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Erschienen in: BMC Medicine 1/2024

Open Access 01.12.2024 | Research article

Substantial health and economic burden of COVID-19 during the year after acute illness among US adults not at high risk of severe COVID-19

verfasst von: Amie Scott, Wajeeha Ansari, Richard Chambers, Maya Reimbaeva, Tomasz Mikolajczyk, Michael Benigno, Florin Draica, Joanna Atkinson

Erschienen in: BMC Medicine | Ausgabe 1/2024

Abstract

Background

Patients recovering from SARS-CoV-2 infection and acute COVID-19 illness can experience a range of long-term post-acute effects. The potential clinical and economic burden of these outcomes in the USA is unclear. We evaluated diagnoses, medications, healthcare utilization, and medical costs before and after acute COVID-19 illness in US patients who were not at high risk of severe COVID-19.

Methods

This study included eligible adults who were diagnosed with COVID-19 from April 1 to May 31, 2020, who were 18 − 64 years of age, and enrolled within Optum’s de-identified Clinformatics® Data Mart Database for 12 months before and 13 months after COVID-19 diagnosis. Patients with any condition or risk factor placing them at high risk of progression to severe COVID-19 were excluded. Percentages of diagnoses, medications, healthcare utilization, and costs were calculated during baseline (12 months preceding diagnosis) and the post-acute phase (12 months after the 30-day acute phase of COVID-19). Data were stratified into 3 cohorts according to disposition during acute COVID-19 illness (i.e., not hospitalized, hospitalized without intensive care unit [ICU] admission, or admitted to the ICU).

Results

The study included 3792 patients; 56.5% of patients were men, 44% were White, and 94% did not require hospitalization. Compared with baseline, patients during the post-acute phase had percentage increases in the diagnosis of the following disorders: blood (166%), endocrine and metabolic (123%), nervous system (115%), digestive system (76%), and mental and behavioral (75%), along with increases in related prescriptions. Substantial increases in all measures of healthcare utilization were observed among all 3 cohorts. Total medical costs increased by 178% during the post-acute phase. Those who were hospitalized with or without ICU admission during the acute phase had the greatest increases in comorbidities and healthcare resource utilization. However, the burden was apparent across all cohorts.

Conclusions

As evidenced by resource use in the post-acute phase, COVID-19 places a significant long-term clinical and economic burden among US individuals, even among patients whose acute infection did not merit hospitalization.
Hinweise

Supplementary Information

The online version contains supplementary material available at https://​doi.​org/​10.​1186/​s12916-023-03235-5.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Abkürzungen
ACTH
Adrenocorticotropic hormone
CDC
US Centers for Disease Control and Prevention
CDM
Optum’s de-identified Clinformatics® Data Mart Database
CPT
Current Procedural Terminology
ED
Emergency department
HCPCS
Healthcare Common Procedure Coding System
ICD-10
International Classification of Diseases, 10th Revision
ICD-10-CM
International Classification of Diseases, 10th Revision, Clinical Modification
ICD-10-PCS
International Classification of Diseases, 10th Revision, Procedure Coding System
ICU
Intensive care unit
LOS
Length of stay
LTCF
Long-term care facility
NC
Not calculable
NDC
National Drug Code
PASC
Post-acute sequelae of COVID-19
Q1
Quartile 1
Q3
Quartile 3
SAS
Statistical analysis software
SNF
Skilled nursing facility
USC
Uniform System of Classification
USD
United States dollars

Background

Nearly 20% of adults diagnosed with COVID-19 experience symptoms for ≥ 3 months after first contracting the virus [1, 2]. These highly variable signs and symptoms, often termed post-COVID conditions, can either begin at the time of initial infection and persist for several months or may be new symptoms or syndromes that develop only after the acute phase of COVID-19 [35]. For many individuals, post-COVID conditions involve multiple organ systems and significantly impair daily functioning and productivity [6]. Although a universally accepted definition and timeframe of the condition has not yet been developed, a clinical diagnosis of post-acute sequelae of COVID-19 (PASC) was assigned an International Classification of Diseases 10 (ICD-10) code (U09.9) in October of 2021 [7, 8].
Although it is widely accepted that older age, belonging to racial and ethnic minority groups, and certain underlying medical conditions are associated with an increased risk of progression to severe COVID-19 upon initial infection [9], the characteristics associated with risk of developing post-COVID conditions are largely unknown. Some overlapping but distinct risk factors, such as female sex and older age, have been identified, as well as an association between acute COVID-19 severity and duration of symptoms [1012]. However, numerous reports from several countries have identified high rates of post-COVID conditions, even among patient cohorts with mixed disease severity or mild cases of COVID-19 [4, 1315]. In the current landscape where mild COVID-19 illness is becoming more common, owing both to vaccination [16] and the highly transmissible but potentially less virulent Omicron strain [1619], it is necessary to understand the burden on health and healthcare systems after an acute COVID-19 infection among patients who do not have underlying comorbidities and who did not require hospitalization for acute COVID-19. An understanding of long-term health effects after acute COVID-19 infection, the populations at risk, and the associated strain on healthcare systems is imperative to inform accurate estimations of the evolving clinical and economic burden of COVID-19.
We conducted a descriptive, retrospective analysis of morbidity, healthcare resource utilization, and costs associated with the post-acute phase of COVID-19 among adult patients aged < 65 years and without any underlying conditions placing them at high risk of progression to severe disease. In a companion report [20], we describe an identical analysis conducted among patients with ≥ 1 underlying condition or who were aged ≥ 65 years. The companion report and the current report were both purely descriptive with no formal statistical comparisons, with the goal to present a broad and unbiased dataset that can inform future hypothesis generation.

Methods

This descriptive, retrospective cohort study compared baseline healthcare utilization data from patients during the year before contracting COVID-19 with their healthcare utilization data during the year after recovery from the 30-day acute phase (from day 31 through day 390 after diagnosis). All patients served as their own control for evaluation of diagnoses, medications, healthcare utilization, and costs before compared with after acute COVID-19. Details regarding the study design, data source, and inclusion and exclusion criteria have been included in the companion manuscript regarding individuals at high risk of progression to severe COVID-19 [20].
Briefly, enrolled patients were diagnosed with COVID-19 (ICD-10 diagnosis code of U07.1) between April 1 and May 31, 2020 (the index period). Information regarding diagnoses, medications, healthcare utilization, and costs were collected from Optum’s de-identified Clinformatics® Data Mart Database (CDM), which contains patient-level information derived from administrative health claims of commercial and Medicare Advantage plan members. Data extracted from CDM were not sufficient to determine whether any post-COVID-19 diagnosis, medication prescription, or healthcare utilization was specifically caused by COVID-19; therefore, it was unknown whether any individual diagnosis or adverse health outcome was truly a “post-COVID condition” or was caused by unrelated factors [5]. Eligible patients were continuously enrolled in CDM (with gaps of ≤ 45 days permitted) over the 12 months before and 13 months after COVID-19 diagnosis and were aged 18 to 64 years on the index date. Patients were excluded if they had a diagnosis code (ICD-10-Clinical Modification [ICD-10-CM]), procedure code (ICD-10-Procedure Coding System [ICD-10-PCS], Current Procedural Terminology [CPT®], Healthcare Common Procedures Coding System [HCPCS]), or National Drug Code (NDC) for any condition placing them at high risk of progression to severe COVID-19, per CDC definitions as of October 14, 2021 [9], within the 12 months before the index date. Additional exclusion criteria were hospitalizations for ≥ 5 consecutive days during the baseline phase; any time spent at a long-term care facility, skilled nursing facility, inpatient rehabilitation, or hospice during baseline or at index date; an ICD-10 code for confirmed COVID-19 before the index period; or death during the acute phase of COVID-19.
The top 500 ICD-10 diagnosis codes were analyzed by ICD-10 code chapter (a system of organization based on the most affected organ systems or types of injury/disease), and medications were categorized according to Uniform System of Classification class. All diagnosis and medication categories applicable to < 2% of the overall population during the baseline phase were excluded from analysis. The “biologics” category was also excluded based on incomplete data capture. Standard medical cost means, standard deviations, medians, and quartiles were calculated using the number of patients with a related visit or service, and nonzero costs were calculated using the number of patients with a cost > 0 associated with that visit or service. No adjustments were made for patients who died during the 12-month post-acute phase; all deaths that occurred during the post-acute phase were accounted for and reported. Absolute and relative change from baseline to the post-acute phase were calculated for each outcome where possible using frequency counts. To better understand the relationship between post-acute outcomes and initial infection severity, all data were presented for the overall population and stratified by patient disposition during the acute phase of COVID-19 (within 30 days after diagnosis): not hospitalized, hospitalized without intensive care unit (ICU) admission, or admitted to the ICU. Analyses were performed using SAS version 9.4 (SAS, Cary, NC), and no statistical inference tests were conducted.

