Secondary Use Of Patient Data Research Articles

National standardisierter Broad Consent in der Praxis: erste Erfahrungen, aktuelle Entwicklungen und kritische Betrachtungen

ZusammenfassungHintergrundDie Digitalisierung im Gesundheitswesen verspricht eine Sekundärnutzung von Patientendaten im Sinne eines lernenden Gesundheitssystems. Die Arbeitsgruppe Consent der Medizininformatik-Initiative (MII) hat mit einheitlichen Einwilligungsdokumenten eine ethische und rechtliche Grundlage hierfür geschaffen. Beschrieben wird die systematisch begleitete Einführung dieser Dokumente an den Standorten der MII.MethodenDie Begleitung der Einführung umfasste regelmäßige Online-Umfragen, die vertiefte Analyse der Einführungsprozesse an ausgewählten Standorten sowie die Untersuchung der jeweils eingesetzten Dokumente. Zudem wurden Anfragen und Rückmeldungen einer Vielzahl von Stakeholdern ausgewertet.ErgebnisseDie Online-Umfragen ergaben, dass 27 der 32 befragten Standorte nach und nach die Einwilligungsdokumente produktiv eingeführt haben, mit aktuell insgesamt 173.289 Einwilligungen. Die Analyse der Umsetzungsverfahren offenbarte heterogene organisatorische Rahmenbedingungen an den Standorten. Anforderungen verschiedener Stakeholder konnten durch die Erarbeitung und Bereitstellung ergänzender Versionen der Einwilligungsdokumente und zusätzlicher Informationsmaterialien erfüllt werden.DiskussionDie Einführung der Einwilligungsdokumente der MII an den Universitätskliniken schafft eine einheitliche Rechtsgrundlage für die Sekundärnutzung von Patientendaten. Die flächendeckende Implementierung innerhalb der Standorte bleibt jedoch herausfordernd. Minimalanforderungen an die Patientenaufklärung und ergänzende Best-Practice-Empfehlungen sind hierfür zu erarbeiten. Die Weiterentwicklung des nationalen Rechtsrahmens für die Forschung wird die hier entwickelten Mitsprache- und Transparenzmechanismen für Betroffene nicht obsolet machen.

How to Make Outpatient Healthcare Data in Germany Available for Research in the Dynamic Course of Digital Transformation.

There is increasing interest on re-use of outpatient healthcare data for research, as most medical diagnosis and treatment is provided in the ambulatory sector. One of the early projects to bring primary data from German ambulatory care into clinical research technically, organizationally and in compliance with legal demands has been the RADAR project, that is based on a broad consent and has used the then available practice information system's interfaces to extract and transfer data to a research repository. In course of the digital transformation of the German healthcare system, former standards are abandoned and new interoperability standards, interfaces and regulations on secondary use of patient data are defined, however with slow adoption by Health-IT systems. Therefore, it is of importance for all initiatives that aim at using ambulatory healthcare data for research, how to access this data in an efficient and effective way. Currently defined healthcare standards are compared regarding coverage of data relevant for research as defined by the RADAR project. We compare four architectural options to access ambulatory health data through different components of healthcare and health research data infrastructures along the technical, organizational and regulatory conditions, the timetable of dissemination and the researcher's perspective. A high-level comparison showed a high degree of semantic overlap in the information models used. Electronic patient records and practice information systems are alternative data sources for ambulatory health data - but differ strongly in data richness and accessibility. Considering the compared dimensions of architectural routes to access health data for secondary research use we conclude that data extraction from practice information systems is currently the most promising way due to data availability on a mid-term perspective. Integration of routine data into the national research data infrastructures might be enforced by convergence of to date different information models.

