Abstract
Introduction
There is limited evidence on the economic burden of COVID-19 in Germany. This study aims to quantify healthcare resource utilisation (HCRU) and direct medical costs associated with COVID-19 in paediatrics in Germany.
Methods
This was a population-based retrospective cohort study using data from the German Statutory Health Insurance (SHI) claims database to define outpatient (April 2020 to December 2021) and hospitalised (April 2020 to October 2022) cohorts of paediatric patients (aged 1–17 years) with a COVID-19 diagnosis.
Results
In the outpatient cohort (n = 104,656), most (77%) patients had ≥ 2 COVID-19-related general practitioner (GP) visits and 29% had ≥ 1 specialist visit during their diagnosis quarter. Outpatient resource use was greater in high-risk patients. When stratified by age, a greater proportion of children aged 1–4 years had ≥ 2 GP consultations, with specialist visits more common in those aged 5–11 years. The median cost per COVID-19 diagnosis quarter per patient was €192. Among the hospitalised cohort (n = 3129), the median general inpatient length of hospital stay (LoS) per patient per admission was 6.0 days; LoS was highest in those aged 5–11 years (7.0 days), at high risk (7.0 days) and during Alpha and Omicron predominance (both 7.0 days). The median cost per admission per patient was €12,503. Admission to critical care was observed in 13%, in whom the median cost per hospitalisation was €21,193.
Conclusions
COVID-19-associated HCRU and costs among the paediatric population in Germany are non-negligible, driven largely by hospitalisations, particularly those who had a critical care admission and were at high risk.
Supplementary Information
The online version contains supplementary material available at 10.1007/s12325-025-03313-5.
Keywords: COVID-19, Primary care, Secondary care, Hospitalisation, Costs, Paediatrics
Key Summary Points
| Why carry out this study? |
| Whilst coronavirus disease 2019 (COVID-19) is less severe in children compared to adults, among those who are hospitalised a high proportion require intensive care. |
| Evidence assessing healthcare resource utilisation (HCRU) and associated costs is predominantly based in the USA or single-centred studies. |
| This study aimed to quantify HCRU, and direct medical costs associated with COVID-19 in paediatrics in Germany. |
| What was learned from the study? |
| Hospitalisations, critical care admissions and being at high risk of severe COVID-19 were drivers of the higher healthcare resource use and costs associated with COVID-19 in children based in Germany. |
| Differences in HCRU and costs were found across COVID-19 variant predominance periods. |
| Findings from this study can be used to inform healthcare resource allocation and optimisation for the management of COVID-19 in children. |
Introduction
Coronavirus disease 2019 (COVID-19) in paediatrics is less severe compared to adults [1]. However, among those who are hospitalised it is estimated that approximately 20% require SARS-CoV-2 therapy, such as remdesivir or casirivimab with imdevimab, and 3% require intensive care support, of whom the majority (approx. 85%) require respiratory support [2]. In most paediatric COVID-19 cases the clinical course is typically mild but can still result in healthcare resource use and associated costs through management in the outpatient or community setting [1]. To reduce risk of hospitalisation and further burden on the healthcare system, non-hospitalised patients at high risk of clinical progression may be offered outpatient drug treatment with nirmatrelvir with ritonavir, remdesivir or molnupiravir [3].
Underlying health conditions [4–6] and multisystem inflammatory syndrome (MIS-C) [4] are important risk factors for severe COVID-19 [1]. Further, during Omicron predominance, an increasing number of SARS-CoV-2 infections were observed; however, evidence using serological testing to define COVID-19 cases demonstrates that over the course of the pandemic, morbidity in paediatrics decreased in Germany, except for those aged < 5 years during Delta predominance where an increase in hospitalisation and intensive care unit admission was observed [7].
Prior studies assessing COVID-associated healthcare resource utilisation (HCRU) and costs in children are highly concentrated in the USA [8–10], which has different healthcare system structure when comparing with Europe, or are limited to single-centre experience [11, 12], or are conducted in selected groups of patients with specific clinical conditions of interests [13–15], or with a small sample size [16]. Little is known about the economic burden of COVID-19 in paediatrics in Germany; such evidence may be used for healthcare budget allocation and inform health policy decisions. In addition, limited evidence exists on the variation in HCRU by variant predominance, and for other healthcare interactions such as specialist visits in the outpatient setting.
Aims and Objectives
This study aimed to quantify HCRU and direct costs associated with COVID-19 in paediatrics in Germany, by age, risk of severe COVID-19 disease and COVID-19 variant predominance.
Methods
Study Design and Setting
This retrospective, population-based cohort study utilised anonymised claims information from Germany’s Statutory Health Insurance (SHI) system. SHI provides coverage to approximately 90% of the German population, with insurance providers offering similar health services and remuneration for cost of treatment [17]. For the present study, we accessed a representative random sample from the SHI, encompassing approximately five million individuals, which is about 6% of the national population. The dataset includes comprehensive longitudinal records of outpatient and inpatient claims, pharmacy dispensations, and associated healthcare expenditures [18]. As SHI data is fully anonymised, no ethics review and institutional review board approval were required. However, approvals from the involved SHIs were obtained to use their data for this study, and the data that support the findings of this study are not publicly available. Patient consent was waived as this study was a retrospective database analysis based on previously available and fully anonymised data and did not involve any new studies of human or animal subjects performed by any of the authors.
