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).
| Variables | Total Frequency | Without Delay Frequency | Delayed Frequency | P-Value |
|---|---|---|---|---|
| Gender | 0.001 | |||
| Male | 18731 (49.1) | 4729 (25.2) | 14002 (74.8) | |
| Female | 19393 (50.9) | 4570 (23.6) | 14823 (76.4) | |
| Habitat | 0.001 | |||
| Urban | 32489 (85.2) | 8224 (25.3) | 24265 (74.7) | |
| Rural | 5635 (14.8) | 1075 (19.1) | 4560 (80.9) | |
| Job | 0.001 | |||
| Free | 5440 (14.3) | 1491 (27.4) | 3949 (72.6) | |
| Retired | 5891 (15.5) | 1446 (24.5) | 4445 (75.5) | |
| Unemployed/student/soldier | 1190 (3.1) | 503 (42.3) | 687 (57.7) | |
| Housewife | 8545 (22.4) | 2040 (23.9) | 6505 (76.1) | |
| Child/student | 5750 (15.1) | 1300 (22.6) | 4450 (77.4) | |
| Healthcare workers/government employee | 620 (1.6) | 287 (46.3) | 333 (53.7) | |
| Farmer/rancher | 57 (0.1) | 35 (61.4) | 22 (38.6) | |
| Other | 10631 (27.9) | 2197 (20.7) | 8434 (79.3) | |
| Age | 0.001 | |||
| < 18 | 5750 (15.1) | 1300 (22.6) | 4450 (77.4) | |
| 18 - 29 | 2481 (6.5) | 658 (26.5) | 1823 (73.5) | |
| 29 - 59 | 14314 (37.5) | 3353 (23.4) | 10961 (76.6) | |
| > 59 | 15579 (40.9) | 3988 (25.6) | 11591 (74.4) | |
| Smoking | 0.001 | |||
| Yes | 501 (1.3) | 27 (5.4) | 474 (94.6) | |
| No | 37623 (98.7) | 9272 (24.6) | 28351 (75.4) | |
| Opioid use | 0.001 | |||
| yes | 606 (1.6) | 24 (4) | 582 (96) | |
| No | 37518 (98.4) | 9275 (24.7) | 28243 (75.3) | |
| Corona vaccine injection | 0.001 | |||
| Yes | 6221 (16.3) | 596 (9.6) | 5625 (90.4) | |
| No | 31903 (83.7) | 8703 (27.3) | 23200 (72.7) | |
| Pregnancy | 0.001 | |||
| Yes | 621 (7.7) | 120 (19.3) | 501(80.7) | |
| No | 7450 (92.3) | 1778 (23.9) | 5672 (76.1) | |
| Cancer | 0.3 | |||
| Yes | 793 (2.1) | 181 (22.8) | 612 (77.2) | |
| No | 37331 (97.9) | 9118 (24.4) | 28213 (75.6) | |
| Lung disease | 0.17 | |||
| Yes | 2801 (7.3) | 713 (25.5) | 2088 (74.5) | |
| No | 35323 (92.7) | 8586 (24.3) | 26737 (75.7) | |
| Hypertension | 0.001 | |||
| Yes | 5334 (14) | 676 (12.7) | 4658 (87.3) | |
| No | 32790 (86) | 8623 (26.3) | 24167 (73.7) | |
| Diabetes | 0.001 | |||
| Yes | 4512 (11.8) | 1012 (22.4) | 3500 (77.6) | |
| No | 33612 (88.2) | 8287 (24.7) | 25325 (75.3) | |
| Cardiovascular disease | 0.1 | |||
| Yes | 7417 (19.5) | 1755 (23.7) | 5662 (76.3) | |
| No | 30707 (80.5) | 7544 (24.6) | 23163 (75.4) | |
| Other chronic diseases | 0.001 | |||
| Yes | 4205 (11) | 1389 (33) | 2816 (67) | |
| No | 33919 (89) | 7910 (23.3) | 26009 (76.7) | |
| Age (y) | 49.61 ± 25.27 | 50.65 ± 25.21 | 49.27 ± 25.28 | 0.001 |
| Hospitalization period (d) | 4.33 ± 4.67 | 2.66 ± 4.69 | 4.49 ± 4.64 | 0.001 |
| Delay in referral (d) | 3.67 ± 3.68 | - | - | - |
a Values are expressed as mean ± SD or No. (%),
b Chronic diseases: Blood fat, nervous and mental diseases, metabolic diseases, weak immune system. Women aged 9 years and older who are of reproductive age.
