Skip to main content
Health Economics Review logoLink to Health Economics Review
. 2021 Nov 3;11:43. doi: 10.1186/s13561-021-00340-0

Hospitalization budget impact during the COVID-19 pandemic in Spain

F J Carrera-Hueso 1, L Álvarez-Arroyo 1,2,, J E Poquet-Jornet 3, P Vázquez-Ferreiro 4, R Martínez-Gonzalbez 5, D El-Qutob 6, M A Ramón-Barrios 7, F Martínez-Martínez 8, J L Poveda-Andrés 9, C Crespo-Palomo 10,11
PMCID: PMC8565649  PMID: 34734323

Abstract

Objectives

The aim was to determine the direct impact of the COVID-19 pandemic on Spain’s health budget.

Methods

Budget impact analyses based on retrospective data from patients with suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) admitted to a Spanish hospital between February 26 and May 21, 2020. Direct medical costs from the perspective of the hospital were calculated. We analyzed diagnostic tests, drugs, medical and nursing care, and isolation ward and ICU stays for three cohorts: patients seen in the emergency room only, hospitalized patients who tested positive for SARS-CoV-2, and patients who tested negative.

Results

The impact on the hospital’s budget for the 3 months was calculated at €15,633,180, 97.4% of which was related to health care and hospitalization. ICU stays accounted for 5.3% of the total costs. The mean cost per patient was €10,744. The main costs were staffing costs (10,131 to 11,357 €/patient for physicians and 10,274 to 11,215 €/patient for nurses). Scenario analysis showed that the range of hospital expenditure was between €14,693,256 and €16,524,924. The median impact of the pandemic on the Spanish health budget in the sensitivity analysis using bootstrapped individual data was €9357 million (interquartile range [IQR], 9071 to 9689) for the conservative scenario (113,588 hospital admissions and 11,664 ICU admissions) and €10,385 million (IQR, 110,030 to 10,758) for the worst-case scenario (including suspected cases).

Conclusion

The impact of COVID-19 on the Spanish public health budget (12.3% of total public health expenditure) is greater than multiple sclerosis, cancer and diabetes cost.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13561-021-00340-0.

Keywords: Costs and cost analysis, COVID-19, Health care costs, Clinical laboratory tests, Hospitalization, Budgets

Introduction

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was declared a pandemic by the World Health Organization. By the end of June, it had affected 188 countries, with over 9 million confirmed cases and rising infection rates [1]. A variety of public health measures have been adopted to control the pandemic and ease the burden on healthcare systems [2].

The long-term health consequences and potential sequelae of COVID-19 are unknown [3, 4], but the social and economic impacts are already worse than those of the Second World War [3]. While major COVID-19-related research efforts are underway, there is a paucity of studies examining the impacts of the pandemic on public health budgets. This information is crucial to correctly manage the ongoing crisis, prepare for second waves [5], and guide the implementation and management of new services such as telemedicine or the creation of dedicated COVID-19 clinic units. Budget information is also needed to establish intervention-specific costs and is essential for analyzing the cost-effectiveness of new treatments for COVID-19. It can also help identify diagnostic groups that should allow for improved management.

The aim of this study was to conduct a hospital budget impact analysis to assess the impact of COVID-19 at its peak on the Spanish public health budget.

Methods

Study design, population, and resources

We estimated the impact of COVID-19, considering all direct medical costs, on the Spanish public health budget by extrapolating data from a retrospective cohort study covering a period of 86 days during the peak of the pandemic. The study was conducted in a 252-bed Spanish hospital that serves a catchment area of 187,258 people. It was registered with the Spanish Agency of Medicines and Medical Products (AEMPS) and approved by the hospital’s ethics committee. Verbal informed consent in the presence of a witness was obtained from all patients and noted in the patients’ medical records. This procedure was authorized by the Spanish Health authorities in view of the exceptional epidemiological situation. Eligible patients were adults (> 18 years) with suspected COVID-19 who visited the hospital’s emergency room (ER) between February 26 and May 21, 2020. Pregnant women were excluded. In cases of readmission, data from the first admission only were analyzed.

The patients were classified into three cohorts: 1) those not requiring hospital admission (ER cohort), 2) those admitted to the hospital and who received a positive real-time polymerase chain reaction (RT-PCR) result within 24 h (SARS-CoV-2-positive cohort), and 3) those admitted to the hospital and who received a negative RT-PCR result within 24 h (SARS-CoV-2-negative cohort).

Individual records of all patients in the ER cohort were reviewed to identify the tests performed (RT-PCR, chest X-ray, and blood tests [complete blood count, biochemical parameters, coagulation test]. A record was also made of time spent in the ER for all patients. Stays of 16 h or less were classified as medical visits, while longer stays were classified as ER stays.

Individual information was also collected on all tests performed during hospitalization. These included RT-PCR, imaging studies, blood tests [complete blood count, biochemical parameters, coagulation test], blood gas analysis, other laboratory tests (ferritin, D-dimer, C-reactive protein, and procalcitonin), and microbiological tests (blood cultures and testing for multiple atypical respiratory pathogens). We also calculated lengths of intensive care unit stays (ICU stays) and isolation ward stays (general stays). For the SARS-CoV-2-negative cohort, we calculated resources used in the first 48 h of hospitalization, as this was the maximum time for receiving RT-PCR results. We also analyzed survival at the end of follow-up for SARS-CoV-2-positive and -negative cohorts.

