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J Inflamm Dis

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Modeling the Impact of Factors Associated with Delay in Healthcare Seeking on the Survival of Hospitalized Patients with COVID-19

Author(s):
Abuzar ShiraziAbuzar Shirazi1, Ali DianatiAli Dianati2, Mehrdad HayatiMehrdad Hayati3, Abdollah Mohammadian-HafshejaniAbdollah Mohammadian-Hafshejani4, Soleiman KheiriSoleiman KheiriSoleiman Kheiri ORCID4, Masoumeh Sadat MousaviMasoumeh Sadat MousaviMasoumeh Sadat Mousavi ORCID5,*
1Department of Epidemiology and Biostatistics, School of Public Health, Shahrekord University of Medical Sciences, Shahrekord, Iran
2Trauma Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
3Instructor of Medical Surgical Nursing, Shiraz University of Medical Sciences, Shiraz, Iran
4Department of Epidemiology and Biostatistics, Modeling in Health Research Center, School of Health, Shahrekord University of Medical Sciences, Shahrekord, Iran
5Department of Public Health, Faculty of Science, Eghlid Branch, Islamic Azad University, Eghlid, Iran

Journal of Inflammatory Diseases:Vol. 29, issue 1; e160511
Published online:Mar 31, 2025
Article type:Research Article
Received:Feb 10, 2025
Accepted:Mar 25, 2025
How to Cite:Shirazi A, Dianati A, Hayati M, Mohammadian-Hafshejani A, Kheiri S, et al. Modeling the Impact of Factors Associated with Delay in Healthcare Seeking on the Survival of Hospitalized Patients with COVID-19.J Inflamm Dis.2025;29(1):e160511.https://doi.org/10.69107/jid-160511.

Abstract

Background:

The delay between the onset of initial symptoms and hospitalization is a critical issue in the context of COVID-19 awareness.

Objectives:

This study aims to identify the factors influencing the delay in healthcare-seeking among hospitalized patients with COVID-19 in Chaharmahal and Bakhtiari province.

Methods:

This cross-sectional analytical study was conducted on all patients hospitalized from 2020 to 2022 in Chaharmahal and Bakhtiari province. Chi-square tests, t-tests, and logistic regression were used to establish the relationship between referral delay and various variables.

Results:

This study was conducted on 38,124 patients hospitalized with COVID-19 in Chaharmahal and Bakhtiari, with an average age of 25.27 ± 49.61 years. The mean duration of hospitalization and patient care was 4.67 ± 4.33 days. The average delay in seeking healthcare was 3.68 ± 3.67 days, and 75.6% of the cases with delay sought care at health and treatment centers. Those who experienced a delay in seeking care [2.09 (1.98 - 2.20, P = 0.01)] were more likely to be hospitalized. Individuals with a history of hypertension [2.46 (2.25 - 2.67, P = 0.001)] and diabetes [1.13 (1.05 - 1.22, P = 0.001)] had a higher chance of delay compared to their respective counterparts. Those with a positive lung scan [8.25 (7.59 - 8.97, P = 0.001)] had a higher chance of delay, and patients with abnormal radiological findings [3.18 (2.86 - 3.54, P = 0.001)] were more likely to experience a delay in seeking care.

Conclusions:

Delay in seeking care at healthcare centers during COVID-19 infection depends on gender, place of residence, occupation, individuals' history of chronic disease, and other demographic variables, as well as the onset of initial disease symptoms.

