Understanding the Burden of Illness: Steps Towards an Ontology of Patient Experience

Emerging Marketing Research on Healthcare and Medical Decision Making: Toward a Consumer-Centric and Pluralistic Methodological Perspective

This chapter contains sections titled: The Protege Ontology Editor and BFO, The Web Ontology Language (OWL), Building Ontologies with Basic Formal Ontology, Infectious Disease Ontology (IDO), Information Artifact Ontology (IAO), The Emotion Ontology (MFO-EM), Facilitation of Interoperability, Further Reading on OWL, RDFS, and RDF

Policy PointsEfforts to address a perceived decline of comprehensiveness in primary care are hampered by the absence of a clear and common understanding of what comprehensiveness means.This scoping review mapped two domains of comprehensiveness (breadth of care and approach to care) as well as a set of factors that enable comprehensive practice.The resulting conceptual map supports greater clarity for future use of the term comprehensiveness, facilitating more precisely targeted research, practice, and policy efforts to improve primary care systems.ContextAssociated with system efficiency and patient‐perceived quality, comprehensiveness is widely recognized as foundational to high‐quality primary care. However, there is concern that comprehensiveness is declining and that primary care physicians are providing a narrower range of services. Efforts to address this perceived decline are hampered by the many different and sometimes vague definitions of comprehensiveness in current use. This scoping review explored how comprehensiveness in primary care is conceptualized and defined in order to map its attributes in support of being able to more clearly and precisely define this key concept in research, practice, and policy.MethodsWe conducted a scoping review, following the methods of Arksey and O'Malley and Levac and colleagues. The search included terms for two key concepts: primary care and comprehensiveness. Developed in Ovid Medical Literature Analysis and Retrieval System Online (MEDLINE), the search was adapted for Cumulated Index in Nursing and Allied Health Literature (CINAHL) and Embase, as well as for gray literature. After a multistep review, included sources underwent detailed data extraction.FindingsA total of 360 sources were extracted; 57% were empirical studies and 65% were published between 2010 and 2022. Across these sources, we identified nine attributes of comprehensiveness in primary care. We mapped these attributes into two conceptual domains: breadth of care (services, settings, health needs and conditions, patients served, and availability) and approach to care (one‐stop shop, whole‐person care, referrals and coordination, and longitudinal care). Additionally, we identified three enablers of comprehensiveness, namely structures and resources, teams, and competency.ConclusionsThe conceptual map of comprehensiveness in primary care offers a valuable tool that supports clarity for future use of the term comprehensiveness. The domains and attributes we identified can be used to develop definitions and measures that are appropriate to research, practice, and policy contexts, enabling more precise efforts to improve primary care systems.

This paper is intended to help novice researchers understand key concepts in educational research, particularly in the field of language education. It uses as its samples two peer-reviewed research articles on early childhood literacy development, bilingual and multilingual issues and identity consitution. It first attempts to analyze how the key concepts in educational research were incorporated into the research process. Of particular importance, this paper critically looks at the extent to which those key concepts were logically linked so as to provide the research with strong coherence. The discussion also takes into account the issues of ethics, how this was sufficiently dealt with by the author and what possible factors might have come into play to degrade the validity of the research. This paper conludes with my views on the research design and process as a whole and my suggestions on some of the issues uncovered during the discussion.Â

2 - Key Concepts in Research

2 - Key concepts in research

At its core, the practice of medicine is an information-intensive endeavor. Most of what physicians do involves the collection, review, and management of information. Examples of such activities include obtaining and recording patient information, consulting colleagues, reading the scientific literature, planning diagnostic procedures, devising strategies for patient care, interpreting tests, and conducting research. The ever-increasing biomedical knowledge base that must be considered to deliver optimal patient care only adds to the challenges facing medicine today. Successfully addressing these challenges to deliver the best health care possible requires not only the existence of valid and generalizable data sets derived from systematic basic, clinical, and epidemiological research efforts but also the ability to apply the knowledge derived from these research efforts at the point of care. It is easy to understand, therefore, why the field of biomedical informatics, a field that is concerned with collecting, managing, and optimally using information in health care and biomedicine, is critical to the current and future practice of medicine and the study of healthcare outcomes that result from such practice.1,2 Biomedical informatics approaches and related health information technology (health IT) platforms are key to enabling knowledge-driven healthcare and practice improvement initiatives based on a solid research foundation. Similar biomedical informatics approaches and resources are also critical to advancing outcomes research. Indeed, such technologies such as electronic health records (EHRs), clinical data repositories, and research-specific data management systems are already transforming the way we practice medicine and conduct research. This transformation is being further advanced by federally directed funding and research infrastructure development efforts.3,4 In the sections that follow, we provide an overview of how biomedical informatics and health IT processes and tools can affect the conduct of research and the delivery of evidence-based health care from our perspective. Given the current state of development …