Epidemiology of ocular emergencies in a large Canadian eye centre

ObjectifLa clinique ophtalmologique d'urgence de l'Institut oculaire de l'Alberta (EIA, pour Eye Institute of Alberta) est un centre de soins tertiaires qui procure des soins ophtalmologiques d'urgence à une population de plus de 1 million de personnes. Notre étude avait pour objectif de décrire l’épidémiologie des urgences oculaires de cette clinique. NatureÉtude épidémiologique prospective fondée sur une utilisation secondaire des données de patients. ParticipantsTous les patients examinés à la clinique ophtalmologique d'urgence de l'EIA en semaine de juillet 2020 à juin 2021. MéthodesLes données démographiques des patients, le motif d'orientation vers la clinique, les diagnostics finaux, les besoins en matière d'imagerie, les interventions d'urgence ou les renvois ultérieurs vers une autre ressource médicale ont été tirés des dossiers des patients. Le logiciel SPSS Statistics a servi à réaliser l'analyse des données. RésultatsAu total, 2586 patients ont été examinés pendant la période à l’étude. Dans la plupart des cas (58 %), ce sont des urgentologues qui ont adressé les patients à la clinique. Les optométristes et les généralistes, pour leur part, ont adressé 14 % et 11 % des patients, respectivement. La plupart des diagnostics des patients ainsi dirigés à la clinique relevaient d'une inflammation (32 %) et d'un traumatisme (22 %). Les cas d'inflammation se déclinaient comme suit : 41 % d'infections oculaires et 8 % d'infections des annexes oculaires. De plus, 44 % et 7 % des cas présentaient une inflammation non infectieuse des yeux et des annexes oculaires, respectivement. Au nombre des interventions d'urgence souvent réalisées, citons le retrait d'un corps étranger dans la cornée ou la conjonctive (39 %) et le grattage cornéen (14 %). ConclusionsLes urgentologues, les généralistes et les optométristes pourraient tirer grand profit d'une formation continue sur les soins oculaires d'urgence portant sur les catégories diagnostiques les plus fréquentes, comme l'inflammation et les traumatismes. Il serait également être utile de mettre sur pied des programmes de formation ciblée à l'intention du grand public sur la prévention des traumatismes et des infections, qui feraient par exemple la promotion du port de lunettes de protection et de l'hygiène des lentilles cornéennes.

Health Research with Data in a Time of Privacy: Which Information do Patients Want?

When hospitals ask broad consent for the secondary use of patient data for scientific research, it is unknown for which studies the data will be used. We investigated what patients at a cancer hospital consider to be an adequate level and most suitable method of information provision using questionnaires (n = 71) and interviews (n = 24). A part of the respondents indicated that they would feel sufficiently informed by either being notified about potential further use, or by receiving a general brochure before being asked for consent. Others stated that additional information would be interesting and appreciated. Yet, when discussing required resources needed to provide additional information, interviewees lowered the bar of what they considered minimally required, voicing the importance of spending resources on research.

Generating evidence on privacy outcomes to inform privacy risk management: A way forward?

Effective and efficient privacy risk management (PRM) is a necessary condition to support digitalization in health care and secondary use of patient data in research. To reduce privacy risks, current PRM frameworks are rooted in an approach trying to reduce undesired technical/organizational outcomes such as broken encryption or unintentional data disclosure. Comparing this with risk management in preventive or therapeutic medicine, a key difference becomes apparent: in health-related risk management, medicine focuses on person-specific health outcomes, whereas PRM mostly targets more indirect, technical/organizational outcomes. In this paper, we illustrate and discuss how a PRM approach based on evidence of person-specific privacy outcomes might look using three consecutive steps: i) a specification of undesired person-specific privacy outcomes, ii) empirical assessments of their frequency and severity, and iii) empirical studies on how effectively the available PRM interventions reduce their frequency or severity. After an introduction of these three steps, we cover their status quo and outline open questions and PRM-specific challenges in need of further conceptual clarification and feasibility studies. Specific challenges of an outcome-oriented approach to PRM include the potential delays between concrete threats manifesting and the resulting person/group-specific privacy outcomes. Moreover, new ways of exploiting privacy-sensitive information to harm individuals could be developed in the future. The challenges described are of technical, legal, ethical, financial and resource-oriented nature. In health research, however, there is explicit discussion about how to overcome such challenges to make important outcome-based assessments as feasible as possible. This paper concludes that it might be the time to have this discussion in the PRM field as well.

