"Alone and Adrift in Analytics" - Insights from Long-term Involvements with Stroke Clinicians when Using Care Quality Monitoring Systems:Alone and Adrift in Analytics of Stroke Care Quality Monitoring

Care quality improvement systems (CQIS) allow hospitals to monitor and improve their care by analysing performance data. However, many CQIS fail at helping clinicians improve as they see decreased use and stagnating care quality. In this paper, we investigate the use of one CQIS through ten qualitative activities carried out across five years. We synthesize and present our results regarding specific problems various stakeholder face, what exact data visualization tasks clinicians struggle with, and concrete problems and solutions described by clinicians. Our research proposes steps that designers can take towards integrating data analysis interfaces and conversational AI systems in CQIS to assist with concrete data visualization problems identified by the 74 clinicians who participated in our studies.

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Publication Details

Journal
VBN Forskningsportal (Aalborg Universitet)
Published
2026-01-15
Primary Topic
Data Visualization and Analytics
Type
article
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article

"Alone and Adrift in Analytics" - Insights from Long-term Involvements with Stroke Clinicians when Using Care Quality Monitoring Systems:Alone and Adrift in Analytics of Stroke Care Quality Monitoring

Michał Karliński, Mathias Sand Kristensen, Hendrik Knoche, Hamzah Ziadeh et al.
VBN Forskningsportal (Aalborg Universitet)
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article

"Alone and Adrift in Analytics" - Insights from Long-term Involvements with Stroke Clinicians when Using Care Quality Monitoring Systems:Alone and Adrift in Analytics of Stroke Care Quality Monitoring

Michał Karliński, Mathias Sand Kristensen, Hendrik Knoche, Hamzah Ziadeh, Terry Quinn, Lina Palaiodimou, Robert Mikulik
article en

Abstract

Care quality improvement systems (CQIS) allow hospitals to monitor and improve their care by analysing performance data. However, many CQIS fail at helping clinicians improve as they see decreased use and stagnating care quality. In this paper, we investigate the use of one CQIS through ten qualitative activities carried out across five years. We synthesize and present our results regarding specific problems various stakeholder face, what exact data visualization tasks clinicians struggle with, and concrete problems and solutions described by clinicians. Our research proposes steps that designers can take towards integrating data analysis interfaces and conversational AI systems in CQIS to assist with concrete data visualization problems identified by the 74 clinicians who participated in our studies.

VBN Forskningsportal (Aalborg Universitet)
Openalex Percentile: Top 41%
Data Visualization and Analytics
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