1. Background

Timely patient referral to healthcare centers plays a crucial role in promoting rapid recovery, reducing mortality rates, and mitigating disease-related complications (1). A delay in diagnosing patients is associated with an increase in secondary complications resulting from exposure to the index case (2). Moreover, delayed diagnosis can lead to treatment complexities and, ultimately, patient mortality (3). Such delays may stem from postponed patient referral, which includes the period between the onset of symptoms and the patient’s first visit to a healthcare facility or physician (4). A study conducted in Italy on children with COVID-19 who experienced delayed emergency care revealed that half of these patients were admitted to the ICU, and 33.3% succumbed to the disease (5). Additionally, research indicates that a prolonged interval between symptom onset and hospital admission exacerbates disease severity and increases mortality rates, particularly among the elderly (6). An investigation into the causes of delayed emergency care for seven critically ill children found that a major contributing factor was parental fear of entering healthcare facilities or contracting the coronavirus during the visit, which significantly delayed the reporting of severe patient conditions (7). Early and accurate diagnosis of COVID-19 is essential for its effective management. Therefore, understanding the causes and consequences of delays in patient referral and diagnosis can aid in improving both prevention and treatment strategies.

Despite numerous studies addressing the factors influencing delays in seeking medical care, notable research gaps persist. One of the most significant is the lack of a comprehensive and systematic analysis of the social, cultural, and economic factors influencing delays in care-seeking behavior (3, 8). Furthermore, prior research has predominantly focused on developed countries or communities with adequate access to healthcare services. In contrast, there is limited data concerning underserved populations or developing nations. The impact of healthcare infrastructure, economic barriers such as treatment costs and insurance, and the influence of quarantine policies and social restrictions have also been underexplored (9-11).

2. Objectives

This study aims to examine the factors associated with delays in the referral of hospitalized COVID-19 patients and the consequent mortality.

3. Methods

This cross-sectional analytical study was conducted on 38,124 patients hospitalized in hospitals across Chaharmahal and Bakhtiari province from 2020 to 2022. Duplicate and overlapping data were removed using Excel software and patients’ national identification codes. To determine the referral delay, the number of days between the onset of symptoms and the first visit to a doctor or healthcare center was calculated. In the case of asymptomatic COVID-19 patients, the delay was calculated based on the interval between the date of contact with a confirmed positive case and the date of referral to a doctor or healthcare center. Data analysis was carried out using SPSS version 16 and STATA software. Chi-square tests, t-tests, and logistic regression were employed to assess the relationship between referral delay and various variables.

4. Results

The mean duration of hospitalization and patient care was 4.67 ± 4.33 days. The average delay in referral was 3.68 ± 3.67 days, with 75.6% of patients experiencing delays in seeking care at health and treatment centers (Table 1). A total of 4,059 patients (10.6%) had abnormal radiological findings, and 21,423 patients (56.2%) had blood oxygen levels below 93. Overall, the disease outcome resulted in death for 3,209 patients (8.4%) (Table 2). After adjustment, the odds for intubated patients decreased by 27-fold, while for those who were ventilated, the odds increased by 3.07-fold. It was also observed that with an increase in the duration of hospitalization, the odds of delay increased by 1.22 in the unadjusted (raw) model and by 2.09 in the adjusted model (Table 3).