We established two separate non-mutually exclusive patient cohorts of paediatric COVID-19 cases to describe healthcare utilisation and direct costs:
The outpatient cohort: Paediatric (aged 1–17 years) patients who had a recorded ICD-10-GM (International Statistical Classification of Diseases and Related Health Problems, 10th revision, German Modification) COVID-19 diagnosis (U07.1) within the outpatient setting i.e. family physician/GP practitioner were included. Given SHI data limitations, the index date was set to the first quarter in which a COVID-19 diagnosis was recorded (e.g. January–March was defined as quarter 1), as actual COVID-19 diagnosis dates were not available within the outpatient setting. Patients in this cohort may have also received inpatient COVID-19 care.
The hospitalised cohort: Paediatric (aged 1–17 years) who had a recorded ICD-10-GM primary or secondary COVID-19 diagnosis (U07.1) documented at hospital discharge were included. Hospitalisations were clustered into 90-day COVID-19 episodes, whereby COVID-19-related hospitalisations occurring within 90 days of a first COVID-19 hospitalisation were considered as part of the same episode [18, 19]. Hospitalisations separated by more than 90 days were treated as distinct and were considered as reinfection; hence, patients may have had multiple index dates.
Study Population and Eligibility Criteria
We included patients aged 1–17 years, diagnosed with COVID-19 from 1 April 2020 to 31 December 2021 for the outpatient cohort, or diagnosed from 1 April 2020 to 2 October 2022 for the hospitalised cohort. The index period start date was determined by the standardised reporting of all COVID-19 test results within the German healthcare setting. The end date, however, was determined by outpatient and inpatient data availability within SHI. Patients were required to be continuously enrolled with an SHI insurer for ≥ 12 months. We excluded persons who had a COVID-19 diagnosis prior to April 2020, or a death date that was prior to their first COVID-19 diagnosis.
Demographic and Clinical Characteristics
Baseline information captured for each participant included age, sex, and geographical region in Germany. Clinical data extracted consisted of comorbidities assessed by Quan-Charlson Comorbidity Index (CCI) 2011 [20] within 2 years of index. Immunocompromised status was determined according to established criteria in which patients were classified as immunocompromised at index if they had ≥ 1 health condition meeting Davidson et al.’s definition of immunocompromised status [21], and risk of severe COVID-19 was classified on the basis of Germany’s COVID-19 vaccination prioritisation criteria defined by the Robert Koch Institute’s (RKI) definition of patients at risk of severe COVID-19 (as of 26 November 2021) [22], see Supplementary Appendix 1 for details on health conditions. Among the hospitalised cohort, disease severity was assessed using the Ordinal Scale for Clinical Improvement within the World Health Organization’s (WHO’s) COVID-19 Therapeutic Trial Synopsis [23], reflecting the most intensive intervention required during hospitalisation: (1) hospitalised, no oxygen therapy; (2) oxygen by mask or nasal prongs; (3) non-invasive ventilation or high-flow oxygen; (4) intubation and mechanical ventilation and (5) ventilation and additional organ support. Additionally, the timing of infection was contextualised according to SARS-CoV-2 variant predominance period, and was categorised as follows: wild-type (1 April 2020 [indexing period start date] to 28 February 2021), Alpha (1 March 2021 to 20 June 2021), Delta (21 June 2021 to 31 December 2021) and Omicron (1 January 2022 to 2 October 2022, for the hospitalised cohort only) [24].
Healthcare Resource Utilisation (HCRU) Outcomes and Follow-up
All HCRU and associated costs within the COVID-19 diagnosis quarter (outpatient cohort) and COVID-19 90-day episode (hospitalised cohort), including and following the index date, were calculated and reported for the following:
Outpatient consultations: All general practitioner (GP) consultations (which include consultations with other healthcare professionals such as the assistant GP and nurse) during the COVID-19 diagnosis quarter were reported. Separately, all-cause outpatient specialist consultations were also reported (i.e. all specialist consultations during the COVID-19 diagnosis quarter). Method of access to specialists (referrals, direct access) was not considered.
Hospitalisations: Length of stay (LoS) per hospital admission to general inpatient and critical care during the 90-day episode were reported. In patients with reinfections, data were aggregated across multiple COVID-19 episodes. A sensitivity analysis was conducted accounting for data where a hospitalisation surpassed the 90-day episode.
Medication use: A pre-defined list of medications for the treatment of COVID-19 that were prescribed in the outpatient setting during the same quarter as a COVID-19 diagnosis were considered for the outpatient cohort, whereas for the hospitalised cohort inpatient prescriptions per 90-day episode were considered and, as such, use of these medications was attributed to COVID-19. Medications included: (1) nirmatrelvir with ritonavir, (2) molnupiravir, (3) dexamethasone, (4) regdanvimab, (5) tixagevimab with cilgavimab, (6) remdesivir, (7) sotrovimab, (8) tocilizumab, (9) casirivimab with imdevimab, (10) anakinra and (11) sarilumab, where 1–5 were only captured in the outpatient setting and 6–11 were captured in both settings. See Supplementary Table 1 for medication ATC codes. Medication use was defined as patients receiving ≥ 1 COVID-19 medication, listed above, during the COVID-19 diagnosis quarter. Medication costs were reported among those who had a prescription (i.e. resource users).
