@article{demelo_ontology-driven_2017,

title = {Ontology-Driven Search and Triage: Design of a Web-Based Visual Interface for MEDLINE},

author = {Jonathan Demelo and Paul Parsons and Kamran Sedig},

url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5314102/},

doi = {10.2196/medinform.6918},

issn = {2291-9694},

year  = {2017},

date = {2017-01-01},

urldate = {2019-01-25},

journal = {JMIR Medical Informatics},

volume = {5},

number = {1},

abstract = {Background 

Diverse users need to search health and medical literature to satisfy open-ended goals such as making evidence-based decisions and updating their knowledge. However, doing so is challenging due to at least two major difficulties: (1) articulating information needs using accurate vocabulary and (2) dealing with large document sets returned from searches. Common search interfaces such as PubMed do not provide adequate support for exploratory search tasks. 

 

Objective 

Our objective was to improve support for exploratory search tasks by combining two strategies in the design of an interactive visual interface by (1) using a formal ontology to help users build domain-specific knowledge and vocabulary and (2) providing multi-stage triaging support to help mitigate the information overload problem. 

 

Methods 

We developed a Web-based tool, Ontology-Driven Visual Search and Triage Interface for MEDLINE (OVERT-MED), to test our design ideas. We implemented a custom searchable index of MEDLINE, which comprises approximately 25 million document citations. We chose a popular biomedical ontology, the Human Phenotype Ontology (HPO), to test our solution to the vocabulary problem. We implemented multistage triaging support in OVERT-MED, with the aid of interactive visualization techniques, to help users deal with large document sets returned from searches. 

 

Results 

Formative evaluation suggests that the design features in OVERT-MED are helpful in addressing the two major difficulties described above. Using a formal ontology seems to help users articulate their information needs with more accurate vocabulary. In addition, multistage triaging combined with interactive visualizations shows promise in mitigating the information overload problem. 

 

Conclusions 

Our strategies appear to be valuable in addressing the two major problems in exploratory search. Although we tested OVERT-MED with a particular ontology and document collection, we anticipate that our strategies can be transferred successfully to other contexts.},

keywords = {healthcare, information visualization, search},

pubstate = {published},

tppubtype = {article}

}

@article{Sedig2015,

title = {Reconsidering healthcare evidence as dynamic and distributed: the role of information and cognition},

author = {Kamran Sedig and Paul Parsons and Anthony Naimi and Keith Willoughby},

url = {https://www.dvclab.net/wp-content/uploads/2020/04/Sedig-et-al-2015-IJEBH.pdf},

doi = {10.1097/XEB.0000000000000030},

issn = {1744-1609},

year  = {2015},

date = {2015-01-01},

journal = {International Journal of Evidence-Based Healthcare},

volume = {13},

number = {2},

pages = {43--51},

abstract = {AIM. The basic thrust of evidence-based healthcare is that current best evidence should be used explicitly and judiciously for diagnosis, management, and other activities in healthcare settings. For this to be possible, researchers, practitioners, and other stakeholders must have a clear and accurate conceptualization of what constitutes ‘evidence’ in healthcare environments, and the manner in which it is used in decision-making and other activities. Currently, the dominant conceptualization of evidence is that of a body of information that can be retrieved by stakeholders for use in healthcare practice. The aim of this article is to critically examine the concept of evidence, particularly in light of recent models of human cognition and information use in decision-making and other cognitive activities. METHODS. In this theoretical article, we employ both analytical and synthetic methods to critically examine the concepts under investigation. Key concepts, such as evidence and information, and the essential relationships between them are analyzed from the vantage point of cognitive science, information science, and other relevant disciplines to explicate a conceptualization of evidence that moves past static and objectivist accounts. RESULTS. We demonstrate that evidence is fundamentally information that takes various forms—i.e., artifacts, mental structures, or communication processes. Specific forms and manifestations of evidence can thus be described in the context of information use in dynamic information environments. Furthermore, evidence-based healthcare activities are shown to be fundamentally cognitive in nature. For any given evidence-based healthcare activity, its quality and outcome can be understood in the context of how different sources of evidence are coordinated within a distributed cognitive system. In this sense, evidence based health care activity becomes more a matter of understanding the movement of information and knowledge within a distributed and dynamic cognitive system than mere access to or translation of a ready-at-hand resource. CONCLUSIONS. The conceptualization of evidence presented in this article has a number of implications for evidence- based healthcare—in terms of where attention is focused, the direction of future research efforts, how evidence generation, use, and practice are conceptualized and discussed, and how healthcare technologies are designed and evaluated. Furthermore, the conceptualization presented in this article has implications for the manner in which evidence ‘hierarchies’ are developed. Such hierarchies do not provide a complete picture of evidence and the way it is used in healthcare activities. Understanding the dynamic nature of evidence and its role in distributed cognitive activities may lead to more robust and multi-faceted taxonomies, frameworks, and hierarchies related to evidence-based healthcare.},

note = {ISBN: 0000000000000},

keywords = {distributed cognition, healthcare},

pubstate = {published},

tppubtype = {article}

}

@article{Sedig2012b,

title = {Beyond information access: Support for complex cognitive activities in public health informatics tools},

author = {Kamran Sedig and Paul Parsons and Mark Dittmer and Oluwakemi Ola},

url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3615827/},

year  = {2012},

date = {2012-01-01},

journal = {Online Journal of Public Health Informatics},

volume = {4},

number = {3},

pages = {23},

abstract = {Public health professionals work with a variety of information sources to carry out their everyday activities. In recent years, interactive computational tools have become deeply embedded in such activities. Unlike the early days of computational tool use, the potential of tools nowadays is not limited to simply providing access to information; rather, they can act as powerful mediators of human-information discourse, enabling rich interaction with public health information. If public health informatics tools are designed and used properly, they can facilitate, enhance, and support the performance of complex cognitive activities that are essential to public health informatics, such as problem solving, forecasting, sense-making, and planning. However, the effective design and evaluation of public health informatics tools requires an understanding of the cognitive and perceptual issues pertaining to how humans work and think with information to perform such activities. This paper draws on research that has examined some of the relevant issues, including interaction design, complex cognition, and visual representations, to offer some human-centered design and evaluation considerations for public health informatics tools.},

keywords = {cognition, design, healthcare},

pubstate = {published},

tppubtype = {article}

}