Quantifying care delivery team influences on the hospitalization outcomes of patients with multimorbidity: Implications for clinical informatics
The primary objective was to quantify the influences of care delivery teams on the outcomes of patients with multimorbidity. Electronic medical record data on 68,883 patient care encounters (i.e., 54,664 patients) were extracted from the Arkansas Clinical Data Repository. Social network analysis ass...
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2023-05-01
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| Series: | Journal of Multimorbidity and Comorbidity |
| Online Access: | https://doi.org/10.1177/26335565231176168 |
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| author | Tremaine B Williams Taiquitha Robins Jennifer L Vincenzo Riley Lipschitz Ahmad Baghal Kevin Wayne Sexton |
| author_facet | Tremaine B Williams Taiquitha Robins Jennifer L Vincenzo Riley Lipschitz Ahmad Baghal Kevin Wayne Sexton |
| author_sort | Tremaine B Williams |
| collection | DOAJ |
| description | The primary objective was to quantify the influences of care delivery teams on the outcomes of patients with multimorbidity. Electronic medical record data on 68,883 patient care encounters (i.e., 54,664 patients) were extracted from the Arkansas Clinical Data Repository. Social network analysis assessed the minimum care team size associated with improved care outcomes (i.e., hospitalizations, days between hospitalizations, and cost) of patients with multimorbidity. Binomial logistic regression further assessed the influence of the presence of seven specific clinical roles. When compared to patients without multimorbidity, patients with multimorbidity had a higher mean age (i.e., 47.49 v. 40.61), a higher mean dollar amount of cost per encounter (i.e., $3,068 v. $2,449), a higher number of hospitalizations (i.e., 25 v. 4), and a higher number of clinicians engaged in their care (i.e., 139,391 v. 7,514). Greater network density in care teams (i.e., any combination of two or more Physicians, Residents, Nurse Practitioners, Registered Nurses, or Care Managers) was associated with a 46–98% decreased odds of having a high number of hospitalizations. Greater network density (i.e., any combination of two or more Residents or Registered Nurses) was associated with 11–13% increased odds of having a high cost encounter. Greater network density was not significantly associated with having a high number of days between hospitalizations. Analyzing the social networks of care teams may fuel computational tools that better monitor and visualize real-time hospitalization risk and care cost that are germane to care delivery. |
| format | Article |
| id | doaj-art-d2a980df6a3b46d0940e674416b2eda8 |
| institution | Kabale University |
| issn | 2633-5565 |
| language | English |
| publishDate | 2023-05-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Journal of Multimorbidity and Comorbidity |
| spelling | doaj-art-d2a980df6a3b46d0940e674416b2eda82024-11-14T08:03:19ZengSAGE PublishingJournal of Multimorbidity and Comorbidity2633-55652023-05-011310.1177/26335565231176168Quantifying care delivery team influences on the hospitalization outcomes of patients with multimorbidity: Implications for clinical informaticsTremaine B WilliamsTaiquitha RobinsJennifer L VincenzoRiley LipschitzAhmad BaghalKevin Wayne SextonThe primary objective was to quantify the influences of care delivery teams on the outcomes of patients with multimorbidity. Electronic medical record data on 68,883 patient care encounters (i.e., 54,664 patients) were extracted from the Arkansas Clinical Data Repository. Social network analysis assessed the minimum care team size associated with improved care outcomes (i.e., hospitalizations, days between hospitalizations, and cost) of patients with multimorbidity. Binomial logistic regression further assessed the influence of the presence of seven specific clinical roles. When compared to patients without multimorbidity, patients with multimorbidity had a higher mean age (i.e., 47.49 v. 40.61), a higher mean dollar amount of cost per encounter (i.e., $3,068 v. $2,449), a higher number of hospitalizations (i.e., 25 v. 4), and a higher number of clinicians engaged in their care (i.e., 139,391 v. 7,514). Greater network density in care teams (i.e., any combination of two or more Physicians, Residents, Nurse Practitioners, Registered Nurses, or Care Managers) was associated with a 46–98% decreased odds of having a high number of hospitalizations. Greater network density (i.e., any combination of two or more Residents or Registered Nurses) was associated with 11–13% increased odds of having a high cost encounter. Greater network density was not significantly associated with having a high number of days between hospitalizations. Analyzing the social networks of care teams may fuel computational tools that better monitor and visualize real-time hospitalization risk and care cost that are germane to care delivery.https://doi.org/10.1177/26335565231176168 |
| spellingShingle | Tremaine B Williams Taiquitha Robins Jennifer L Vincenzo Riley Lipschitz Ahmad Baghal Kevin Wayne Sexton Quantifying care delivery team influences on the hospitalization outcomes of patients with multimorbidity: Implications for clinical informatics Journal of Multimorbidity and Comorbidity |
| title | Quantifying care delivery team influences on the hospitalization outcomes of patients with multimorbidity: Implications for clinical informatics |
| title_full | Quantifying care delivery team influences on the hospitalization outcomes of patients with multimorbidity: Implications for clinical informatics |
| title_fullStr | Quantifying care delivery team influences on the hospitalization outcomes of patients with multimorbidity: Implications for clinical informatics |
| title_full_unstemmed | Quantifying care delivery team influences on the hospitalization outcomes of patients with multimorbidity: Implications for clinical informatics |
| title_short | Quantifying care delivery team influences on the hospitalization outcomes of patients with multimorbidity: Implications for clinical informatics |
| title_sort | quantifying care delivery team influences on the hospitalization outcomes of patients with multimorbidity implications for clinical informatics |
| url | https://doi.org/10.1177/26335565231176168 |
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