Direct healthcare costs: For the outpatient cohort, a flat rate fee (Uniform Evaluative Standard: Einheitlicher Bewertungsmaßstab [EBM]) for each patient consultation within the single COVID-19 diagnosis quarter was used to calculate cost per patient. A flat rate fee refers to a fixed, predetermined reimbursement amount for all consultations, regardless of the actual number or duration of consultations provided. This included all forms of general practice care regardless of healthcare professional or consultation mode (i.e. telephone or face-to-face visits) and separately for outpatient specialist visits. Separately, COVID-19 medication use cost, per COVID-19 diagnosis quarter, was also calculated. Total annual outpatient costs, per patient, were reported for 2020 and 2021, separately. Further, costs per patient per COVID episode for each quarter throughout the study indexing period were presented. For the hospitalised cohort, a flat fee for each admission was determined using DRG codes. Consequently, costs per hospitalisation, per episode per patient were calculated as well as the overall costs for all hospitalisations, per episode per patient. All costs were reported as recorded in the SHI claims data and reflect the actual amounts reimbursed for services during the study period. No inflation adjustment was applied.
Statistical Analysis
Descriptive analyses were used to summarise the data, calculating means (standard deviation, SD), or medians (quartile 1, quartile 3 [Q1, Q3]) for numeric variables. Categorical variables were presented using frequency counts and percentages. Results are presented separately for the outpatient and hospitalised cohorts. When reporting the direct healthcare costs for the hospitalised cohort, subgroup analyses are presented separately for those with a critical care admission and those who were not admitted to critical care. Results with fewer than five patients were suppressed to protect patient privacy and to comply with SHI claims reporting rules, with secondary suppression implemented where relevant to avoid back-calculation of the value that has been initially suppressed. All analyses were conducted in R version 3.4.0.
Stratifying Variables
Outcomes were evaluated by age group (1–4, 5–11, and 12–17 years), risk status as per the RKI criteria (high risk and not at high risk of severe COVID-19) and SARS-CoV-2 variant predominance period (wild-type; Alpha; Delta; Omicron [Omicron period was only available in the hospitalised cohort]).
Results
Patient Sociodemographic and Clinical Characteristics
The outpatient cohort: In total, 104,656 patients were included in the outpatient cohort. The mean (SD) age was 9.1 (5.0) years, approximately half (51.7%) were male and most lived in the German regions North Rhine-Westphalia (22.8%) or Bavaria (19.3%) (Table 1). Most (83.0%) had a CCI score of 0, 0.1% were immunocompromised and 61.6% were defined as being at risk of severe COVID-19. A greater proportion of patients had COVID-19 during the Wild-type (39.2%) variant predominance period, followed by Delta (31.4%) and Alpha (29.4%).
Table 1.
Sociodemographic and clinical characteristics of the study population at baseline
| Outpatient cohort N = 104,656 |
Hospitalised cohort N = 3129 |
|
|---|---|---|
| Age, years | ||
| Mean (SD) | 9.1 (5.0) | 8.4 (5.7) |
| 1–4 | 25,597 (24.5) | 1132 (36.2) |
| 5–11 | 41,129 (39.3) | 863 (27.6) |
| 12–17 | 37,930 (36.2) | 1134 (36.2) |
| Sex | ||
| Male | 54,066 (51.7) | 1551 (49.6) |
| Female | 50,590 (48.3) | 1578 (50.4) |
| Region of residence | ||
| Lower Saxony | 8624 (8.2) | 297 (9.5) |
| Hesse | 9948 (9.5) | 256 (8.2) |
| Baden-Wurttemberg | 14,550 (13.9) | 503 (16.1) |
| Bavaria | 20,161 (19.3) | 496 (15.9) |
| North Rhine-Westphalia | 23,869 (22.8) | 782 (25.0) |
| Other regions | 22,683 (21.7) | 686 (21.9) |
| Unknown | 4821 (4.6) | 109 (3.5) |
| Quan-CCI (2011) | ||
| Mean (SD) | 0.2 (0.5) | 0.4 (0.9) |
| 0 | 86,860 (83.0) | 2318 (74.1) |
| 1–2 | 17,255 (16.5) | 716 (22.9) |
| 3–4 | 446 (0.4) | 70 (2.2) |
| ≥ 5 | 95 (0.1) | 25 (0.8) |
| Immune system status | ||
| Immunocompromised | 129 (0.1) | 27 (0.9) |
