Cluster analysis of COVID-19 recovery center patients at a clinic in Boston, MA 2021–2022: impact on strategies for access and personalized care
Abstract Background There are known disparities in COVID-19 resource utilization that may persist during the recovery period for some patients. We sought to define subpopulations of patients seeking COVID-19 recovery care in terms of symptom reporting and care utilization to better personalize their...
| Main Authors: | , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-03-01
|
| Series: | Archives of Public Health |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13690-023-01033-2 |
| _version_ | 1797865460335640576 |
|---|---|
| author | Ann-Marcia C. Tukpah Jhillika Patel Beret Amundson Miguel Linares Meera Sury Julie Sullivan Tajmah Jocelyn Brenda Kissane Gerald Weinhouse Nancy Lange-Vaidya Daniela Lamas Khalid Ismail Chandan Pavuluri Michael H. Cho Elizabeth B. Gay Matthew Moll |
| author_facet | Ann-Marcia C. Tukpah Jhillika Patel Beret Amundson Miguel Linares Meera Sury Julie Sullivan Tajmah Jocelyn Brenda Kissane Gerald Weinhouse Nancy Lange-Vaidya Daniela Lamas Khalid Ismail Chandan Pavuluri Michael H. Cho Elizabeth B. Gay Matthew Moll |
| author_sort | Ann-Marcia C. Tukpah |
| collection | DOAJ |
| description | Abstract Background There are known disparities in COVID-19 resource utilization that may persist during the recovery period for some patients. We sought to define subpopulations of patients seeking COVID-19 recovery care in terms of symptom reporting and care utilization to better personalize their care and to identify ways to improve access to subspecialty care. Methods Prospective study of adult patients with prior COVID-19 infection seen in an ambulatory COVID-19 recovery center (CRC) in Boston, Massachusetts from April 2021 to April 2022. Hierarchical clustering with complete linkage to differentiate subpopulations was done with four sociodemographic variables: sex, race, language, and insurance status. Outcomes included ICU admission, utilization of supplementary care, self-report of symptoms. Results We included 1285 COVID-19 patients referred to the CRC with a mean age of 47 years, of whom 71% were female and 78% White. We identified 3 unique clusters of patients. Cluster 1 and 3 patients were more likely to have had intensive care unit (ICU) admissions; Cluster 2 were more likely to be White with commercial insurance and a low percentage of ICU admission; Cluster 3 were more likely to be Black/African American or Latino/a and have commercial insurance. Compared to Cluster 2, Cluster 1 patients were more likely to report symptoms (ORs ranging 2.4–3.75) but less likely to use support groups, psychoeducation, or care coordination (all p < 0.05). Cluster 3 patients reported greater symptoms with similar levels of community resource utilization. Conclusions Within a COVID-19 recovery center, there are distinct groups of patients with different clinical and socio-demographic profiles, which translates to differential resource utilization. These insights from different subpopulations of patients can inform targeted strategies which are tailored to specific patient needs. |
| first_indexed | 2024-04-09T23:09:29Z |
| format | Article |
| id | doaj.art-30ebd8f42d974c3d992e43badaaad63b |
| institution | Directory Open Access Journal |
| issn | 2049-3258 |
| language | English |
| last_indexed | 2024-04-09T23:09:29Z |
| publishDate | 2023-03-01 |
| publisher | BMC |
| record_format | Article |
| series | Archives of Public Health |
| spelling | doaj.art-30ebd8f42d974c3d992e43badaaad63b2023-03-22T10:30:04ZengBMCArchives of Public Health2049-32582023-03-018111810.1186/s13690-023-01033-2Cluster analysis of COVID-19 recovery center patients at a clinic in Boston, MA 2021–2022: impact on strategies for access and personalized careAnn-Marcia C. Tukpah0Jhillika Patel1Beret Amundson2Miguel Linares3Meera Sury4Julie Sullivan5Tajmah Jocelyn6Brenda Kissane7Gerald Weinhouse8Nancy Lange-Vaidya9Daniela Lamas10Khalid Ismail11Chandan Pavuluri12Michael H. Cho13Elizabeth B. Gay14Matthew Moll15Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s HospitalRobert Wood Johnson Medical SchoolDepartment of Medicine, Brigham and Women’s HospitalDepartment of Medicine, Brigham and Women’s HospitalDepartment of Medicine, Brigham and Women’s HospitalDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s HospitalDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s HospitalDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s HospitalDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s HospitalDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s HospitalDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s HospitalDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s HospitalChanning Division of Network Medicine, Brigham and Women’s HospitalChanning Division of Network Medicine, Brigham and Women’s HospitalDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s HospitalDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s HospitalAbstract Background There are known disparities in COVID-19 resource utilization that may persist during the recovery period for some patients. We sought to define subpopulations of patients seeking COVID-19 recovery care in terms of symptom reporting and care utilization to better personalize their care and to identify ways to improve access to subspecialty care. Methods Prospective study of adult patients with prior COVID-19 infection seen in an ambulatory COVID-19 recovery center (CRC) in Boston, Massachusetts from April 2021 to April 2022. Hierarchical clustering with complete linkage to differentiate subpopulations was done with four sociodemographic variables: sex, race, language, and insurance status. Outcomes included ICU admission, utilization of supplementary care, self-report of symptoms. Results We included 1285 COVID-19 patients referred to the CRC with a mean age of 47 years, of whom 71% were female and 78% White. We identified 3 unique clusters of patients. Cluster 1 and 3 patients were more likely to have had intensive care unit (ICU) admissions; Cluster 2 were more likely to be White with commercial insurance and a low percentage of ICU admission; Cluster 3 were more likely to be Black/African American or Latino/a and have commercial insurance. Compared to Cluster 2, Cluster 1 patients were more likely to report symptoms (ORs ranging 2.4–3.75) but less likely to use support groups, psychoeducation, or care coordination (all p < 0.05). Cluster 3 patients reported greater symptoms with similar levels of community resource utilization. Conclusions Within a COVID-19 recovery center, there are distinct groups of patients with different clinical and socio-demographic profiles, which translates to differential resource utilization. These insights from different subpopulations of patients can inform targeted strategies which are tailored to specific patient needs.https://doi.org/10.1186/s13690-023-01033-2InformaticsEquityDisparitiesCommunity healthQuality of care |
| spellingShingle | Ann-Marcia C. Tukpah Jhillika Patel Beret Amundson Miguel Linares Meera Sury Julie Sullivan Tajmah Jocelyn Brenda Kissane Gerald Weinhouse Nancy Lange-Vaidya Daniela Lamas Khalid Ismail Chandan Pavuluri Michael H. Cho Elizabeth B. Gay Matthew Moll Cluster analysis of COVID-19 recovery center patients at a clinic in Boston, MA 2021–2022: impact on strategies for access and personalized care Archives of Public Health Informatics Equity Disparities Community health Quality of care |
| title | Cluster analysis of COVID-19 recovery center patients at a clinic in Boston, MA 2021–2022: impact on strategies for access and personalized care |
| title_full | Cluster analysis of COVID-19 recovery center patients at a clinic in Boston, MA 2021–2022: impact on strategies for access and personalized care |
| title_fullStr | Cluster analysis of COVID-19 recovery center patients at a clinic in Boston, MA 2021–2022: impact on strategies for access and personalized care |
| title_full_unstemmed | Cluster analysis of COVID-19 recovery center patients at a clinic in Boston, MA 2021–2022: impact on strategies for access and personalized care |
| title_short | Cluster analysis of COVID-19 recovery center patients at a clinic in Boston, MA 2021–2022: impact on strategies for access and personalized care |
| title_sort | cluster analysis of covid 19 recovery center patients at a clinic in boston ma 2021 2022 impact on strategies for access and personalized care |
| topic | Informatics Equity Disparities Community health Quality of care |
| url | https://doi.org/10.1186/s13690-023-01033-2 |
| work_keys_str_mv | AT annmarciactukpah clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare AT jhillikapatel clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare AT beretamundson clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare AT miguellinares clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare AT meerasury clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare AT juliesullivan clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare AT tajmahjocelyn clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare AT brendakissane clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare AT geraldweinhouse clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare AT nancylangevaidya clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare AT danielalamas clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare AT khalidismail clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare AT chandanpavuluri clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare AT michaelhcho clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare AT elizabethbgay clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare AT matthewmoll clusteranalysisofcovid19recoverycenterpatientsataclinicinbostonma20212022impactonstrategiesforaccessandpersonalizedcare |