHIS that enable affirming clinical interactions and care. This case study will demonstrate how applying the HL7 GHM can address the harms reported in a recently published account of one patient in Canada. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Appropriate data models are essential for the systematic collection, aggregation, and integration of health data and for subsequent analysis. However, recommendations for modeling health data are often not publicly available within specific projects. Therefore, the project Zukunftslabor Gesundheit investigates recommendations for modeling. Expert interviews with five experts were conducted and analyzed using qualitative content analysis. Based on the condensed categories "governance", "modeling" and "standards", the project team generated eight hypotheses for recommendations on health data modeling. In addition, relevant framework conditions such as different roles, international cooperation, education/training and political influence were identified. Although emerging from interviewing a small convenience sample of experts, the results help to plan more extensive data collections and to create recommendations for health data modeling. [ABSTRACT FROM AUTHOR]

Background: There are many medical knowledge bases with potential for supporting medical professionals in their decision-making during routine care, yet usage of these sources remains low. Standardized linking of Clinical Decision Support (CDS) applications and existing medical knowledge bases is not a common practice. Objectives: Using existing eHealth standards to increase the utilization of knowledge bases and implement a prototype. Methods: Linking an existing online knowledge base via a FHIR CodeSystem supplement to the Austrian national EHR (ELGA) terminology server and accessing these data using CDS Hooks and FHIR. Results: We tested the approach by incorporating photosensitivity data of medications into a local copy of the Austrian terminology server. These data are directly used by a CDS Hooks compliant CDS service. Conclusion: The Austrian Terminology Server could be an important interface to access existing knowledge bases from within EHR systems. FHIR and CDS Hooks could lead the way for a simple and open integration of CDS services into EHR systems. [ABSTRACT FROM AUTHOR]

Background: Health information systems (HIS) represent an essential part of the infrastructure for the delivery of good health care. Objectives: To present the author’s personal views on HIS developments over the last decades and on the opportunities and priorities for future HIS developments. Methods: Reflecting on his views, the author identified relevant semantic dimensions, which are denoted as development paths, and searched for appropriate periods to characterize HIS development leaps. Results: HIS developments were divided into the periods past (1961-2016), present (2017-2022), and future (the next decades). Eight development paths for HIS were considered as being relevant to presenting the author’s views: life situations related to health care, entities for health care, health care facilities, settings of health care, data to be processed, features for functions, architectures of HIS, and management of HIS. For each of these paths, the past and present states as well as challenges and opportunities for future HIS developments were outlined. Discussion and Conclusions: The presented views on HIS developments and the selected development paths and periods are by nature subjective ‘avant la lettre‘. The views were, however, formed over almost half a century during which the author has been engaged with HIS developments, and thus may be worth reporting and discussion. If past is prologue, the tremendous HIS developments in the past and in the present may predict a similar development intensity in the future. Present HIS are significantly better than HIS of the past, however they leave room for continued improvement with an end of HIS developments far from sight. [ABSTRACT FROM AUTHOR]

Background: Health information systems (HIS) represent an essential part of the infrastructure for the delivery of good health care. Objectives: To present the author's personal views on HIS developments over the last decades and on the opportunities and priorities for future HIS developments. Methods: Reflecting on his views, the author identified relevant semantic dimensions, which are denoted as development paths, and searched for appropriate periods to characterize HIS development leaps. Results: HIS developments were divided into the periods past (1961-2016), present (2017-2022), and future (the next decades). Eight development paths for HIS were considered as being relevant to presenting the author's views: life situations related to health care, entities for health care, health care facilities, settings of health care, data to be processed, features for functions, architectures of HIS, and management of HIS. For each of these paths, the past and present states as well as challenges and opportunities for future HIS developments were outlined. Discussion and Conclusions: The presented views on HIS developments and the selected development paths and periods are by nature subjective 'avant la lettre'. The views were, however, formed over almost half a century during which the author has been engaged with HIS developments, and thus may be worth reporting and discussion. If past is prologue, the tremendous HIS developments in the past and in the present may predict a similar development intensity in the future. Present HIS are significantly better than HIS of the past, however they leave room for continued improvement with an end of HIS developments far from sight. [ABSTRACT FROM AUTHOR]