Table 1.Frequency of Delay in Referral Based on Demographic Variables a,b
VariablesTotal FrequencyWithout Delay FrequencyDelayed FrequencyP-Value
Gender0.001
Male18731 (49.1)4729 (25.2)14002 (74.8)
Female19393 (50.9)4570 (23.6)14823 (76.4)
Habitat0.001
Urban32489 (85.2)8224 (25.3)24265 (74.7)
Rural5635 (14.8)1075 (19.1)4560 (80.9)
Job0.001
Free5440 (14.3)1491 (27.4)3949 (72.6)
Retired5891 (15.5)1446 (24.5)4445 (75.5)
Unemployed/student/soldier1190 (3.1)503 (42.3)687 (57.7)
Housewife 8545 (22.4)2040 (23.9)6505 (76.1)
Child/student5750 (15.1)1300 (22.6)4450 (77.4)
Healthcare workers/government employee620 (1.6)287 (46.3)333 (53.7)
Farmer/rancher57 (0.1)35 (61.4)22 (38.6)
Other 10631 (27.9)2197 (20.7)8434 (79.3)
Age0.001
< 18 5750 (15.1)1300 (22.6)4450 (77.4)
18 - 292481 (6.5)658 (26.5)1823 (73.5)
29 - 5914314 (37.5)3353 (23.4)10961 (76.6)
> 5915579 (40.9)3988 (25.6)11591 (74.4)
Smoking0.001
Yes501 (1.3)27 (5.4)474 (94.6)
No37623 (98.7)9272 (24.6)28351 (75.4)
Opioid use0.001
yes606 (1.6)24 (4)582 (96)
No37518 (98.4)9275 (24.7)28243 (75.3)
Corona vaccine injection 0.001
Yes6221 (16.3)596 (9.6)5625 (90.4)
No31903 (83.7)8703 (27.3)23200 (72.7)
Pregnancy0.001
Yes621 (7.7)120 (19.3)501(80.7)
No7450 (92.3)1778 (23.9)5672 (76.1)
Cancer0.3
Yes793 (2.1)181 (22.8)612 (77.2)
No37331 (97.9)9118 (24.4)28213 (75.6)
Lung disease0.17
Yes2801 (7.3)713 (25.5)2088 (74.5)
No35323 (92.7)8586 (24.3)26737 (75.7)
Hypertension0.001
Yes5334 (14)676 (12.7)4658 (87.3)
No32790 (86)8623 (26.3)24167 (73.7)
Diabetes0.001
Yes4512 (11.8)1012 (22.4)3500 (77.6)
No33612 (88.2)8287 (24.7)25325 (75.3)
Cardiovascular disease0.1
Yes7417 (19.5)1755 (23.7)5662 (76.3)
No30707 (80.5)7544 (24.6)23163 (75.4)
Other chronic diseases0.001
Yes4205 (11)1389 (33)2816 (67)
No33919 (89)7910 (23.3)26009 (76.7)
Age (y)49.61 ± 25.2750.65 ± 25.2149.27 ± 25.280.001
Hospitalization period (d)4.33 ± 4.672.66 ± 4.694.49 ± 4.640.001
Delay in referral (d)3.67 ± 3.68---

Frequency of Delay in Referral Based on Demographic Variables a,b

Table 2.Frequency of Delay in Referral Based on Symptoms and Outcome of the Disease a
VariablesTotal FrequencyWithout Delay FrequencyDelayed FrequencyP-Value
Lab result0.001
Positive16568 (43.5)3840 (23.2)12728 (76.8)
Negative21104 (55.3)5306 (25.1)15798 (74.9)
Further investigation is needed452 (1.2)153 (33.8)299 (66.2)
Disease classification0.001
Confirmed16150 (42.4)3913 (24.2)12237 (75.8)
Suspected21436 (56.2)5112 (23.8)16324 (76.2)
Probable538 (1.4)274 (50.9)264 (49.1)
Hospitalization in ICU0.001
Yes2319 (6.1)418 (18)1901 (82)
No35805 (93.9)8881 (24.8)26924 (75.2)
Shivering0.001
Yes12242 (32.1)1079 (8.8)11163 (91.2)
No25882 (67.9)8220 (31.8)17662 (68.2)
Body pain0.001
Yes15840 (41.5)2622 (16.6)13218 (83.4)
No22284 (58.5)6677 (30)15607 (70)
Test disorder0.001
Yes549 (1.4)75 (13.7)474 (86.3)
No37575 (98.6)9224 (24.5)28351 (75.5)
Abnormal finding radiology0.001
Yes4059 (10.6)405 (10)3654 (90)
No34065 (89.4)8894 (26.1)25171 (73.9)
Cough0.001
Yes21455 (56.3)4306(20.1)17149(79.9)
No16669 (43.7)4993(30)11676(70)
Diarrhea0.001
Yes 2711 (7.1)554 (20.4)2157 (79.6)
No35413 (92.9)8745 (24.7)26668 (75.3)
Hard breath0.001
Yes23529 (61.7)4683 (19.9)18846 (80.1)
No14595 (38.3)4616 (31.6)9979 (68.4)
Headache0.001
Yes7666 (20.1)1441 (18.8)6225 (81.2)
No30458 (79.9)7858 (25.8)22600 (74.2)
Sore throat0.001
Yes5288 (13.9)1192 (22.5)4096 (77.5)
No32836 (86.1)8107 (24.7)24729 (75.3)
Lung scan0.001
Has symptoms11673 (30.6)649 (5.6)11024 (94.4)
No symptoms26451 (69.4)8650 (32.7)17801 (67.3)
Intubation0.001
Yes1590 (4.2)108 (6.8)1482 (93.2)
No36534 (95.8)9191 (25.2)27343 (74.8)
Using ventilator 0.001
Yes2096 (5.5)414 (19.8)1682 (80.2)
No36028 (94.5)8885 (24.7)27143 (75.3)
Blood oxygen level0.001
> 938780 (23)432 (4.9)8348 (95.1)
< 9321423 (56.2)946 (4.4)20477 (95.6)
Unknown7921 (20.8)921 (100)0
Fever0.001
No fever14749 (38.7)2433 (16.5)12316 (83.5)
Mild fever18505 (87.2)4056 (21.9)14449 (78.1)
High fever434 (1.1)109 (25.1)325 (74.9)
Unknown4436 (11.6)2701 (60.9)1735 (39.1)
Outcome0.001
Death3060 (8)1004 (32.8)2056 (67.2)
Recovery34915 (92)8259 (23.7)26656 (76.3)