Results

Patient population

Overall, the cohort included 3792 patients with a median (quartile 1; quartile 3) age of 40 (31; 50) years (Table 1). A slight majority of patients were male (56.5%), and 44.0% of patients were White. When categorized by disposition during the acute phase of COVID-19, 3546 patients (93.5%) did not require hospitalization, 164 (4.3%) were hospitalized without ICU admission, and 82 (2.2%) were admitted to the ICU. Patients who were male, Black, or aged 50 to 64 years were more highly represented within the cohort with ICU admission than within the overall population.
Table 1
Baseline demographic and clinical characteristics
  
Disposition during acute COVID-19 illness
Characteristic
All patients
(N = 3792)
No hospitalization
(n = 3546)
Hospitalization without ICU admission
(n = 164)
ICU admission
(n = 82)
Sex, n (%)
 Female
1648 (43.5)
1571 (44.3)
56 (34.1)
21 (25.6)
 Male
2144 (56.5)
1975 (55.7)
108 (65.9)
61 (74.4)
Age, years
 Mean ± SD
40.4 ± 12.2
39.9 ± 12.2
46.4 ± 11.8
48.0 ± 10.3
 Median (Q1; Q3)
40 (31; 50)
39 (30; 50)
47 (36.5; 56)
50.5 (41; 56)
Age group, years, n (%)
 18–29
859 (22.7)
838 (23.6)
15 (9.1)
6 (7.3)
 30–49
1900 (50.1)
1791 (50.5)
78 (47.6)
31 (37.8)
 50–64
1033 (27.2)
917 (25.9)
71 (43.3)
45 (54.9)
Race or ethnicity, n (%)
 White
1670 (44.0)
1599 (45.1)
49 (29.9)
22 (26.8)
 Black
397 (10.5)
359 (10.1)
21 (12.8)
17 (20.7)
 Hispanic
1078 (28.4)
984 (27.7)
66 (40.2)
28 (34.1)
 Asian
229 (6.0)
215 (6.1)
10 (6.1)
4 (4.9)
 Unknown
418 (11.0)
389 (11.0)
18 (11.0)
11 (13.4)
Geographic division, n (%)
 New England
236 (6.2)
227 (6.4)
7 (4.3)
2 (2.4)
 Mid-Atlantic
764 (20.1)
730 (20.6)
27 (16.5)
7 (8.5)
 East North Central
729 (19.2)
670 (18.9)
39 (23.8)
20 (24.4)
 West North Central
402 (10.6)
374 (10.5)
20 (12.2)
8 (9.8)
 South Atlantic
664 (17.5)
617 (17.4)
33 (20.1)
14 (17.1)
 East South Central
93 (2.5)
87 (2.5)
4 (2.4)
2 (2.4)
 West South Central
330 (8.7)
305 (8.6)
14 (8.5)
11 (13.4)
 Mountain
295 (7.8)
285 (8.0)
5 (3.0)
5 (6.1)
 Pacific
252 (6.7)
236 (6.7)
10 (6.1)
6 (7.3)
Insurance, n (%)
 Commercial
3756 (99.1)
3523 (99.4)
155 (94.5)
78 (95.1)
 Medicare
36 (0.9)
23 (0.6)
9 (5.5)
4 (4.9)
Care setting of COVID-19 diagnosis, n (%)
 Inpatient
181 (4.8)
0 (0.0)
128 (78.0)
53 (64.6)
 Outpatient
3611 (95.2)
3546 (100)
36 (22.0)
29 (35.4)
Disposition during acute COVID-19 illness, n (%)
 No hospitalization
3546 (93.5)
   
 Hospitalization without ICU admission
164 (4.3)
   
 ICU admission
82 (2.2)
   
COVID-19 inpatient stay that overlaps acute and post-acute phases (> 30 days), n (%)
9 (0.2)
0 (0.0)
2 (1.2)
7 (8.5)
ICU intensive care unit, Q1 quartile 1, Q3 quartile 3
Most patients (95.2%) were diagnosed with COVID-19 in the outpatient setting (Table 1). Very few patients (0.2% of those hospitalized at any time during the acute phase) had hospital stays that lasted > 30 days, overlapping the acute and post-acute phases of the study. None of the patients died during the post-acute phase. A full list of reasons for exclusion from the analysis is shown in Table S1.

Diagnoses

In the overall population, the frequency of ICD-10 diagnosis codes increased within several chapters (diagnosis categories) between the baseline and post-acute phases (Fig. 1). The number of patients with “diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism” increased by 166.0% from baseline, as well as a 123.2% increase in “endocrine, nutritional, and metabolic diseases,” a 115.2% increase in “diseases of the nervous system,” a 76.3% increase in “diseases of the digestive system,” and a 74.6% increase in “mental and behavioral disorders” (Fig. 1). Frequencies of diagnoses within these chapters increased within all 3 cohorts (Table 2), with the smallest percentage increases observed among patients who were not hospitalized for acute COVID-19 and the largest percentage increases observed among patients who were admitted to the ICU.
Table 2
Diagnoses during the baseline and post-acute phasesa stratified by disposition during acute COVID-19
  
