Cognitive and learning sciences in biomedical and health instructional design: A review with lessons for biomedical informatics education

Theoretical and methodological advances in the cognitive and learning sciences can greatly inform curriculum and instruction in biomedicine and also educational programs in biomedical informatics. It does so by addressing issues such as the processes related to comprehension of medical information, clinical problem-solving and decision-making, and the role of technology. This paper reviews these theories and methods from the cognitive and learning sciences and their role in addressing current and future needs in designing curricula, largely using illustrative examples drawn from medical education. The lessons of this past work are also applicable, however, to biomedical and health professional curricula in general, and to biomedical informatics training, in particular. We summarize empirical studies conducted over two decades on the role of memory, knowledge organization and reasoning as well as studies of problem-solving and decision-making in medical areas that inform curricular design. The results of this research contribute to the design of more informed curricula based on empirical findings about how people learn and think, and more specifically, how expertise is developed. Similarly, the study of practice can also help to shape theories of human performance, technology-based learning, and scientific and professional collaboration that extend beyond the domain of medicine. Just as biomedical science has revolutionized health care practice, research in the cognitive and learning sciences provides a scientific foundation for education in biomedicine, the health professions, and biomedical informatics.     

Cognitive informatics in biomedicine and healthcare

Cognitive Informatics (CI) is a burgeoning interdisciplinary domain comprising of the cognitive and information sciences that focuses on human information processing, mechanisms and processes within the context of computing and computer applications. Based on a review of articles published in the Journal of Biomedical Informatics (JBI) between January 2001 and March 2014, we identified 57 articles that focused on topics related to cognitive informatics. We found that while the acceptance of CI into the mainstream informatics research literature is relatively recent, its impact has been significant – from characterizing the limits of clinician problem-solving and reasoning behavior, to describing coordination and communication patterns of distributed clinical teams, to developing sustainable and cognitively-plausible interventions for supporting clinician activities. Additionally, we found that most research contributions fell under the topics of decision-making, usability and distributed team activities with a focus on studying behavioral and cognitive aspects of clinical personnel, as they performed their activities or interacted with health information systems. We summarize our findings within the context of the current areas of CI research, future research directions and current and future challenges for CI researchers.     

Envisioning the future of ‘big data’ biomedicine

Through the increasing availability of more efficient data collection procedures, biomedical scientists are now confronting ever larger sets of data, often finding themselves struggling to process and interpret what they have gathered. This, while still more data continues to accumulate. This torrent of biomedical information necessitates creative thinking about how the data are being generated, how they might be best managed, analyzed, and eventually how they can be transformed into further scientific understanding for improving patient care. Recognizing this as a major challenge, the National Institutes of Health (NIH) has spearheaded the “Big Data to Knowledge” (BD2K) program – the agency’s most ambitious biomedical informatics effort ever undertaken to date. In this commentary, we describe how the NIH has taken on “big data” science head-on, how a consortium of leading research centers are developing the means for handling large-scale data, and how such activities are being marshalled for the training of a new generation of biomedical data scientists. All in all, the NIH BD2K program seeks to position data science at the heart of 21^st Century biomedical research.     

Modeling in biomedical informatics: an exploratory analysis part 2

OBJECTIVE: Modeling is a significant part of research, education and practice in biomedical and health informatics. Our objective was to explore which types of models of processes are used in current biomedical/health informatics research, as reflected in publications of scientific journals in this field. Also, the implications for medical informatics curricula were investigated. METHODS: Retrospective, prolective observational study on recent publications of the two official journals of the International Medical Informatics Association (IMIA), the International Journal of Medical Informatics (IJMI) and Methods of Information in Medicine (MIM). All publications of the years 2004 and 2005 from these journals were indexed according to a given list of model types. Random samples out of these publications were analysed in more depth. RESULTS: Three hundred and eighty-four publications have been analysed, 190 of IJMI and 194 of MIM. For publications in special issues (121 in IJMI) and special topics (132 in MIM) we found differences between theme-centered and conference-centered special issues/special topics (SIT) publications. In particular, we could observe a high variation between modeling in publications of theme-centered SITs. It became obvious that often sound formal knowledge as well as a strong engineering background is needed for carrying out this type of research. Usually, this knowledge and the related skills can be best provided in consecutive B.Sc. and M.Sc. programs in medical informatics (respectively, health informatics, biomedical informatics). If the focus should be primarily on health information systems and evaluation this can be offered in a M.Sc. program in medical informatics. CONCLUSIONS: In analysing the 384 publications it became obvious that modeling continues to be a major task in research, education and practice in biomedical and health informatics. Knowledge and skills on a broad range of model types are needed in biomedical/health informatics.     