In the EU project FAIR4Health, a ETL pipeline for the FAIRification of structured health data as well as an agent-based, distributed query platform for the analysis of research hypotheses and the training of machine learning models were developed. The system has been successfully tested in two clinical use cases with patient data from five university hospitals. Currently, the solution is also being considered for use in other hospitals. However, configuring the system and deploying it in the local IT architecture is non-trivial and meets with understandable concerns about security. This paper presents a model for describing the information architecture based on a formal approach, the 3LGM metamodel. The model was evaluated by the developers. As a result, the clear separation of tasks and the software components that implement them as well as the rich description of interactions via interfaces were positively emphasized. [ABSTRACT FROM AUTHOR]

The usage of context open data, such as environmental data, socioeconomic resources, etc., in clinical settings has been limited till now. But in recent years the number of studies that consider these factors is increasing. However, for clinicians, researchers or other stakeholders to be able to use this information in clinical practice, appropriate visualizations tools must be developed. At the same time, the data are generally displayed in formats that are difficult to interpret. The use of geolocalized visualizing tools through maps provides a better understanding in most cases. The proposed tool aims to contribute to the development of systems that can help to the exploitation of clinical and context open data, making them more easily interpretable. [ABSTRACT FROM AUTHOR]

Among 1,650 persons in an internet panel survey in October 2020 in Finland, over 89% reported use of the nationwide My Kanta online patient portal. Only 1.5% of the respondents did not know the service. Compared with non-users, among My Kanta users there were more females, less living in countryside, household net income was higher, and more reported independent use of online services. My Kanta use increased by poorly self-rated health status, increasing number of reported prescribed medicines, long-term diseases and physician visits during the six previous months. [ABSTRACT FROM AUTHOR]

Secondary use of clinical data is an increasing application that is affected by the data quality (DQ) of its source systems. Techniques such as audits and riskbased monitoring for controlling DQ often rely on source data verification (SDV). SDV requires access to data generating systems. We present an approach to a targeted SDV based on manual input and synthetic data that is applicable in low resource settings with restricted system access. We deployed the protocol in the DQ management of the AKTIN Emergency Department Data Registry. Our targeted approach has shown to be feasible to form a DQ baseline that can be used for different DQ monitoring processes such as the identification of different error sources. [ABSTRACT FROM AUTHOR]

In many developing countries like India, there is a widespread lack of general awareness about the importance of good oral health, which causes dental patients to neglect their oral hygiene, thus precipitating many long-term ailments. We developed an application that promotes the significance of regular dental checkups and oral health care by explaining to patients how these are intrinsic to overall health. Our application, in essence, extracts relevant health information from published scientific studies according to a patient's medical history and shares it with the patient at the discretion of the supervising dentist, thereby empowering patients to make more informed decisions. We present a detailed overview of our semiautonomous machine learning-based solution, along with the complex challenges involved in the design, development, and real-world deployment of our application. Finally, we conducted a randomized parallel-group study in India with 224 dental patients over two years to assess the utility of our proposed solution. Results show our application improved the patient recall rate from 21.1% to 37.8% (p-value = 0.024). [ABSTRACT FROM AUTHOR]

The issue of lacking standardized organizational guidance is examined in the context of providing patient-centered care to meet the needs of an aging population. Standardization across an integrated organization is increasingly recognized as a social justice concern in the pursuit of equitable and timely healthcare delivery, particularly as the healthcare industry grapples with a severe nursing shortage in the United States. A master project plan methodology (MPPM) was tested to effectively develop an electronic Age-Friendly 4Ms documentation tool using the system development lifecycle (SDLC) framework. The MPPM successfully guided the design and national implementation, achieving an 84% installation rate across 124 facilities within one of America's largest integrated healthcare systems. [ABSTRACT FROM AUTHOR]

Accident and emergency informatics has become a new approach to accident research in the era of digitization, where it has become realistic to integrate data recorded at accident sites with data in electronic health records of patients. This chapter deals with the question on whether the existing and well-established evaluation methodologies used in accident-centered research as well as in patient-centered research within clinical medicine are sufficient and should also be used for such integrated data or whether they have to be modified or extended. Based on the Gaus-Muche-Nomenclature on studies in clinical medicine, it will be outlined which types of studies are appropriate here. In addition to observational studies and registers, controlled trials using randomization are also be regarded as an important approach for gaining new knowledge. In order to appropriately access data from health records and from accidents, standards for representing and communicating data for such studies will be of importance. Another criterion is referential integrity. Here and with respect to accidents the International Standard Accident Number (ISAN) may be of importance. [ABSTRACT FROM AUTHOR]