No hospitalization
(n = 3546)
Hospitalization without ICU admission
(n = 164)
ICU admission
(n = 82)
ICD diagnosis description
ICD diagnosis code
Baseline phase, n (%)
Post-acute phase, n (%)
Change from baseline to post-acute phase,
Δ (% change)
Baseline phase, n (%)
Post-acute phase, n (%)
Change from baseline to post-acute phase,
Δ (% change)
Baseline phase, n (%)
Post-acute phase, n (%)
Change from baseline to post-acute phase,
Δ (% change)
Diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism
D50-D89
96 (2.7)
242 (6.8)
146 (152.1)
6 (3.7)
20 (12.2)
14 (233.3)
1 (1.2)
12 (14.6)
11 (1100.0)
Endocrine, nutritional, and metabolic diseases
E00-E90
476 (13.4)
1008 (28.4)
532 (111.8)
19 (11.6)
67 (40.9)
48 (252.6)
6 (7.3)
43 (52.4)
37 (616.7)
Diseases of the nervous system
G00-G99
231 (6.5)
477 (13.5)
246 (106.5)
10 (6.1)
27 (16.5)
17 (170.0)
3 (3.7)
21 (25.6)
18 (600.0)
Diseases of the digestive system
K00-K95
326 (9.2)
560 (15.8)
234 (71.8)
21 (12.8)
39 (23.8)
18 (85.7)
3 (3.7)
18 (22.0)
15 (500.0)
Mental and behavioral disorders
F00-F99
349 (9.8)
582 (16.4)
233 (66.8)
7 (4.3)
23 (14.0)
16 (228.6)
2 (2.4)
20 (24.4)
18 (900.0)
Diseases of the skin and subcutaneous tissue
L00-L99
383 (10.8)
585 (16.5)
202 (52.7)
12 (7.3)
31 (18.9)
19 (158.3)
2 (2.4)
16 (19.5)
14 (700.0)
External causes of morbidity and mortality
V00-Y99
96 (2.7)
137 (3.9)
41 (42.7)
5 (3.0)
9 (5.5)
4 (80.0)
1 (1.2)
2 (2.4)
1 (100.0)
Injury, poisoning, and certain other consequences of external causes
S00-T98
379 (10.7)
503 (14.2)
124 (32.7)
14 (8.5)
32 (19.5)
18 (128.6)
4 (4.9)
10 (12.2)
6 (150.0)
Diseases of the genitourinary system
N00-N99
558 (15.7)
726 (20.5)
168 (30.1)
16 (9.8)
27 (16.5)
11 (68.8)
2 (2.4)
23 (28.0)
21 (1050.0)
Factors influencing health status and contact with health services
Z00-Z99
2166 (61.1)
2834 (79.9)
668 (30.8)
79 (48.2)
120 (73.2)
41 (51.9)
31 (37.8)
60 (73.2)
29 (93.5)
Diseases of the musculoskeletal system and connective tissue
M00-M99
843 (23.8)
1063 (30.0)
220 (26.1)
37 (22.6)
59 (36.0)
22 (59.5)
11 (13.4)
31 (37.8)
20 (181.8)
Diseases of the eye and adnexa
H00-H59
280 (7.9)
354 (10.0)
74 (26.4)
16 (9.8)
27 (16.5)
11 (68.8)
7 (8.5)
7 (8.5)
0 (0.0)
Diseases of the ear and mastoid process
H60-H95
184 (5.2)
206 (5.8)
22 (12.0)
7 (4.3)
9 (5.5)
2 (28.6)
4 (4.9)
3 (3.7)
–1 (–25.0)
Symptoms, signs, and abnormal clinical laboratory findings not elsewhere classified
R00-R99
1715 (48.4)
1735 (48.9)
20 (1.2)
75 (45.7)
104 (63.4)
29 (38.7)
31 (37.8)
56 (68.3)
25 (80.6)
Certain infectious and parasitic diseases
A00-B99
574 (16.2)
430 (12.1)
–144 (–25.1)
24 (14.6)
26 (15.9)
2 (8.3)
8 (9.8)
23 (28.0)
15 (187.5)
Diseases of the respiratory system
J00-J99
1107 (31.2)
764 (21.5)
–343 (–31.0)
42 (25.6)
60 (36.6)
18 (42.9)
22 (26.8)
37 (45.1)
15 (68.2)
ICD International Classification of Diseases, ICU intensive care unit
aThe baseline period was the 12 months before the index date, and the post-acute phase spanned from 1 to 13 months after the index date
The greatest decrease observed within the overall cohort was a − 26.5% change from baseline in the frequency of “diseases of the respiratory system” (Fig. 1). This value reflected a combination of decreased acute diagnoses, as well as a 73.0% increase in the frequency of “chronic lower respiratory diseases” (Fig. 2).

Medication use

In the overall population, medications from several different classes were prescribed in greater numbers during the post-acute phase compared with baseline (Table 3). The greatest observed changes were a 188.6% increase in hormones (primarily corticoids and glucocorticoids; Table S2), a 113.1% increase in vascular agents, a 62.7% increase in musculoskeletal agents, a 61.5% increase in antihyperlipidemic agents, and a 61.0% increase in neurological/neuromuscular agents. In contrast, there was also a 73.5% decrease in prescriptions of cough/cold/flu preparations and a 48.8% decrease in antivirals.
Table 3
New medication prescriptions during baseline and post-acute phasesa in the overall population (N = 3792)
USC medication class description
Baseline phase, n (%)
Post-acute phase, n (%)
Change from baseline to post-acute phase,
Δ (% change)
Hormones
228 (6.0)
658 (17.4)
430 (188.6)
Vascular agents
130 (3.4)
277 (7.3)
147 (113.1)
Musculoskeletal
153 (4.0)
249 (6.6)
96 (62.7)
Antihyperlipidemic agents
148 (3.9)
239 (6.3)
91 (61.5)
Neurological/neuromuscular disorders
118 (3.1)
190 (5.1)
72 (61.0)
Analgesics
302 (8.0)
485 (12.8)
183 (60.6)
Psychotherapeutic drugs
354 (9.3)
560 (14.8)
206 (58.2)
Gastrointestinal
191 (5.0)
285 (7.5)
94 (49.2)
Ophthalmic preparations
112 (3.0)
157 (4.1)
45 (40.2)
Genitourinary
168 (4.4)
235 (6.2)
67 (39.9)
Antinauseants
162 (4.3)
213 (5.6)
51 (31.5)
Antiarthritics
381 (10.0)
492 (13.0)
111 (29.1)
Dermatologicals
139 (3.7)
171 (4.5)
32 (23.0)
Thyroid therapy
105 (2.8)
129 (3.4)
24 (22.9)
Anti-fungal agents
206 (5.4)
236 (6.2)
30 (14.6)
Contraceptives
278 (7.3)
281 (7.4)
3 (1.1)
Anti-infectives, systemic
1020 (26.9)
928 (24.5)
–92 (–9.0)
Respiratory therapy
469 (12.4)
369 (9.7)
–100 (–21.3)
Antivirals
287 (7.6)
147 (3.9)
–140 (–48.8)
Cough/cold/flu preparations
302 (8.0)
80 (2.1)
–222 (–73.5)
USC Uniform System of Classification
aThe baseline period was the 12 months before the index date, and the post-acute phase spanned from 1 to 13 months after the index date
For most medication classes, increases in prescriptions from the baseline to the post-acute phase were observed across all 3 cohorts but were generally greatest among those who were admitted to the ICU for acute COVID-19 (Table 4). As an exception, the magnitude of the percentage increases in hormone prescriptions was relatively consistent across cohorts.
Table 4
New medication prescriptions during the baseline and post-acute phasesa stratified by disposition during acute COVID-19
USC medication class description
No hospitalization
(n = 3546)
Hospitalization without ICU admission
(n = 164)
ICU admission
(n = 82)
Baseline phase, n (%)
Post-acute phase, n (%)
Change from baseline to post-acute phase, Δ (% change)
Baseline phase, n (%)
Post-acute phase, n (%)
Change from baseline to post-acute phase,
Δ (% change)
Baseline phase, n (%)
Post-acute phase, n (%)
Change from baseline to post-acute phase, Δ (% change)
Hormones
214 (6.0)
617 (17.4)
403 (188.3)
9 (5.5)
27 (16.5)
18 (200.0)
5 (6.1)
14 (17.1)
9 (180.0)
Vascular agents
114 (3.2)
227 (6.4)
113 (99.1)
9 (5.5)
25 (15.2)
16 (177.8)
7 (8.5)
25 (30.5)
18 (257.1)
Musculoskeletal
140 (3.9)
232 (6.5)
92 (65.7)
11 (6.7)
12 (7.3)
1 (9.1)
2 (2.4)
5 (6.1)
3 (150.0)
Antihyperlipidemic agents
136 (3.8)
208 (5.9)
72 (52.9)
8 (4.9)
17 (10.4)
9 (112.5)
4 (4.9)
14 (17.1)
10 (250.0)
Neurological/neuromuscular disorders
110 (3.1)
171 (4.8)
61 (55.5)
5 (3.0)
10 (6.1)
5 (100.0)
3 (3.7)
9 (11.0)
6 (200.0)
Analgesics
274 (7.7)
438 (12.4)
164 (59.9)
17 (10.4)
29 (17.7)
12 (70.6)
11 (13.4)
18 (22.0)
7 (63.6)
Psychotherapeutic drugs
341 (9.6)
520 (14.7)
179 (52.5)
9 (5.5)
24 (14.6)
15 (166.7)
4 (4.9)
16 (19.5)
12 (300.0)
Gastrointestinal
178 (5.0)
258 (7.3)
80 (44.9)
12 (7.3)
19 (11.6)
7 (58.3)
1 (1.2)
8 (9.8)
7 (700.0)
Ophthalmic preparations
102 (2.9)
143 (4.0)
41 (40.2)
8 (4.9)
12 (7.3)
4 (50.0)
2 (2.4)
2 (2.4)
0 (0.0)
Genitourinary
161 (4.5)
222 (6.3)
61 (37.9)
7 (4.3)
6 (3.7)
–1 (–14.3)
0 (0.0)
7 (8.5)
7 (NC)
Antinauseants
149 (4.2)
194 (5.5)
45 (30.2)
10 (6.1)
13 (7.9)
3 (30.0)
3 (3.7)
6 (7.3)
3 (100.0)
Antiarthritics
345 (9.7)
452 (12.7)
107 (31.0)
25 (15.2)
26 (15.9)
1 (4.0)
11 (13.4)
14 (17.1)
3 (27.3)
Dermatologicals
135 (3.8)
160 (4.5)
25 (18.5)
2 (1.2)
3 (1.8)
1 (50.0)
2 (2.4)
8 (9.8)
6 (300.0)
Thyroid therapy
103 (2.9)
123 (3.5)
20 (19.4)
1 (0.6)
3 (1.8)
2 (200.0)
1 (1.2)
3 (3.7)
2 (200.0)
Anti-fungal agents
197 (5.6)
221 (6.2)
24 (12.2)
6 (3.7)
8 (4.9)
2 (33.3)
3 (3.7)
7 (8.5)
4 (133.3)
Contraceptives
273 (7.7)
273 (7.7)
0 (0.0)
3 (1.8)
6 (3.7)
3 (100.0)
2 (2.4)
2 (2.4)
0 (0.0)
Anti-infectives, systemic
963 (27.2)
867 (24.5)
–96 (–10.0)
39 (23.8)
43 (26.2)
4 (10.3)
18 (22.0)
18 (22.0)
0 (0.0)
Respiratory therapy
442 (12.5)
328 (9.3)
–114 (–25.8)
18 (11.0)
25 (15.2)
7 (38.9)
9 (11.0)
16 (19.5)
7 (77.8)
Antivirals
280 (7.9)
142 (4.0)
–138 (–49.3)
2 (1.2)
4 (2.4)
2 (100.0)
5 (6.1)
1 (1.2)
–4 (–80.0)
Cough/cold/flu preparations
282 (8.0)
70 (2.0)
–212 (–75.2)
14 (8.5)
6 (3.7)
–8 (–57.1)
6 (7.3)
4 (4.9)
–2 (–33.3)
ICU intensive care unit, NC not calculable, USC Uniform System of Classification
aThe baseline period was the 12 months before the index date, and the post-acute phase spanned from 1 to 13 months after the index date
Prescription increases were also observed within several medication classes that were not included in the main analysis because they were prescribed to < 2% of the overall cohort during the baseline phase (Table S3). These included increases of > 100% within the classes of hemostatic modifiers, diabetes therapy, cardiac agents, and blood factors.