Frequency of Delay in Referral Based on Symptoms and Outcome of the Disease a

Table 3.Modeling Factors Associated with Delay in Seeking Medical Care
VariablesCrudeAdjusted
OR (95% CI)P-ValueOR (95% CI)P-Value
Gender
Female a----
Male0.91 (0.87 - 0.96)0.0010.86 (0.73 - 1)0.06
Habitat
Rural a----
Urban0.69 (0.65 - 0.75)0.0011.16 (0.99 - 1.36)0.05
Job
Free a----
Retired1.16 (1.07 - 1.26)0.0011.01 (0.79 - 1.29)0.92
Unemployed/student/soldier0.52 (0.45 - 0.59)0.0011.12 (0.84 - 1.48)0.44
Housewife1.20 (1.11 - 1.30)0.0010.80 (0.64 - 1.02)0.07
Child/student1.29 (1.18 - 1.41)0.0011.02 (0.65 - 1.59)0.93
Healthcare workers/government employee0.44 (0.37 - 0.52)0.0010.89 (0.50 - 1.60)0.71
Farmer/rancher0.24 (0.14 - 0.41)0.0010.24 (0.06 - 0.89)0.03
Other1.45 (1.34 - 1.56)0.0010.89 (0.74 - 1.09)0.3
Age
< 18 a----
18 - 290.81 (0.73 - 0.90)0.0010.72 (0.53 - 0.98)0.04
29 - 590.95 (0.89 - 1.03)0.220.85 (0.71 - 1.02)0.07
< 590.85 (0.79 - 0.91)0.001
Smoking
No a----
Yes5.74 (3.89 - 8.47)0.0010.71 (0.44 - 1.16)0.18
Opioid use
No a----
Yes7.96 (5.29 - 11.99)0.0011.32 (0.79 - 2.17)0.3
Corona vaccine injection
No a----
Yes3.54 (3.24 - 3.87)0.0011.04 (0.89 - 1.21)0.64
Pregnancy
No a----
Yes1.35 (1.10 - 1.65)0.0031.03 (0.83 - 1.27)0.8
Cancer
No a----
Yes1.09 (0.92 - 1.29)0.3
Lungdisease
No a----
Yes0.94 (0.86 - 1.03)0.170.66 (0.54 - 0.81)0.001
Hypertension
No a----
Yes2.46 (2.26 - 2.67)0.0010.81 (0.68 - 0.96)0.02
Diabetic
No a----
Yes1.13 (1.05 - 1.22)0.0010.85 (0.71 - 1.02)0.08
Cardiovasculardisease
No a----
Yes1.05 (0.99 - 1.15)0.101.13 (0.95 - 1.34)0.16
Other chronic diseases
No a----
Yes0.62 (0.57 - 0.66)0.0011.08 (0.88 - 1.33)0.46
Lab result
Negative a----
Positive1.13 (1.06 - 1.17)0.0010.71 (0.51 - 0.97)0.03
Further investigation is needed0.66 (0.54 - 0.80)0.0010.88 (0.51 - 1.53)0.66
Disease classification
Probable a----
Suspected3.31 (2.79 - 3.94)0.0010.44 (0.17 - 1.11)0.08
Confirmed3.24 (2.73 - 3.85)0.0010.55 (0.21 - 1.42)0.21
Outcome
Death a----
Recovery1.57 (1.46 - 1.71)0.0010.87 (0.67 - 1.13)0.31
Hospitalization in ICU
No a----
Yes1.5 (1.35 - 1.67)0.0010.54 (0.43 - 0.67)0.001
Shivering
No a----
YES4.81 (4.5 - 5.15)0.0010.9 (0.79 - 1.02)0.1
Body pain
No a----
Yes2.16 (2.05 - 2.27)0.0011.31 (1.16 - 1.47)0.001
Taste disorder
No a----
Yes2.06 (1.61 - 2.62)0.0010.86 (0.57 - 1.29)0.46
Abnormal finding radiology
No a----
Yes3.18 (2.87 - 3.54)0.0010.56(0.48 - 0.66)0.001