Table 2.Frequency of Delay in Referral Based on Symptoms and Outcome of the Disease a
| Variables | Total Frequency | Without Delay Frequency | Delayed Frequency | P-Value |
|---|---|---|---|---|
| Lab result | 0.001 | |||
| Positive | 16568 (43.5) | 3840 (23.2) | 12728 (76.8) | |
| Negative | 21104 (55.3) | 5306 (25.1) | 15798 (74.9) | |
| Further investigation is needed | 452 (1.2) | 153 (33.8) | 299 (66.2) | |
| Disease classification | 0.001 | |||
| Confirmed | 16150 (42.4) | 3913 (24.2) | 12237 (75.8) | |
| Suspected | 21436 (56.2) | 5112 (23.8) | 16324 (76.2) | |
| Probable | 538 (1.4) | 274 (50.9) | 264 (49.1) | |
| Hospitalization in ICU | 0.001 | |||
| Yes | 2319 (6.1) | 418 (18) | 1901 (82) | |
| No | 35805 (93.9) | 8881 (24.8) | 26924 (75.2) | |
| Shivering | 0.001 | |||
| Yes | 12242 (32.1) | 1079 (8.8) | 11163 (91.2) | |
| No | 25882 (67.9) | 8220 (31.8) | 17662 (68.2) | |
| Body pain | 0.001 | |||
| Yes | 15840 (41.5) | 2622 (16.6) | 13218 (83.4) | |
| No | 22284 (58.5) | 6677 (30) | 15607 (70) | |
| Test disorder | 0.001 | |||
| Yes | 549 (1.4) | 75 (13.7) | 474 (86.3) | |
| No | 37575 (98.6) | 9224 (24.5) | 28351 (75.5) | |
| Abnormal finding radiology | 0.001 | |||
| Yes | 4059 (10.6) | 405 (10) | 3654 (90) | |
| No | 34065 (89.4) | 8894 (26.1) | 25171 (73.9) | |
| Cough | 0.001 | |||
| Yes | 21455 (56.3) | 4306(20.1) | 17149(79.9) | |
| No | 16669 (43.7) | 4993(30) | 11676(70) | |
| Diarrhea | 0.001 | |||
| Yes | 2711 (7.1) | 554 (20.4) | 2157 (79.6) | |
| No | 35413 (92.9) | 8745 (24.7) | 26668 (75.3) | |
| Hard breath | 0.001 | |||
| Yes | 23529 (61.7) | 4683 (19.9) | 18846 (80.1) | |
| No | 14595 (38.3) | 4616 (31.6) | 9979 (68.4) | |
| Headache | 0.001 | |||
| Yes | 7666 (20.1) | 1441 (18.8) | 6225 (81.2) | |
| No | 30458 (79.9) | 7858 (25.8) | 22600 (74.2) | |
| Sore throat | 0.001 | |||
| Yes | 5288 (13.9) | 1192 (22.5) | 4096 (77.5) | |
| No | 32836 (86.1) | 8107 (24.7) | 24729 (75.3) | |
| Lung scan | 0.001 | |||
| Has symptoms | 11673 (30.6) | 649 (5.6) | 11024 (94.4) | |
| No symptoms | 26451 (69.4) | 8650 (32.7) | 17801 (67.3) | |
| Intubation | 0.001 | |||
| Yes | 1590 (4.2) | 108 (6.8) | 1482 (93.2) | |
| No | 36534 (95.8) | 9191 (25.2) | 27343 (74.8) | |
| Using ventilator | 0.001 | |||
| Yes | 2096 (5.5) | 414 (19.8) | 1682 (80.2) | |
| No | 36028 (94.5) | 8885 (24.7) | 27143 (75.3) | |
| Blood oxygen level | 0.001 | |||
| > 93 | 8780 (23) | 432 (4.9) | 8348 (95.1) | |
| < 93 | 21423 (56.2) | 946 (4.4) | 20477 (95.6) | |
| Unknown | 7921 (20.8) | 921 (100) | 0 | |
| Fever | 0.001 | |||
| No fever | 14749 (38.7) | 2433 (16.5) | 12316 (83.5) | |
| Mild fever | 18505 (87.2) | 4056 (21.9) | 14449 (78.1) | |
| High fever | 434 (1.1) | 109 (25.1) | 325 (74.9) | |
| Unknown | 4436 (11.6) | 2701 (60.9) | 1735 (39.1) | |
| Outcome | 0.001 | |||
| Death | 3060 (8) | 1004 (32.8) | 2056 (67.2) | |
| Recovery | 34915 (92) | 8259 (23.7) | 26656 (76.3) |
a Values are expressed No. (%).