Medical care and hospitalizations

Between the baseline and post-acute phases, increases were observed across all measures of healthcare utilization in the overall population and among all 3 cohorts (Tables 5 and 6). The greatest changes were related to inpatient resources: a 3100% increase in inpatient lab tests, a 3000% increase in total days spent in the ICU, a 1269% increase in length of stay (LOS), and a 527% increase in number of hospitalizations (Table 5). With the exception of emergency department (ED) visits, increases in all measures of healthcare utilization were greatest among those who were admitted to the ICU for acute COVID-19 (Table 6).
Table 5
Healthcare resource utilization during the baseline and post-acute phasesa in the overall population (N = 3792)
Visit or procedure
Baseline phase, n (%)
Post-acute phase, n (%)
Change from baseline to post-acute phase,
Δ (% change)
Outpatient lab tests
 Tests
2200
4750
2550 (115.9)
 Patients
1253
1768
515 (41.1)
 Mean ± SD
0.6 ± 1.1
1.3 ± 2.6
0.7
 Median (Q1; Q3)
0 (0; 1)
0 (0; 2)
0
Outpatient visits (specialist or nonspecialist)
 Visits
18,691
39,570
20,879 (111.7)
 Patients
3026
3316
290 (9.6)
 Mean ± SD
4.9 ± 6.7
10.4 ± 14.0
5.5
 Median (Q1; Q3)
3 (1; 6)
6 (2; 13)
3
Emergency department visits
 Visits
492
662
170 (34.6)
 Patients
392
471
79 (20.2)
 Mean ± SD
0.1 ± 0.4
0.2 ± 0.6
0.0
 Median (Q1; Q3)
0 (0; 0)
0 (0; 0)
0
Prescription classes
 Prescriptions
5713
7539
1826 (32.0)
 Patients
2255
2541
286 (12.7)
 Mean ± SD
1.5 ± 1.8
2.0 ± 2.2
0.5
 Median (Q1; Q3)
1 (0; 2)
1 (0; 3)
0
Inpatient visits
 Visits
22
138
116 (527.3)
 Patients
21
94
73 (347.6)
 Mean ± SD
0.0 ± 0.1
0.0 ± 0.3
0.0
 Median (Q1; Q3)
0 (0; 0)
0 (0; 0)
0
Inpatient lab tests
 Tests
1
32
31 (3100)
 Patients
1
11
10 (1000.0)
 Mean ± SD
0.0 ± 0.0
0.0 ± 0.2
0.0
 Median (Q1; Q3)
0 (0; 0)
0 (0; 0)
0
Length of hospital stay
 Days
86
1177
1091 (1268.6)
 Patients
21
94
73 (347.6)
 Mean ± SD
4.1 ± 3.8
12.5 ± 25.8
8.4 (205.8)
 Median (Q1; Q3)
3 (2; 5)
4 (3; 8)
1
Length of ICU stay
 Days
1
31
30 (3000.0)
 Patients
1
17
16 (1600.0)
 Mean ± SD
0.0 ± 0.2
0.3 ± 1.1
0.3 (592.6)
 Median (Q1; Q3)
0 (0; 0)
0 (0; 0)
0
Invasive mechanical ventilation use, patient n (%)
0 (0.0)
5 (0.1)
5 (NC)
Noninvasive mechanical ventilation use, patient n (%)
0 (0.0)
4 (0.1)
4 (NC)
Supplemental oxygen use, patient n (%)
0 (0.0)
7 (0.2)
7 (NC)
Readmission within 30 days, patient n (%)
0 (0.0)
23 (0.6)
23 (NC)
ICU intensive care unit, NC not calculable, Q1 quartile 1, Q3 quartile 3
For visits, tests, prescriptions, and procedures, means or percentages were calculated using the total number of patients within the cohort as the denominator. For length of hospital stay and ICU stay, means were calculated as the total number of days divided by the number of patients with any inpatient hospital stay
aThe baseline period was the 12 months before the index date, and the post-acute phase spanned from 1 to 13 months after the index date
Table 6
Healthcare resource utilization during the baseline and post-acute phasesa stratified by disposition during acute COVID-19
Visit or procedure
No hospitalization
(n = 3546)
Hospitalization without ICU admission
(n = 164)
ICU admission
(n = 82)
Baseline phase
Post-acute phase
Change from baseline to post-acute phase,
Δ (% change)
Baseline phase
Post-acute phase
Change from baseline to post-acute phase,
Δ (% change)
Baseline phase
Post-acute phase
Change from baseline to post-acute phase,
Δ (% change)
Outpatient lab tests
 Tests, n
2121
4518
2397 (113.0)
60
156
96 (160.0)
19
76
57 (300.0)
 Patients, n
1204
1662
458 (38.0)
37
71
34 (91.9)
12
35
23 (191.7)
 Mean ± SD
0.6 ± 1.1
1.3 ± 2.6
0.7
0.4 ± 0.9
1.0 ± 1.9
0.6
0.2 ± 0.7
0.9 ± 1.4
0.7
 Median (Q1; Q3)
0 (0; 1)
0 (0; 2)
0
0 (0; 0)
0 (0; 1)
0
0 (0; 0)
0 (0; 1)
0
Outpatient visits (specialist or nonspecialist)
 Visits, n
17,763
36,146
18,383 (103.5)
687
2172
1485 (216.2)
241
1252
1011 (419.5)
 Patients, n
2865
3106
241 (8.4)
113
145
32 (28.3)
48
65
17 (35.4)
 Mean ± SD
5.0 ± 6.7
10.2 ± 13.5
5.2
4.2 ± 6.5
13.2 ± 18.8
9.1
2.9 ± 7.9
15.3 ± 21.7
12.3
 Median (Q1; Q3)
3 (1; 7)
6 (2; 13)
3
2 (0; 5.5)
7 (2; 16)
5
1 (0; 3)
7 (2; 15)
6
Emergency department visits
 Visits, n
445
595
150 (33.7)
34
51
17 (50.0)
13
16
3 (23.1)
 Patients, n
356
428
72 (20.2)
27
34
7 (25.9)
9
9
0 (0.0)
 Mean ± SD
0.1 ± 0.4
0.2 ± 0.6
0.0
0.2 ± 0.5
0.3 ± 0.7
0.1
0.2 ± 0.5
0.2 ± 0.7
0.0
 Median (Q1; Q3)
0 (0; 0)
0 (0; 0)
0
0 (0; 0)
0 (0; 0)
0
0 (0; 0)
0 (0; 0)
0
Prescription classes
 Prescriptions, n
5374
6882
1508 (28.1)
235
397
162 (68.9)
104
260
156 (150.0)
 Patients, n
2128
2373
245 (11.5)
91
112
21 (23.1)
36
56
20 (55.6)
 Mean ± SD
1.5 ± 1.8
1.9 ± 2.2
0.4
1.4 ± 1.9
2.4 ± 2.8
1.0
1.3 ± 1.9
3.2 ± 3.6
1.9
 Median (Q1; Q3)
1 (0; 2)
1 (0; 3)
0
1 (0; 2)
1 (0; 4)
0
0 (0; 2)
3 (0; 5)
3
Inpatient visits
 Visits, n
19
76
57 (300.0)
3
22
19 (633.3)
0
40
40 (NC)