Costs

Direct medical costs from the perspective of the hospital were calculated in 2020 Euros (€). Discounts and indirect or intangible costs were not considered. Unit costs for ER and ICU stays, hospitalization, and staff salaries were obtained from the official rates established for our hospital for 2020 and checked against rates for several hospitals in different regions of Spain [6]. These were then multiplied by resource use data for each cohort to provide a combined total. Drug prices were obtained from the hospital’s pharmacy department. The main drug groups considered were antivirals, anti-inflammatories, antibiotics, antihypertensives, and gastroprotectives. We also computed the costs of laboratory tests and imaging studies performed during hospitalization. We do not include in our analyses indirect cost because our cohort is mainly hospitalized patients.

Once we had calculated the costs for the three cohorts, we estimated the impact of the COVID-19 pandemic for the period analyzed on the hospital’s budget for each cohort. The patients in the SARS-CoV-2-negative cohort were included as they had come to the hospital because they thought they had COVID-19 and would not have come had the pandemic not existed. As these criteria might vary according to the research team, we applied two additional approaches to estimate the total impact.

  1. In the first case, we calculated the impact of the pandemic for ER and SARS-CoV-2-positive cohorts only.

  2. In the second case, we estimated a false-negative rate of 29% [7], as the true rate was not available. In other words, we assumed that 29% of SARS-CoV-2-negative patients were actually infected and would have returned to the hospital for care, thereby adding to the costs.

Estimation of the National Level

Using official data reported for COVID-19-related hospital and ICU stays in Spain in June 2020 [8], we estimated the global impact of COVID-19 on the Spanish health budget using a linear approach. The number of cases for the ER cost analysis was estimated by calculating the ratio of SARS-CoV-2-positive patients to both ER patients (1:3.58) and SARS-CoV-2-negative patients (1:1.32) at our hospital.

We evaluated two scenarios: a conservative scenario for which we calculated the costs associated with the official cases reported for Spanish hospitals (113,558 hospital admissions and 11,664 ICU admissions) [8] and a worst-case scenario for which we assumed that 52.2% of SARS-CoV-2-positive patients would be hospitalized and that 5.9% of these would require ICU admission [8]. In these cases, the missing values were filled using linear interpolation, giving 115,877 hospital admissions and 14,806 ICU admissions.

Sensitivity analyses

We performed univariate sensitivity analysis to assess the uncertainty surrounding all the parameters in our study. Considering the potential uncertainty arising from differences in clinical practice across Spain, we estimated and compared ranges of unit costs for seven autonomous communities: Andalusia, the Canary Islands, Cantabria, Catalonia, Madrid, Navarre, and the Basque Country (supplementary material Table S1).

We finally performed a probabilistic sensitivity analysis by bootstrapping individual patient data to obtain the most realistic estimates possible [9]. The bootstrap approach is a non-parametric method that makes no distributional assumptions concerning the statistic in question. Instead, it employs the original data in a resampling exercise in order to give an empirical estimate of the sampling distribution of that estimate keeping the correlations between the costs and effects of our population.

We generated 1500 bootstrap samples for each cohort using the size of the original sample and performing resampling with replacement. For each subsample, we calculated mean costs and budget impacts for the reference hospital and Spain as a whole.

Main assumptions

  1. Personal protective equipment (PPE) costs (which have spiraled during the COVID-19 pandemic) were calculated as hospitalization costs. Indirect costs were not included for the lack of information.

  2. Even though PPE and disinfectant costs have increased substantially because of the pandemic, price increases were not contemplated in our analyses.

  3. Staff overtime telework outside ordinary working hours, and increased workload in other departments (e.g., laundry services) were not considered.

  4. Future cost projections were not calculated, as the COVID-19 sequelae are not yet well known. Individual patient requirements during hospitalization or after discharge were also not contemplated.

  5. Even though antibiotics are not recommended as prophylactic agents for COVID-19, they were included in the cost analyses as they are part of the workflow at our hospital.

  6. The calculations for ICU costs included unit costs and complete blood count, blood gas analysis, and chest X-ray costs.

Microsoft Excel 2010 was used for analyzing the initial scenario, modelling, bootstrapping, and the sensitivity analysis, while SPSS for Windows 26 (IBM Corp. Released 2010) was used to compare cohorts.

Results

We evaluated 1602 patients, of whom 1446 fulfilled the inclusion criteria. Their characteristics are summarized in Table 1. Between February 26 and May 21, 2020, 912 patients tested positive for SARS-CoV-2 by RT-PCR. Based on the total catchment population for our hospital (187,258), this corresponds to a rate of 487 cases per 100,000 population.

Table 1.