| Immunocompetent | 104,527 (99.9) | 3102 (99.1) |
| Risk of severe COVID-19, as defined per the RKI definition | 64,449 (61.6) | 2569 (82.1) |
| COVID-19 variant predominance period | ||
| Wild-type | 41,036 (39.2) | 262 (8.3) |
| Alpha | 30,800 (29.4) | 187 (6.0) |
| Delta | 32,820 (31.4) | 284 (9.1) |
| Omicron | N/A | 2396 (76.6) |
| COVID-19 severitya | ||
| No oxygen therapy | – | 3093 (98.9) |
| Low-flow oxygen | – | < 5 |
| Non-invasive ventilation or high-flow oxygen | – | 15 (0.5) |
| Intubation/mechanical ventilation | – | 20 (0.6) |
| Ventilation and additional organ support | – | < 5 |
| COVID-19 hospital episodesb | ||
| 1 | – | 2945 (94.1) |
| 2 | – | 89 (2.8) |
| ≥ 3 | – | 95 (3.0) |
Data are presented as n (%) unless otherwise specified
COVID-19 coronavirus disease 2019, Quan-CCI Quan-Charlson comorbidity index, SD standard deviation, N/A not applicable
aHighest level of severity experienced during the hospitalisation, not measured within baseline
bThe number of episodes was assessed during patient follow-up (i.e. not baseline), with > 1 episode representing patients with reinfection
The hospitalised cohort: A total of 3129 paediatric patients were included in the hospitalised cohort. The mean (SD) age was 8.4 (5.7) years, half (49.6%) were male, and the geographic regional distribution was similar to that observed in the outpatient cohort (Table 1). Whilst many (74.1%) had a CCI score of 0, 82.1% were defined to be at risk of severe COVID-19 (higher than that observed in the outpatient cohort) and 0.9% were immunocompromised. The majority (76.6%) of patients were hospitalised with COVID-19 during the Omicron predominance period. Most (94.1%) had no documented oxygen therapy or respiratory support, and during follow-up few patients (5.8%) had ≥ 2 COVID-19-related hospitalisations across separate COVID-19 episodes.
HCRU and Associated Costs (€) During the COVID-19 Diagnosis Quarter in the Outpatient Cohort
In total, 80,376 (76.8%) had ≥ 2 consultations with the GP and 28.8% (n = 30,141) had ≥ 1 outpatient specialist consultation during the COVID-19 diagnosis quarter (Table 2). The median (Q1, Q3) cost for GP and specialist consultations was €49 (41, 75) and €132 (62, 204) per patient per diagnosis quarter, respectively. The total outpatient costs (GP and outpatient specialist combined) per patient per diagnosis quarter was €192 (109, 316). When stratified by diagnosis year, total outpatient cost per patient was numerically higher in 2020 than the cost observed in 2021 (median [Q1, Q3] €767 [94, 976] vs. €697 [110, 979] (see Supplementary Table 2 for cost of GP and outpatient specialist consultations by diagnosis year, separately, and total outpatient cost per patient for each quarter during the study period).
Table 2.
Outpatient cohort, HCRU and associated costs (€) during the COVID-19 diagnosis quarter
| Outpatient Cohort HCRU per COVID-19 diagnosis quarter | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| All (N = 104,656) |
Age | Risk status | COVID-19 variant predominance period | ||||||
| 1–4 (n = 25,597) |
5–11 (n = 41,129) | 12–17 (n = 37,930) |
At higher risk of severe COVID-19 (n = 64,449) |
Not at higher risk of severe COVID-19 (n = 40,207) |
Wildtype (n = 41,036) |
Alpha (n = 30,800) | Delta (n = 32,820) |
||
| GP consultations per COVID-19 diagnosis quarter | |||||||||
| 1 consultation, n (%) | 24,280 (23.2%) | 4,479 (17.5%) | 9,665 (23.5%) | 10,136 (26.7%) | 13,251 (20.6%) | 11,029 (27.4%) |
8,631 (21.0%) |
8,931 (29.0%) |
6,718 (20.5%) |
| ≥ 2 consultations, n (%) | 80,376 (76.8%) | 21,118 (82.5%) | 31,464 (76.5%) | 27,794 (73.3%) | 51,198 (79.4%) | 29,178 (72.6%) | 32,405 (79.0%) |
21,869 (71.0%) |
26,102 (79.5%) |
| Mean (SD) | 7.2 (5.3) | 8.3 (10.8) | 7.4 (11.6) | 6.3 (12.3) | 7.4 (12.2) | 6.9 (11.7) | 7.7 (4.8) | 7.4 (10.1) | 6.4 (8.0) |
| Median (Q1, Q3) | 3.0 (1.0, 6.0) | 5.0 (1.0, 7.0) | 4.0 (1.0, 6.0) | 3.0 (1.0,5.0) | 5.0 (1.0, 7.0) | 2.0 (1.0, 4.0) | 4.0 (1.0, 7.0) | 3.0 (1.0,6.0) | 3.0 (1.0,6.0) |
| Outpatient specialist consultations, per COVID-19 diagnosis quarter | |||||||||
| ≥ 1 consultation, n (%) | 30,141 (28.8%) |
