A Visual Analytics Design for Connecting Healthcare Team Communication to Patient Outcomes
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916083864174592 |
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| author | Lu, Hsiao-Ying Li, Yiran Ma, Kwan-Liu |
| author_facet | Lu, Hsiao-Ying Li, Yiran Ma, Kwan-Liu |
| contents | Communication among healthcare professionals (HCPs) is crucial for the quality of patient treatment. Surrounding each patient's treatment, communication among HCPs can be examined as temporal networks, constructed from Electronic Health Record (EHR) access logs. This paper introduces a visual analytics system designed to study the effectiveness and efficiency of temporal communication networks mediated by the EHR system. We present a method that associates network measures with patient survival outcomes and devises effectiveness metrics based on these associations. To analyze communication efficiency, we extract the latencies and frequencies of EHR accesses. Our visual analytics system is designed to assist in inspecting and understanding the composed communication effectiveness metrics and to enable the exploration of communication efficiency by encoding latencies and frequencies in an information flow diagram. We demonstrate and evaluate our system through multiple case studies and an expert review. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_03700 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Visual Analytics Design for Connecting Healthcare Team Communication to Patient Outcomes Lu, Hsiao-Ying Li, Yiran Ma, Kwan-Liu Social and Information Networks Human-Computer Interaction Machine Learning Communication among healthcare professionals (HCPs) is crucial for the quality of patient treatment. Surrounding each patient's treatment, communication among HCPs can be examined as temporal networks, constructed from Electronic Health Record (EHR) access logs. This paper introduces a visual analytics system designed to study the effectiveness and efficiency of temporal communication networks mediated by the EHR system. We present a method that associates network measures with patient survival outcomes and devises effectiveness metrics based on these associations. To analyze communication efficiency, we extract the latencies and frequencies of EHR accesses. Our visual analytics system is designed to assist in inspecting and understanding the composed communication effectiveness metrics and to enable the exploration of communication efficiency by encoding latencies and frequencies in an information flow diagram. We demonstrate and evaluate our system through multiple case studies and an expert review. |
| title | A Visual Analytics Design for Connecting Healthcare Team Communication to Patient Outcomes |
| topic | Social and Information Networks Human-Computer Interaction Machine Learning |
| url | https://arxiv.org/abs/2401.03700 |