 Patients, n
18
63
45 (250.0)
3
16
13 (433.3)
0
15
15 (NC)
 Mean ± SD
0.0 ± 0.1
0.0 ± 0.2
0.0
0.0 ± 0.1
0.1 ± 0.5
0.1
0.0 ± 0.0
0.5 ± 1.5
0.5
 Median (Q1; Q3)
0 (0; 0)
0 (0; 0)
0
0 (0; 0)
0 (0; 0)
0
0 (0; 0)
0 (0; 0)
0
Inpatient lab tests
 Tests, n
1
10
9 (900.0)
0
9
9 (NC)
0
13
13 (NC)
 Patients, n
1
6
5 (500.0)
0
3
3 (NC)
0
2
2 (NC)
 Mean ± SD
0.0 ± 0.0
0.0 ± 0.1
0.0
0.0 ± 0.0
0.1 ± 0.4
0.1
0.0 ± 0.0
0.2 ± 1.2
0.2
 Median (Q1; Q3)
0 (0; 0)
0 (0; 0)
0
0 (0; 0)
0 (0; 0)
0
0 (0; 0)
0 (0; 0)
0
Length of hospital stay
 Days, n
77
388
311 (403.9)
9
162
153 (1700.0)
0
627
627 (NC)
 Patients, n
18
63
45 (250.0)
3
16
13 (433.3)
0
15
15 (NC)
 Mean ± SD
4.3 ± 4.0
6.2 ± 7.3
1.9 (44.0)
3.0 ± 2.0
10.1 ± 10.6
7.1 (237.5)
NC
41.8 ± 54.3
NC
 Median (Q1; Q3)
3 (2; 5)
4 (3; 5)
1
3 (1; 5)
5.5 (3.5; 14.0)
2.5
NC
7 (3; 79)
NC
Length of ICU stay
 Days, n
1
6
5 (500.0)
0
9
9 (NC)
0
16
16 (NC)
 Patients, n
1
6
5 (500.0)
0
4
4 (NC)
0
7
7 (NC)
 Mean ± SD
0.06 ± 0.24
0.10 ± 0.30
0.04 (71.4)
0.0 ± 0.0
0.6 ± 1.5
0.6 (NC)
NC
1.1 ± 2.1
NC
 Median (Q1; Q3)
0 (0; 0)
0 (0; 0)
0
0 (0; 0)
0 (0; 0.5)
0
NC
0 (0; 1)
NC
Patients with invasive mechanical ventilation use, n (%)
0 (0.0)
1 (0.0)
1 (NC)
0 (0.0)
1 (0.6)
1 (NC)
0 (0.0)
3 (3.7)
3 (NC)
Patients with noninvasive mechanical ventilation use, n (%)
0 (0.0)
1 (0.0)
1 (NC)
0 (0.0)
1 (0.6)
1 (NC)
0 (0.0)
2 (2.4)
2 (NC)
Patients with supplemental oxygen use, n (%)
0 (0.0)
1 (0.0)
1 (NC)
0 (0.0)
1 (0.6)
1 (NC)
0 (0.0)
5 (6.1)
5 (NC)
Patients with readmission within 30 days, n (%)
0 (0.0)
7 (0.2)
7 (NC)
0 (0.0)
7 (4.3)
7 (NC)
0 (0.0)
9 (11.0)
9 (NC)
ICU, intensive care unit; NC, not calculable; Q1, quartile 1; Q3, quartile 3
For visits, tests, prescriptions and procedures, means were calculated as the total value divided by the total number of patients within the cohort
For length of hospital stay and ICU stay, means were calculated as the total number of days divided by the number of patients in the cohort with any inpatient hospital stay
aThe baseline period was the 12 months before the index date, and the post-acute phase spanned from 1 to 13 months after the index date
Increases in healthcare utilization were also represented by a shift in patterns of discharge status (Table 7). The percentages of hospitalized patients who were discharged to home or self-care were 95.5% during the baseline phase and 65.2% during the post-acute phase. During the post-acute phase, larger percentages of patients were discharged to either a home care service or other facility (such as a hospice or skilled nursing facility), were transferred within the institution, or had an unknown discharge status.
Table 7
Hospital discharge status during the baseline and post-acute phasesa in the overall population (N = 3792)
 
Baseline phase
Post-acute phase
Hospitalizations, N
22
138
Discharge status, n (%)
 Discharged to home or self-care
21 (95.5)
90 (65.2)
 Discharged to home under care of home health service organization
0 (0.0)
5 (3.6)
 Discharged to other facilitya
0 (0.0)
16 (11.6)
 Still patient/transferred within institution
0 (0.0)
8 (5.8)
 Unknown status
1 (4.5)
19 (13.8)
Percentages were calculated in relation to the total number of hospital discharges during the specified period
aIncludes short-term general hospital, skilled nursing facility, intermediate care facility, federal healthcare facility, home hospice, medical facility hospice, inpatient rehabilitation facility, long-term care hospital, nursing facility certified under Medicare, psychiatric hospital or psychiatric distinct part/unit of a hospital, critical access hospital or other type of healthcare institution

Healthcare costs

During the post-acute phase, total medical costs (including prescription, inpatient, and outpatient costs) increased from baseline by 177.9% in the overall population (Table 8). When stratified by disposition during acute COVID-19 illness, cost increases were highest among those admitted to the ICU during acute COVID-19 (+ 1694.6%) but were also apparent among those who were not hospitalized (+ 138.4%) (Table 9). Increases of varying magnitudes were observed across all measures of healthcare costs and across all cohorts.
Table 8
Medical costs during the baseline and post-acute phasesa in the overall population (N = 3792)
Cost description
Baseline phase
Post-acute phase
Change from baseline to post-acute phase,
Δ (% change)
Inpatient visits
 Total cost
337,095
3,531,778
3,194,684 (947.7)
 Standard costs, patient n
21
94
 
  Mean ± SD
16,052 ± 9903
37,572 ± 44,018
21,520 (134.1)
  Median (Q1; Q3)
14,335 (11,150; 20,114)
17,503 (11,376; 45,755)
3169 (22.1)
 Nonzero costs, patient n
21
91
70 (333.3)
  Mean ± SD
160,052 ± 9903
38,811 ± 44,199
22,759 (141.8)
  Median (Q1; Q3)
14,335 (11,150; 20,114)
17,633 (11,786; 53,778)
3298 (23.0)
Readmission
 Total cost
0
1,295,928
1,295,928 (NC)
 Standard costs, patient n
0
23
 