Research data management requires stable, trustworthy repositories to safeguard scientific research results. In this context, rich markup with metadata is crucial for the discoverability and interpretability of the relevant resources. SEEK is a web-based software to manage all important artifacts of a research project, including project structures, involved actors, documents and datasets. SEEK is organized along the ISA model (Investigation -- Study -- Assay). It offers several machine-readable serializations, including JSON and RDF. In this paper, we extend the power of RDF serialization by leveraging the W3C Data Catalog Vocabulary (DCAT). DCAT was specifically designed to improve interoperability between digital assets on the Web and enables cross-domain markup. By using community-consented gold standard vocabularies and a formal knowledge description language, findability and interoperability according to the FAIR principles are significantly improved. [ABSTRACT FROM AUTHOR]

In response to epidemics and pandemics, access to authentic sources of information plays a critical role in informing public health practices. However, infodemic, i.e., an overabundance of health information, misinformation, and disinformation, impede implementing best public health policies during a public health crisis such as COVID-19. In this bibliometric study, we aim to report on concept mapping of infodemic literature, and in line with the World Health Organization (WHO)'s repeated calls for actions in managing infodemic, we highlight fruitful avenues for future directions. Through a visualization approach on a set of 414 records, a concept mapping was carried out. This map revealed 42 infodemic-related nodes in five clusters. We also propose an infodemic research platform in which a combination of the research nodes (e.g., COVID, pandemic, disinformation, fake news, post-truth, fact-checking, social networks, Facebook, WhatsApp, and lockdown) with impactful questions suggest future directions. [ABSTRACT FROM AUTHOR]

Background: Considering the impacts of the COVID-19 pandemic on health service delivery, the US Office for Civil Rights (OCR) updated the policies on health data processing, and Health Insurance Portability and Accountability Act (HIPAA). Objectives: In this study, we investigated discourses on HIPAA in relation to COVID-19. Methods: Through a search of media sources in the Factiva database, relevant texts were identified. We applied a text mining approach to identify concepts and themes in these texts. Results: Our analysis revealed six central themes, namely, Health, HIPAA, Privacy, Security, Patients, and Need, as well as their associated concepts. Among these, Health was the most frequently discussed theme. It comprised concepts such as public, care, emergency, providers, telehealth, entity, use, discretion, OCR, Health and Human Services (HHS), enforcement, business, and services. Conclusion: Our discourse analysis of media outlets highlights the role of health data privacy law in the response to global public health emergencies and demonstrates how discourse analysis and computational methods can inform health data protection policymaking in the digital health era. [ABSTRACT FROM AUTHOR]

IHE has defined more than 200 integration profiles in order to improve the interoperability of application systems in healthcare. These profiles describe how standards should be used in particular use cases. These profiles are very helpful but their correct use is challenging, if the user is not familiar to the specifications. Therefore, inexperienced modelers of information systems quickly lose track of existing IHE profiles. In addition, the users of these profiles are often not aware of rules that are defined within these profiles and of dependencies that exist between the profiles. There are also modelers that do not notice the differences between the implemented actors, because they do not know the optional capabilities of some actors. The aim of this paper is therefore to describe a concept how modelers of information systems can be supported in the selection and use of IHE profiles and how this concept was prototypically implemented in the "Three-layer Graph-based meta model" modeling tool (3LGM² Tool). The described modeling process consists of the following steps that can be looped: defining the use case, choosing suitable integration profiles, choosing actors and their options and assigning them to application systems, checking for required actor groupings and modeling transactions. Most of these steps were implemented in the 3LGM² Tool. Further implementation effort and evaluation of our approach by inexperienced users is needed. But after that our tool should be a valuable tool for modelers planning healthcare information system architectures, in particular those based on IHE. [ABSTRACT FROM AUTHOR]

Information management and the usability of health information systems (HIS) are important for the development of HIS in occupational health services. User participation in the HIS development process has been shown to contribute to the success of an HIS. The purpose of this study was to analyze how user participation in HIS development affected evaluation of the success of HIS. The success was assessed on the basis of the DeLone and McLean Information Systems (IS) Success Model. The study was conducted within occupational health services and the data (n=210) was analyzed with quantitative methods. The results showed that users participating in the HIS development process assessed the success of the HIS as better than those that had not taken part in the development. This difference could be seen in all seven dimensions of the DeLone and McLean IS success model but was statistically significant only for System Quality and Intention to Use. The results also showed that the users that had participated in the HIS development process also used the HIS more often and more extensively than those that had not participated in the development. The results indicate that user participation in the development process positively influences their assessment of the HIS and increases their active use of the IS. However, more research is needed to determine the longterm effects of using participatory design in HIS development. [ABSTRACT FROM AUTHOR]