9,983 (39.0%) |
18,919 (46.0%) | 1,239 (3.3%) | 21,939 (34.0%) | 8,202 (20.4%) |
13,874 (33.8%) |
8,040 (26.1%) |
8,227 (25.1%) |
| Mean (SD) | 2.4 (3.2) | 2.7 (4.3) | 2.6 (5.1) | 2.1 (3.7) | 2.9 (5.2) | 2.3 (3.1) | 2.5 (4.2) | 2.6 (3.6) | 2.4 (3.3) |
| Median (Q1, Q3) | 1.0 (1.0, 3.0) | 2.0 (1.0, 4.0) | 1.0 (1.0, 3.0) | 1.0 (1.0, 2.0) | 1.0 (1.0, 3.0) | 1.0 (1.0,3.0) | 2.0 (1.0, 4.0) | 1.0 (1.0, 3.0) | 1.0 (1.0, 3.0) |
| Any COVID-19 medication use, n (%) | 820 (0.8%) | 739 (2.9%) | 75 (0.2%) | 6 (< 0.1%) | 666 (1.0%) | 154 (0.4%) | 293 (0.7%) | 231 (0.8%) | 296 (0.9%) |
| Outpatient Cohort HCRU associated costs | |||||||||
| Total outpatient costs, per patient per COVID-19 diagnosis quarter (€) | |||||||||
| Mean (SD) | 110 (168) | 108 (188) | 121 (216) | 132 (259) | 119 (310) | 96 (289) | 86 (376) | 146 (469) | 108 (622) |
| Median (Q1, Q3) | 192 (109, 316) | 154 (81, 308) | 120 (82, 161) | 134 (90, 160) | 153 (106, 252) | 182 (97, 211) | 194 (82, 101) | 142 (22, 159) | 86 (32, 161) |
| Total outpatient costs, per patient, in 2020 (€) | |||||||||
| Mean (SD) | 395 (650) | 387 (714) | 404 (703) | 398 (687) | 416 (784) | 338 (540) | 378 (745) | – | – |
| Median (Q1, Q3) | 767 (94, 976) | 795 (211, 912) | 1,235 (378, 1,702) | 661 (48, 917) | 299 (269, 1,002) | 973 (289, 1,578) | 214 (211, 912) | – | – |
| Total outpatient costs, per patient, in 2021 (€) | |||||||||
| Mean (SD) | 420 (663) | 389 (725) | 393 (625) | 432 (712) | 503 (907) | 397 (700) | – | 369 (727) | 550 (723) |
| Median (Q1, Q3) | 697 (110, 979) | 502 (73, 602) | 1,308 (62, 1,516) | 721 (190, 1,721) | 705 (91, 939) | 908 (116, 908) | – |
1,388 (62, 1516) |
770 (190, 1,721) |
| GP consultation costs, per patient per COVID-19 diagnosis quarter (€) | |||||||||
| Mean (SD) | 87 (149) | 88 (128) | 84 (138) | 90 (159) | 86 (180) | 89 (168) | 92 (194) | 75 (205) | 93 (229) |
| Median (Q1, Q3) | 49 (41, 75) | 49 (47, 64) | 48 (43, 94) | 48 (43, 83) | 54 (48, 94) | 47 (19, 64) | 49 (42, 173) | 54 (45, 81) | 59 (55, 90) |
| Outpatient specialist consultation costs, per patient per COVID-19 diagnosis quarter (€) | |||||||||
| Mean (SD) | 106 (178) | 101 (159) | 109 (178) | 106 (193) | 103 (231) | 116 (229) | 91 (259) | 100 (287) | 139 (323) |
| Median (Q1, Q3) | 132 (62, 204) | 121 (79, 189) | 115 (110, 137) | 134 (124, 180) | 195 (54, 304) | 123 (66, 215) | 168 (63, 211) | 132 (64, 180) | 84 (69, 109) |
| Medication costs, per patient per COVID-19 diagnosis quarter (€) | |||||||||
| Mean (SD) | 903 (1,524) | 783 (1,302) | 842 (1,555) | 1027 (1,959) | 952 (2,225) | 691 (2,226) | 887 (2,541) | 898 (3,132) | 958 (3,944) |
| Median (Q1, Q3) | 688 (31, 1,671) | 543 (26, 1,366) | 788 (31, 1,467) | 623 (30, 2,508) | 543 (27, 1,413) | 782 (39, 1,712) | 639 (26, 1,464) | 721 (31, 1,644) | 832 (37, 2,979) |
COVID-19 coronavirus disease, GP general practitioner, HCRU healthcare resource utilisation, Q1/Q3 quintile 1/3, SD standard deviation
The stratified results showed multiple GP consultations were more common in paediatrics aged 1–4 years (82.5%), at high risk of severe COVID-19 (79.4%), and COVID diagnosis during the Delta variant (79.5%) or wild-type (79.0%) predominance period. Similarly, stratified results in those with ≥ 1 outpatient specialist consultation were common in high-risk patients (34.0%); however, other results differed: consultations were more common in those aged 5–11 years (46.0%) and during the wild-type predominance period (33.8%). The median (Q1, Q3) total outpatient costs per patient, per COVID-19 diagnosis quarter, were numerically higher in those aged 1–4 years (€154), at not at high risk (€182) and during the wild-type variant predominance period (€194).
COVID-19-related medication use was limited (n = 820; 0.8%), although the median (Q1, Q3) cost was numerically higher than the total outpatient cost per patient per COVID-19 diagnosis quarter (€688 [31, 1671] vs. €192 [109, 316]). Stratified by diagnosis year, COVID-19 medication cost was numerically higher in 2021 than the cost observed in 2020 (median [Q1, Q3] €2768 [78, 3453] vs. €2752 [72, 3168] (see Supplementary Table 2).