  Mean ± SD
NC
56,345 ± 51,072
56,345 (NC)
  Median (Q1; Q3)
NC
38,770 (14,209; 100,488)
38,770 (NC)
 Nonzero costs, patient n
0
22
22 (NC)
  Mean ± SD
NC
58,906 ± 50,740
58,906 (NC)
  Median (Q1; Q3)
NC
39,325 (16,802; 100,488)
39,325 (NC)
Outpatient visits
 Total cost
4,701,415
12,257,210
7,555,795 (160.7)
 Standard costs, patient n
3026
3316
 
  Mean ± SD
1554 ± 2609
3696 ± 10,454
2143 (137.9)
  Median (Q1; Q3)
664 (278; 1773)
1371 (511; 3369)
707 (106.6)
 Nonzero costs, patient n
3025
3315
290 (9.6)
  Mean ± SD
1554 ± 2609
3698 ± 10,455
2143 (137.9)
  Median (Q1; Q3)
664 (278; 1773)
1371 (511; 3372)
707 (106.5)
Emergency department visits
 Total cost
778,045
1,088,805
310,760 (39.9)
 Standard costs, patient n
392
471
 
  Mean ± SD
1985 ± 1487
2312 ± 2205
327 (16.5)
  Median (Q1; Q3)
1638 (1057; 2665)
1687 (1074; 2774)
48 (3.0)
 Nonzero costs, patient n
391
471
80 (20.5)
  Mean ± SD
1990 ± 1485
2312 ± 2205
322 (16.2)
  Median (Q1; Q3)
1643 (1061; 2668)
1687 (1074; 2774)
44 (2.7)
Prescription claims
 Total cost
1,227,016
1,620,145
393,129 (32.0)
 Standard costs, patient n
2327
2603
 
  Mean ± SD
527 ± 2081
622 ± 2212
95 (18.0)
  Median (Q1; Q3)
74 (21; 239)
86 (31; 304)
13 (17.6)
 Nonzero costs, patient n
2327
2603
276 (11.9)
  Mean ± SD
527 ± 2081
622 ± 2212
95 (18.0)
  Median (Q1; Q3)
74 (21; 239)
86 (31; 304)
13 (17.6)
All medical costs (outpatient, inpatient, and prescription claims)
 Total cost
6,265,526
17,409,133
11,143,608 (177.9)
 Standard costs, patient n
3215
3430
 
  Mean ± SD
1949 ± 3655
5076 ± 15,425
3127 (160.4)
  Median (Q1; Q3)
768 (286; 2068)
1536 (526; 3921)
767 (99.9)
 Nonzero costs, patient n
3214
3430
216 (6.7)
  Mean ± SD
1949 ± 3655
5076 ± 15,425
3126 (160.4)
  Median (Q1; Q3)
769 (286; 2068)
1536 (526; 3921)
767 (99.7)
NC not calculable, Q1 quartile 1, Q3 quartile 3
Standard cost patient n’s (used to calculate standard mean and median) reflect the number of patients who had any healthcare encounter for the specified outcome (e.g., all patients with ≥ 1 outpatient visit during the specified period). Nonzero cost patient n’s (used to calculate nonzero mean and median) reflect the number of patients who had any costs associated with the specified outcome (e.g., all patients with costs > 0 attributable to outpatient visits)
aAll costs are in US dollars rounded to the nearest dollar. The baseline phase was the 12 months before the index date, and the post-acute phase spanned from 1 to 13 months after the index date
Table 9
Medical costs during the baseline and post-acute phasesa stratified by disposition during acute COVID-19
Cost description
No hospitalization
(n = 3546)
Hospitalization without ICU admission
(n = 164)
ICU admission
(n = 82)
Baseline phase
Post-acute phase
Change from baseline to post-acute phase,
Δ (% change)
Baseline phase
Post-acute phase
Change from baseline to post-acute phase, Δ (% change)
Baseline phase
Post-acute phase
Change from baseline to post-acute phase, Δ (% change)
Inpatient visits
 Total cost
304,291
2,062,445
1,758,153 (577.8)
32,803
486,273
453,469 (1382.4)
0
983,061
983,061 (NC)
 Standard costs, patient n
18
63
 
3
16
 
0
15
 
 Mean ± SD
16,905 ± 9847
32,737 ± 38,912
15,832 (93.7)
10,934 ± 10,516
30,392 ± 28,430
19,458 (177.9)
NC
65,537 ± 65,556
65,537 (NC)
 Median (Q1; Q3)
14,777 (11,159; 20,114)
16,007 (11,786; 44,054)
1229 (8.3)
10,701 (537; 21,566)
27,602 (2506; 49,195)
16,902 (158.0)
NC
40,266 (4928; 120,540)
40,266 (NC)
 Nonzero costs, patient n
18
63
45 (250.0)
3
13
10 (333.3)
0
15
15 (NC)
 Mean ± SD
16,905 ± 9847
32,737 ± 38,912
15,832 (93.7)
10,934 ± 10,516
37,406 ± 26,946
26,471 (242.1)
NC
65,537 ± 65,556
65,537 (NC)
 Median (Q1; Q3)
14,777 (11,159; 20,114)
16,007 (11,786; 44,054)
1229 (8.3)
10,701 (537; 21,566)
38,496 (16,802; 53,778)
27,795 (259.7)
NC
40,266 (4928; 120,540)
40,266 (NC)
Readmission
 Total cost
0
367,979
367,979 (NC)
0
236,797
236,797 (NC)
0
691,151
691,151 (NC)
 Standard costs, patient n
0
7
 
0
7
 
0
9
 
 Mean ± SD
NC
52,568 ± 56,501
52,568 (NC)
NC
33,828 ± 24,414
33,828 (NC)
NC
76,795 ± 58,354
76,795 (NC)
 Median (Q1; Q3)
NC
25,493 (12,064; 125,240)
25,493 (NC)
NC
37,651 (16,802; 53,778)
37,651 (NC)
NC
65,694 (38,770; 118,210)
65,694 (NC)
 Nonzero costs, patient n
0
7
7 (NC)
0
6
6 (NC)
0
9
9 (NC)
 Mean ± SD
NC
52,568 ± 56,501
52,568 (NC)
NC
39,466 ± 21,171
39,466 (NC)
NC
76,795 ± 58,354
76,795 (NC)
 Median (Q1; Q3)
NC
25,493 (12,064; 125,240)
25,493 (NC)
NC
38,766 (17,217; 53,778)
38,766 (NC)
NC
65,694 (38,770; 118,210)
65,694 (NC)
Outpatient visits
 Total cost
4,440,316
10,621,198
6,180,882 (139.2)
186,676
1,180,731
994,056 (532.5)
74,423
455,281
380,857 (511.7)
 Standard costs, patient n
2865
3106
 
113
145
 
48
65
 
 Mean ± SD
1550 ± 2616
3420 ± 8433
1870 (120.6)
1652 ± 2294
8143 ± 29,601
6491 (392.9)
1550 ± 2910
7004 ± 13,389
5454 (351.7)
 Median (Q1; Q3)
667 (280; 1762)
1351 (510; 3300)
684 (102.5)
626 (275; 1962)
1752 (465; 5795)
1126 (180.0)
393 (160; 1229)
1672 (743; 4673)
1279 (325.5)
 Nonzero costs, patient n
2864
3105
241 (8.4)
113
145
32 (28.3)
48
65
17 (35.4)
 Mean ± SD
1550 ± 2617
3421 ± 8434
1870 (120.6)
1652 ± 2294
8143 ± 29,601
6491 (392.9)
1550 ± 2910
7004 ± 13,389
5454 (351.7)
 Median (Q1; Q3)
667 (280; 1764)
1351 (510; 3300)
684 (102.5)
626 (275; 1962)
1752 (465; 5795)
1126 (180.0)
393 (160; 1229)
1672 (743; 4673)
1279 (325.5)
Emergency department visits
 Total cost
708,502
985,099
276,597 (39.0)
48,565
81,825
33,260 (68.5)
20,978
21,880
903 (4.3)
 Standard costs, patient n
356
428
 