Medical informatics and bioinformatics: European efforts to facilitate synergy

Over the past decade there have been several attempts to rethink the basic strategies and scope of medical informatics. Meanwhile, bioinformatics has only recently experienced a similar debate about its scientific character. Both disciplines envision the development of novel diagnostic, therapeutic, and management tools, and products for patient care. A combination of the expertise of medical informatics in developing clinical applications and the focused principles that have guided bioinformatics could create a synergy between the two areas of application. Such interaction could have a great influence on future health research and the ultimate goal, namely continuity and individualization of health care. This article summarizes current activities related to facilitating synergy between medical informatics and bioinformatics, emphasizing activities in Europe while relating them to efforts in other parts of the world. The report provides examples of the analysis that European investigators are carrying out, aiming to propose new ideas for collaborations between medical informatics and bioinformatics researchers in a variety of areas.     

Distributed cognition: an alternative model of cognition for medical informatics

BACKGROUND: Medical informatics has been guided by an individual-centered model of human cognition, inherited from classical theory of mind, in which knowledge, problem-solving, and information-processing responsible for intelligent behavior all derive from the inner workings of an individual agent. OBJECTIVES AND RESULTS: In this paper we argue that medical informatics commitment to the classical model of cognition conflates the processing performed by the minds of individual agents with the processing performed by the larger distributed activity systems within which individuals operate. We review trends in cognitive science that seek to close the gap between general-purpose models of cognition and applied considerations of real-world human performance. One outcome is the theory of distributed cognition, in which the unit of analysis for understanding performance is the activity system which comprises a group of human actors, their tools and environment, and is organized by a particular history of goal-directed action and interaction. CONCLUSION: We describe and argue for the relevance of distributed cognition to medical informatics, both for the study of human performance in healthcare and for the design of technologies meant to enhance this performance.     

Facilitating biomedical researchers’ interrogation of electronic health record data: Ideas from outside of biomedical informatics

Electronic health records (EHR) are a vital data resource for research uses, including cohort identification, phenotyping, pharmacovigilance, and public health surveillance. To realize the promise of EHR data for accelerating clinical research, it is imperative to enable efficient and autonomous EHR data interrogation by end users such as biomedical researchers. This paper surveys state-of-art approaches and key methodological considerations to this purpose. We adapted a previously published conceptual framework for interactive information retrieval, which defines three entities: user, channel, and source, by elaborating on channels for query formulation in the context of facilitating end users to interrogate EHR data. We show the current progress in biomedical informatics mainly lies in support for query execution and information modeling, primarily due to emphases on infrastructure development for data integration and data access via self-service query tools, but has neglected user support needed during iteratively query formulation processes, which can be costly and error-prone. In contrast, the information science literature has offered elaborate theories and methods for user modeling and query formulation support. The two bodies of literature are complementary, implying opportunities for cross-disciplinary idea exchange. On this basis, we outline the directions for future informatics research to improve our understanding of user needs and requirements for facilitating autonomous interrogation of EHR data by biomedical researchers. We suggest that cross-disciplinary translational research between biomedical informatics and information science can benefit our research in facilitating efficient data access in life sciences.     