General characteristics of the study population

ER cohort SARS-CoV-2-positive cohort SARS-CoV-2-negative cohort
Total patients, n 989 265 348
< 18 years old, n 111 2 7
Readmissions, n 9 18
Patients included, N 878 254 323
Age, mean (SD) 49.3 (16.2) 68.4 (15.9) 70.7 (17.9)
Male, n (%) 381 (43.4) 139 (54.7) 174 (53.9)
Deaths, n (%) 3 (0.3) 43 (16.9) 32 (9.9)
Days of hospitalization, mean (SD) 1 (0.1) * 44.1 (4.8) 8.3 (1.7)
Days in ICU, mean (SD) 0 (0.1) 37.8 (4.3) 4.7 (1.9)

ER, emergency room; ICU, intensive care unit; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; SD, standard deviation; ICU, intensive care unit

* Stays of 16 h or less were classified as medical visits, while longer stays were classified as ER stays

The total estimated impact of COVID-19 on the hospital’s budget for the 86 days analyzed was €15,633,180. The vast bulk of this spending (94.7%) was related to the treatment and management of SARS-CoV-2-positive patients admitted to hospital. The mean cost per patient was €10,744 (€307 for the ER cohort, €1710 for the SARS-CoV-2-negative cohort, €50,132 for the SARS-CoV-2-positive cohort without ICU admission, and €280,956 for the SARS-CoV-2 positive cohort with ICU admission. The breakdown of costs per cohort is given in Table 2.

Table 2.

Impact on study hospital budget

Cost in € 2020
Items ER cohort* SARS-CoV-2-positive cohort SARS-CoV-2-negative cohort
Diagnostic tests
 RT-PCR for SARS-CoV-2 47,855.80 25,673.99 20,888,41
 Complete blood count 3745.74 1949,48
 Laboratory test† 19,075.58 10,745.74 5574.59
 Coagulation† 25,264.79 13,130.77
 Microbiology‡ 169.44 1279.36
 Blood gas analysis 12,287.42 6606.97
 D dimer 8620.25 4255.46
 C-reactive protein 7481.50 3861.00
 Ferritin 5758.36 3173.56
 Procalcitonin 21,370.62 12,017.19
 Troponin 12,613.64 6835.14
 Interleukin 6 327.00 1918.40
 ICU tests 43,775.00 0.00
Total test costs 66,931.38 177,359.34 81,490.33
Drugs
 Antivirals 10,034.86 691.36
 Corticosteroids 1007.80 192.20
 Tocilizumab 27,212.75 0.00
 Others, anti-inflammatory 5115.51 53.44
 Low-molecular-weight heparins 6272.06 1123.29
 Antibiotics§ 2868.16 1795.92
 Mucolytics 383.74 81.40
 ACE inhibitors/ARBs 64.10 18.99
 Beta-blockers 29.21 8.95
 Calcium antagonists 19.88 4.38
 Alpha-blockers 19.08 6.84
 Diuretics 7.92 1.74
 Statins 19.76 5.37
 Proton pump inhibitors 285.22 87.36
 Analgesics 219.10 44.15
 Antithrombotics 0 195.52
 Drugs in ICU 30,519.30 0.00
Total drug costs 0.00 84,078.45 4310.91
Imaging tests
 Chest X-ray, portable 36,533.58 73,108.77 26,880.06
 Computed tomography angiography 0.00 53,095.50 84,952.80
Total imaging costs 36,533.58 126,204.27 111,832.86
Hospitalization
 Medical visits 5,933,775.37 1951,26
 Nursing hours 6,095,260.01 2004,36
 ER stays 166,492,90
 Hospitalization stays 1,570,847.58 350,648.36
 Medical visits, ICU 103,660.58 0.00
 Nursing hours, ICU 255,555.95 0.00
 ICU stays§§ 464,198.60 0.00
Total hospitalization costs 166,492,90 14,423,298.09 354,648.36
TOTAL
 TOTAL cost 269,957.86 14,810,940.15 552,282.36
 Cost / patient 307.47 58,310.79 1709.85

ACE, angiotensin-converting enzyme; ARBs, angiotensin II receptor blockers; ICU, intensive care unit; RT-PCR, real-time polymerase chain reaction; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2

* Emergency room blood tests include complete blood count, biochemical profile, and coagulation test. Drugs are included as general care costs in the ER

** Includes glycemia, cholesterol, triglycerides, potassium, sodium, albumin, total protein, GPT, GOT, GGT, CPK, LDH, calcium, magnesium, phosphate, transferrin, creatinine, urea, and bilirubin

† Includes: prothrombin time, APTT, and fibrinogen

‡ Includes blood culture, sputum culture, and tests for respiratory viruses (adenovirus, coronavirus, Middle Eastern Respiratory Syndrome, metapneumovirus, rhinovirus, enterovirus, influenza A, influenza B, parainfluenza, respiratory syncytial virus, Bordetella pertussis, Chlamydophila pneumoniae, Mycoplasma pneumoniae)

§ Includes amoxicillin/clavulanic acid, vancomycin, ceftriaxone, linezolid, levofloxacin, moxifloxacin, ciprofloxacin, piperacillin/tazobactam, imipenem, meropenem, ertapenem, daptomycin, and ceftoriden

§§ In the ICU, daily blood test and blood gas analysis

The main cost components in the SARS-CoV-2-positive cohort were hospital care and hospitalization, at €14,423,298 (97.4% of total); laboratory tests, at €177,359 (1.2%); imaging tests, at €126,204 (0.9%); and drugs, at €84,078 (0.6%).