HCRU and Associated Costs (€) During the COVID-19 Episode in the Hospitalised Cohort
Among the 3129 hospitalised patients, median (Q1, Q3) general inpatient LoS (excluding critical care) per hospitalisation was 6.0 (2.0, 9.0) days (mean [SD] 8.5 (9.0) days) (Table 3). General inpatient stay was numerically higher in those aged 5–11 years (median [Q1, Q3] 7.0 [2.0, 9.0] days), at high risk (median [Q1, Q3] 7.0 [2.0, 9.0] days) and among those hospitalised during Alpha and Omicron predominance period (median [Q1, Q3] 7.0 [2.0, 9.0]; 7.0 [2.0, 8.0] days, respectively). Critical care admissions were observed in 13.0% (n = 406); among these, median (Q1, Q3) LoS within critical care was 32.0 (2.0, 34.0) days (mean [SD] 49.2 [69.0] days). When stratified, patterns were similar to those observed for general inpatient stay only admissions, except for the COVID-19 variant predominance period stratification. COVID-19-related medication use in the hospital setting was low (n = 13; 0.4%).
Table 3.
Hospitalised cohort, HCRU and associated costs (€) per 90-day COVID-19 episode
| Hospitalised cohort HCRU per COVID-19 episode | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| All (N = 3129) |
Age | Risk status | COVID-19 variant predominance period | |||||||
| 1–4 (n = 1132) |
5–11 (n = 863) |
12–17 (n = 1134) |
At higher risk of severe COVID-19 (n = 2569) |
Not at higher risk of severe COVID-19 (n = 560) |
Wild-type (n = 262) |
Alpha (n = 187) |
Delta (n = 284) |
Omicron (n = 2396) |
||
| LoS in general inpatient, per hospitalisation | ||||||||||
| Mean (SD) | 8.5 (9.0) | 9.3 (10.0) | 8.8 (12.0) | 7.3 (10.0) | 9.2 (12.0) | 5.0 (6.0) | 9.6 (10.0) | 8.5 (12.0) | 8.0 (10.0) | 8.2 (15.0) |
| Median (Q1, Q3) | 6.0 (2.0, 9.0) | 5.0 (2.0, 7.0) | 7.0 (2.0, 9.0) | 6.0 (2.0, 8.0) | 7.0 (2.0, 9.0) | 5.0 (2.0, 9.0) | 6.0 (2.0, 7.0) | 7.0 (2.0, 9.0) | 6.0 (2.0, 8.0) | 7.0 (2.0, 8.0) |
| Critical care admissions, n (%) | 406 (13.0%) | 138 (12.2%) | 125 (14.5%) | 143 (12.6%) | 351 (13.7%) | 55 (9.8%) | 42 (16.0%) | 26 (13.9%) | 37 (13.0%) | 301 (12.6%) |
| LoS in critical care, per hospitalisation | ||||||||||
| Mean (SD) | 49.2 (69.0) | 50.2 (69.0) | 49.2 (50.0) | 48.1 (66.0) | 52.3 (67.0) | 34.8 (49.0) | 48.2 (72.0) | 47.7 (59.0) | 50.1 (62.0) | 46.7 (64.0) |
| Median (Q1, Q3) | 32.0 (2.0, 34.0) | 21.0 (2.0, 38.0) | 34.0 (2.0, 28.0) | 27.0 (2.0, 42.0) | 33.0 (2.0, 35.0) | 2.01 (2.0, 31.0) | 39.0 (2.0, 42.0) | 41.0 (2.0, 43.0) | 31.0 (2.0, 34.0) | 32.0 (2.0, 35.0) |
| Medication use, n (%) | 13 (0.4%) | 5 (0.4%) | < 5 | 6 (0.5%) | 11 (0.4%) | < 5 | < 5 | < 5 | < 5 | 9 (0.4%) |
| Hospitalised cohort HCRU associated costs | ||||||||||
| Total healthcare costs, per hospitalisation per patient (€) | ||||||||||
| Mean (SD) | 16,129 (22,097) | 17,170 (22,493) | 16,319 (21,704) | 10,465 (14,128) | 17,616 (24,310) | 12,259 (15,446) | 16,064 (21,854) | 16,497 (21,191) | 16,559 (22,406) | 15,503 (21,147) |
| Median (Q1, Q3) | 12,503 (4307, 17,829) | 14,930 (4123, 16,482) | 13,948 (5401, 14,829) | 9100 (3942, 16,380) | 13,049 (4849, 15,201) | 9807 (4307, 17,834) | 12,503 (4307, 17,829 | 12,600 (4400, 17,500) | 12,700 (4300, 17,600) | 12,400 (4200, 17,700) |
| Total healthcare costs, per hospitalisation per patient in non-critical care patients (€) | ||||||||||
| Mean (SD) | 6393 (8758) | 6642 (8967) | 5841 (8119) | 5850 (7722) | 7152 (10,084) | 6321 (8597) | 6418 (9065) | 6519 (8548) | 6437 (8705) | 6056 (8986) |
| Median (Q1, Q3) | 4918 (3929, 10,293) | 5109 (3849, 8394) | 4827 (4139, 9839) | 5087 (4220, 183,92) | 5298 (4307, 17,833) | 4682 (3629, 13,929) | 4918 (4100, 10,300) | 5000 (4200, 10,400) | 5100 (4100, 10,200) | 5700 (4200, 12,300) |
| Total healthcare costs, per hospitalisation per patient in critical care patients (€) | ||||||||||
| Mean (SD) | 35,175 (35,351) | 36,542 (51,524) | 34,571 (47,708) | 34,377 (46,753) | 34,453 (45,478) | 31,049 (42,537) | 36,189 (34,255) | 35,312 (36,836) | 33,985 (34,997) | 33,357 (36,164) |
| Median (Q1, Q3) | 21,193 (7839, 23,020) | 21,731 (5681, 24,091) | 20,812 (7839, 23,020) | 19,328 (3827, 23,121) | 19,281 (5021, 22, 833) | 19,121 (6102, 19,283) | 21,920 (7800, 22,500) | 20,811 (7900, 22,800) | 21,631 (7700, 22,500) | 21,115 (7900, 22,300) |
| Medication costs, per hospitalisation per patient (€) | ||||||||||
| Mean (SD) | 3634 (5372) | 4371 (7392) | < 5 | < 5 | 3982 (4829) | < 5 | < 5 | < 5 | < 5 | 3477 (5095) |
| Median (Q1, Q3) | 2782 (62, 4592) | 3298 (2102, 8651) | < 5 | < 5 | 2679 (62, 4592) | < 5 | < 5 | < 5 | < 5 | 2807 (95, 3980) |
