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Distinct phenotypes of patients and healthcare resource utilization after hospitalization for COVID-19: an
Claire Marant Micallef1, Manon Belhassen2, Florence Ader3,4
1PELyon, Pharmacoépidémiologie Lyon, 210 Avenue Jean Jaurès, Lyon, 69007, France. claire.marant-micallef@pelyon.fr.
Insights
Post-COVID-19 hospitalization patients show 8 distinct healthcare resource use profiles. These patient clusters help anticipate future care needs after coronavirus disease 2019 recovery.
Area of Science:
- Public Health
- Epidemiology
- Health Services Research
Background:
- Healthcare resource use (HCU) post-hospitalization for coronavirus disease 2019 (COVID-19) is not well understood.
- Identifying distinct patient profiles based on post-discharge care is crucial for effective resource allocation.
Purpose of the Study:
- To identify distinct patient profiles based on post-discharge healthcare resource use (HCU) after hospitalization for COVID-19.
- To understand the varied healthcare needs of patients recovering from severe COVID-19.
Main Methods:
- Retrospective cohort study of 68,822 patients hospitalized for COVID-19 in France.
- Analysis of healthcare resource use (HCU) over 5 months post-discharge using French National Health System claims data.
- Ward's ascendant hierarchical clustering (AHC) to identify patient profiles based on HCU and clinical characteristics.
Main Results:
- Eight distinct patient clusters were identified based on post-COVID-19 HCU.
- Clusters varied in age, comorbidities (cancer, mental disorders, cardiac/respiratory failure), obesity, and index hospital stay complexity.
- The largest cluster (n=35,501) was representative of the overall study population.
Conclusions:
- Ascendant hierarchical clustering identified 8 clinically relevant profiles of patients surviving COVID-19 hospitalization.
- These profiles highlight the diverse and long-term health impacts of COVID-19.
- The identified clusters can aid in anticipating future healthcare needs for COVID-19 survivors.
Background:
Little is known about postdischarge healthcare resource use (HCU) among patients hospitalized for coronavirus disease 2019 (COVID-19). The objective was to identify distinct profiles of patients based on postdischarge cares.
Methods:
This was a retrospective cohort study using the French National Health System claims database. We followed up all patients hospitalized for COVID-19 between 2020/02/01 and 2020/06/30 for 6 months; the discharge date was the index date. We excluded patients who died during the index stay or within 30 days after discharge. We described patients' HCU over 5 months from day 31 after the index date to the end of follow-up, i.e., the post-COVID-19 period. We described the sociodemographic and clinical characteristics of the participants and 44 selected types of HCU, including medical and emergency room visits, medications, medical and biological tests, oxygen therapy, rehabilitation, rehospitalization, nurse visits, and sick leave. We performed Ward's ascendant hierarchical clustering (AHC) analysis to identify groups of patients with similar post-COVID-19 HCU and described HCU and clinical characteristics by cluster.
Results:
The study population included 68,822 patients (median age: 64.8 years, 47% women). Eight clusters of patients were identified, each comprising between 1,163 and 35,501 patients. Four clusters were characterized by older patients and high proportions of comorbidities, i.e. cancer (cluster 3), mental disorders (cluster 4), cardiac insufficiency (cluster 5) and respiratory failure (cluster 6). Cluster 8 was characterized by younger patients, often obese and with low mortality. Another cluster was characterized by complex index stays (cluster 7) and a last cluster (cluster 2) by specific medical contacts and therapy. The main cluster (cluster 1, n = 35,501) was similar to the overall study population. The duration and complexity of the index stay also varied across clusters.
Conclusions:
Based on HCU data, AHC identified 8 clinically relevant profiles of patients surviving the acute episode of COVID-19 hospitalization. The clusters illustrate the many impacts of COVID on the health status of infected patients and may help anticipate future needs of care in a similar context.
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