Downtime of information systems is a universal challenge faced by health care institutions. Regardless of whether downtime is planned or unplanned, the unavailability of essential information requires alternative solutions. In this paper, we conduct a scoping review of how hospitals deal with downtime. A total of 13 papers were included in the final analysis, and we found that coping can be grouped into three strategies; 1) Increasing communication, 2) Analog fallback, and 3) Restricted redundant systems. As the majority of coping mechanisms are related to increasing communication and analog fall back, our findings point to the importance of customizing coping mechanisms for individual healthcare institutions. [ABSTRACT FROM AUTHOR]

Health information systems (HIS) and clinical workflows generate medication errors that affect the quality of patient care. The rigorous evaluation of the medication process’s error risk, control, and impact on clinical practice enable the understanding of latent and active factors that contribute to HIS-induced errors. This paper reports the preliminary findings of an evaluation case study of a 1000- bed Japanese secondary care teaching hospital using observation, interview, and document analysis methods. Findings were analysed from a process perspective by adopting a recently introduced framework known as Human, Organisation, Process, and Technology-fit. Process factors influencing risk in medication errors include template- and calendar-based systems, intuitive design, barcode check, ease of use, alert, policy, systematic task organisation, and safety culture Approaches for managing medication errors also exert an important role on error reduction and clinical workflow. [ABSTRACT FROM AUTHOR]

The web portal Medfloss.org lists over 360 medical free/libre and open source software (MEDFLOSS) projects. These projects are described with the help of a self-developed nomenclature. Due to inconsistencies, the nomenclature shall be replaced by HITO, the Health IT Ontology. HITO is developed iteratively based on different use cases. This paper aims to describe methods and results of the second HITO use case in which HITO is extended to improve the description, retrieval and comparisons of MEDFLOSS projects on Medfloss.org. We use a mixed-methods approach to add concepts and relationships to describe MEDFLOSS precisely. The resulting HITO version stresses functional descriptions based on features and supported enterprise functions, rather than just describing technical characteristics. However, describing a larger number of MEDFLOSS projects requires the commitment of the community. [ABSTRACT FROM AUTHOR]

Background: Assessing Mental Workload related to Health Information Systems can help to analyze weak points of the use of Health Information Systems and in health care work processes. Our objectives were to give an overview of current research and applied measurement methods as well as gaining insights into influencing factors of mental workload on the use of health information systems and vice versa. Methods: We applied a structured literature research by searching for "mental workload" on PubMed. Studies were included into our review if they assessed related to Health Information Systems. Results: The research in PubMed led to 124 articles, resulting in 17 papers taken into in-depth analyses. We identified three categories referring to different study design types. Additionally, articles showed that mental workload was influenced by using health information systems and vice versa. Discussion: The review was limited to only one database but revealed that future research with sociotechnical focus including mental workload is necessary. Conclusion: In contrast to the high relevance only a few articles address mental workload in Health Information systems. The quality of the studies in terms of evidence and external validity appears to be largely in need of development and should be improved in ongoing research. [ABSTRACT FROM AUTHOR]

Phenotyping means the determination of clinical relevant phenotypes, e.g. by classification or calculation based on EHR data. Within the German Medical Informatics Initiative, the SMITH consortium is working on the implementation of a phenotyping pipeline. to extract, structure and normalize information from the EHR data of the hospital information systems of the participating sites; to automatically apply complex algorithms and models and to enrich the data within the research data warehouses of the distributed data integration centers with the computed results. Here we present the overall picture and essential building blocks and workflows of this concept. [ABSTRACT FROM AUTHOR]

Digital health is widely believed to have vast potential in improving patient care. MyHealthRecord (MyHR) is a digital health information system which enables Australian citizens to access their health information centrally, making it available anywhere, at anytime. The aim of this study is to explore the adoption of MyHR in general practices in Victoria and understand its impacts. A qualitative case study research method was used to underpin this investigation. Ten general practices were engaged where MyHR was implemented/used. Detailed interviews with MyHR implementers were held and GPs were engaged in short interviews. Twenty observations were made during GP/patient consultations for health summary uploads. Findings indicate that the practice incentive payment (PIP) funding policy change encouraged the use of MyHR, but the adoption was limited to satisfy funding criteria. Change management was often extemporised. Health summary upload was a quick and easy process but was influenced by clinical system data quality and GP familiarity with the system. Community awareness and GP interest in MyHR was lacking. The conclusion is that MyHR was not well integrated in general practices nor the community. As a result, an improved engagement approach between healthcare organisations, the MyHR system operator and Australians is required. [ABSTRACT FROM AUTHOR]