Cough
No a----
Yes1.7 (1.62 - 1.78)0.0011.04 (0.92 - 1.17)0.56
Diarrhea
No a----
Yes1.28 (1.16 - 1.41)0.0010.92 (0.73 - 1.14)0.43
Hard breath
No a----
Yes1.86 (1.77 - 1.95)0.0010.93 (0.82 - 1.06)0.26
Headache
No a----
Yes1.50 (1.41 - 1.59)0.0011.04 (0.91 - 1.19)0.56
Sore throat
No a----
Yes1.13 (1.05 - 1.21)0.0010.96 (0.81 - 1.13)0.61
Lung scan
No symptoms a----
Have symptoms8.25 (7.59 - 8.97)0.0010.82 (0.73 - 0.94)0.003
Intubation
No a----
Yes4.61 (3.78 - 5.62)0.0010.26 (0.16 - 0.42)0.001
Using ventilator
No a----
Yes1.33 (1.19 - 1.48)0.0013.18 (1.93 - 5.26)0.001
Blood oxygen level
> 93 a----
< 931.12 (.99 - 1.26)0.061.05 (0.93 - 1.19)0.43
Unknown00
Fever
No fever a----
Mild fever0.7 (0.66 - 0.74)0.0011.01 (0.89 - 1.14)0.93
High fever0.59 (0.47 - 0.73)0.0010.77 (0.42 - 1.41)0.39
Unknown0.13 (0.12 - 0.14)0.0010.01 (0.002 - 0.11)0.001
Period time hospitalization
Day a1.22 (1.19 - 1.24)0.0012.14 (2.02 - 2.25)0.001

Modeling Factors Associated with Delay in Seeking Medical Care

5. Discussion

Our study results showed that patients admitted to intensive care units experienced greater delays in seeking medical care. This finding is consistent with results from Italy, where children who experienced delayed medical care had higher rates of admission to intensive care units and significantly elevated mortality rates (5). Our results also demonstrated that individuals who presented with symptoms such as body aches, chills, taste disturbances, cough, diarrhea, headache, shortness of breath, sore throat, and fever were more likely to experience delays in seeking care. These symptoms are consistent with common manifestations of COVID-19, and a study conducted in Brazil found that individuals presenting with such symptoms were less likely to seek immediate healthcare services.

The findings of our study indicated that urban residents had a lower likelihood of experiencing delayed medical care compared to rural residents. This disparity could be attributed to better transportation options, increased accessibility to healthcare facilities, and potentially superior financial resources among urban populations (12). Numerous studies have consistently demonstrated that delays in seeking medical care are more prevalent in rural regions and in areas located further from healthcare services, which aligns with the results of our study (13).

