Tracking Referents in Electronic Health Records

Electronic Health Records (EHRs) are organized around two kinds of statements: those reporting observations made, and those reporting acts performed. In neither case does the record involve any direct reference to what such statements are actually about. They record not: what is happening on the side of the patient, but rather: what is said about what is happening. While the need for a unique patient identifier is generally recognized, we argue that we should now move to an EHR regime in which all clinically salient particulars – from the concrete disorder on the side of the patient and the body parts in which it occurs to the concrete treatments given – should be uniquely identified. This will allow us to achieve interoperability among different systems of records at the level where it really matters: in regard to what is happening in the real world. It will also allow us to keep track of particular disorders and of the effects of particular treatments in a precise and unambiguous way. We discuss the ontological and epistemological aspects of our claim and describe a scenario for implementation within EHR systems

Clinical data wrangling using Ontological Realism and Referent Tracking

Ontological realism aims at the development of high quality ontologies that faithfully represent what is general in reality and to use these ontologies to render heterogeneous data collections comparable. To achieve this second goal for clinical research datasets presupposes not merely (1) that the requisite ontologies already exist, but also (2) that the datasets in question are faithful to reality in the dual sense that (a) they denote only particulars and relationships between particulars that do in fact exist and (b) they do this in terms of the types and type-level relationships described in these ontologies. While much attention has been devoted to (1), work on (2), which is the topic of this paper, is comparatively rare. Using Referent Tracking as basis, we describe a technical data wrangling strategy which consists in creating for each dataset a template that, when applied to each particular record in the dataset, leads to the generation of a collection of Referent Tracking Tuples (RTT) built out of unique identifiers for the entities described by means of the data items in the record. The proposed strategy is based on (i) the distinction between data and what data are about, and (ii) the explicit descriptions of portions of reality which RTTs provide and which range not only over the particulars described by data items in a dataset, but also over these data items themselves. This last feature allows us to describe particulars that are only implicitly referred to by the dataset; to provide information about correspondences between data items in a dataset; and to assert which data items are unjustifiably or redundantly present in or absent from the dataset. The approach has been tested on a dataset collected from patients seeking treatment for orofacial pain at two German universities and made available for the NIDCR-funded OPMQoL project

Ontology as the core discipline of biomedical informatics: Legacies of the past and recommendations for the future direction of research

The automatic integration of rapidly expanding information resources in the life sciences is one of the most challenging goals facing biomedical research today. Controlled vocabularies, terminologies, and coding systems play an important role in realizing this goal, by making it possible to draw together information from heterogeneous sources – for example pertaining to genes and proteins, drugs and diseases – secure in the knowledge that the same terms will also represent the same entities on all occasions of use. In the naming of genes, proteins, and other molecular structures, considerable efforts are under way to reduce the effects of the different naming conventions which have been spawned by different groups of researchers. Electronic patient records, too, increasingly involve the use of standardized terminologies, and tremendous efforts are currently being devoted to the creation of terminology resources that can meet the needs of a future era of personalized medicine, in which genomic and clinical data can be aligned in such a way that the corresponding information systems become interoperable

Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain

Ontology is a burgeoning field, involving researchers from the computer science, philosophy, data and software engineering, logic, linguistics, and terminology domains. Many ontology-related terms with precise meanings in one of these domains have different meanings in others. Our purpose here is to initiate a path towards disambiguation of such terms. We draw primarily on the literature of biomedical informatics, not least because the problems caused by unclear or ambiguous use of terms have been there most thoroughly addressed. We advance a proposal resting on a distinction of three levels too often run together in biomedical ontology research: 1. the level of reality; 2. the level of cognitive representations of this reality; 3. the level of textual and graphical artifacts. We propose a reference terminology for ontology research and development that is designed to serve as common hub into which the several competing disciplinary terminologies can be mapped. We then justify our terminological choices through a critical treatment of the ‘concept orientation’ in biomedical terminology research

Introducing realist ontology for the representation of adverse events

The goal of the REMINE project is to build a high performance prediction, detection and monitoring platform for managing Risks against Patient Safety (RAPS). Part of the work involves developing in ontology enabling computer-assisted RAPS decision support on the basis of the disease history of a patient as documented in a hospital information system. A requirement of the ontology is to contain a representation for what is commonly referred to by the term 'adverse event', one challenge being that distinct authoritative sources define this term in different and context-dependent ways. The presence of some common ground in all definitions is, however, obvious. Using the analytical principles underlying Basic Formal Ontology and Referent Tracking, both developed in the tradition of philosophical realism, we propose a formal representation of this common ground which combines a reference ontology consisting exclusively of representations of universals and an application ontology which consists representations of defined classes. We argue that what in most cases is referred to by means of the term 'adverse event' - when used generically - is a defined class rather than a universal. In favour of the conception of adverse events as forming a defined class are the arguments that (1) there is no definition for 'adverse event' that carves out a collection of particulars which constitutes the extension of a universal, and (2) the majority of definitions require adverse events to be (variably) the result of some observation, assessment or (absence of) expectation, thereby giving these entities a nominal or epistemological flavour