Biobanks, translational research and medical informatics

When we think of medical research, one intuitively associates it with the analysis of study data collected for aspecific research question or with the secondary use of patient data from routine care. However, these are not the only sources for answering scientific questions. Especially for translational research, tissue and liquid samples such as blood, DNA or other body fluids provide essential insights into disease pathogenesis, development of new therapies and treatment decisions. Access to these biomedical materials is provided by so-called biobanks. By collecting, characterizing, documenting and, if necessary, processing human biospecimens in accordance with high quality standards, they can support research of the causes of diseases, early diagnosis and the targeted treatment of diseases, or make asignificant contribution to the investigation of common diseases.

Construction of text resources for automatic identification of clinical information in unstructured narratives

A significant proportion of the clinical record is in free text format, making it difficult to extract key information and make secondary use of patient data. Automatic detection of information within narratives initially requires humans, following specific protocols and rules, to identify medical entities of interest. To build a linguistic resource of annotated medical entities on texts produced in Chilean hospitals. A clinical corpus was constructed using 150 referrals in public hospitals. Three annotators identified six medical entities: clinical findings, diagnoses, body parts, medications, abbreviations, and family members. An annotation scheme was designed, and an iterative approach to train the annotators was applied. The F1-Score metric was used to assess the progress of the annotator's agreement during their training. An average F1-Score of 0.73 was observed at the beginning of the project. After the training period, it increased to 0.87. Annotation of clinical findings and body parts showed significant discrepancy, while abbreviations, medications, and family members showed high agreement. A linguistic resource with annotated medical entities on texts produced in Chilean hospitals was built and made available, working with annotators related to medicine. The iterative annotation approach allowed us to improve performance metrics. The corpus and annotation protocols will be released to the research community.

Development and Usability Analysis of a Multimedia eConsent Solution.

More and more medical data is being stored digitally in routine care. The secondary use of patient data is only possible to a limited extent for data protection reasons. In order to enable a long-term and far-reaching use of secondary data, a possible approach is to obtain "broad consent" from patients, e.g. on research projects whose purpose is still unknown at the time of consent. To develop and evaluate an interactive eConsent prototype that presents the extensive contents of the "broad consent" in multimedia form for the purpose of a successful and resource-efficient information and consent process. The eConsent prototype was designed on basis of a literature review and in accordance with the goals of the German medical informatics initiative. User tests and subsequent questionnaire surveys using the System Usability Scale (SUS) were carried out with patients from a university hospital to assess the prototype's usability. The study was conducted in a quasi-experimental, one-group posttest-only design. The created interactive prototype can present the contents acoustically and visually and offers the possibility to retrieve additional information. With a SUS score of 84,1/100 the results indicate a very good usability of the prototype. The next steps will include further refinements of the prototype based on the feedback received and a subsequent study with a broader user group aimed at introducing an eConsent tool as part of a patient portal.

A Review of Recent Advances in Translational Bioinformatics: Bridges from Biology to Medicine

Summary Objectives: To highlight and provide insights into key developments in translational bioinformatics between 2014 and 2016. Methods: This review describes some of the most influential bioinformatics papers and resources that have been published between 2014 and 2016 as well as the national genome sequencing initiatives that utilize these resources to routinely embed genomic medicine into healthcare. Also discussed are some applications of the secondary use of patient data followed by a comprehensive view of the open challenges and emergent technologies. Results: Although data generation can be performed routinely, analyses and data integration methods still require active research and standardization to improve streamlining of clinical interpretation. The secondary use of patient data has resulted in the development of novel algorithms and has enabled a refined understanding of cellular and phenotypic mechanisms. New data storage and data sharing approaches are required to enable diverse biomedical communities to contribute to genomic discovery. Conclusion: The translation of genomics data into actionable knowledge for use in healthcare is transforming the clinical landscape in an unprecedented way. Exciting and innovative models that bridge the gap between clinical and academic research are set to open up the field of translational bioinformatics for rapid growth in a digital era.