ICU stays accounted for 5.3% of the total cost (€823,415.13). This cost corresponded to 9 patients (3.54% of the SARS-CoV-2-positive cohort) with a mean (SD) stay of 37.8 (12.9) days. ICU care accounted for 5.6% of the total cost for the overall SARS-CoV-2-positive cohort and 32.6% of the total cost for the SARS-CoV-2-positive cohort with ICU admission. ICU staffing costs were €103,661 (12.6%) for physicians and €255,556 (31.0%) for nursing staff. The cost of ICU stays for the SARS-CoV-2-positive cohort was €464,199 (56.4%).

The most used antiviral treatment was hydroxychloroquine combined with azithromycin, but lopinavir/ritonavir (€4335, 43.2%) and gamma interferon (€3594, 35.8%) were by far the largest cost components in this drug category. The most expensive treatment was tocilizumab (€27,213). Testing costs were mainly driven by RT-PCR tests (€94,418) and procalcitonin (€33,388). Imaging studies, at €238,037, accounted for just 1.5% of the total costs for all patients admitted (SARS-CoV-2-positive and -negative).

According to the results of the parametric sensitivity analysis, if the RT-PCR test-negative patients had not been treated, the total impact on the hospital’s budget would have been €14,693,256€ (€12,980 per patient). Likewise, if we assume a non-false-negative rate, the total cost would have been €19,376,071 (€17,117 per patient).

Estimation of the National Level

In the conservative scenario, the total estimated impact of the COVID-19 pandemic on the Spanish public health budget was €9375 million; 1.5% of this cost corresponded to the ER cohort, 3.0% to the SARS-CoV-2-negative cohort, 63.2% to the SARS-CoV-2-positive cohort without ICU admission, and 32.3% to the SARS-CoV-2-positive cohort with ICU admission (Table 3). In the worst-case scenario, the total impact was €10,392 million (€139 million for the ER cohort, €284 million for the SARS-CoV-2-negative cohort, €5809 million for the SARS-CoV-2-positive cohort without ICU admission, and €4160 million for the SARS-CoV-2-positive cohort with ICU admission) (Table 3).

Table 3.

Impact on Spanish public health budget

Cohort No. of patients Mean cost per patient Budget impact
(€ million)
Conservative scenario
 ER cohort 432,854 €307.47 €133.09
 SARS-CoV-2-negative cohort 159,239 €1709.85 €272.28
 SARS-CoV-2-positive cohort without ICU stay 113,558 €50,131.99 €5692.89
 SARS-CoV-2-positive cohort with ICU stay 11,664 €280,955.81 €3277.07
TOTAL €9375.32
Worst-case scenario
 ER cohort 451,730 €307.47 €138.89
 SARS-CoV-2-negative cohort 166,183 €1709.85 €284.15
 SARS-CoV-2-positive cohort without ICU stay 115,877 €50,131.99 €5809.14
 SARS-CoV-2-positive cohort with ICU stay 14,806 €280,955.81 €4159.82
TOTAL €10,391.99

At the time of writing (end of June 2020), the pandemic is still going on and the total number of cases, hospitalizations, and ICU admissions continues to rise. Assuming that the total number of hospitalizations remains below 185,000 and ICU admissions remain below 25,000, the estimated budget impact of the pandemic should remain below €15,000 million (Table 4).

Table 4.