Although e-health is an area recognized as essential in the rapid development of healthcare systems in low resource contexts, many challenges prevent the emergence of an effective e-health ecosystem. Lack in capacity around health informatics is one of the main challenges. Based on a longitudinal case study gathering data pertaining to a master's program in biomedical informatics in Sri Lanka designed for doctors, in this paper we demonstrate that creating 'hybrid doctors' may be the way forward. We illustrate how hybrid doctors conversant in healthcare and information and communication technology (ICT) are able to facilitate the creation of an ehealth ecosystem in a way that it would contribute significantly to the ICT driven healthcare reforms. Through this case study we highlight the importance of multidisciplinarity, participatory design, strategic investments, learning that aligns with developmental needs, networking, gaining legitimacy and re-packaging perspectives on 'health informatics capacity development'. [ABSTRACT FROM AUTHOR]

Detection of difficult for understanding words is a crucial task for ensuring the proper understanding of medical texts such as diagnoses and drug instructions. We propose to combine supervised machine learning algorithms using various features with word embeddings which contain context information of words. Data in French are manually cross-annotated by seven annotators. On the basis of these data, we propose crossvalidation scenarios in order to test the generalization ability of models to detect the difficulty of medical words. On data provided by seven annotators, we show that the models are generalizable from one annotator to another. [ABSTRACT FROM AUTHOR]

Enterprise Architecture allows addressing technologies and processes in a holistic way and mirrors choices related to process standardization and data integration. It has the potential to address long-standing problems in health information systems related to fragmented IT portfolios, immature IT infrastructures, and silo-structured organizing. Nevertheless, uptake of Enterprise Architecture in hospitals has been slow. To understand the issues related to this slow uptake we have undertaken an interview study with architects and managers. The issues identified reveal a level of incongruence between healthcare as a domain and the practice of EA. Specifically, by analyzing the experiences of architects and managers we identified four different areas of such incongruence that create the need to reconcile a) Bottom-up vs. Top-down Planning b) Clinical vs. SystemsÂ' Knowledge, c) Local vs. Global Arrangements and d) Patient Safety vs. Patient Privacy. Building on prior related research we propose ways for resolving the incongruence issues identified. [ABSTRACT FROM AUTHOR]

The development of electronic services for healthcare presents challenges related to the effective cooperation of systems and stakeholders in a highly regulated environment. Assessing the interoperability maturity of the provided services helps to identify interoperability issues in public administration. This paper presents a typical healthcare digital service: the inpatient admission in a public hospital in Greece. The Interoperability Maturity Model (IMM) is applied to assess its maturity, identify improvement priorities, and compare it with digital services of the healthcare sector. An analysis is also performed to compare a group of fourteen healthcare digital public services with sixty-seven public services of other sectors in the country. The IMM is a useful tool to facilitate awareness raising and priority setting concerning interoperability in public administration. What is discovered, through this preliminary assessment, is that healthcare digital services seem to have higher overall interoperability maturity than those of other sectors in Greece. [ABSTRACT FROM AUTHOR]

It is widely anticipated that the use and analysis of health-related big data will enable further understanding and improvements in human health and wellbeing. Here, we propose an innovative infrastructure, which supports secure and privacy-preserving analysis of personal health data from multiple providers with different governance policies. Our objective is to use this infrastructure to explore the relation between Type 2 Diabetes Mellitus status and healthcare costs. Our approach involves the use of distributed machine learning to analyze vertically partitioned data from the Maastricht Study, a prospective population-based cohort study, and data from the official statistics agency of the Netherlands, Statistics Netherlands (Centraal Bureau voor de Statistiek; CBS). This project seeks an optimal solution accounting for scientific, technical, and ethical/legal challenges. We describe these challenges, our progress towards addressing them in a practical use case, and a simulation experiment. [ABSTRACT FROM AUTHOR]

Objective: To characterize the scientific reproducibility of biomedical research studies by query and analysis of semantic provenance graphs generated from provenance metadata terms extracted from PubMed articles. Methods. We develop a new semantic provenance graph generation algorithm that uses a provenance ontology developed as part of the Provenance for Clinical and Health Research (ProvCaRe) project. The ProvCaRe project has processed and extracted provenance metadata from more than 1.6 million full text articles from the PubMed database. Results. The semantic provenance graph generation algorithm is evaluated using provenance terms extracted from 75 selected articles describing sleep medicine research studies. In addition, we use eight provenance queries to evaluate the quality of semantic provenance graphs generated by the new algorithm. Conclusion. The ProvCaRe project has created a unique resource to characterize the reproducibility of biomedical research studies and the semantic provenance graph generation algorithm enables users to effectively query and analyze the provenance metadata in the ProvCaRe knowledge repository. [ABSTRACT FROM AUTHOR]