Table 3.Modeling Factors Associated with Delay in Seeking Medical Care
| Variables | Crude | Adjusted | ||
|---|---|---|---|---|
| OR (95% CI) | P-Value | OR (95% CI) | P-Value | |
| Gender | ||||
| Female a | - | - | - | - |
| Male | 0.91 (0.87 - 0.96) | 0.001 | 0.86 (0.73 - 1) | 0.06 |
| Habitat | ||||
| Rural a | - | - | - | - |
| Urban | 0.69 (0.65 - 0.75) | 0.001 | 1.16 (0.99 - 1.36) | 0.05 |
| Job | ||||
| Free a | - | - | - | - |
| Retired | 1.16 (1.07 - 1.26) | 0.001 | 1.01 (0.79 - 1.29) | 0.92 |
| Unemployed/student/soldier | 0.52 (0.45 - 0.59) | 0.001 | 1.12 (0.84 - 1.48) | 0.44 |
| Housewife | 1.20 (1.11 - 1.30) | 0.001 | 0.80 (0.64 - 1.02) | 0.07 |
| Child/student | 1.29 (1.18 - 1.41) | 0.001 | 1.02 (0.65 - 1.59) | 0.93 |
| Healthcare workers/government employee | 0.44 (0.37 - 0.52) | 0.001 | 0.89 (0.50 - 1.60) | 0.71 |
| Farmer/rancher | 0.24 (0.14 - 0.41) | 0.001 | 0.24 (0.06 - 0.89) | 0.03 |
| Other | 1.45 (1.34 - 1.56) | 0.001 | 0.89 (0.74 - 1.09) | 0.3 |
| Age | ||||
| < 18 a | - | - | - | - |
| 18 - 29 | 0.81 (0.73 - 0.90) | 0.001 | 0.72 (0.53 - 0.98) | 0.04 |
| 29 - 59 | 0.95 (0.89 - 1.03) | 0.22 | 0.85 (0.71 - 1.02) | 0.07 |
| < 59 | 0.85 (0.79 - 0.91) | 0.001 | ||
| Smoking | ||||
| No a | - | - | - | - |
| Yes | 5.74 (3.89 - 8.47) | 0.001 | 0.71 (0.44 - 1.16) | 0.18 |
| Opioid use | ||||
| No a | - | - | - | - |
| Yes | 7.96 (5.29 - 11.99) | 0.001 | 1.32 (0.79 - 2.17) | 0.3 |
| Corona vaccine injection | ||||
| No a | - | - | - | - |
| Yes | 3.54 (3.24 - 3.87) | 0.001 | 1.04 (0.89 - 1.21) | 0.64 |
| Pregnancy | ||||
| No a | - | - | - | - |
| Yes | 1.35 (1.10 - 1.65) | 0.003 | 1.03 (0.83 - 1.27) | 0.8 |
| Cancer | ||||
| No a | - | - | - | - |
| Yes | 1.09 (0.92 - 1.29) | 0.3 | ||
| Lungdisease | ||||
| No a | - | - | - | - |
| Yes | 0.94 (0.86 - 1.03) | 0.17 | 0.66 (0.54 - 0.81) | 0.001 |
| Hypertension | ||||
| No a | - | - | - | - |
| Yes | 2.46 (2.26 - 2.67) | 0.001 | 0.81 (0.68 - 0.96) | 0.02 |
| Diabetic | ||||
| No a | - | - | - | - |
| Yes | 1.13 (1.05 - 1.22) | 0.001 | 0.85 (0.71 - 1.02) | 0.08 |
| Cardiovasculardisease | ||||
| No a | - | - | - | - |
| Yes | 1.05 (0.99 - 1.15) | 0.10 | 1.13 (0.95 - 1.34) | 0.16 |
| Other chronic diseases | ||||
| No a | - | - | - | - |
| Yes | 0.62 (0.57 - 0.66) | 0.001 | 1.08 (0.88 - 1.33) | 0.46 |
| Lab result | ||||
| Negative a | - | - | - | - |
| Positive | 1.13 (1.06 - 1.17) | 0.001 | 0.71 (0.51 - 0.97) | 0.03 |