Impact on Spanish public health budget according to hospitalized and ICU cases

€ million No. of ICU cases
No. of hospitalized cases 1500 3000 4500 6000 7500 9000 10,500 12,000 13,500 15,000 16,500 18,000 19,500 21,000 22,500 24,000 25,500 27,000 28,500 30,000
5000 613 959 1306
20,000 1414 1760 2106 2452 2799 3145 3491 3837 4184 4530 4876 5222 5568
35,000 2214 2560 2907 3253 3599 3945 4292 4638 4984 5330 5677 6023 6369 6715 7061 7408 7754 8100 8446 8793
50,000 3015 3361 3707 4053 4400 4746 5092 5438 5785 6131 6477 6823 7170 7516 7862 8208 8554 8901 9247 9593
65,000 3815 4161 4508 4854 5200 5546 5893 6239 6585 6931 7278 7624 7970 8316 8663 9009 9355 9701 10,047 10,394
80,000 4616 4962 5308 5654 6001 6347 6693 7039 7386 7732 8078 8424 8771 9117 9463 9809 10,156 10,502 10,848 11,194
95,000 5416 5763 6109 6455 6801 7147 7494 7840 8186 8532 8879 9225 9571 9917 10,264 10,610 10,956 11,302 11,649 11,995
110,000 6217 6563 6909 7256 7602 7948 8294 8640 8987 9333 9679 10,025 10,372 10,718 11,064 11,410 11,757 12,103 12,449 12,795
125,000 7017 7364 7710 8056 8402 8749 9095 9441 9787 10,134 10,480 10,826 11,172 11,518 11,865 12,211 12,557 12,903 13,250 13,596
140,000 7818 8164 8510 8857 9203 9549 9895 10,242 10,588 10,934 11,280 11,627 11,973 12,319 12,665 13,011 13,358 13,704 14,050 14,396
155,000 8618 8965 9311 9657 10,003 10,350 10,696 11,042 11,388 11,735 12,081 12,427 12,773 13,120 13,466 13,812 14,158 14,504 14,851 15,197
170,000 9419 9765 10,111 10,458 10,804 11,150 11,496 11,843 12,189 12,535 12,881 13,228 13,574 13,920 14,266 14,613 14,959 15,305 15,651 15,997
185,000 10,220 10,566 10,912 11,258 11,604 11,951 12,297 12,643 12,989 13,336 13,682 14,028 14,374 14,721 15,067 15,413 15,759 16,106 16,452 16,798
200,000 11,020 11,366 11,713 12,059 12,405 12,751 13,097 13,444 13,790 14,136 14,482 14,829 15,175 15,521 15,867 16,214 16,560 16,906 17,252 17,599
215,000 11,821 12,167 12,513 12,859 13,206 13,552 13,898 14,244 14,590 14,937 15,283 15,629 15,975 16,322 16,668 17,014 17,360 17,707 18,053 18,399
230,000 12,621 12,967 13,314 13,660 14,006 14,352 14,699 15,045 15,391 15,737 16,083 16,430 16,776 17,122 17,468 17,815 18,161 18,507 18,853 19,200
245,000 13,422 13,768 14,114 14,460 14,807 15,153 15,499 15,845 16,192 16,538 16,884 17,230 17,577 17,923 18,269 18,615 18,961 19,308 19,654 20,000
260,000 14,222 14,568 14,915 15,261 15,607 15,953 16,300 16,646 16,992 17,338 17,685 18,031 18,377 18,723 19,070 19,416 19,762 20,108 20,454 20,801
275,000 15,023 15,369 15,715 16,061 16,408 16,754 17,100 17,446 17,793 18,139 18,485 18,831 19,178 19,524 19,870 20,216 20,563 20,909 21,255 21,601
290,000 15,823 16,170 16,516 16,862 17,208 17,554 17,901 18,247 18,593 18,939 19,286 19,632 19,978 20,324 20,671 21,017 21,363 21,709 22,056 22,402
305,000 16,624 16,970 17,316 17,663 18,009 18,355 18,701 19,047 19,394 19,740 20,086 20,432 20,779 21,125 21,471 21,817 22,164 22,510 22,856 23,202

Sensitivity analysis

The main sources of cost variation were physician salaries (range, €10,131 to €11,357/patient), nursing staff salaries (€10,274 to €11,215/patient), and general stays (€10,612 to €10,876/patient). The budget impact ranged from €14,741,399 to €16,524,924 for hospitals and from €15,050,529 (€10,344/patient) to €16,913,800 (€11,625/patient) for regions.

The probabilistic analysis showed that the total median impact of the COVID-19 pandemic on the hospital budget was €15,581,235 (Fig. 1). By cohort, the median impact was €14,754,694 for the SARS-CoV-2-positive cohort, €551,592 for the SARS-CoV-2-negative cohort, and €269,947 for the ER cohort.

Fig. 1.

Fig. 1

Sensitivity analysis of the economic impact overall and by cohort (bootstrapping method). SARS-CoV-2, severe acute respiratory syndrome coronavirus 2

Median per-patients costs in the SARS-CoV-2-positive cohort were €53,373 for general stays, €3108 for ICU stays, €692 for laboratory tests, €497 for diagnostic tests, and €330 for drugs. In the SARS-CoV-2-negative cohort, the median per-patient costs were €1098 for general stays, €346 for diagnostic tests, €252 for blood tests, and €13 for drugs. The median cost per patient in the ER cohort was €307.

The median estimated impact on the Spanish public health budget was €9357 million (interquartile range (IQR), €9071 to €9689 million) for the conservative scenario and €10,385 million (IQR, €10,030 to €10,758 million) for the worst-case scenario (Fig. 2).

Fig. 2.

Fig. 2

Impact of COVID-19 pandemic on the Spanish public health budget (bootstrapping method)

Discussion

The COVID-19 impact on the Spanish public health budget during the peak of the pandemic (86 days), considering direct medical costs only, was estimated at over €9.4 billion (12.3% of total public health expenditure) [10]. This is greater than the impact reported for numerous conditions in Spain, such as multiple sclerosis (€1.4 billion) [11], cancer (€4.8 billion) [12], and diabetes (€5.8 billion) [13]. These figures give a picture of how big the cost of the pandemic has been at its peak in Spain. The overall impact on the healthcare system, however, can be assumed to be even greater, as care provision for other diseases was disrupted during the peak of the pandemic, as occurred in 68% of countries in Europe [14, 15]. In Spain, for example, the number of percutaneous coronary interventions to treat myocardial infarction fell by 40% during the pandemic [16], increasing future risks and potential costs.

