23 research outputs found
A novel framework for standardizing and digitizing clinical pathways in healthcare information systems
Most healthcare institutions are reorganizing their healthcare delivery systems based on
Clinical Pathways (CPs). CPs are medical management plans designed to standardize
medical activities, reduce cost, optimize resource usage, and improve quality of service.
However, most CPs are still paper-based and not fully integrated with Health Information
Systems (HISs). More CP automation research is therefore required to fully benefit from
the practical potentials of CPs. The common theme of current research in this field is to
connect CPs with Electronic Medical Record (EMR) systems. Such view positions EMRs
at the centre of HISs. A major long-term objective of this research is the placement of CP
systems at the centre of HISs, because within CPs lies the very heart of medical planning,
treatment and impressions, including healthcare quality and cost factors. An important
contribution to the realization of this objective is to develop an international CP-specific
digital coding system, and to fully standardize and digitize CPs based on the Systematized
Nomenclature of Medicine-Clinical Terms (SNOMED CT) medical terminology system.
This makes CPs digitally visible and machine-readable. In addition, to achieve semantic
interoperability of CPs, we propose a CP knowledge representation using ontology engineering and HL7 standard. Our proposed framework makes CP systems smoothly linkable
across various HISs. To show the feasibility and potential of the proposed framework,
we developed a prototype Clinical Pathway Management System (CPMS) based on CPs
currently in use at hospitals. The results show that CPs can be fully standardized and
digitized using SNOMED CT terms and codes, and the CPMS can work as an independent
healthcare system, performing novel CP-related functions including useful decision-support
tasks. Furthermore, CP data were captured without loss, which contributes to reducing
missing patient data and improving the results of data mining algorithms in healthcare.
Standardized CPs can also be easily compared for auditing and quality management. The
proposed framework is promising, and contributes toward solving major challenges related
to CP standardization, digitization, independence, and proper inclusion in today’s modern
computerized hospitals
Issues of the adoption of HIT related standards at the decision-making stage of six tertiary healthcare organisations in Saudi Arabia
Due to interoperability barriers between clinical information systems, healthcare organisations are facing potential limitations with regard to acquiring the benefits such systems offer; in particular, in terms of reducing the cost of medical services. However, to achieve the level of interoperability required to reduce these problems, a high degree of consensus is required regarding health data standards. Although such standards essentially constitute a solution to the interoperability barriers mentioned above, the level of adoption of these standards remains frustratingly low. One reason for this is that health data standards are an authoritative field in which marketplace mechanisms do not work owing to the fact that health data standards developed for a particular market cannot, in general, be applied in other markets without modification.
Many countries have launched national initiatives to develop and promote national health data standards but, although certain authors have mapped the landscape of the standardisation process for health data in some countries, these studies have failed to explain why the healthcare organisations seem unwilling to adopt those standards. In addressing this gap in the literature, a conceptual model of the adoption process of HIT related standards at the decision-making stage in healthcare organisations is proposed in this research. This model was based on two predominant theories regarding IT related standards in the IS field: Rogers paradigm (1995) and the economics of standards theory. In addition, the twenty one constructs of this model resulted from a comprehensive set of factors derived from the related literature; these were then grouped in accordance with the Technology-Organisation Environment (TOE), a well-known taxonomy within innovation adoption studies in the IS field. Moving from a conceptual to an empirical position, an interpretive, exploratory, multiple-case study methodology was conducted in Saudi Arabia to examine the proposed model. The empirical qualitative evidence gained necessitated some revision to be made to the proposed model. One factor was abandoned, four were modified and eight new factors were added. This consistent empirical model makes a novel contribution at two levels. First, with regard to the body of knowledge in the IS area, this model offers an in-depth understanding of the adoption process of HIT related standards which the literature still lacks. It also examines the applicability of IS theories in a new area which allows others to relate their experiences to those reported. Secondly, this model can be used by decision makers in the healthcare sector, particularly those in developing countries, as a guideline while planning for the adoption of health data standards
Towards a system of concepts for Family Medicine. Multilingual indexing in General Practice/ Family Medicine in the era of Semantic Web
UNIVERSITY OF LIÈGE, BELGIUM
Executive Summary
Faculty of Medicine
Département Universitaire de Médecine Générale.