Secondary Use of Recorded or Self-expressed Personal Data: Consumer Health Informatics and Education in the Era of Social Media and Health Apps

Summary Objective: To summarize the state of the art during the year 2016 in the areas related to consumer health informatics and education with a special emphasis in secondary use of patient data. Methods: We conducted a systematic review of articles published in 2016, using PubMed with a predefined set of queries. We identified over 320 potential articles for review. Papers were considered according to their relevance for the topic of the section. Using consensus, we selected the 15 most representative papers, which were submitted to external reviewers for full review and scoring. Based on the scoring and quality criteria, five papers were finally selected as best papers Results: The five best papers can be grouped in two major areas: 1) methods and tools to identify and collect formal requirements for secondary use of data, and 2) innovative topics highlighting the interest of carrying on “secondary” studies on patient data, more specifically on the data self-expressed by patients through social media tools. Regarding the formal requirements about informed consent, the selected papers report a comparison of legal aspects in European countries to find a common and unified grammar around the concept of “data donation”. Regarding innovative approaches to value patient data, the selected papers report machine learning algorithms to extract knowledge from patient experience and satisfaction with health care delivery, drug and medication use, treatment compliance and barriers during cancer disease, or acceptation of public health actions such as vaccination. Conclusions: Secondary use of patient data (apart from personal health care record data) can be expressed according to many ways. Requirements to allow this secondary use have to be harmonized between countries, and social media platforms can be efficiently used to explore and create knowledge on patient experience with health problems or activities. Machine learning algorithms can explore those massive amounts of data to support health care professionals, and institutions provide more accurate knowledge about use and usage, behaviour, sentiment, or satisfaction about health care delivery.

Health Information Management: Changing with Time

Summary Objective: With the evolution of patient medical records from paper to electronic media and the changes to the way data is sourced, used, and managed, there is an opportunity for health information management (HIM) to learn and facilitate the increasing expanse of available patient data. Methods: This paper discusses the emerging trends and lessons learnt in relation with the following four areas: 1) data and information governance, 2) terminology standards certification, 3) International Classification of Diseases, 11th edition (ICD-11), and 4) data analytics and HIM. Results: The governance of patient data and information increasingly requires the HIM profession to incorporate the roles of data scientists and data stewards into its portfolio to ensure data analytics and digital transformation is appropriately managed. Not only are terminology standards required to facilitate the structure and primary use of this data, developments in Canada in relation with the standards, role descriptions, framework and curricula in the form of certification provide one prime example of ensuring the quality of the secondary use of patient data. The impending introduction of ICD-11 brings with it the need for the HIM profession to manage the transition between ICD versions and country modifications incorporating changes to standards and tools, and the availability and type of patient data available for secondary use. Conclusions: In summary, the health information management profession now requires abilities in leadership, data, and informatics in addition to health information science and coding skills to facilitate the expanding secondary use of patient data.

Transforming Data into Knowledge: How to Improve the Efficiency of Clinical Care?

Summary Objectives: To provide an introduction to the 2017 IMIA Yearbook of Medical Informatics by the editors. Methods: We present a brief overview of the 2017 special topic “Learning from experience: Secondary use of patient data”. We review our choice of special topic section editors, present the new section “Health Information Management”, and discuss transitions in the editorial team. Results: In this edition of the Yearbook, we focused on one of the most important issues for the medical informatics community: The secondary use of clinical data. With the ubiquitous adoption of electronic health records (EHRs) and the increasing availability of genomic and environmental data, as well as the accessibility of unstructured data in social media, issues related to data integration, storage, and management, as well as the need for novel analytic approaches are clear challenges. The paradigm of Learning Health Systems (LHSs) is presented in the keynote paper and survey papers review the significant developments in allied fields such as clinical research, clinical systems, translational informatics, and public health over the past two years. IMIA Working Groups also contributed to this topic. Conclusion: The 2017 issue of the IMIA yearbook focuses on the secondary use of patient data and presents the difficulties that still need to be solved before witnessing the actual development of LHSs.

Secondary Use of Patient Data: Review of the Literature Published in 2016

Summary Objectives: To summarize recent research and emerging trends in the area of secondary use of healthcare data, and to present the best papers published in this field, selected to appear in the 2017 edition of the IMIA Yearbook. Methods: A literature review of articles published in 2016 and related to secondary use of healthcare data was performed using two bibliographic databases. From this search, 941 papers were identified. The section editors independently reviewed the papers for relevancy and impact, resulting in a consensus list of 14 candidate best papers. External reviewers examined each of the candidate best papers and the final selection was made by the editorial board of the Yearbook. Results: From the 941 retrieved papers, the selection process resulted in four best papers. These papers discuss data quality concerns, issues in preserving privacy of patients in shared datasets, and methods of decision support when consuming large amounts of raw electronic health record (EHR) data. Conclusion: In 2016, a significant effort was put into the development of new systems which aim to avoid significant human understanding and pre-processing of healthcare data, though this is still only an emerging area of research. The value of temporal relationships between data received significant study, as did effective information sharing while preserving patient privacy.