The mean cost estimated for treating a patient with suspected or confirmed COVID-19 at our hospital was €10,744. While this is lower than the costs of preterm birth, specialized surgical procedures, or treatments for solid cancer, it is higher than those of most procedures in a medium-sized hospital such as ours, where treating a patient with septicemia requiring mechanical ventilation for more than 96 h, for example, costs €9087.

Our budget impact analysis of the COVID-19 pandemic in Spain will be a useful tool for hospital and department planning and preparedness purposes. Our findings may also be of help to other countries wishing to forecast the impact of the pandemic on their healthcare systems, although this would require adaptation to local procedures and costs. Cost-estimation studies are also needed to document the investment and use of public funds during the pandemic. Our estimates could also help healthcare authorities and governments design mitigation plans to protect the healthcare system and prevent staff burnout. Disease prevention is increasingly crucial for ensuring the well-being of both society and the economy.

Although our hospital was equipped with additional ICU beds during the initial phase of the pandemic, these were insufficient to meet all our mechanical ventilation needs, meaning that some patients needed to be transferred to other hospitals. We therefore performed a sensitivity analysis in which we varied the percentage of patients admitted to the ICU based on data from other published cohorts (10.2%) [8]. The results showed an increase in cost per patient from €10,744 to €13,411. ICU stays accounted for 5.6% of total costs, even though just 3.5% of patients required ICU care. The main drivers of costs were staff salaries and general and ICU stays (97.8%). Drug treatments accounted for just 0.6% of total costs and can therefore be considered a relatively small cost component.

Using a prediction model for prolonged hospital stays among patients with COVID-19 in China, Hong et al. [17] estimated a mean cost per patient of €925 (IQR, €636 to €1395), which is 11.6 times lower than the figure calculated in our study. This difference could be due to the relatively small sample size analyzed by Hong et al. and the exclusion of patients with severe disease. In addition, the study was not a formal cost-analysis study. Another recent Chinese study of 70 patients hospitalized for a median of 16 days (IQR, 10–20 days) estimated a cost of $6827 per episode of COVID-19 [18], which is closer to our figure. Nonetheless, the median length of stay for SARS-CoV-2-positive patients in our series was just 8 days (IQR, 5–15 days) but the cost per patient was much higher, at €50,132. This difference can largely be attributed to staff costs, as our study was performed during the peak of the pandemic, when the hospital was overstretched. Other possible reasons include cultural differences and differences in healthcare system organization and costs. A US study that developed a Monte Carlo simulation model based on the assumption that 80% of the population would become infected calculated a total median direct medical cost of $654 billion (95% CI: 615.8–692.8) [19], with a median cost of $14,366 (95% CI: 13,545-15,129) per hospitalized patient and $215 million (95% CI: 209–221) for symptomatic patients. Our study, however, is based on real-world data and is not comparable.

To date, two Spanish studies have been published. Rodríguez-Gonzalez et al. [20] performed a cost analysis in a referral hospital (n = 1255) with global costs (€ 0.44 million per 1000 hospitalized patient and € 408 per patient) similar to our results (€ 307 per patient). These differences may be due to the higher incidence in Madrid during the first wave of COVID-19. However, we also present an estimate of the budgetary impact on the national health system of € 9357 million, by carrying out a probabilistic sensitivity analysis that took into account different incidence scenarios of the disease. In the second study [21] they make a totally theoretical estimate based on gross domestic product and not on real data like us.

Retrospective cohort studies are prone to selection bias. In an attempt to minimize this risk, we included all patients with suspected SARS-CoV-2 infection who visited the ER at our hospital. One notable strength of our study is the use of individual-level data for both diagnostic tests and treatments.

Another limitation of our study is related to possible false-negative misclassifications. False-negative rates ranging from 16 to 66% have been reported for RT-PCR, although these have improved over time [7, 22]. The prevalence of SARS-CoV-2 infection also varies by region, although the mean age and sex of hospitalized patients in our cohort were similar to those reported at the national level (66 years and 55% males for general-stay patients and 63 years and 55% males for ICU patients) [8]. The main limitation of our study, however, is that our calculations are based on data from a single hospital and cannot therefore be generalized to hospitals with other characteristics. Furthermore, to calculate the national costs, we assumed a constant ratio between negative and positive cohorts. Although, we analyzed the uncertainty of this parameter in the sensitivity analysis, readers must take attention that this relationship might not be linear.

Finally, we did not analyze indirect costs, such as productivity loss, but as most of the patients in the cohort were elderly and healthcare provider perspective.

Conclusions

The total estimated impact of COVID-19 on our hospital’s budget for a period of 86 days during the peak of the pandemic was €15.6 million, or €10,744 per patient. On extrapolating these estimates to Spain as a whole, the total direct medical cost accrued up to the end of June 2020 is €10.4 billion.

Supplementary Information

13561_2021_340_MOESM1_ESM.docx (26.7KB, docx)

Additional file 1: Table S1. Unit cost for seven autonomous communities.

Acknowledgments

To Mrs. Anne Murray for her support to translate the manuscript. This article is part of the doctoral thesis of Laura Álvarez as part of the Doctoral Program in Pharmacy, Granada University (Spain).