Health informatics and the delivery of care to older people

In the light of an aging society, effective delivery of healthcare will be more dependent on different technological solutions supporting the decentralisation of healthcare, higher patient involvement and increased societal demands. The aim of this article is therefore, to describe the role of health informatics in the care of elderly people and to give an overview of the state of the art in this field. Based on a review of the existing scientific literature, 29 review articles from the last 15 years and 119 original articles from the last 5 years were selected and further analysed. Results show that review articles cover the fields of information technology in the home environment, integrated health information systems, public health systems, consumer health informatics and non-technology oriented topics such as nutrition, physical behaviour, medication and the aging process in general. Articles presenting original data can be divided into 5 major clusters: information systems and decision support, consumer health informatics, emerging technologies, home telehealth, and informatics methods. Results show that health informatics in elderly care is an expanding field of interest but we still do lack knowledge about the elderly person's needs of technology and how it should best be designed. Surprisingly, few studies cover gender differences related to technology use. Further cross-disciplinary research is needed that relates informatics and technology to different stages of the aging process and that evaluates the effects of technical solutions.     

Clinical cognition and biomedical informatics: issues of patient safety

Recent developments in biomedical informatics research have afforded possibilities for great advances in health care delivery. These exciting opportunities also present a number of challenges to the implementation and integration of technologies in the workplace. As in most domains, there is a gulf between technologic artifacts and end users, which compromises the culture of safety in the workplace. Because clinical practice is a human endeavor, there is a need for bridging disciplines to enable clinicians to benefit from rapid technologic advances. This, in turn, necessitates a broadening of disciplinary boundaries to consider cognitive and social factors related to the design and use of technology. The authors argue for a place of prominence for cognitive science in understanding nursing factors associated with patient safety. Cognitive science provides a framework for the analysis and modeling of complex human performance. Studies of clinical cognition can meaningfully inform and shape design, development and assessment of information systems. Furthermore, they have a decisive impact on whether information technology has a positive influence on human performance and are especially important in understanding and promoting safe practices. These issues are discussed in the context of clinical informatics with a focus on nursing practice.     

Anatomical informatics: Millennial perspectives on a newer frontier

One of the most ancient of sciences, anatomy has evolved over many centuries. Its methods have progressively encompassed dissection instruments, manual illustration, stains, microscopes, cameras and photography, and digital imaging systems. Like many other more modern scientific disciplines in the late 20th century, anatomy has also benefited from the revolutionary development of digital computers and their automated information management and analytical capabilities. By using newer methods of computer and information sciences, anatomists have made outstanding contributions to science, medicine, and education. In that regard, there is a strong rationale for recognizing anatomical informatics as a proper subdiscipline of anatomy. A high-level survey of the field reveals important anatomical applications of computer sciences methods in imaging, image processing and visualization, virtual reality, modeling and simulation, structural database processing, networking, and artificial intelligence. Within this framework, computational anatomy is a developing field focusing on data-driven mathematical models of bodily structures. Mastering such computer sciences and informatics methods is crucial for new anatomists, who will shape the future in research, clinical knowledge, and teaching.     

The impact of clinical leadership on health information technology adoption: Systematic review

PurposeTo conduct a systematic review to examine evidence of associations between clinical leadership and successful information technology (IT) adoption in healthcare organisations.MethodsWe searched Medline, Embase, Cinahl, and Business Source Premier for articles published between January 2000 to May 2013 with keywords and subject terms related to: (1) the setting – healthcare provider organisations; (2) the technology – health information technology; (3) the process – adoption; and (4) the intervention – leadership. We identified 3121 unique citations, of which 32 met our criteria and were included in the review. Data extracted from the included studies were assessed in light of two frameworks: Bassellier et al.’s IT competence framework; and Avgar et al.’s health IT adoption framework.ResultsThe results demonstrate important associations between the attributes of clinical leaders and IT adoption. Clinical leaders who have technical informatics skills and prior experience with IT project management are likely to develop a vision that comprises a long-term commitment to the use of IT. Leaders who possess such a vision believe in the value of IT, are motivated to adopt it, and can maintain confidence and stability through the adversities that IT adoptions often entail. This leads to proactive leadership behaviours and partnerships with IT professionals that are associated with successful organisational and clinical outcomes.ConclusionsThis review provides evidence that clinical leaders can positively contribute to successful IT adoption in healthcare organisations. Clinical leaders who aim for improvements in the processes and quality of care should cultivate the necessary IT competencies, establish mutual partnerships with IT professionals, and execute proactive IT behaviours to achieve successful IT adoption.     