| Further investigation is needed | 0.66 (0.54 - 0.80) | 0.001 | 0.88 (0.51 - 1.53) | 0.66 |
| Disease classification | ||||
| Probable a | - | - | - | - |
| Suspected | 3.31 (2.79 - 3.94) | 0.001 | 0.44 (0.17 - 1.11) | 0.08 |
| Confirmed | 3.24 (2.73 - 3.85) | 0.001 | 0.55 (0.21 - 1.42) | 0.21 |
| Outcome | ||||
| Death a | - | - | - | - |
| Recovery | 1.57 (1.46 - 1.71) | 0.001 | 0.87 (0.67 - 1.13) | 0.31 |
| Hospitalization in ICU | ||||
| No a | - | - | - | - |
| Yes | 1.5 (1.35 - 1.67) | 0.001 | 0.54 (0.43 - 0.67) | 0.001 |
| Shivering | ||||
| No a | - | - | - | - |
| YES | 4.81 (4.5 - 5.15) | 0.001 | 0.9 (0.79 - 1.02) | 0.1 |
| Body pain | ||||
| No a | - | - | - | - |
| Yes | 2.16 (2.05 - 2.27) | 0.001 | 1.31 (1.16 - 1.47) | 0.001 |
| Taste disorder | ||||
| No a | - | - | - | - |
| Yes | 2.06 (1.61 - 2.62) | 0.001 | 0.86 (0.57 - 1.29) | 0.46 |
| Abnormal finding radiology | ||||
| No a | - | - | - | - |
| Yes | 3.18 (2.87 - 3.54) | 0.001 | 0.56(0.48 - 0.66) | 0.001 |
| Cough | ||||
| No a | - | - | - | - |
| Yes | 1.7 (1.62 - 1.78) | 0.001 | 1.04 (0.92 - 1.17) | 0.56 |
| Diarrhea | ||||
| No a | - | - | - | - |
| Yes | 1.28 (1.16 - 1.41) | 0.001 | 0.92 (0.73 - 1.14) | 0.43 |
| Hard breath | ||||
| No a | - | - | - | - |
| Yes | 1.86 (1.77 - 1.95) | 0.001 | 0.93 (0.82 - 1.06) | 0.26 |
| Headache | ||||
| No a | - | - | - | - |
| Yes | 1.50 (1.41 - 1.59) | 0.001 | 1.04 (0.91 - 1.19) | 0.56 |
| Sore throat | ||||
| No a | - | - | - | - |
| Yes | 1.13 (1.05 - 1.21) | 0.001 | 0.96 (0.81 - 1.13) | 0.61 |
| Lung scan | ||||
| No symptoms a | - | - | - | - |
| Have symptoms | 8.25 (7.59 - 8.97) | 0.001 | 0.82 (0.73 - 0.94) | 0.003 |
| Intubation | ||||
| No a | - | - | - | - |
| Yes | 4.61 (3.78 - 5.62) | 0.001 | 0.26 (0.16 - 0.42) | 0.001 |
| Using ventilator | ||||
| No a | - | - | - | - |
| Yes | 1.33 (1.19 - 1.48) | 0.001 | 3.18 (1.93 - 5.26) | 0.001 |
| Blood oxygen level | ||||
| > 93 a | - | - | - | - |
| < 93 | 1.12 (.99 - 1.26) | 0.06 | 1.05 (0.93 - 1.19) | 0.43 |
| Unknown | 0 | 0 | ||
| Fever | ||||
| No fever a | - | - | - | - |
| Mild fever | 0.7 (0.66 - 0.74) | 0.001 | 1.01 (0.89 - 1.14) | 0.93 |
| High fever | 0.59 (0.47 - 0.73) | 0.001 | 0.77 (0.42 - 1.41) | 0.39 |
| Unknown | 0.13 (0.12 - 0.14) | 0.001 | 0.01 (0.002 - 0.11) | 0.001 |
| Period time hospitalization | ||||
| Day a | 1.22 (1.19 - 1.24) | 0.001 | 2.14 (2.02 - 2.25) | 0.001 |
a Reference group.
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.