Authors‘contributions

Dr. Carrera and R Martínez-Gonzalbez had full access to all the data in the study and are responsible for the integrity of the data and the accuracy of the analysis. Dr. Vazquez checked all data. Laura Alvarez and Dr. Poquet contributed to the publication process control Concept and design: Dr. Carrera y Dr. Martínez promoted the study; and Dr. Vazquez, Dr. Crespo, and Dr. Carrera designed it. Acquisition, analysis, or interpretation of data: Dr. Carrera, R Martínez-Gonzalbez, Dr. Vázquez, Dr. El-Qutob, MA Ramón-Barrios, and Dr. Crespo. Drafting of the manuscript: The first draft of the manuscript was written by Javier Carrera and Laura Alvarez; and revised by Dr. Martínez, Dr. Crespo, MA Ramon Barrios, Dr. El-Qutob, and Dr. Poquet. The last version was written and corrected by Dr. Carrera, Dr. Vazquez, Dr. Crespo, Dr. Poveda and Laura Alvarez. Critical revision of the manuscript for important intellectual content: All authors had revised and approved last version of this manuscript. Statistical analysis: Modelling: Dr. Carrera, Dr. Crespo; Statistical and data managament: Dr. Vázquez, Dr. Carrera, and R Martínez-Gonzalbez. Funding: Dr. Poquet and Dr. Martinez. Administrative, technical, or material support: All authors.

Abbreviations

COVID-19

Coronavirus disease 2019

SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2

AEMPS

Spanish Agency of Medicines and Medical Products

ER

hospital’s emergency room

RT-PCR

real-time polymerase chain reaction

ICU

Intensive Care Unit

Euros

PPE

Personal protective equipment

IQR

interquartile range

Funding

The authors did not receive support from any organization for the submitted work.

Availability of data and materials

The data that support the findings of this study are available on request from the corresponding author.

Declarations

Ethics approval and consent to participate

The study was registered with the Spanish Agency of Medicines and Medical Products (AEMPS) and approved by the hospital’s ethics committee.

Verbal informed consent was obtained from all patients and noted in the patients’ medical records. This procedure was authorized by the Spanish Health authorities in view of the exceptional epidemiological situation.

Consent for publication

The work described has not been published previously, is not under consideration for publication elsewhere and, if accepted, will not be published elsewhere without the written consent of the copyright-holder. Its publication is approved by all authors and tacitly or explicitly by the responsible authorities.

Competing interests

Dr. Crespo received grant or personal fees outside the submitted work from Novartis, Pfizer, Abbvie, Gebro, Takeda, Shire, Mundipharma, Almirall, Boston Scientific, Dexcom, Hospital Clinic of Barcelona and GlaxoSmithKline.

The other authors declare that they have not conflict of interest.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