Furthermore, our study indicated that patients hospitalized in special care units experienced longer delays in seeking medical care. This supports findings from Italy, where children with delayed medical attention had higher intensive care unit admission rates and a significantly increased mortality rate (5). Our findings also emphasized that individuals exhibiting symptoms such as body pain, shivering, taste disorders, cough, diarrhea, headache, shortness of breath, sore throat, and fever had a higher probability of delay. These symptoms reflect typical clinical features of COVID-19, and supporting evidence from a Brazilian study showed that individuals with these symptoms were less inclined to seek prompt healthcare services (14).

Patients with lower blood oxygen levels (below 93) also exhibited a higher likelihood of delayed medical care. Various studies have identified hypoxia as a significant factor contributing to delays in medical care and increased mortality among COVID-19 patients (12, 15, 16).

Patients with a history of hypertension and diabetes showed a higher probability of delayed medical care. This finding aligns with other studies demonstrating that individuals with chronic conditions are more likely to hesitate in seeking medical attention, resulting in increased disease severity and higher mortality rates from COVID-19 (17-19).

The study also indicated that delays in seeking medical care were less common among middle-aged and elderly individuals compared to younger individuals. This contradicts findings from a study conducted in Tehran, which reported that delays increased with age. This discrepancy may reflect variations in healthcare-seeking behavior across different populations (7, 20).

One of the key factors influencing delays in seeking medical care is hospital capacity and the availability of hospital beds. In many regions, hospitals faced a sudden influx of COVID-19 patients, leading to capacity saturation and a reduced ability to admit new patients. This situation caused some individuals to postpone seeking care due to concerns about receiving inadequate services or facing overcrowded conditions in hospitals (21, 22).

Additionally, the availability of COVID-19 diagnostic tests plays a crucial role in patients’ decisions to seek medical care. In areas where diagnostic tests are limited or where test results are delayed, patients may face uncertainty in obtaining a definitive diagnosis. This can lead to postponement in their decision to visit healthcare facilities (21, 23).

The inefficiency of healthcare systems is another significant factor contributing to delays in seeking care. Inefficient healthcare systems — characterized by a shortage of medical personnel, poor resource management, and a lack of coordination among healthcare facilities — can increase patient waiting times and discourage timely visits. Furthermore, the absence of an effective referral system may compel patients to move between different healthcare centers, thereby further delaying necessary medical attention (21, 22, 24).

In summary, enhancing hospital capacity, increasing access to diagnostic testing, and improving the efficiency of healthcare systems can play a crucial role in reducing delays in seeking care among COVID-19 patients. These improvements can ultimately lead to more effective disease management at the community level (25).

5.1. Conclusions

Delay in seeking care at healthcare centers during COVID-19 infection is influenced by gender, place of residence, occupation, history of chronic diseases, and other demographic variables, as well as the timing of initial symptom onset. This study underscores the critical importance of prompt healthcare-seeking behavior. Recommendations derived from this study include the development of awareness programs to educate the public about disease symptoms and the enhancement of equitable access to healthcare services for all segments of the population.