Although e-health is an area recognized as essential in the rapid development of healthcare systems in low resource contexts, many challenges prevent the emergence of an effective e-health ecosystem. Lack in capacity around health informatics is one of the main challenges. Based on a longitudinal case study gathering data pertaining to a master's program in biomedical informatics in Sri Lanka designed for doctors, in this paper we demonstrate that creating 'hybrid doctors' may be the way forward. We illustrate how hybrid doctors conversant in healthcare and information and communication technology (ICT) are able to facilitate the creation of an ehealth ecosystem in a way that it would contribute significantly to the ICT driven healthcare reforms. Through this case study we highlight the importance of multidisciplinarity, participatory design, strategic investments, learning that aligns with developmental needs, networking, gaining legitimacy and re-packaging perspectives on 'health informatics capacity development'. [ABSTRACT FROM AUTHOR]

Detection of difficult for understanding words is a crucial task for ensuring the proper understanding of medical texts such as diagnoses and drug instructions. We propose to combine supervised machine learning algorithms using various features with word embeddings which contain context information of words. Data in French are manually cross-annotated by seven annotators. On the basis of these data, we propose crossvalidation scenarios in order to test the generalization ability of models to detect the difficulty of medical words. On data provided by seven annotators, we show that the models are generalizable from one annotator to another. [ABSTRACT FROM AUTHOR]

Enterprise Architecture allows addressing technologies and processes in a holistic way and mirrors choices related to process standardization and data integration. It has the potential to address long-standing problems in health information systems related to fragmented IT portfolios, immature IT infrastructures, and silo-structured organizing. Nevertheless, uptake of Enterprise Architecture in hospitals has been slow. To understand the issues related to this slow uptake we have undertaken an interview study with architects and managers. The issues identified reveal a level of incongruence between healthcare as a domain and the practice of EA. Specifically, by analyzing the experiences of architects and managers we identified four different areas of such incongruence that create the need to reconcile a) Bottom-up vs. Top-down Planning b) Clinical vs. Systems´ Knowledge, c) Local vs. Global Arrangements and d) Patient Safety vs. Patient Privacy. Building on prior related research we propose ways for resolving the incongruence issues identified. [ABSTRACT FROM AUTHOR]

The development of electronic services for healthcare presents challenges related to the effective cooperation of systems and stakeholders in a highly regulated environment. Assessing the interoperability maturity of the provided services helps to identify interoperability issues in public administration. This paper presents a typical healthcare digital service: the inpatient admission in a public hospital in Greece. The Interoperability Maturity Model (IMM) is applied to assess its maturity, identify improvement priorities, and compare it with digital services of the healthcare sector. An analysis is also performed to compare a group of fourteen healthcare digital public services with sixty-seven public services of other sectors in the country. The IMM is a useful tool to facilitate awareness raising and priority setting concerning interoperability in public administration. What is discovered, through this preliminary assessment, is that healthcare digital services seem to have higher overall interoperability maturity than those of other sectors in Greece. [ABSTRACT FROM AUTHOR]

It is widely anticipated that the use and analysis of health-related big data will enable further understanding and improvements in human health and wellbeing. Here, we propose an innovative infrastructure, which supports secure and privacy-preserving analysis of personal health data from multiple providers with different governance policies. Our objective is to use this infrastructure to explore the relation between Type 2 Diabetes Mellitus status and healthcare costs. Our approach involves the use of distributed machine learning to analyze vertically partitioned data from the Maastricht Study, a prospective population-based cohort study, and data from the official statistics agency of the Netherlands, Statistics Netherlands (Centraal Bureau voor de Statistiek; CBS). This project seeks an optimal solution accounting for scientific, technical, and ethical/legal challenges. We describe these challenges, our progress towards addressing them in a practical use case, and a simulation experiment. [ABSTRACT FROM AUTHOR]