The Role of Free/Libre and Open Source Software in Learning Health Systems

Summary Objective: To give an overview of the role of Free/Libre and Open Source Software (FLOSS) in the context of secondary use of patient data to enable Learning Health Systems (LHSs). Methods: We conducted an environmental scan of the academic and grey literature utilising the MedFLOSS database of open source systems in healthcare to inform a discussion of the role of open source in developing LHSs that reuse patient data for research and quality improvement. Results: A wide range of FLOSS is identified that contributes to the information technology (IT) infrastructure of LHSs including operating systems, databases, frameworks, interoperability software, and mobile and web apps. The recent literature around the development and use of key clinical data management tools is also reviewed. Conclusions: FLOSS already plays a critical role in modern health IT infrastructure for the collection, storage, and analysis of patient data. The nature of FLOSS systems to be collaborative, modular, and modifiable may make open source approaches appropriate for building the digital infrastructure for a LHS.

Secondary Use of Patient Data: Review of the Literature Published in 2016.

Objectives: To summarize recent research and emerging trends in the area of secondary use of healthcare data, and to present the best papers published in this field, selected to appear in the 2017 edition of the IMIA Yearbook. Methods: A literature review of articles published in 2016 and related to secondary use of healthcare data was performed using two bibliographic databases. From this search, 941 papers were identified. The section editors independently reviewed the papers for relevancy and impact, resulting in a consensus list of 14 candidate best papers. External reviewers examined each of the candidate best papers and the final selection was made by the editorial board of the Yearbook. Results: From the 941 retrieved papers, the selection process resulted in four best papers. These papers discuss data quality concerns, issues in preserving privacy of patients in shared datasets, and methods of decision support when consuming large amounts of raw electronic health record (EHR) data. Conclusion: In 2016, a significant effort was put into the development of new systems which aim to avoid significant human understanding and pre-processing of healthcare data, though this is still only an emerging area of research. The value of temporal relationships between data received significant study, as did effective information sharing while preserving patient privacy.

Secondary Use and Analysis of Big Data Collected for Patient Care

Summary Objectives: To identify common methodological challenges and review relevant initiatives related to the re-use of patient data collected in routine clinical care, as well as to analyze the economic benefits derived from the secondary use of this data. Through the use of several examples, this article aims to provide a glimpse into the different areas of application, namely clinical research, genomic research, study of environmental factors, and population and health services research. This paper describes some of the informatics methods and Big Data resources developed in this context, such as electronic phenotyping, clinical research networks, biorepositories, screening data banks, and wide association studies. Lastly, some of the potential limitations of these approaches are discussed, focusing on confounding factors and data quality. Methods: A series of literature searches in main bibliographic databases have been conducted in order to assess the extent to which existing patient data has been repurposed for research. This contribution from the IMIA working group on “Data mining and Big Data analytics” focuses on the literature published during the last two years, covering the timeframe since the working group’s last survey. Results and Conclusions: Although most of the examples of secondary use of patient data lie in the arena of clinical and health services research, we have started to witness other important applications, particularly in the area of genomic research and the study of health effects of environmental factors. Further research is needed to characterize the economic impact of secondary use across the broad spectrum of translational research.

Health Information Management: Changing with Time

Objective: With the evolution of patient medical records from paper to electronic media and the changes to the way data is sourced, used, and managed, there is an opportunity for health information management (HIM) to learn and facilitate the increasing expanse of available patient data. Methods: This paper discusses the emerging trends and lessons learnt in relation with the following four areas: 1) data and information governance, 2) terminology standards certification, 3) International Classification of Diseases, 11th edition (ICD-11), and 4) data analytics and HIM. Results: The governance of patient data and information increasingly requires the HIM profession to incorporate the roles of data scientists and data stewards into its portfolio to ensure data analytics and digital transformation is appropriately managed. Not only are terminology standards required to facilitate the structure and primary use of this data, developments in Canada in relation with the standards, role descriptions, framework and curricula in the form of certification provide one prime example of ensuring the quality of the secondary use of patient data. The impending introduction of ICD-11 brings with it the need for the HIM profession to manage the transition between ICD versions and country modifications incorporating changes to standards and tools, and the availability and type of patient data available for secondary use. Conclusions: In summary, the health information management profession now requires abilities in leadership, data, and informatics in addition to health information science and coding skills to facilitate the expanding secondary use of patient data.