What do identifiers in HL7 identify? An essay in the ontology of identity

Health Level 7 (HL7) is an organization seeking to provide universal standards for the exchange of healthcare information. In a document entitled ‘HL7 Version 3 Standard: Data Types’, the HL7 organization advances descriptions of data types recom- mended for use as identifiers. We will argue that the descriptions supplied provide insufficient guidance as to what exactly the entities are which these data types uniquely identify. Are they real things, such as persons or pieces of equipment? Or are they representations of such real things in information artifacts? We here outline the problems faced by HL7 in providing answers to such questions, problems which arise because of the lack of anything like a coherent ontology in the HL7 standard, and we make some recommendations for future improvements

Patient’s Utilization of Health Information Technologies for Disease Self-Management

Background: The rapid growth of Health Information Technologies (HITs) provides patients with greater opportunity to take control over their health. HITs utilization has been proven to be a critical component of disease self-management and can result in positive outcomes. Its widespread adoption and utilization is still relatively low among patients with chronic disease. It is important to understand the factors that may impact HITs utilization, such as the perceived Task-Technology Fit (TTF). A very limited number of studies have examined the relationship between HITs utilization and the perceived fit between task and technology in the context of TTF theory. Aims/ Purpose: The purpose of this study was to explore the factors that impact patient utilization of HITs for disease self-management. We examined the relationships between patient demographics and their utilization of HITs in relation to disease self-management and TTF. Methods and Design: A quantitative descriptive correlational research design was used for this data-based study. Data from the most recent Health Information National Trends Survey (HINTS 5, cycle 2) collected in 2018 was used for this study, (N= 3,504). Results: Sociodemographic disparities still exist among patient groups in terms of HITs utilization for disease self-management. Patients with lower education attainment and lower income were less likely to access their online medical records. Also, these study findings show a significant positive relationship between perceived TTF and patient utilization of the various HITs. Open communication and discussions with healthcare provider remain the most frequently reported HIT attribute associated with patient utilization of HITs for disease self-management. Implications: Findings of this study may inform a better understanding of TTF factors. This new knowledge may influence HITs developers to include the patient perspective in future designs. These study findings may also assist researchers in developing tailored interventions that are driven by the unique individual patient technological needs for disease self-management, which in turn, can promote patient safety, improve health outcomes, and enhance the utilization of such technologies

Anatomical information science

The Foundational Model of Anatomy (FMA) is a map of the human body. Like maps of other sorts – including the map-like representations we find in familiar anatomical atlases – it is a representation of a certain portion of spatial reality as it exists at a certain (idealized) instant of time. But unlike other maps, the FMA comes in the form of a sophisticated ontology of its objectdomain, comprising some 1.5 million statements of anatomical relations among some 70,000 anatomical kinds. It is further distinguished from other maps in that it represents not some specific portion of spatial reality (say: Leeds in 1996), but rather the generalized or idealized spatial reality associated with a generalized or idealized human being at some generalized or idealized instant of time. It will be our concern in what follows to outline the approach to ontology that is represented by the FMA and to argue that it can serve as the basis for a new type of anatomical information science. We also draw some implications for our understanding of spatial reasoning and spatial ontologies in general

A growing disconnection from nature is evident in cultural products

Human connection with nature is widely believed to be in decline, even though empirical evidence on the magnitude and temporal pattern of the change is scarce. Studying works of popular culture in English throughout the 20th century and later, we document a cultural shift away from nature, beginning in the 1950s. Since then, references to nature have been decreasing steadily in fiction, song lyrics, and film storylines. No parallel decline is observed in references to the human-made environment. These findings are cause for concern, not only because they imply foregone benefits from engagement with nature, but also because cultural products are agents of socialization that can evoke curiosity, respect, and concern for the natural world

The perceived benefits of healthcare information technology adoption: construct and survey development

This paper is a part of a large study, which examines healthcare professionals’ attitudes regarding the adoption, use and perceived benefits of healthcare information technology (HIT). To date, literature on HIT has shown many important benefits related to quality and efficiency as well as limitations related to generalization and to a lack of empirical data on benefits. The aim of this paper is to develop a survey instrument focused the perceived benefits of HIT adoption. We exhaustively reviewed the construct of perceived benefits in various research areas to identify established approaches to predicting individual’s intentions to adopt technology. The items of perceived benefits taken from previous studies were developed and modified, and three benefit dimensions (direct, indirect and strategic benefits) were described. The questionnaire addressed the following issues: demographic information, perceived benefits of computerized physician/provider order entry (CPOE), and intent to adopt CPOE. We present a survey instrument containing the perceived benefits construct targeting healthcare executives. This is developed and validated by the translational validity test that attempts to assess the degree to which we accurately translated our construct into the operationalization. The Importance of the instrument for perceived benefits of HIT adoption as well as its limitations is also presented