Footnotes

References

  • 1.
    Mishra K, Locci-Molina NC, Chauhan B, Raker CA, Sung VW. Delay in Seeking Care for Pelvic Floor Disorders Among Caregivers. Female Pelvic Med Reconstr Surg. 2020;26(7):458-63. [PubMed ID: 30045052]. https://doi.org/10.1097/SPV.0000000000000609.
  • 2.
    Wei Y, Mi F, Cui Y, Li Y, Wu X, Guo H. Delay in seeking medical care after the onset of symptoms in patients with sight-threatening diabetic retinopathy. J Int Med Res. 2021;49(5):3000605211013220. [PubMed ID: 34013762]. [PubMed Central ID: PMC8150428]. https://doi.org/10.1177/03000605211013224.
  • 3.
    Goyal M, Singh P, Singh K, Shekhar S, Agrawal N, Misra S. The effect of the COVID-19 pandemic on maternal health due to delay in seeking health care: Experience from a tertiary center. Int J Gynaecol Obstet. 2021;152(2):231-5. [PubMed ID: 33128794]. [PubMed Central ID: PMC9087665]. https://doi.org/10.1002/ijgo.13457.
  • 4.
    Wang Z, Tang Y, Cui Y, Guan H, Cui X, Liu Y, et al. Delay in seeking health care from community residents during a time with low prevalence of COVID-19: A cross-sectional national survey in China. Front Public Health. 2023;11:1100715. [PubMed ID: 36895687]. [PubMed Central ID: PMC9989024]. https://doi.org/10.3389/fpubh.2023.1100715.
  • 5.
    Lazzerini M, Barbi E, Apicella A, Marchetti F, Cardinale F, Trobia G. Delayed access or provision of care in Italy resulting from fear of COVID-19. Lancet Child Adolesc Health. 2020;4(5):e10-1. [PubMed ID: 32278365]. [PubMed Central ID: PMC7146704]. https://doi.org/10.1016/S2352-4642(20)30108-5.
  • 6.
    Sarkar J, Chakrabarti P. A machine learning model reveals older age and delayed hospitalization as predictors of mortality in patients with COVID-19. MedRxiv. 2020;Perprint. https://doi.org/10.1101/2020.03.25.20043331.
  • 7.
    Alsharif W, Qurashi A. Effectiveness of COVID-19 diagnosis and management tools: A review. Radiography (Lond). 2021;27(2):682-7. [PubMed ID: 33008761]. [PubMed Central ID: PMC7505601]. https://doi.org/10.1016/j.radi.2020.09.010.
  • 8.
    Latunji OO, Akinyemi OO. Factors Influencing Health-Seeking Behaviour among Civil Servants in Ibadan, Nigeria. Ann Ib Postgrad Med. 2018;16(1):52-60. [PubMed ID: 30254559]. [PubMed Central ID: PMC6143883].
  • 9.
    Nieminen M, Atula T, Back L, Makitie A, Jouhi L, Aro K. Factors influencing patient and health care delays in Oropharyngeal Cancer. J Otolaryngol Head Neck Surg. 2020;49(1):22. [PubMed ID: 32326977]. [PubMed Central ID: PMC7181590]. https://doi.org/10.1186/s40463-020-00413-w.
  • 10.
    Aburayya A, Alshurideh M, Albqaeen A, Alawadhi D, A'Yadeh IA. An investigation of factors affecting patients waiting time in primary health care centers: An assessment study in Dubai. Management Science Letters. 2020;10(6):1265-76. https://doi.org/10.5267/j.msl.2019.11.031.
  • 11.
    Rahman AS, Shi S, Meza PK, Jia JL, Svec D, Shieh L. Waiting it out: consultation delays prolong in-patient length of stay. Postgrad Med J. 2019;95(1119):1-5. [PubMed ID: 30674619]. https://doi.org/10.1136/postgradmedj-2018-136269.
  • 12.
    Pujolar G, Oliver-Angles A, Vargas I, Vazquez ML. Changes in Access to Health Services during the COVID-19 Pandemic: A Scoping Review. Int J Environ Res Public Health. 2022;19(3). [PubMed ID: 35162772]. [PubMed Central ID: PMC8834942]. https://doi.org/10.3390/ijerph19031749.
  • 13.
    Jirathananuwat A. Factors affecting access to health services by older adults in an urban community in Thailand: a cross-sectional study. F1000Research. 2022;11. https://doi.org/10.12688/f1000research.110551.1.
  • 14.