F. J. Carrera-Hueso, Email: javier_carrera2690@yahoo.es

L. Álvarez-Arroyo, Email: lauraalvarez6@yahoo.es

D. El-Qutob, Email: elqutob@comv.es

M. A. Ramón-Barrios, Email: mramonbarrios@yahoo.es

F. Martínez-Martínez, Email: femartin@ugr.es

J. L. Poveda-Andrés, Email: poveda_josand@gva.es

References

  • 1.Home - Johns Hopkins Coronavirus Resource Center [Internet]. Available from: https://coronavirus.jhu.edu/ Accessed 30 January 2021.
  • 2.Alfano V, Ercolano S. The efficacy of lockdown against COVID-19: a cross-country panel analysis. Appl Health Econ Health Policy. 2020;4(4):509–517. doi: 10.1007/s40258-020-00596-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Yamin M. Counting the cost of COVID-19. Int J Inf Technol. 2020;13:1–7.  10.1007/s41870-020-00466-0. [DOI] [PMC free article] [PubMed]
  • 4.Kabir M, Afzal MS, Khan A, Ahmed H. COVID-19 economic cost; impact on forcibly displaced people. Travel Med Infect Dis. 2020;35:101661. doi: 10.1016/j.tmaid.2020.101661. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Teasdale B, Schulman KA. Are U.S. Hospitals still "recession-proof"? [published online ahead of print, 2020 Jul 1]. N Engl J Med (2020); 10.1056/NEJMp2018846, 383, 13, e82. [DOI] [PubMed]
  • 6.ACUERDO de 8 de noviembre de 2019, del Consell, por el cual se autorizan determinadas transferencias de crédito para la aplicación del incremento retributivo previsto en el Real decreto ley 24/2018, de 21 de diciembre, por importe global de 9.650.760,22 euros. Expediente 06.001/19–001 (II parte). [2019/10711] [Internet]. Available from: http://www.dogv.gva.es/portal/ficha_disposicion.jsp?L=1&sig=009701%2F2019 Accessed 30 January 2021.
  • 7.Arevalo-Rodriguez I, Buitrago-Garcia D, Simancas-Racines D, Zambrano-Achig P, del Campo R, Ciapponi A, Sued O, Martinez-García L, Rutjes AW, Low N, Bossuyt PM, Perez-Molina JA, Zamora J. False-negative results of initial RT-PCR assays for COVID-19: a systematic review. PLoS One. 2020;15(12):e0242958. doi: 10.1371/journal.pone.0242958. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.[Update n° 153. Coronavirus disease (COVID-19). [Internet]. Available from: https://www.mscbs.gob.es/en/profesionales/saludPublica/ccayes/alertasActual/nCov-China/documentos/Actualizacion_153_COVID-19.pdf Accessed 1 July 2020.
  • 9.Tibshirani EB. Introd bootstrap Chaprnan hall N Y EEUU. 1993. [Google Scholar]
  • 10.Ministerio de Sanidad, Consumo y Bienestar Social - Portal Estadístico del SNS - Informe anual del Sistema Nacional de Salud [Internet]. Available from: https://www.mscbs.gob.es/estadEstudios/estadisticas/sisInfSanSNS/tablasEstadisticas/InfAnSNS.htm. .
  • 11.Fernández O, Calleja-Hernández MA, Meca-Lallana J, Oreja-Guevara C, Polanco A, Pérez-Alcántara F. Estimate of the cost of multiple sclerosis in Spain by literature review. Expert Rev Pharmacoecon Outcomes Res. 2017;17(4):321–333. doi: 10.1080/14737167.2017.1358617. [DOI] [PubMed] [Google Scholar]
  • 12.Badía X, Tort M, Manganelli AG, Camps C, Díaz-Rubio E. The burden of cancer in Spain. Clin Transl Oncol. 2019;21(6):729–734. doi: 10.1007/s12094-018-1972-7. [DOI] [PubMed] [Google Scholar]
  • 13.Crespo C, Brosa M, Soria-Juan A, López-Alba A, López-Martínez N, Soria B. Direct cost of diabetes mellitus and its complications in Spain (SECCAID study: Spain estimated cost Ciberdem-Cabimer in diabetes) Avances en Diabetologia. 2013;29(6):182–189. doi: 10.1016/j.avdiab.2013.07.007. [DOI] [Google Scholar]
  • 14.WHO/Europe | Regional Director - Statement – Preparing for the autumn is a priority now at the WHO Regional Office for Europe [Internet]. Available from: https://www.euro.who.int/en/about-us/regional-director/statements/statement-preparing-for-the-autumn-is-a-priority-now-at-the-who-regional-office-for-europe. Accessed 1 July 2020.
  • 15.Roffi M, Capodanno D, Windecker S, Baumbach A, Dudek D. Impact of the COVID-19 pandemic on interventional cardiology practice: results of the EAPCI survey. EuroIntervention. 2020;16(3):247–250. doi: 10.4244/EIJ-D-20-00528. [DOI] [PubMed] [Google Scholar]
  • 16.Rodriguez-Leor O, Cid-Alvarez B, Ojeda S. Impact of the COVID-19 pandemic on care activity in interventional cardiology in Spain. REC Interv Cardiol. 2020; 10.24875/RECICE.M20000123.
  • 17.Hong Y, Wu X, Qu J, Gao Y, Chen H, Zhang Z. Clinical characteristics of coronavirus disease 2019 and development of a prediction model for prolonged hospital length of stay. Ann Transl Med. 2020;8(7):443. doi: 10.21037/atm.2020.03.147. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Li XZ, Jin F, Zhang JG, Deng YF, Shu W, Qin JM, Ma X, Pang Y. Treatment of coronavirus disease 2019 in Shandong, China: a cost and affordability analysis. Infect Dis Poverty. 2020;9(1):78. doi: 10.1186/s40249-020-00689-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Bartsch SM, Ferguson MC, McKinnell JA, et al. The potential health care costs and resource use associated with COVID-19 in the United States. Health Aff (Millwood) 2020;39(6):927–935. doi: 10.1377/hlthaff.2020.00426. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Rodriguez-Gonzalez CG, Chamorro-de-Vega E, Valerio M, Amor-Garcia MA, Tejerina F, Sancho-Gonzalez M, Narrillos-Moraza A, Gimenez-Manzorro A, Manrique-Rodriguez S, Machado M, Olmedo M, Escudero-Vilaplana V, Villanueva-Bueno C, Torroba-Sanz B, Melgarejo-Ortuño A, Vicente-Valor J, Herranz A, Bouza E, Muñoz P, Sanjurjo M. COVID-19 in hospitalised patients in Spain: a cohort study in Madrid. Int J Antimicrob Agents. 2021;57(2):106249. doi: 10.1016/j.ijantimicag.2020.106249. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.González-López-Valcárcel B. Vallejo-Torres, Laura. The costs of COVID-19 and the cost-effectiveness of testing. Applied Economic Analysis. 2021;29(85):77–89. doi: 10.1108/AEA-11-2020-0162. [DOI] [Google Scholar]
  • 22.Woloshin S, Patel N, Kesselheim AS. False negative tests for SARS-CoV-2 infection—challenges and implications. N Engl J Med. 2020;383(6):e38. doi: 10.1056/NEJMp2015897. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

13561_2021_340_MOESM1_ESM.docx (26.7KB, docx)

Additional file 1: Table S1. Unit cost for seven autonomous communities.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author.


Articles from Health Economics Review are provided here courtesy of Springer-Verlag

RESOURCES