COVID-19 coronavirus disease, HCRU healthcare resource utilisation, LoS length of stay, Q1/Q3 quintile 1/3, SD standard deviation
The median (Q1, Q3) cost per hospitalisation per patient was €12,503 (4307, 17,829); when stratified, cost per hospitalisation per patient was numerically higher in those aged 1–4 years (median [Q1, Q3] €14,930 [4123, 16,482]) and at high risk (median [Q1, Q3] €13,049 [4849, 15,201]) but were lowest during Omicron predominance (median [Q1, Q3] €12,400 [4200, 17,700]) (Table 3). Similar trends across stratifications were observed for patients who were admitted to critical care and those not admitted to critical care costs (Table 3); the overall median (Q1, Q3) costs were €21,193 (7839, 23,020) and €4,918 (3929, 10,293), respectively.
When assessing HCRU and associated costs over the 90-day episode, the overall median (Q1, Q3) length of general inpatient stay was approximately 2 days greater (8.0 [2.0, 9.0] days) (see Supplementary Table 3). Overall, similar trends were observed across stratifications to those in the main analysis, except for COVID-19 predominance period, where patterns varied across outcomes compared to the main analysis (see Supplementary Table 3).
Discussion
To the best of our knowledge, this is the first study to quantify HCRU and associated direct healthcare costs among paediatric patients with COVID-19 in the outpatient and inpatient settings in Germany. Our study findings underpin the importance of optimising resource allocation in children following SARS-CoV-2 infection to mitigate both clinical and economic burdens.
We observed that paediatrics aged 1–4 years had on average a greater number of GP consultations compared to other age groups. COVID-19-related prescriptions in the outpatient setting were low; however, these were more common in those aged 1–4 years. These findings are consistent with other studies [25, 26], including an English population-based study, which showed that between August 2020 and April 2022, primary care consultations (i.e. GP and nurse consultations) in paediatric patients with COVID-19 were most common among those aged 1–4 years compared to those aged 5–17 [16]. These findings may partly be explained by the perception of caregivers that younger children with respiratory infections are more vulnerable than older children [27]. Further, as a result of the limitations within the dataset, only all-cause outpatient resource use could be observed. The Standing Committee on Vaccination (STIKO) in Germany recommends a range of vaccinations in the first 18 months of a child’s life [28] which may also drive health-seeking behaviour in the younger ages and therefore results should be interpreted with caution.
We observed the largest proportion of hospitalised cases and the lowest proportion of critical care admissions during the Omicron period, which is in keeping with literature showing a reduction in critical care use between the early waves of the pandemic and Omicron predominance, despite an increase in admissions [29, 30]. It is likely that these observations are in part due to the higher transmissibility but less severe clinical outcomes of Omicron, compared to earlier variants [31–33]. As SARS-CoV-2 continues to evolve and give rise to new strains, it is important to monitor the association between viral mutation and severity of the disease in children, informing resource allocation.
Regardless of inpatient setting, hospital LoS in children was greater than previous estimates from England (mean (SD) overall LoS 3.4 [4.0]; mean (SD) critical care LoS 4.0 [1.9]) [16] and the USA (mean (SD) overall LoS 4.3 [7.6]; mean (SD) intensive care unit and received mechanical ventilation LoS 17.0 [21.6]) [9]. However, we also observed that 13% of hospitalised patients were admitted to critical care during our study period, a proportion that is higher than recent estimates from Germany based on 2020 data [34]. That said, this study’s longer LoS estimates may also be explained by the study design; we assessed outcomes during a 90-day episode period and used a broader definition to identify hospitalised patients, whereby those with either a primary or secondary discharge diagnosis of COVID-19 were included. Further, primary diagnoses of viral pneumonia and acute upper respiratory tract infections are common within hospitalised COVID-19 cases in Germany, with primary diagnoses such as disease of the circulatory system and digestive system becoming more prevalent in the later stages of the pandemic; hence, our LoS estimates may be partly attributed to conditions that co-presented with COVID-19 during hospitalisation [9].