Unité de recherche Soins Primaires et Santé
Doctor in biomedical sciences
Towards a system of concepts for Family Medicine.
Multilingual indexing in General Practice/ Family Medicine in the era
of SemanticWeb
by Dr. Marc JAMOULLE
Introduction
This thesis is about giving visibility to the often overlooked work of family
physicians and consequently, is about grey literature in General Practice
and Family Medicine (GP/FM). It often seems that conference organizers
do not think of GP/FM as a knowledge-producing discipline that deserves
active dissemination. A conference is organized, but not much is done with
the knowledge shared at these meetings. In turn, the knowledge cannot be
reused or reapplied. This these is also about indexing. To find knowledge
back, indexing is mandatory. We must prepare tools that will automatically
index the thousands of abstracts that family doctors produce each year in
various languages. And finally this work is about semantics1. It is an introduction
to health terminologies, ontologies, semantic data, and linked
open data. All are expressions of the next step: Semantic Web for health
care data. Concepts, units of thought expressed by terms, will be our target
and must have the ability to be expressed in multiple languages. In turn,
three areas of knowledge are at stake in this study: (i) Family Medicine as a
pillar of primary health care, (ii) computational linguistics, and (iii) health
information systems.
Aim
• To identify knowledge produced by General practitioners (GPs) by
improving annotation of grey literature in Primary Health Care
• To propose an experimental indexing system, acting as draft for a
standardized table of content of GP/GM
• To improve the searchability of repositories for grey literature in GP/GM.
1For specific terms, see the Glossary page 257
x
Methods
The first step aimed to design the taxonomy by identifying relevant concepts
in a compiled corpus of GP/FM texts. We have studied the concepts
identified in nearly two thousand communications of GPs during
conferences. The relevant concepts belong to the fields that are focusing
on GP/FM activities (e.g. teaching, ethics, management or environmental
hazard issues).
The second step was the development of an on-line, multilingual, terminological
resource for each category of the resulting taxonomy, named
Q-Codes. We have designed this terminology in the form of a lightweight
ontology, accessible on-line for readers and ready for use by computers of
the semantic web. It is also fit for the Linked Open Data universe.
Results
We propose 182 Q-Codes in an on-line multilingual database (10 languages)
(www.hetop.eu/Q) acting each as a filter for Medline. Q-Codes are also available
under the form of Unique Resource Identifiers (URIs) and are exportable
in Web Ontology Language (OWL). The International Classification of Primary
Care (ICPC) is linked to Q-Codes in order to form the Core Content
Classification in General Practice/Family Medicine (3CGP). So far, 3CGP is
in use by humans in pedagogy, in bibliographic studies, in indexing congresses,
master theses and other forms of grey literature in GP/FM. Use by
computers is experimented in automatic classifiers, annotators and natural
language processing.
Discussion
To the best of our knowledge, this is the first attempt to expand the ICPC
coding system with an extension for family physician contextual issues,
thus covering non-clinical content of practice. It remains to be proven that
our proposed terminology will help in dealing with more complex systems,
such as MeSH, to support information storage and retrieval activities.
However, this exercise is proposed as a first step in the creation of an ontology
of GP/FM and as an opening to the complex world of Semantic Web
technologies.
Conclusion
We expect that the creation of this terminological resource for indexing abstracts
and for facilitating Medline searches for general practitioners, researchers
and students in medicine will reduce loss of knowledge in the
domain of GP/FM. In addition, through better indexing of the grey literature
(congress abstracts, master’s and doctoral theses), we hope to enhance
the accessibility of research results and give visibility to the invisible work
of family physicians
Front-Line Physicians' Satisfaction with Information Systems in Hospitals
Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe
Clinical foundations and information architecture for the implementation of a federated health record service
Clinical care increasingly requires healthcare professionals to access patient record information that
may be distributed across multiple sites, held in a variety of paper and electronic formats, and
represented as mixtures of narrative, structured, coded and multi-media entries. A longitudinal
person-centred electronic health record (EHR) is a much-anticipated solution to this problem, but
its realisation is proving to be a long and complex journey.
