Related Experiment Video
Updated: Mar 6, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Describing knowledge encounters in healthcare: a mixed studies systematic review and development of a classification
Dominic Hurst1,2, Sharon Mickan3,4,5
1Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK. r.d.hurst@qmul.ac.uk.
Background:
Implementation science seeks to promote the uptake of research and other evidence-based findings into practice, but for healthcare professionals, this is complex as practice draws on, in addition to scientific principles, rules of thumb and a store of practical wisdom acquired from a range of informational and experiential sources. The aims of this review were to identify sources of information and professional experiences encountered by healthcare workers and from this to build a classification system, for use in future observational studies, that describes influences on how healthcare professionals acquire and use information in their clinical practice.
Methods:
This was a mixed studies systematic review of observational studies.
Data Sources:
OVID MEDLINE and Embase and Google Scholar were searched using terms around information, knowledge or evidence and sharing, searching and utilisation combined with terms relating to healthcare groups.
Eligibility:
Studies were eligible if one of the intentions was to identify information or experiential encounters by healthcare workers.
Data Extraction:
Data was extracted by one author after piloting with another.
Study Appraisal:
Studies were assessed using the Mixed Methods Appraisal Tool (MMAT).
Primary Outcome:
The primary outcome extracted was the information source or professional experience encounter.
Analysis:
Similar encounters were grouped together as single constructs. Our synthesis involved a mixed approach using the top-down logic of the Bliss Bibliographic Classification System (BC2) to generate classification categories and a bottom-up approach to develop descriptive codes (or "facets") for each category, from the data. The generic terms of BC2 were customised by an iterative process of thematic content analysis. Facets were developed by using available theory and keeping in mind the pragmatic end use of the classification.
Results:
Eighty studies were included from which 178 discreet knowledge encounters were extracted. Six classification categories were developed: what information or experience was encountered; how was the information or experience encountered; what was the mode of encounter; from whom did the information originate or with whom was the experience; how many participants were there; and where did the encounter take place. For each of these categories, relevant descriptive facets were identified.
Conclusions:
We have sought to identify and classify all knowledge encounters, and we have developed a faceted description of key categories which will support richer descriptions and interrogations of knowledge encounters in healthcare research.
More Related Videos
05:47Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
07:35A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
Published on: October 13, 2023
Related Concept Videos
Classification of Illness
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
Health Information Technology and Healthcare Information System
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
Healthcare Associated Infections I: Iatrogenic, Exogenic and Endogenic
HAIs significantly increase the cost of health care. Extended stays in healthcare institutions, increased disability, increased costs of medications, including specialized antibiotics, and prolonged recovery times add to the patient's expenses and the healthcare institution and funding bodies.
Nursing Clinical Information System
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
Tertiary Healthcare System
Methods of Documentation VI: Case Management Model
For example, a patient with a chronic...