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Provider Networks in the Neonatal Intensive Care Unit Associate with Length of Stay.
IEEE Conf Collab Internet Comput. 2019 Dec; 2019:127-134.IC

Abstract

We strive to understand care coordination structures of multidisciplinary teams and to evaluate their effect on post-surgical length of stay (PSLOS) in the Neonatal Intensive Care Unit (NICU). Electronic health record (EHR) data were extracted for 18 neonates, who underwent gastrostomy tube placement surgery at the Vanderbilt University Medical Center NICU. Based on providers' interactions with the EHR (e.g. viewing, documenting, ordering), provider-provider relations were learned and used to build patient-specific provider networks representing the care coordination structure. We quantified the networks using standard network analysis metrics (e.g., in-degree, out-degree, betweenness centrality, and closeness centrality). Coordination structure effectiveness was measured as the association between the network metrics and PSLOS, as modeled by a proportional-odds, logistical regression model. The 18 provider networks exhibited various team compositions and various levels of structural complexity. Providers, whose patients had lower PSLOS, tended to disperse patient-related information to more colleagues within their network than those, who treated higher PSLOS patients (P = 0.0294). In the NICU, improved dissemination of information may be linked to reduced PSLOS. EHR data provides an efficient, accessible, and resource-friendly way to study care coordination using network analysis tools. This novel methodology offers an objective way to identify key performance and safety indicators of care coordination and to study dissemination of patient-related information within care provider networks and its effect on care. Findings should guide improvements in the EHR system design to facilitate effective clinical communications among providers.

Authors+Show Affiliations

Department of Mathematics, Vanderbilt University, Nashville, TN.Department of Pediatrics, UT Southwestern, Dallas, TX.Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN.Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN.Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN.Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32637942

Citation

Kim, Cindy, et al. "Provider Networks in the Neonatal Intensive Care Unit Associate With Length of Stay." ... IEEE Conference On Collaboration and Internet Computing. IEEE Conference On Collaboration and Internet Computing, vol. 2019, 2019, pp. 127-134.
Kim C, Lehmann CU, Hatch D, et al. Provider Networks in the Neonatal Intensive Care Unit Associate with Length of Stay. IEEE Conf Collab Internet Comput. 2019;2019:127-134.
Kim, C., Lehmann, C. U., Hatch, D., Schildcrout, J. S., France, D. J., & Chen, Y. (2019). Provider Networks in the Neonatal Intensive Care Unit Associate with Length of Stay. ... IEEE Conference On Collaboration and Internet Computing. IEEE Conference On Collaboration and Internet Computing, 2019, 127-134. https://doi.org/10.1109/CIC48465.2019.00024
Kim C, et al. Provider Networks in the Neonatal Intensive Care Unit Associate With Length of Stay. IEEE Conf Collab Internet Comput. 2019;2019:127-134. PubMed PMID: 32637942.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Provider Networks in the Neonatal Intensive Care Unit Associate with Length of Stay. AU - Kim,Cindy, AU - Lehmann,Christoph U, AU - Hatch,Dupree, AU - Schildcrout,Jonathan S, AU - France,Daniel J, AU - Chen,You, Y1 - 2020/02/13/ PY - 2020/7/9/entrez PY - 2020/7/9/pubmed PY - 2020/7/9/medline KW - Audit Logs KW - Care Coordination KW - Electronic Health Records (EHR) KW - Neonatal Intensive Care Unit (NICU) KW - Network Analysis KW - Post-Surgical Length of Stay (PSLOS) SP - 127 EP - 134 JF - ... IEEE Conference on Collaboration and Internet Computing. IEEE Conference on Collaboration and Internet Computing JO - IEEE Conf Collab Internet Comput VL - 2019 N2 - We strive to understand care coordination structures of multidisciplinary teams and to evaluate their effect on post-surgical length of stay (PSLOS) in the Neonatal Intensive Care Unit (NICU). Electronic health record (EHR) data were extracted for 18 neonates, who underwent gastrostomy tube placement surgery at the Vanderbilt University Medical Center NICU. Based on providers' interactions with the EHR (e.g. viewing, documenting, ordering), provider-provider relations were learned and used to build patient-specific provider networks representing the care coordination structure. We quantified the networks using standard network analysis metrics (e.g., in-degree, out-degree, betweenness centrality, and closeness centrality). Coordination structure effectiveness was measured as the association between the network metrics and PSLOS, as modeled by a proportional-odds, logistical regression model. The 18 provider networks exhibited various team compositions and various levels of structural complexity. Providers, whose patients had lower PSLOS, tended to disperse patient-related information to more colleagues within their network than those, who treated higher PSLOS patients (P = 0.0294). In the NICU, improved dissemination of information may be linked to reduced PSLOS. EHR data provides an efficient, accessible, and resource-friendly way to study care coordination using network analysis tools. This novel methodology offers an objective way to identify key performance and safety indicators of care coordination and to study dissemination of patient-related information within care provider networks and its effect on care. Findings should guide improvements in the EHR system design to facilitate effective clinical communications among providers. UR - https://www.unboundmedicine.com/medline/citation/32637942/Provider_Networks_in_the_Neonatal_Intensive_Care_Unit_Associate_with_Length_of_Stay L2 - https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/32637942/ DB - PRIME DP - Unbound Medicine ER -
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