某三级甲等医院外科临床护士科研能力调查分析

目的 调查某三甲医院外科护士的科研能力,了解分析科研能力现状及影响因素,为提高我国护理人员的科研能力提供依据。方法 采用便利抽样法选取某三甲医院血管外科、肛肠外科、泌尿外科、胸心外科、胸心外科、骨创伤外科、整形外科、甲乳外科、烧伤监护室等131名护士为调查对象,使用自行设计的调查问卷对其进行护理科研能力调查。结果 131名外科护士中,学习过护理科研相关课程的有69人,主要是工作期间参加护理科研培训。能够熟练且经常运用中、英文文献检索、统计学知识、统计学软件的分别仅占3.05%、0.76%、2.29%、0.76%;对护理科研非常感兴趣仅占0.76%,对自己掌握的护理科研知识及能力不满意占77.10%,认为对护理科研知识的掌握程度缺乏的占54.96%;认为做护理科研很有必要的只占7.63%,只有4.58%的外科护士迫切需要提升自身科研能力。护理第一学历主要为大专（83.21%）,撰写过护理文章的占23.66%,主要为护师,工作年限为4~9年占45.16%。结论 外科护士的护理科研知识不足,科研能力偏低,科研意识不强,科研水平较低,其科研能力水平的提高可以提升临床护理质量,应使其认识护理科研的重要性,培养科研思维,丰富自身科研知识,提高护理科研水平。     

Health informatics in the Asia Pacific region.

Although health informatics has been an established science in some Asia Pacific countries since the 1970s, its current degree of awareness among countries in this region can largely be attributed to the efforts of the Asia Pacific Association for Medical Informatics. These efforts have included the spawning of national health informatics associations in some countries, creating opportunities for cross-country scientific interactions at national health informatics meetings and promoting regional health informatics activities and expertise through the APAMI web site. This presentation gives a review of the current status of health informatics activities among APAMI member countries as well as a cross-section of some of their health informatics projects.     

The evolution of medical informatics in China: A retrospective study and lessons learned

BackgroundIn contrast to China’s giant health information technology (HIT) market and tremendous investments in hospital information systems the contributions of Chinese scholars in medical informatics to the global community are very limited. China would like to have a more important position in the global medical informatics community.ObjectiveA better understanding of the differences between medical informatics research and education in China and the discipline that emerged abroad will better inform Chinese scholars to develop right strategies to advance the field in China and help identify an appropriate means to collaborate more closely with medical informatics scholars globally.MethodFor the first time, this paper divides the evolution of medical informatics in China into four stages based on changes in the core content of research, the educational orientation and other developmental characteristics. The four stages are infancy, incubation, primary establishment and formal establishment. This paper summarizes and reviews major supporting journals and publications, as well as major organizations. Finally, we analyze the main problems that exist in the current disciplinary development in China related to medical informatics research and education and offer suggestions for future improvement.ConclusionsThe evolution of medical informatics shows a strong and traditional concentration on medical library/bibliographic information rather than medical (hospital information or patient information) information. Misdirected-concentration, a lack of formal medical informatics trained teaching staff and mistakenly positioning medical informatics as an undergraduate discipline are some of the problems inhibiting the development of medical informatics in China. These lessons should be shared and learned for the global community.     

The influence of a professional physician network on clinical decision making

ObjectiveThe aim of this study was to examine the role of physicians’ professional networks in decision-making processes.MethodsA professional network was examined in three stages: content analysis and categorization of discussions concerning decision-making processes, in-depth interviews, and a questionnaire.ResultsThe RAMBAM network has professional as well as social roles. On a professional level, physicians seek approval of their initial line of reasoning regarding their clinical cases, but will consider other approaches if such are suggested by persons of professional repute or if answers are based on evidence-based medicine and include referral to a relevant source. On a social level, physicians want to be part of their professional community and share information and experiences.ConclusionPhysicians’ professional networks have a social role that is expressed by a feeling of belonging to a community, as well as a professional role of capturing and disseminating medical knowledge during physicians’ decision-making processes. Professional networks constitute a unique source of tacit knowledge that extends existing formal knowledge resources.Practice implicationsThe study can increase physicians’ awareness of professional networks as a unique source of tacit knowledge and can assist in the future design of medical professional networks as knowledge resources for medical decision making.     

