Article ; Online: An Unsupervised Cluster Analysis of Post-COVID-19 Mental Health Outcomes and Associated Comorbidities.
AMIA ... Annual Symposium proceedings. AMIA Symposium
2023 Volume 2022, Page(s) 289–298
Abstract: The COVID-19 pandemic continues to be widespread, and little is known about mental health impacts from dealing with the disease itself. This retrospective study used a deidentified health information exchange (HIE) dataset of electronic health record ... ...
| Abstract | The COVID-19 pandemic continues to be widespread, and little is known about mental health impacts from dealing with the disease itself. This retrospective study used a deidentified health information exchange (HIE) dataset of electronic health record data from the state of Rhode Island and characterized different subgroups of the positive COVID-19 population. Three different clustering methods were explored to identify patterns of condition groupings in this population. Increased incidence of mental health conditions was seen post-COVID-19 diagnosis, and these individuals exhibited higher prevalence of comorbidities compared to the negative control group. A self-organizing map cluster analysis showed patterns of mental health conditions in half of the clusters. One mental health cluster revealed a higher comorbidity index and higher severity of COVID-19 disease. The clinical features identified in this study motivate the need for more in-depth analysis to predict and identify individuals at high risk for developing mental illness post-COVID-19 diagnosis. |
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| MeSH term(s) | Humans ; COVID-19 ; Retrospective Studies ; Pandemics ; COVID-19 Testing ; Comorbidity ; Cluster Analysis ; Outcome Assessment, Health Care |
| Language | English |
| Publishing date | 2023-04-29 |
| Publishing country | United States |
| Document type | Journal Article ; Research Support, N.I.H., Extramural |
| ISSN | 1942-597X |
| ISSN (online) | 1942-597X |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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