    Macinko J, Woolley NO, Seixas BV, Andrade FB, Lima-Costa MF. Health care seeking due to COVID-19 related symptoms and health care cancellations among older Brazilian adults: the ELSI-COVID-19 initiative. Cad Saude Publica. 2020;36Suppl 3(Suppl 3). e00181920. [PubMed ID: 33053060]. https://doi.org/10.1590/0102-311X00181920.
  • 15.
    Silva NND, Favacho VBC, Boska GA, Andrade EDC, Merces NPD, Oliveira MAF. Access of the black population to health services: integrative review. Rev Bras Enferm. 2020;73(4). e20180834. [PubMed ID: 32490989]. https://doi.org/10.1590/0034-7167-2018-0834.
  • 16.
    Tuczynska M, Matthews-Kozanecka M, Baum E. Accessibility to Non-COVID Health Services in the World During the COVID-19 Pandemic: Review. Front Public Health. 2021;9:760795. [PubMed ID: 34976922]. [PubMed Central ID: PMC8716399]. https://doi.org/10.3389/fpubh.2021.760795.
  • 17.
    Istiko SN, Durham J, Elliott L. (Not That) Essential: A Scoping Review of Migrant Workers' Access to Health Services and Social Protection during the COVID-19 Pandemic in Australia, Canada, and New Zealand. Int J Environ Res Public Health. 2022;19(5). [PubMed ID: 35270672]. [PubMed Central ID: PMC8909973]. https://doi.org/10.3390/ijerph19052981.
  • 18.
    Nunez A, Sreeganga SD, Ramaprasad A. Access to Healthcare during COVID-19. Int J Environ Res Public Health. 2021;18(6). [PubMed ID: 33799417]. [PubMed Central ID: PMC7999346]. https://doi.org/10.3390/ijerph18062980.
  • 19.
    Blanchet K, Alwan A, Antoine C, Cros MJ, Feroz F, Amsalu Guracha T, et al. Protecting essential health services in low-income and middle-income countries and humanitarian settings while responding to the COVID-19 pandemic. BMJ Glob Health. 2020;5(10). [PubMed ID: 33028701]. [PubMed Central ID: PMC7542611]. https://doi.org/10.1136/bmjgh-2020-003675.
  • 20.
    Liu L, Xie J, Wu W, Chen H, Li S, Hu M, et al. A Simple Nomogram for Predicting Failure of Non-Invasive Respiratory Therapies in Adults with COVID-19: A Retrospective Multicenter Study. SSRN Electronic J. 2020;Preprint. https://doi.org/10.2139/ssrn.3619813.
  • 21.
    Kumar D, Dey T. Treatment delays in oncology patients during COVID-19 pandemic: A perspective. J Glob Health. 2020;10(1):10367. [PubMed ID: 32566158]. [PubMed Central ID: PMC7296208]. https://doi.org/10.7189/jogh.10.010367.
  • 22.
    Zheng W, Kampfen F, Huang Z. Health-seeking and diagnosis delay and its associated factors: a case study on COVID-19 infections in Shaanxi Province, China. Sci Rep. 2021;11(1):17331. [PubMed ID: 34462494]. [PubMed Central ID: PMC8405662]. https://doi.org/10.1038/s41598-021-96888-2.
  • 23.
    Chan ACY, Sneed RS. Factors Associated With Health Care Delays Among Adults Over 50 During the COVID-19 Pandemic. J Gerontol A Biol Sci Med Sci. 2023;78(4):630-6. [PubMed ID: 36006299]. [PubMed Central ID: PMC9452159]. https://doi.org/10.1093/gerona/glac174.
  • 24.
    Papautsky EL, Rice DR, Ghoneima H, McKowen ALW, Anderson N, Wootton AR, et al. Characterizing Health Care Delays and Interruptions in the United States During the COVID-19 Pandemic: Internet-Based, Cross-sectional Survey Study. J Med Internet Res. 2021;23(5). e25446. [PubMed ID: 33886489]. [PubMed Central ID: PMC8136407]. https://doi.org/10.2196/25446.
  • 25.
    Mullangi S, Aviki EM, Chen Y, Robson M, Hershman DL. Factors Associated With Cancer Treatment Delay Among Patients Diagnosed With COVID-19. JAMA Netw Open. 2022;5(7). e2224296. [PubMed ID: 35900758]. [PubMed Central ID: PMC9335143]. https://doi.org/10.1001/jamanetworkopen.2022.24296.
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