27
34
 
9
9
 
 Mean ± SD
1990 ± 1472
2302 ± 2198
311 (15.6)
1799 ± 1419
2407 ± 2466
608 (33.8)
2331 ± 2258
2431 ± 1595
100 (4.3)
 Median (Q1; Q3)
1661 (1064; 2676)
1686 (1080; 2745)
25 (1.5)
1491 (951; 2391)
1581 (724; 3152)
90 (6.1)
1012 (905; 3223)
1991 (1422; 2774)
978 (96.7)
 Nonzero costs, patient n
355
428
73 (20.6)
27
34
7 (25.9)
9
9
0 (0.0)
 Mean ± SD
1996 ± 1470
2302 ± 2198
306 (15.3)
1799 ± 1419
2407 ± 2466
608 (33.8)
2331 ± 2258
2431 ± 1595
100 (4.3)
 Median (Q1; Q3)
1663 (1067; 2684)
1686 (1080; 2745)
22 (1.3)
1491 (951; 2391)
1581 (724; 3152)
90 (6.1)
1012 (905; 3223)
1991 (1422; 2774)
978 (96.7)
Prescription claims
 Total cost
1,169,654
1,417,668
248,013 (21.2)
48,249
141,684
93,435 (193.7)
9112
60,793
51,681 (567.2)
 Standard costs, patient n
2197
2432
 
94
114
 
36
57
 
 Mean ± SD
532 ± 2109
583 ± 2083
51 (9.5)
513 ± 1751
1243 ± 4089
730 (142.1)
253 ± 718
1067 ± 2016
813 (321.4)
 Median (Q1; Q3)
76 (22; 243)
84 (31; 291)
8 (10.1)
46 (16; 171)
131 (35; 628)
84 (181.1)
43 (22.9; 148.5)
139 (55; 760)
95 (219.2)
 Nonzero costs, patient n
2197
2432
235 (10.7)
94
114
20 (21.3)
36
57
21 (58.3)
 Mean ± SD
532 ± 2109
583 ± 2083
51 (9.5)
513 ± 1751
1243 ± 4089
730 (142.1)
253 ± 718
1067 ± 2016
813 (321.4)
 Median (Q1; Q3)
76 (22; 243)
84 (31; 291)
8 (10.1)
46 (16; 171)
131 (35; 628)
84 (181.1)
43 (22.9; 148.5)
139 (55; 760)
95 (219.2)
All medical costs (outpatient, inpatient, and prescription claims)
 Total cost
5,914,262
14,101,310
8,187,048 (138.4)
267,728
1,808,688
1,540,960 (575.6)
83,535
1,499,135
1,415,600 (1694.6)
 Standard costs, patient n
3034
3211
 
128
152
 
53
67
 
 Mean ± SD
1949 ± 3668
4392 ± 11,640
2442 (125.3)
2092 ± 3625
11,899 ± 35,146
9808 (468.9)
1576 ± 2890
22,375 ± 50,108
20,799 (1319.6)
 Median (Q1; Q3)
776 (288; 2068)
1510 (521; 3792)
734 (94.5)
626 (235; 2050)
1990 (439; 7527)
1364 (218.0)
379 (161; 1213)
2264 (940; 9140)
1885 (497.8)
 Nonzero costs, patient n
3033
3211
178 (5.9)
128
152
24 (18.8)
53
67
14 (26.4)
 Mean ± SD
1950 ± 3669
4392 ± 11,640
2442 (125.2)
2092 ± 3625
11,899 ± 35,146
9808 (468.9)
1576 ± 2890
22,375 ± 50,108
20,799 (1319.6)
 Median (Q1; Q3)
776 (289; 2068)
1510 (521; 3792)
734 (94.5)
626 (235; 2050)
1990 (439; 7527)
1364 (218.0)
379 (161; 1213)
2264 (940; 9140)
1885 (497.8)
ICU intensive care unit, NC not calculable, Q1 quartile 1, Q3 quartile 3
Standard cost patient n’s (used to calculate standard mean and median) reflect the number of patients who had any healthcare encounter for the specified outcome (e.g., all patients with ≥ 1 outpatient visit during the specified period). Nonzero cost patient n’s (used to calculate nonzero mean and median) reflect the number of patients who had any costs associated with the specified outcome (e.g., all patients with costs > 0 attributable to outpatient visits)
aAll costs are in US dollars rounded to the nearest dollar. The baseline phase was the 12 months before the index date, and the post-acute phase spanned from 1 to 13 months after the index date
Matching the trends in healthcare utilization (Table 5), the greatest cost increases were associated with inpatient hospitalizations, including readmissions within 30 days of hospital discharge (Table 8). Smaller but substantial increases were associated with outpatient visits, including ED visits, and prescription claims. With the exception of ED visit costs, all cost increases were greatest among those admitted to the ICU during acute COVID-19 (Table 9).