This Thesis explores the history and evolution of clinical information systems, and establishes a set
of clinical and ethico-legal requirements for a generic EHR server. A federation approach (FHR) to
harmonising distributed heterogeneous electronic clinical databases is advocated as the basis for
meeting these requirements.
A set of information models and middleware services, needed to implement a Federated Health
Record server, are then described, thereby supporting access by clinical applications to a distributed
set of feeder systems holding patient record information. The overall information architecture thus
defined provides a generic means of combining such feeder system data to create a virtual
electronic health record. Active collaboration in a wide range of clinical contexts, across the whole
of Europe, has been central to the evolution of the approach taken.
A federated health record server based on this architecture has been implemented by the author
and colleagues and deployed in a live clinical environment in the Department of Cardiovascular
Medicine at the Whittington Hospital in North London. This implementation experience has fed
back into the conceptual development of the approach and has provided "proof-of-concept"
verification of its completeness and practical utility.
This research has benefited from collaboration with a wide range of healthcare sites, informatics
organisations and industry across Europe though several EU Health Telematics projects: GEHR,
Synapses, EHCR-SupA, SynEx, Medicate and 6WINIT.
The information models published here have been placed in the public domain and have
substantially contributed to two generations of CEN health informatics standards, including CEN
TC/251 ENV 13606
Proceedings of The Tenth International Workshop on Ontology Matching (OM-2015)
shvaiko2016aInternational audienceno abstrac
Teaching and Collecting Technical Standards: A Handbook for Librarians and Educators
Technical standards are a vital source of information for providing guidelines during the design, manufacture, testing, and use of whole products, materials, and components. To prepare students—especially engineering students—for the workforce, universities are increasing the use of standards within the curriculum. Employers believe it is important for recent university graduates to be familiar with standards. Despite the critical role standards play within academia and the workforce, little information is available on the development of standards information literacy, which includes the ability to understand the standardization process; identify types of standards; and locate, evaluate, and use standards effectively.
Libraries and librarians are a critical part of standards education, and much of the discussion has been focused on the curation of standards within libraries. However, librarians also have substantial experience in developing and teaching standards information literacy curriculum. With the need for universities to develop a workforce that is well-educated on the use of standards, librarians and course instructors can apply their experiences in information literacy toward teaching students the knowledge and skills regarding standards that they will need to be successful in their field. This title provides background information for librarians on technical standards as well as collection development best practices. It also creates a model for librarians and course instructors to use when building a standards information literacy curriculum.https://docs.lib.purdue.edu/pilh/1004/thumbnail.jp
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Ontology driven clinical decision support for early diagnostic recommendations
Diagnostic error is a significant problem in medicine and a major cause of concern for patients and clinicians and is associated with moderate to severe harm to patients. Diagnostic errors are a primary cause of clinical negligence and can result in malpractice claims. Cognitive errors caused by biases such as premature closure and confirmation bias have been identified as major cause of diagnostic error. Researchers have identified several strategies to reduce diagnostic error arising from cognitive factors. This includes considering alternatives, reducing reliance on memory, providing access to clear and well-organized information. Clinical Decision Support Systems (CDSSs) have been shown to reduce diagnostic errors.
Clinical guidelines improve consistency of care and can potentially improve healthcare efficiency. They can alert clinicians to diagnostic tests and procedures that have the greatest evidence and provide the greatest benefit. Clinical guidelines can be used to streamline clinical decision making and provide the knowledge base for guideline based CDSSs and clinical alert systems. Clinical guidelines can potentially improve diagnostic decision making by improving information gathering.