Objective: To characterize the scientific reproducibility of biomedical research studies by query and analysis of semantic provenance graphs generated from provenance metadata terms extracted from PubMed articles. Methods. We develop a new semantic provenance graph generation algorithm that uses a provenance ontology developed as part of the Provenance for Clinical and Health Research (ProvCaRe) project. The ProvCaRe project has processed and extracted provenance metadata from more than 1.6 million full text articles from the PubMed database. Results. The semantic provenance graph generation algorithm is evaluated using provenance terms extracted from 75 selected articles describing sleep medicine research studies. In addition, we use eight provenance queries to evaluate the quality of semantic provenance graphs generated by the new algorithm. Conclusion. The ProvCaRe project has created a unique resource to characterize the reproducibility of biomedical research studies and the semantic provenance graph generation algorithm enables users to effectively query and analyze the provenance metadata in the ProvCaRe knowledge repository. [ABSTRACT FROM AUTHOR]

Information quality has an important role in health care as digital services provide patients and healthcare professionals more opportunities for searching and utilising information. Information quality is one of the key factors affecting user satisfaction, perception of digital service usability and intention to use the service. The conceptual framework for this study was the updated Information Systems Success Model of DeLone and McLean. The study was conducted in the context of Health Village, a digital interactive and secured portal providing health services to patients and citizens. The purpose of the study was to survey health professionals' perception (n = 91) of information quality and its effect on user satisfaction. Concerns were raised about the interoperability of the portal with other health information systems and the ease of finding information. Generally, in the Health Village portal, information quality was considered relatively high. [ABSTRACT FROM AUTHOR]

Despite the advances in health information technology and the increasing usage of electronic systems, syntactic and semantic interoperability between different health information systems remains challenging. An emerging standard to tackle interoperability issues is HL7 FHIR, which uses modern web technologies for communication like Representational State Transfer. The electronic patient reported outcome system Mobile Patient Survey (MoPat) was adapted to support metadata import and clinical data export using HL7 FHIR. Thereby, the data models of HL7 FHIR and MoPat were compared and the existing import and export functions of MoPat were extended to support HL7 FHIR. A test protocol including eight test datasets to proof functioning of the new features was successfully conducted. In the near future, a real time searching toolbar of FHIR metadata resources will be integrated within MoPat. MoPat FHIR import and export functions are ready to be used in a clinical setting in combination with a FHIR compliant clinical data server. [ABSTRACT FROM AUTHOR]

EHRs elicit an array of different aspirations all underpinned by the widely held conviction that they can deliver benefits for patients, clinicians, researchers, IT vendors, policy-makers and society as a whole. While techno-centric visions abound, reflection on their history, the challenges evident in their design, implementation and evaluation and the limited evidence of their beneficial impacts over time is instructive. From a socio-technical perspective EHRs appear to be a set of 'wicked problems' unlikely to be resolved in favor of one position or another, but rather requiring judgement, nuance and negotiation around the kinds of problems we want these systems to solve. This paper presents some perspectives on important potential features for next generation EHRs and on the types of problems that these systems could aspire to solve. The focus is not on prediction but rather on actively shaping the kind of future that we desire and how EHRs will support its achievement. [ABSTRACT FROM AUTHOR]

Background: Patient safety is an important issue and receiving increasing attention. Information technology (IT) and IT-based strategies as the secondary use of already existing data within hospital information systems can help to improve patient safety. Objective: To investigate experts' knowledge and opinions regarding relevant patient safety problems, their measurability in existing clinical routine data and potential challenges in the field. We also wanted to get an overview of already deployed indicators for patient safety. Methods: Semi structured interviews with 20 experts from different healthcare domains were conducted and analyzed using a qualitative content analysis methodology. Results: The expert interviews offered a deeper insight into patient safety and quarried relevant patient safety problems including possibilities to measure them. The most often mentioned indicators were infection, complication and pressure ulcer. Conclusion: From an experts' perspective there are several challenges but equally a high potential for improving patient safety by the use of health IT. [ABSTRACT FROM AUTHOR]

In this communication we identify strategies for effectively documenting Sexual Orientation and Gender Identity in Electronic Health Records. For this review a multidisciplinary group composed by three physicians, a nurse, an engineer and a lawyer analyzed the evidence in bibliography related to the topic and summarized the results. After analyzing the information, we summarized and classified them into three major topics: To request, to store and to display and access to the information. How to standardize those data and where data specifically will be populated in EHRs have not been answered yet. The target of all of these efforts should be: to be sensitive with the needs of the patient and to ensure high quality of care. [ABSTRACT FROM AUTHOR]