Secondary Use of Recorded or Self-expressed Personal Data: Consumer Health Informatics and Education in the Era of Social Media and Health Apps.

Objective: To summarize the state of the art during the year 2016 in the areas related to consumer health informatics and education with a special emphasis in secondary use of patient data. Methods: We conducted a systematic review of articles published in 2016, using PubMed with a predefined set of queries. We identified over 320 potential articles for review. Papers were considered according to their relevance for the topic of the section. Using consensus, we selected the 15 most representative papers, which were submitted to external reviewers for full review and scoring. Based on the scoring and quality criteria, five papers were finally selected as best papers Results: The five best papers can be grouped in two major areas: 1) methods and tools to identify and collect formal requirements for secondary use of data, and 2) innovative topics highlighting the interest of carrying on "secondary" studies on patient data, more specifically on the data self-expressed by patients through social media tools. Regarding the formal requirements about informed consent, the selected papers report a comparison of legal aspects in European countries to find a common and unified grammar around the concept of "data donation". Regarding innovative approaches to value patient data, the selected papers report machine learning algorithms to extract knowledge from patient experience and satisfaction with health care delivery, drug and medication use, treatment compliance and barriers during cancer disease, or acceptation of public health actions such as vaccination. Conclusions: Secondary use of patient data (apart from personal health care record data) can be expressed according to many ways. Requirements to allow this secondary use have to be harmonized between countries, and social media platforms can be efficiently used to explore and create knowledge on patient experience with health problems or activities. Machine learning algorithms can explore those massive amounts of data to support health care professionals, and institutions provide more accurate knowledge about use and usage, behaviour, sentiment, or satisfaction about health care delivery.

A Review of Recent Advances in Translational Bioinformatics: Bridges from Biology to Medicine.

Objectives: To highlight and provide insights into key developments in translational bioinformatics between 2014 and 2016. Methods: This review describes some of the most influential bioinformatics papers and resources that have been published between 2014 and 2016 as well as the national genome sequencing initiatives that utilize these resources to routinely embed genomic medicine into healthcare. Also discussed are some applications of the secondary use of patient data followed by a comprehensive view of the open challenges and emergent technologies. Results: Although data generation can be performed routinely, analyses and data integration methods still require active research and standardization to improve streamlining of clinical interpretation. The secondary use of patient data has resulted in the development of novel algorithms and has enabled a refined understanding of cellular and phenotypic mechanisms. New data storage and data sharing approaches are required to enable diverse biomedical communities to contribute to genomic discovery. Conclusion: The translation of genomics data into actionable knowledge for use in healthcare is transforming the clinical landscape in an unprecedented way. Exciting and innovative models that bridge the gap between clinical and academic research are set to open up the field of translational bioinformatics for rapid growth in a digital era.

The Role of Free/Libre and Open Source Software in Learning Health Systems.

Objective: To give an overview of the role of Free/Libre and Open Source Software (FLOSS) in the context of secondary use of patient data to enable Learning Health Systems (LHSs). Methods: We conducted an environmental scan of the academic and grey literature utilising the MedFLOSS database of open source systems in healthcare to inform a discussion of the role of open source in developing LHSs that reuse patient data for research and quality improvement. Results: A wide range of FLOSS is identified that contributes to the information technology (IT) infrastructure of LHSs including operating systems, databases, frameworks, interoperability software, and mobile and web apps. The recent literature around the development and use of key clinical data management tools is also reviewed. Conclusions: FLOSS already plays a critical role in modern health IT infrastructure for the collection, storage, and analysis of patient data. The nature of FLOSS systems to be collaborative, modular, and modifiable may make open source approaches appropriate for building the digital infrastructure for a LHS.