Abstract
Objective: To develop methods for measuring electronic communication networks in virtual care teams using electronic health records (EHR)access-log data. Methods: For a convenient sample of 100 surgical colorectal cancer patients, we used time-stamped EHR access-log data extracted from an academic medical center's EHR system to construct communication networks among healthcare professionals (HCPs)in each patient's virtual care team. We measured communication linkages between HCPs using the inverse of the average time between access events in which the source HCPs sent information to and the destination HCPs retrieved information from the EHR system. Social network analysis was used to examine and visualize communication network structures, identify principal care teams, and detect meaningful structural differences across networks. We conducted a non-parametric multivariate analysis of variance (MANOVA)to test the association between care teams’ communication network structures and patients’ cancer stage and site. Results: The 100 communication networks showed substantial variations in size and structures. Principal care teams, the subset of HCPs who formed the core of the communication networks, had higher proportions of nurses, physicians, and pharmacists and a lower proportion of laboratory medical technologists than the overall networks. The distributions of conditional uniform graph quantiles suggested that our network-construction technique captured meaningful underlying structures that were different from random unstructured networks. MANOVA results found that the networks’ topologies were associated with patients’ cancer stage and site. Conclusions: This study demonstrates that it is feasible to use EHR access-log data to measure and examine communication networks in virtual care teams. The proposed methods captured salient communication patterns in care teams that were associated with patients’ clinical differences.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 46-52 |
| Number of pages | 7 |
| Journal | International Journal of Medical Informatics |
| Volume | 128 |
| DOIs | |
| State | Published - Aug 1 2019 |
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Keywords
- Communication networks
- Electronic health records
- Methods
- Virtual care teams
ASJC Scopus subject areas
- Health Informatics
Cite this
Measuring electronic communication networks in virtual care teams using electronic health records access-log data. / Zhu, Xi; Tu, Shin-Ping; Sewell, Daniel; Yao, Nengliang (Aaron); Mishra, Vimal; Dow, Alan; Banas, Colin.
In: International Journal of Medical Informatics, Vol. 128, 01.08.2019, p. 46-52.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Measuring electronic communication networks in virtual care teams using electronic health records access-log data
AU - Zhu, Xi
AU - Tu, Shin-Ping
AU - Sewell, Daniel
AU - Yao, Nengliang (Aaron)
AU - Mishra, Vimal
AU - Dow, Alan
AU - Banas, Colin
PY - 2019/8/1
Y1 - 2019/8/1
N2 - Objective: To develop methods for measuring electronic communication networks in virtual care teams using electronic health records (EHR)access-log data. Methods: For a convenient sample of 100 surgical colorectal cancer patients, we used time-stamped EHR access-log data extracted from an academic medical center's EHR system to construct communication networks among healthcare professionals (HCPs)in each patient's virtual care team. We measured communication linkages between HCPs using the inverse of the average time between access events in which the source HCPs sent information to and the destination HCPs retrieved information from the EHR system. Social network analysis was used to examine and visualize communication network structures, identify principal care teams, and detect meaningful structural differences across networks. We conducted a non-parametric multivariate analysis of variance (MANOVA)to test the association between care teams’ communication network structures and patients’ cancer stage and site. Results: The 100 communication networks showed substantial variations in size and structures. Principal care teams, the subset of HCPs who formed the core of the communication networks, had higher proportions of nurses, physicians, and pharmacists and a lower proportion of laboratory medical technologists than the overall networks. The distributions of conditional uniform graph quantiles suggested that our network-construction technique captured meaningful underlying structures that were different from random unstructured networks. MANOVA results found that the networks’ topologies were associated with patients’ cancer stage and site. Conclusions: This study demonstrates that it is feasible to use EHR access-log data to measure and examine communication networks in virtual care teams. The proposed methods captured salient communication patterns in care teams that were associated with patients’ clinical differences.
AB - Objective: To develop methods for measuring electronic communication networks in virtual care teams using electronic health records (EHR)access-log data. Methods: For a convenient sample of 100 surgical colorectal cancer patients, we used time-stamped EHR access-log data extracted from an academic medical center's EHR system to construct communication networks among healthcare professionals (HCPs)in each patient's virtual care team. We measured communication linkages between HCPs using the inverse of the average time between access events in which the source HCPs sent information to and the destination HCPs retrieved information from the EHR system. Social network analysis was used to examine and visualize communication network structures, identify principal care teams, and detect meaningful structural differences across networks. We conducted a non-parametric multivariate analysis of variance (MANOVA)to test the association between care teams’ communication network structures and patients’ cancer stage and site. Results: The 100 communication networks showed substantial variations in size and structures. Principal care teams, the subset of HCPs who formed the core of the communication networks, had higher proportions of nurses, physicians, and pharmacists and a lower proportion of laboratory medical technologists than the overall networks. The distributions of conditional uniform graph quantiles suggested that our network-construction technique captured meaningful underlying structures that were different from random unstructured networks. MANOVA results found that the networks’ topologies were associated with patients’ cancer stage and site. Conclusions: This study demonstrates that it is feasible to use EHR access-log data to measure and examine communication networks in virtual care teams. The proposed methods captured salient communication patterns in care teams that were associated with patients’ clinical differences.
KW - Communication networks
KW - Electronic health records
KW - Methods
KW - Virtual care teams
UR - http://www.scopus.com/inward/record.url?scp=85066099336&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85066099336&partnerID=8YFLogxK
U2 - 10.1016/j.ijmedinf.2019.05.012
DO - 10.1016/j.ijmedinf.2019.05.012
M3 - Article
C2 - 31160011
AN - SCOPUS:85066099336
VL - 128
SP - 46
EP - 52
JO - International Journal of Medical Informatics
JF - International Journal of Medical Informatics
SN - 1386-5056
ER -