It has been well acknowledged that children with comorbidities likely require more management [6, 35, 36]. We observed greater inpatient resource use and costs in children at higher risk of severe COVID-19 than those who were not. These findings are consistent with prior studies [12, 16, 37, 38]. Prévost et al. have found that the presence of at least one underlying condition increased the risk of critical care unit admission by 2.66 times in children in France [39]. A recent meta-analysis that included 70 studies has shown that, compared with no comorbidities, having one comorbidity and ≥ 2 comorbidities increased the odds of developing critical disease by approximately 4 and 9.5 times, respectively, in children and adolescents [40]. Hence, health providers need to tailor clinical management per risk stratification in this vulnerable population.
This study has several limitations. First, outpatient data is only collected on a quarterly basis by SHI claims and therefore the exact date of COVID-19 diagnosis could not be determined for the outpatient cohort. This prevented the following: (1) the observation of a complete patient journey through various health settings, (2) derivation of mutually exclusive cohorts and definition of patients who were predominantly managed in the outpatient or hospitalised setting, and (3) identification of COVID-19-related GP or outpatient specialist consultations. Further, we did not differentiate between specific outpatient specialist types or the method of access (referral or direct access) in our analysis. All all-cause specialist consultations within the quarter of a recorded COVID-19 diagnosis were considered. Consequently, the quarterly collection of outpatient data may have resulted in an overestimation of outpatient HCRU and costs. Similarly, prescriptions for a predefined list of medications commonly used for COVID-19 treatment and administered during the same quarter as a COVID-19 diagnosis were included. As the SHI data do not capture the specific indication for each medication, it is possible that some prescriptions may have been used for other conditions, resulting in an overestimation of COVID-19-related medication use. Secondly, as a result of the data availability, only inpatient resource use and associated costs could be described during the Omicron predominance, leaving an evidence gap in the outpatient setting; this is of importance as COVID-19-related clinical outcomes deviated after the Omicron variant from those observed during the early phases of the pandemic [41]. Additionally, the high proportion of patients classified as high risk, particularly in the hospitalised cohort, reflects the use of a broad definition based on national criteria, which includes a wide range of comorbidities. While this reflects the real-world pattern in which children with underlying conditions are more frequently hospitalised for COVID-19, it may reduce the generalisability of our results to the wider paediatric population. Finally, our definition of COVID-19-related hospitalisations was broad; HCRU and costs may therefore be overestimated. Further research is required to quantify the healthcare burden of COVID-19 among outpatient cases beyond the Delta predominance period.
Conclusions
Our study showed that in Germany, despite most cases of COVID-19 in children being managed in the outpatient setting, paediatrics who are at high risk of severe COVID-19 and hospitalised, particularly those who are admitted to critical care, are key drivers of HCRU and associated costs. Findings from this study can be used to inform long-term strategy for healthcare resource allocation for the management of COVID-19 in paediatric patients.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
The acquisition of SHI data and analysis was supported by a third party in Germany, LinkCare. We thank the participants of the study.
Author Contributions
Kiran K. Rai designed, interpreted the data and drafted the manuscript. Hannah Gowman interpreted the data and reviewed the manuscript. Monica Seif interpreted the data and reviewed the manuscript. Lucy Massey interpreted the data and reviewed the manuscript. Hannah Volkman interpreted the data and reviewed the manuscript. Andrea Schmetz interpreted the data and reviewed the manuscript. Jennifer Nguyen conceptualized, revised and reviewed the manuscript. Jingyan Yang conceptualised, designed, interpreted the data, revised and reviewed the manuscript.
Funding
This study was conducted as a collaboration between Pfizer Inc, BioNTech and Adelphi Real World. Pfizer funded the study. Pfizer Inc funded the journal’s Rapid Service and Open Access Fees.
Data Availability
All data relevant to the study are included in the article or uploaded as supplementary information.
Declarations
Conflict of Interest
Jingyan Yang, Hannah Volkman and Jennifer Nguyen are employees of Pfizer and may receive stock and/or stock options. Kiran K. Rai, Hannah Gowman, Monica Seif and Lucy Massey are employees of Adelphi Real World, which received funds from Pfizer in connection with this study and development of the manuscript. Andrea Schmetz is an employee of BioNTech.
Ethical Approval
As SHI data is fully anonymised, no ethics review and institutional review board approval were required. However, approvals from the involved SHIs were obtained to use their data for this study, and the data that support the findings of this study are not publicly available. Patient consent was waived as this study was a retrospective database analysis based on previously available and fully anonymised data and did not involve any new studies of human or animal subjects performed by any of the authors.
Footnotes
Prior Presentation: Works included in this manuscript were previously presented at the European Society for Paediatric Infectious Diseases (ESPID) conference, 20th - 24th May 2024 in Copenhagen, Denmark.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All data relevant to the study are included in the article or uploaded as supplementary information.