Discussion

This retrospective analysis of adults aged < 65 years without any underlying high-risk conditions identified increases in diagnoses, medical prescriptions, healthcare utilization events, and associated costs during the year after the acute phase of COVID-19. As observed previously [10] and in our companion manuscript regarding high-risk patients [20], those who were hospitalized with or without ICU admission during the acute phase had the greatest increase in comorbidities and healthcare resource utilization burden. However, the burden was apparent across all 3 cohorts, including those who were not hospitalized for COVID-19.
Many of the changes observed in this cohort were similar to observations among high-risk patients [20]. Most notably, the greatest increase in both studies was in the percentages of patients with blood-related diseases, which has been identified previously as a feature of post-COVID conditions [21]. In the present study, new diagnoses of blood disorders increased by > 150% during the post-acute phase compared with baseline, even among the cohort of patients who were not hospitalized during the acute phase of illness. New diagnoses of neurological and psychiatric diseases also increased in the year following acute COVID-19 in both patients with and without any risk factors for severe COVID-19, regardless of the level of care setting during the acute phase of illness, which is consistent with previous reports of long-term COVID-19 sequelae [22, 23]. We observed a 27% decrease in respiratory disease during the post-acute phase; similar to results from the high-risk population, this decrease reflected a large increase in chronic lower respiratory diseases that was outweighed by a combination of smaller decreases in acute upper and lower respiratory infections, influenza, and pneumonia. Distinct from observations in high-risk patients, analysis of the cohort described here also revealed a 123% increase in endocrine, nutritional, and metabolic diseases and a 76% increase in diseases of the digestive system.
The analysis of medication use demonstrated the greatest increase in hormone prescriptions, including primarily injectable, oral, and topical glucocorticoids and corticoids (e.g., prednisone, methylprednisolone, and dexamethasone). These medications were typically not prescribed during the baseline phase and were likely being used for the treatment of persistent COVID-19 symptoms, such as joint stiffness and muscle pain [24]. Increases in hormone use were followed by vascular and musculoskeletal agents, and increases across the 3 classes of medications were observed across all levels of care during acute COVID-19. Those results were unique to this population and not observed among high-risk patients [20]. However, when the analysis was conducted including medication classes prescribed to < 2% of the baseline population, a 277% increase in hemostatic modifier prescriptions and a 106% increase in blood factor prescriptions were identified, consistent with results of the same analysis among high-risk patients. It is logical that several of the medication classes prescribed to ≥ 2% of the baseline population in the high-risk patient cohort were prescribed to < 2% of the baseline population in the cohort evaluated here because these patients were overall younger and healthier at baseline.
Healthcare resource utilization and costs were higher during the post-acute phase compared with the baseline phase for all evaluated measures, including outpatient visits, ED visits, inpatient visits and LOS, ICU admission and LOS, 30-day readmissions, and prescriptions. The likelihood of patients being discharged to another hospital department or long-term care facility also increased. The most striking cost changes were observed across measures related to inpatient resources, including an overall increase in inpatient visit costs of nearly 950% in the post-acute phase and resulting in a 178% increase in total medical costs in the overall population.
Cost increases varied in magnitude but were observed for every healthcare outcome across all categories of the acute COVID-19 level of care. Even among those who were not hospitalized during the acute phase of COVID-19, inpatient visit costs during the post-acute phase increased by 578%, outpatient visit costs increased by 139%, and total medical costs increased by 138%. This trend was similar to observations made in the cohort of high-risk patients [20] but was a more surprising result given that the patients in the cohort described here were aged < 65 years and lacked any comorbid conditions placing them at risk of severe COVID-19.
Taken together, health and healthcare resource use results suggest that the risk factors associated with developing post-COVID conditions may be distinct from the risk factors that predict severity of acute disease. Similarly to how biomarkers have been characterized to predict the course of acute COVID-19 [25], there may be a unique set of biomarkers associated with the development of long-term adverse health outcomes. One recent study identified biomarkers associated with vascular transformation among long-COVID patients [26], which is consistent with findings in our present study and companion report regarding a high prevalence of blood-related diseases in the post-acute phase. Importantly, regardless of the mechanisms involved, results indicate that the health and economic impacts of COVID-19 may extend beyond the acute phase of illness even among the wide swath of the population that is relatively young and healthy and has mild symptoms upon infection.
Although limited data are available on strategies to reduce the risk of post-COVID conditions, vaccination against COVID-19 appears to be protective. In a recent prospective study from Antonelli and colleagues [27], fully vaccinated adults with breakthrough infections were less likely than unvaccinated controls to experience symptoms of COVID-19 lasting ≥ 28 days; the effect was observed among both older adults and adults aged < 60 years. In a retrospective cohort study from Taquet and colleagues [28], vaccination among adults who contracted COVID-19 was associated with steep reductions in risk of several long-term adverse health outcomes. Although authors of the Taquet study did not find COVID-19 vaccination to be associated with reduced risk of what they termed “long COVID features” (a collection of specific abdominal, respiratory, psychiatric, and pain-related symptoms), they did identify significantly lower risk of many of the diagnoses discussed in the present report, including blood disorders, muscle disease, certain neurological conditions, and chronic respiratory conditions. Because these outcomes were measured over a 6-month period after infection, they included diagnoses during both the acute and post-acute phases. Highlighting the importance of vaccination even among those not in a high-risk group, protective effects of vaccination against many post-acute sequelae were most robust among individuals aged < 60 years.
Recently, emerging data have also suggested that antiviral treatment for COVID-19, such as nirmatrelvir/ritonavir (Paxlovid®, Pfizer Inc, New York, NY, USA), may reduce the likelihood of developing PASC. In a large study of patients from the Veterans Affairs database [29], authors found that individuals prescribed nirmatrelvir-ritonavir during the acute phase of COVID-19 had reduced risks of prespecified sequelae (including cardiovascular, hematologic, and neurologic disorders), post-acute hospitalization, and post-acute death, regardless of vaccination status. A small case series has furthermore suggested that nirmatrelvir administered during the post-acute phase may alleviate long-term symptom burden [30], although more systematic study of these effects is warranted before conclusions can be drawn.
Our study had several strengths. Primarily, having all patients serve as their own control inherently adjusted for potential confounders, such as demographics and health-seeking behavior. To our knowledge, this was also the first study that evaluated the economic impact of post-acute COVID-19 in adults who were < 65 years of age and had no underlying comorbidities placing them at risk of severe acute COVID-19. The ability to pair these broad, descriptive data with the identical analysis in a cohort of adults with high-risk conditions [20] is of significant value in understanding differences between characteristics that predict acute versus post-acute COVID-19 outcomes. A limitation of our study was that the cohort was confined to individuals with commercial insurance; all enrolled participants were also diagnosed early in the pandemic and survived the acute phase of COVID-19. Additionally, there was no method of confirming that any adverse health outcomes reported here were related to COVID-19. There was also a possibility for incomplete data capture owing to nonbillable diagnoses, and our results may have been influenced by surveillance bias, whereby contracting COVID-19 led to higher medical scrutiny following diagnosis. Finally, the study was conducted in a period before vaccination and previous SARS-CoV-2 infection and before the emergence of SARs-CoV-2 variants of concern. Such factors could limit the generalizability of the findings to the present. Baseline assessments were also performed in the prepandemic period; whereas post-acute COVID-19 assessments were performed during a public health emergency in which healthcare practices could have changed. Thus, clinical burden and health costs during the post-acute COVID-19 period may have been impacted by altered heathcare practices.

Conclusion

Our data suggest that the health and economic burden of COVID-19 stretches well beyond the acute phase of illness, even among younger individuals without preexisting conditions whose acute infection did not merit hospitalization. Understanding the nature and extent of post-COVID conditions, as well as the unique populations at risk, is critical to evaluating the true societal cost–benefit of interventions such as COVID-19 vaccination and treatment.

Acknowledgements

The authors would like to thank Farid Khan, Manuela di Fusco, Leah McGrath, Deepa Malhotra, Jennifer Nguyen, and Jessica E. Atwell of Pfizer Inc for their support in the study design and their contributions to this paper. Programming support and expertise were provided by Klaudia Niezabitowska and Kirsten Astbury of Quanticate. Editorial/medical writing support was provided by Anna Stern, PhD, of ICON (Blue Bell, PA, USA), and was funded by Pfizer Inc.

Declarations

This study was considered exempt from review and the need for informed consent by Sterling institutional review board due to the use of de-identified data.
Not applicable.

Competing interests

AS, WA, RC, MR, MB, FD, and JA are employees of Pfizer Inc and may hold stock or stock options. TM is an employee of Quanticate, which receives consulting fees from Pfizer Inc.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creativecommons.​org/​licenses/​by/​4.​0/​. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Metadaten
Titel
Substantial health and economic burden of COVID-19 during the year after acute illness among US adults not at high risk of severe COVID-19
verfasst von
Amie Scott
Wajeeha Ansari
Richard Chambers
Maya Reimbaeva
Tomasz Mikolajczyk
Michael Benigno
Florin Draica
Joanna Atkinson
Publikationsdatum
01.12.2024
Verlag
BioMed Central
Erschienen in
BMC Medicine / Ausgabe 1/2024
Elektronische ISSN: 1741-7015
DOI
https://doi.org/10.1186/s12916-023-03235-5

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Extreme Arbeitsverdichtung und kaum Supervision: Dr. Andrea Martini, Sprecherin des Bündnisses Junge Ärztinnen und Ärzte (BJÄ) über den Frust des ärztlichen Nachwuchses und die Vorteile des Rucksack-Modells.

„Restriktion auf vier Wochen Therapie bei Schlaflosigkeit ist absurd!“

06.05.2024 Insomnie Nachrichten

Chronische Insomnie als eigenständiges Krankheitsbild ernst nehmen und adäquat nach dem aktuellen Forschungsstand behandeln: Das forderte der Schlafmediziner Dr. Dieter Kunz von der Berliner Charité beim Praxis Update.

GLP-1-Rezeptoragonisten und SGLT-2-Hemmer: zusammen besser

06.05.2024 Typ-2-Diabetes Nachrichten

Immer häufiger wird ein Typ-2-Diabetes sowohl mit einem GLP-1-Rezeptor-Agonisten als auch mit einem SGLT-2-Inhibitor behandelt. Wie sich das verglichen mit den Einzeltherapien auf kardiovaskuläre und renale Komplikationen auswirkt, wurde anhand von Praxisdaten aus Großbritannien untersucht.

Männern mit Zystitis Schmalband-Antibiotika verordnen

03.05.2024 Zystitis Nachrichten

Die akute Zystitis von Männern und ihre Therapie sind wenig erforscht. Norwegische Forscher haben das nachgeholt. Ihr Rat: Erst einmal keine Breitbandantibiotika verordnen.

Update Allgemeinmedizin

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