Discovery of clinical pathway patterns from event logs using probabilistic topic models

Discovery of clinical pathway (CP) patterns has experienced increased attention over the years due to its importance for revealing the structure, semantics and dynamics of CPs, and to its usefulness for providing clinicians with explicit knowledge which can be directly used to guide treatment activities of individual patients. Generally, discovery of CP patterns is a challenging task as treatment behaviors in CPs often have a large variability depending on factors such as time, location and patient individual. Based on the assumption that CP patterns can be derived from clinical event logs which usually record various treatment activities in CP executions, this study proposes a novel approach to CP pattern discovery by modeling CPs using mixtures of an extension to the Latent Dirichlet Allocation family that jointly models various treatment activities and their occurring time stamps in CPs. Clinical case studies are performed to evaluate the proposed approach via real-world data sets recording typical treatment behaviors in patient careflow. The obtained results demonstrate the suitability of the proposed approach for CP pattern discovery, and indicate the promise in research efforts related to CP analysis and optimization.     

A pragmatic method for transforming clinical research data from the research electronic data capture “REDCap” to Clinical Data Interchange Standards Consortium (CDISC) Study Data Tabulation Model (SDTM): Development and evaluation of REDCap2SDTM

The Clinical Data Interchange Standards Consortium (CDISC) Study Data Tabulation Model (SDTM) can be used for new drug application studies as well as secondarily for creating a clinical research data warehouse to leverage clinical research study data across studies conducted within the same disease area. However, currently not all clinical research uses Clinical Data Acquisition Standards Harmonization (CDASH) beginning in the set-up phase of the study. Once already initiated, clinical studies that have not utilized CDASH are difficult to map in the SDTM format. In addition, most electronic data capture (EDC) systems are not equipped to export data in SDTM format; therefore, in many cases, statistical software is used to generate SDTM datasets from accumulated clinical data. In order to facilitate efficient secondary use of accumulated clinical research data using SDTM, it is necessary to develop a new tool to enable mapping of information for SDTM, even during or after the clinical research. REDCap is an EDC system developed by Vanderbilt University and is used globally by over 2100 institutions across 108 countries. In this study, we developed a simulated clinical trial to evaluate a tool called REDCap2SDTM that maps information in the Field Annotation of REDCap to SDTM and executes data conversion, including when data must be pivoted to accommodate the SDTM format, dynamically, by parsing the mapping information using R. We confirmed that generating SDTM data and the define.xml file from REDCap using REDCap2SDTM was possible. Conventionally, generation of SDTM data and the define.xml file from EDC systems requires the creation of individual programs for each clinical study. However, our proposed method can be used to generate this data and file dynamically without programming because it only involves entering the mapping information into the Field Annotation, and additional data into specific files. Our proposed method is adaptable not only to new drug application studies but also to all types of research, including observational and public health studies. Our method is also adaptable to clinical data collected with CDASH at the beginning of a study in non-standard format. We believe that this tool will reduce the workload of new drug application studies and will support data sharing and reuse of clinical research data in academia.     

What is biomedical informatics?

Biomedical informatics lacks a clear and theoretically-grounded definition. Many proposed definitions focus on data, information, and knowledge, but do not provide an adequate definition of these terms. Leveraging insights from the philosophy of information, we define informatics as the science of information, where information is data plus meaning. Biomedical informatics is the science of information as applied to or studied in the context of biomedicine. Defining the object of study of informatics as data plus meaning clearly distinguishes the field from related fields, such as computer science, statistics and biomedicine, which have different objects of study. The emphasis on data plus meaning also suggests that biomedical informatics problems tend to be difficult when they deal with concepts that are hard to capture using formal, computational definitions. In other words, problems where meaning must be considered are more difficult than problems where manipulating data without regard for meaning is sufficient. Furthermore, the definition implies that informatics research, teaching, and service should focus on biomedical information as data plus meaning rather than only computer applications in biomedicine.     

