Identifying the value of a clinical information system during the COVID-19 pandemic
Technovation
; 120, 2023.
Article
in English
| Scopus | ID: covidwho-2242984
ABSTRACT
The COVID-19 pandemic has significantly augmented the urgency for service providers to identify and develop clinically urgent system alterations into healthcare systems to facilitate antibody testing and treatment interventions. However, it has been difficult to determine how users assess the value of an information system in terms of its functionality and features. Conversely, the system development process to address urgent user requirements, for example, developing new functionality for COVID antibody testing, has been beset by a myriad of difficulties as research to understand the value of specific aspects of clinical information systems has been elusive. This study addresses this knowledge gap by identifying specific aspects of a national clinical information system in Wales, UK. Through a series of semi-structured interviews, a quantitative study of 559 clinical users and a focus group, the study deconstructs system-related value into 14 unique attributes that have been found to vary according to different types of user roles and geographic location. Attribution theory is identified in this study as a novel and effective way to study this multifaceted concept of system value. The identification of component attributes of the value of a clinical information system provides insights for service users, system developers, and organization managers to prioritize and focus their system development activity by using an importance ranking identified through this study. © 2021 Elsevier Ltd
Clinical research; COVID-19; Health care; Information use; Medical computing; Medical information systems; Attribute; Clinical information system; Clinician; Healthcare; Healthcare systems; Role; Service provider; System development process; User requirements; Value; Antibodies; Information system; Location
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Prognostic study
Language:
English
Journal:
Technovation
Year:
2023
Document Type:
Article
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