Background: Interventions directed to individuals by health and social care systems should increase health and welfare of patients and customers.Aims: This paper aims to present and define a new concept Clinical Impact Research (CIR) and suggest which study design, either randomized controlled trial (RCT) (experimental) or benchmarking controlled trial (BCT) (observational) is recommendable and to consider the feasibility, validity, and generalizability issues in CIR.Methods: The new concept is based on a narrative review of the literature and on author’s idea that in intervention studies, there is a need to cover comprehensively all the main impact categories and their respective outcomes. The considerations on how to choose the most appropriate study design (RCT or BCT) were based on previous methodological studies on RCTs and BCTs and on author’s previous work on the concepts benchmarking controlled trial and system impact research (SIR).Results: The CIR covers all studies aiming to assess the impact for health and welfare of any health (and integrated social) care or public health intervention directed to an individual. The impact categories are accessibility, quality, equality, effectiveness, safety, and efficiency. Impact is the main concept, and within each impact category, both generic- and context-specific outcome measures are needed. CIR uses RCTs and BCTs.Conclusions: CIR should be given a high priority in medical, health care, and health economic research. Clinicians and leaders at all levels of health care can exploit the evidence from CIR. Key messagesThe new concept of Clinical Impact Research (CIR) is defined as a research field aiming to assess what are the impacts of healthcare and public health interventions targeted to patients or individuals.The term impact refers to all effects caused by the interventions, with particular emphasis on accessibility, quality, equality, effectiveness, safety, and efficiency. CIR uses two study designs: randomized controlled trials (RCTs) (experimental) and benchmarking controlled trials (BCTs) (observational). Suggestions on how to choose between RCT and BCT as the most suitable study design are presented.Simple way of determining the study question in CIR based on the PICO (patient, intervention, control intervention, outcome) framework is presented.CIR creates the scientific basis for clinical decisions. Clinicians and leaders at all levels of health care and those working for public health can use the evidence from CIR for the benefit of patients and the population.

Since the introduction of Digital Engineering (DE) as a well‐defined concept in 2018, organizations and industry groups have been working to interpret the DE concepts to establish consistent meta‐models of those interrelated concepts for integration into their DE processes and tools. To reach the breadth and depth of DE concept definitions, the interpretation of international standard sources is necessary, including ISO/IEC/IEEE 15288, 24765, 42000‐series, 15408, 15206, 27000‐series, and 25000‐series, to effectively model the knowledge domain where digital engineering applies. The harmonization of the concepts used in these international standards continues to improve with each revision, but it may be more effectively accomplished by relying on the descriptive logic formalized in the Web Ontology Language (OWL 2 DL). This paper presents a verified and consistent ontology based on the Basic Formal Ontology (BFO) and Common Core Ontologies (CCO) that defines Seamless Digital Engineering as a digital tooling paradigm that relies on formal verification of digital interfaces to provide a system‐level qualification of the assured integrity of a Digital Engineering Environment. The present work defines classes and equivalence axioms, while using only the BFO‐ and CCO‐defined object properties that relate them, to provide a baseline analysis that may inform future DE‐related ontology development, using a case study to formally define the ‘seamless’ quality in relation to the updated ISO 25010 SQuaRE product quality model. We identified ISO meta‐model inconsistencies that are resolvable using the BFO/CCO ontological framework, and define ‘seamless’ as both a system integration quality and a Human‐Computer Interface quality‐in‐use, working to disambiguate this concept in the context of DE.

Research themes for our future

Reviewing key concepts in research on political news journalism : Conceptualizations, operationalizations, and propositions for future research

Introduction to the International Medical Informatics Association

The attention and interest of governments and related industry areas in the digitization of healthcare systems have been increased significantly in the recent past and the same is being evidenced by numerous initiatives taken by many countries and sectors. Healthcare informatics is a decisive component of a healthcare system that has demonstrated a growing specialization linking healthcare systems, communication systems, and information technology for improving the quality, storage, and safety of patient related information. Healthcare informatics facilitates organizations and service providers to discriminate between huge amount of big-data and the real meaningful data so as to integrate the meaningful data flawlessly into a health system.Healthcare systems must protect the privacy and security of patient data, at the same time carrying quality patient care and following the essential regulatory requirements. With the evolution of technologies like Internet of Things (IoT) and Internet of Everything (IoE) and besides their advantages in today's highly pervasive computing era, there has been a significant demand of secure storage of a huge amount of patient data. New kinds of vulnerabilities and security attacks are threatening the IoT and IoE-based healthcare systems due to many reasons including the usage of various kinds of medical devices, nature of wireless communication, ignorance of security by manufacturers of medical devices, and many others. Electronic healthcare record systems must ensure the CIA requirements of security, i.e., confidentiality, integrity, and availability of the information stored. Moreover, this data must be communicated securely among all the authorized entities like medical practitioners, along with the privileges for accessing particular patient's specific data to expedite diagnosis and treatment.Blockchain technology has evolved rapidly in past few years, and is making most of the centralized systems obsolete owing to its unique properties of immutability, decentralized, transparency, and reduction in cost. Blockchain is going to revolutionize the area of healthcare informatics since it can facilitate the majority of functionalities required for healthcare information system like privacy of stored data, secure sharing of data, data audit, integrity checks, and identity management. In addition to integrity, confidentiality, and availability, blockchain-based security solutions can provide auditability, accountability, authenticity, and anonymity.This chapter aims at exploring the different aspects of developing blockchain-based security solutions for healthcare informatics. The chapter identifies the security requirements and challenges in healthcare system. It also describes the security aspects in centralized/decentralized healthcare systems and also elaborates adaptions and impact of Blockchain Technology in Healthcare Systems. Security attributes and architecture of blockchain and its applicability in developing secure frameworks for healthcare informatics have also been explained here. How the issues of identity and trust management can be addressed in healthcare using blockchain, has also been presented in this chapter. The security of big data in healthcare using blockchain, along with the technologies like IoT and IoE have also been addressed in this chapter. Finally, the chapter speaks about the challenges, opportunities, and future insights of blockchain-based healthcare systems.

Key account management formalization and effectiveness: A fuzzy-set qualitative comparative analysis

Strategic information systems: development, implementation, case studies: D S J Remenyi NCC Blackwell (1990) 190 pp £16.50