Argumentation is an emerging area for dealing with unstructured evidence in domains such as healthcare that are characterized by uncertainty. The knowledge needed to support decision making is expressed in the form of arguments. Argumentation has certain advantages over other decision support reasoning methods. This includes the ability to function with incomplete information, the ability to capture domain knowledge in an easy manner, using non-monotonic logic to support defeasible reasoning and providing recommendations in a manner that can be easily explained to clinicians. Argumentation is therefore a suitable method for generating early diagnostic recommendations. Argumentation-based CDSSs have been developed in a wide variety of clinical domains. However, the impact of an argumentation-based diagnostic Clinical Decision Support System (CDSS) has not been evaluated yet.
The first part of this thesis evaluates the impact of guideline recommendations and an argumentation-based diagnostic CDSS on clinician information gathering and diagnostic decision making. In addition, the impact of guideline recommendations on management decision making was evaluated. The study found that argumentation is a viable method for generating diagnostic recommendations that can potentially help reduce diagnostic error. The study showed that guideline recommendations do have a positive impact on information gathering of optometrists and can potentially help optometrists in asking the right questions and performing tests as per current standards of care. Guideline recommendations were found to have a positive impact on management decision making. The CDSS is dependent on quality of data that is entered into the system. Faulty interpretation of data can lead the clinician to enter wrong data and cause the CDSS to provide wrong recommendations.
Current generation argumentation-based CDSSs and other diagnostic decision support systems have problems with semantic interoperability that prevents them from using data from the web. The clinician and CDSS is limited to information collected during a clinical encounter and cannot access information on the web that could be relevant to a patient. This is due to the distributed nature of medical information and lack of semantic interoperability between healthcare systems. Current argumentation-based decision support applications require specialized tools for modelling and execution and this prevents widespread use and adoption of these tools especially when these tools require additional training and licensing arrangements.
Semantic web and linked data technologies have been developed to overcome problems with semantic interoperability on the web. Ontology-based diagnostic CDSS applications have been developed using semantic web technology to overcome problems with semantic interoperability of healthcare data in decision support applications. However, these models have problems with expressiveness, requiring specialized software and algorithms for generating diagnostic recommendations.
The second part of this thesis describes the development of an argumentation-based ontology driven diagnostic model and CDSS that can execute this model to generate ranked diagnostic recommendations. This novel model called the Disease-Symptom Model combines strengths of argumentation with strengths of semantic web technology. The model allows the domain expert to model arguments favouring and negating a diagnosis using OWL/RDF language. The model uses a simple weighting scheme that represents the degree of support of each argument within the model. The model uses SPARQL to sum weights and produce a ranked diagnostic recommendation. The model can provide justifications for each recommendation in a manner that clinicians can easily understand. CDSS prototypes that can execute this ontology model to generate diagnostic recommendations were developed. The decision support prototypes demonstrated the ability to use a wide variety of data and access remote data sources using linked data technologies to generate recommendations. The thesis was able to demonstrate the development of an argumentation-based ontology driven diagnostic decision support model and decision support system that can integrate information from a variety of sources to generate diagnostic recommendations. This decision support application was developed without the use of specialized software and tools for modelling and execution, while using a simple modelling method.
The third part of this thesis details evaluation of the Disease-Symptom model across all stages of a clinical encounter by comparing the performance of the model with clinicians. The evaluation showed that the Disease-Symptom Model can provide a ranked diagnostic recommendation in early stages of the clinical encounter that is comparable to clinicians. The diagnostic performance can be improved in the early stages using linked data technologies to incorporate more information into the decision making. With limited information, depending on the type of case, the performance of the Disease-Symptom Model will vary. As more information is collected during the clinical encounter the decision support application can provide recommendations that is comparable to clinicians recruited for the study. The evaluation showed that even with a simple weighting and summation method used in the Disease- Symptom Model the diagnostic ranking was comparable to dentists. With limited information in the early stages of the clinical encounter the Disease-Symptom Model was able to provide an accurately ranked diagnostic recommendation validating the model and methods used in this thesis