Cancer surveillance is a process of systematic, continuous collection, storage, analysis, interpretation and dissemination of epidemiological information on cancer cases occurring in a particular geographic area. The process of cancer surveillance is also called ‘cancer registration’. A system to conduct cancer registration is called ‘cancer registry’. The purpose of the project is to implement cancer registry informatics to enhance electronic cancer registry reporting activities that take advantage of emerging health information technology. The expected function of the application is to strengthen the cancer registry data accuracy, completeness, and timeliness. The goals to be achieved are: determine the incidence of cancers with respect to geographic, demographic characteristics; monitor trends and patterns of cancer incidences over time; identify high-risk populations; provide data for epidemiological studies and prioritize health resource allocations. [ABSTRACT FROM AUTHOR]

Recent focus on Precision medicine (PM) has led to a flurry of research activities across the developed world. But how can understaffed and underfunded health care systems in the US and elsewhere evolve to adapt PM to address pressing healthcare needs? We offer guidance on a wide range of sources of healthcare data / knowledge as well as other infrastructure / tools that could inform PM initiatives, and may serve as low hanging fruit easily adapted on the incremental pathway towards a PM based healthcare system. Using these resources and tools, we propose an incremental adoption pathway to inform implementers working in underserved communities around the world on how they should position themselves to gradually embrace the concepts of PM with minimal interruption to existing care delivery. [ABSTRACT FROM AUTHOR]

Persistent problems with healthcare IT that is unusable and unsafe have been reported worldwide. In this paper we present our vision for deploying usability engineering in healthcare in a more substantive way in order to improve the current situation. The argument will be made that stronger and more substantial efforts need to be made to bring multiple usability engineering methods to bear on points in both system design and deployment (and not just as a one-time effort restricted to software product development). In addition, improved processes for ensuring the usability of commercial vendor-based systems being implemented in healthcare organizations need to be addressed. A discussion will also be provided on challenges and barriers that will need to be overcome to ensure that the heatlhcare IT that is released is both usable and safe. [ABSTRACT FROM AUTHOR]

Unique patient identification within health services is an operational challenge in healthcare settings. Use of key identifiers, such as patient names, hospital identification numbers, national ID, and birth date are often inadequate for ensuring unique patient identification. In addition, approximate string comparator algorithms, such as distancebased algorithms, have proven suboptimal for improving patient matching, especially in low-resource settings. Biometric approaches may improve unique patient identification. However, before implementing the technology in a given setting, such as health care, the right scanners should be rigorously tested to identify an optimal package for the implementation. This study aimed to investigate the effects of factors such as resolution, template size, and scan capture area on the matching performance of different fingerprint scanners for use within health care settings. Performance analysis of eight different scanners was tested using the demo application distributed as part of the Neurotech Verifinger SDK 6.0. [ABSTRACT FROM AUTHOR]

The increasing use of electronic health information systems brings up an unresolved issue: the lack of interoperability between these systems. The Clinical Data Interchange Standards Consortium’s Operational Data Model (ODM) is an xml based standard for the exchange of clinical data and metadata. The University of Münster has been using ODM to store medical forms in a web based metadata registry called Portal of Medical Data Models, which includes a complete set of tools to transform ODM forms into other formats. One kind of medical form is the Patient Reported Outcome, a trending type due to its easy integration with mobile data capture systems. ResearchKit is a development framework that allows the easy creation of these for iOS devices; unfortunately its current interoperability is limited. This research proposes a mapping between ODM and ResearchKit and presents the successful implementation of a converter for ODM into JSON based ResearchKit readable files. [ABSTRACT FROM AUTHOR]

The rise of distributed ledger technology, initiated and exemplified by the Bitcoin blockchain, is having an increasing impact on information technology environments in which there is an emphasis on trust and security. Management of electronic health records, where both conformation to legislative regulations and maintenance of public trust are paramount, is an area where the impact of these new technologies may be particularly beneficial. We present a system that enables finegrained personalized control of third-party access to patients’ electronic health records, allowing individuals to specify when and how their records are accessed for research purposes. The use of the smart contract based Ethereum blockchain technology to implement this system allows it to operate in a verifiably secure, trustless, and openly auditable environment, features crucial to health information systems moving forward. [ABSTRACT FROM AUTHOR]

In this paper, the authors outline a vision for the future of mobile usability, workflow and safety testing. The authors argue for the use of glasses that can audio and video record usability, workflow and safety data. Here, citizens, patients and health professionals would become collectors of study data as they use mobile devices and software to support healthcare in the real world. This has become quite feasible with the introduction of low-cost glasses and software applications that allow for the uploading of data for additional analysis by researchers and evaluators of mobile technologies. [ABSTRACT FROM AUTHOR]