Education of medical informatics in Bosnia and Herzegowina

Time of information in which the authors live resulted in the increase of the amount of the information exponential growth of the new kind of knowledge, flourishing of the familiar ones and the appearance of the new sciences. Medical (health) informatics occupies the central place in all the segments of modern medicine in the past 30 years—in practical work, education and scientific research. In all that, computers have taken over the most important role and are used intensively for the development of the health information systems. Following activities develop within the area of health informatics: health-documentation, health-statistics, health-informatics and big-medical, scientific and professional information. The pioneer in the development of the health statistics and informatics in Bosnia and Herzegovina (BiH) was Dr Evgenije Sherstnew, who was the Chief of Health Statistics in the Ministry of Health of BiH from 1946–1952. and who founded and led, from 1952 to the end of his life, the Department of Medical Documentation and Health Statistics of the Central Health Institute of BiH, the core around which a group of experts for the development of this field have gathered. In the eighties computers were intensively used as a tool for the processing medical data and with them the development of health information systems at the level of the outpatient-clinics, hospitals, clinical centers, as well as the integral information system of health, health insurance and the social security system of BiH began. Finally, Society for Medical Informatics of BiH, which as a professional association gathers experts in the area of health informatics, actively propagates this profession in the Republic, was founded. With reform of the lectures and curriculum at the medical faculty in Sarajevo, the course in ‘Medical Informatics’ has been in 1992. into the second semester, since it was assumed that an early insight into the principles of information along with studies of so called basic pre-clinic sciences, especially basics of information, would make things easier for the students the more informative education is in the course of their medical studies. The medical faculty in Sarajevo also established and accepted a course of health informatics and economics of post-graduate studies in 1979, of which the main objective is education of experts for work informatics jobs in health care system and services, especially for needs of the future information systems in BiH.     

Current applications and future directions for the CDISC Operational Data Model standard: A methodological review

IntroductionIn order to further advance research and development on the Clinical Data Interchange Standards Consortium (CDISC) Operational Data Model (ODM) standard, the existing research must be well understood. This paper presents a methodological review of the ODM literature. Specifically, it develops a classification schema to categorize the ODM literature according to how the standard has been applied within the clinical research data lifecycle. This paper suggests areas for future research and development that address ODM’s limitations and capitalize on its strengths to support new trends in clinical research informatics.MethodsA systematic scan of the following databases was performed: (1) ABI/Inform, (2) ACM Digital, (3) AIS eLibrary, (4) Europe Central PubMed, (5) Google Scholar, (5) IEEE Xplore, (7) PubMed, and (8) ScienceDirect. A Web of Science citation analysis was also performed. The search term used on all databases was “CDISC ODM.” The two primary inclusion criteria were: (1) the research must examine the use of ODM as an information system solution component, or (2) the research must critically evaluate ODM against a stated solution usage scenario. Out of 2686 articles identified, 266 were included in a title level review, resulting in 183 articles. An abstract review followed, resulting in 121 remaining articles; and after a full text scan 69 articles met the inclusion criteria.ResultsAs the demand for interoperability has increased, ODM has shown remarkable flexibility and has been extended to cover a broad range of data and metadata requirements that reach well beyond ODM’s original use cases. This flexibility has yielded research literature that covers a diverse array of topic areas. A classification schema reflecting the use of ODM within the clinical research data lifecycle was created to provide a categorized and consolidated view of the ODM literature. The elements of the framework include: (1) EDC (Electronic Data Capture) and EHR (Electronic Health Record) infrastructure; (2) planning; (3) data collection; (4) data tabulations and analysis; and (5) study archival. The analysis reviews the strengths and limitations of ODM as a solution component within each section of the classification schema. This paper also identifies opportunities for future ODM research and development, including improved mechanisms for semantic alignment with external terminologies, better representation of the CDISC standards used end-to-end across the clinical research data lifecycle, improved support for real-time data exchange, the use of EHRs for research, and the inclusion of a complete study design.ConclusionsODM is being used in ways not originally anticipated, and covers a diverse array of use cases across the clinical research data lifecycle. ODM has been used as much as a study metadata standard as it has for data exchange. A significant portion of the literature addresses integrating EHR and clinical research data. The simplicity and readability of ODM has likely contributed to its success and broad implementation as a data and metadata standard. Keeping the core ODM model focused on the most fundamental use cases, while using extensions to handle edge cases, has kept the standard easy for developers to learn and use.