Abstract
Background
To analyse the epidemiological characteristics of orthopaedic trauma patients and thereby optimize healthcare resource allocation and improve treatment efficiency.
Materials and Methods
Relying on the hospital information system (HIS) database, we retrospectively analysed the epidemiological characteristics of orthopaedic trauma inpatients in our hospital between 2013 and 2022, including patient demographic information, causes of injury, location of injury and hospitalization costs.
Results
The median age of the patients was 36 (26–47) years old; the age stratification of the patients was highest in the proportion of patients aged 40–50 years old (29.23%); hypertension was the most common among the patients’ comorbidities (1.29%); patients’ occupation was highest in heavy labourers such as farmers and workers, about 63.04% (n = 13923); patients’ admissions were mainly in the form of emergencies (n = 16875, 76.41%); and patients’ median hospitalization time was 7 (5, 12) days. The highest percentage of the cause of injury was due to exposure to inanimate mechanical forces (75.4%), followed by falls (16.14%) and traffic accidents (6.49%). The highest percentage of cause of injury in all age groups was due to inanimate mechanical force, and the percentage of patients with falls increased with age, and there was a positive correlation between age groups and the percentage of patients with falls (r = 0.964, p < 0.01). The highest percentage of patients with injuries to the upper extremities was about 74%. The distribution of injury sites in all age groups was highest in the upper extremities. Age was positively correlated with trunk injuries (r = 0.469, p = 0.203). The median hospitalization cost for patients over a 10-year period was approximately $1,100.
Conclusions
By analysing the epidemiological characteristics of patients, a general profile of local orthopaedic trauma patients was established, which can help in the development of disease prevention and interventions.
Keywords: Orthopaedic trauma, epidemiologic characteristics, military hospital, inpatients, real-world study
Introduction
Worldwide, trauma is the leading cause of death and disability [1], and a study in the United States showed that the potential loss of lifetime due to trauma exceeds 38 million per year [2, 3]. Nearly, 50% of trauma patients have varying degrees of disability within one year of their injury [4], a problem shared by both low- and middle-income and high-income countries [5, 6]. For those who survive trauma, there is not only a huge financial burden [7], but also a significant impact on mental health [8]. Moreover, as the number of trauma patients increases each year, it also adds a huge social burden [9, 10]. Disability due to musculoskeletal injuries is a significant component of healthcare expenditures and the burden of disease, and more research is needed to develop new and more effective intervention strategies [11]. Research on the epidemiologic characteristics of trauma patients is beneficial for improving the quality and efficiency of trauma treatment and care [12]. orthopaedic patients make up a high percentage of trauma patients [13]; therefore, research related to the orthopaedic management of trauma is an important part of trauma care research.
Epidemiologic characteristics of trauma patients tend to manifest differently in different countries and regions [14]. In addition, patient length of stay and indications for hospitalization are also related to local policies and medical conditions [5], making it difficult to make comparisons across regions. Ningxia is a province in the inland northwest of China with a resident population of about 7,250,000. Among them, the resident population of Yinchuan, the provincial capital, is about 2,882,000, accounting for about 40% of the region’s population [15] and has a relative concentration of advantageous medical resources. Our hospital is a comprehensive Grade 2 A hospital in Yinchuan City, with trauma and orthopaedics as a dominant specialty, which is one of the important components of the local military medical support services. Although a large-scale multicentre study is more valuable for the study of the characteristics of a certain disease in a region, there is no study related to the epidemiological characteristics of trauma and orthopaedic patients in Yinchuan.
This study is an observational real-world study based on hospital information system (HIS) data. The analysis of the epidemiological characteristics of orthopaedic trauma patients provides a reference for the allocation of healthcare resources, as well as the adjustment of policies for the prevention of emergencies.
Materials and methods
Study design and patient population
This retrospective real-world study with a large sample analysed the information of patients discharged from the Department of Orthopaedic Trauma in our hospital from January 1, 2013, to December 31, 2022. The medical records were obtained from our Hospital Information System (HIS) database. The data were collated and analysed by an engineer from the information department and an orthopaedic surgeon after a joint review.
Inclusion criteria: (1) patients of orthopaedic trauma department in our hospital; (2) Patients were discharged between January 1, 2013, and December 31, 2022.
Exclusion criteria: (1) patients with internal fixation removal surgery; (2) patients with various types of locomotor system diseases and non-traumatic orthopaedic diseases; (3) reoperation for non-acute injuries; (4) patients with congenital deformities; (5) patients with missing information; (6) active-duty military personnel.
Statistical analysis
None of the data in the patients’ baseline condition conformed to normality, so quantitative information was expressed as median and interquartile range (IQR). Qualitative information, on the other hand, was expressed as number and percentage. Continuous variables were tested using the Kruskal–Wallis (H) test, categorical variables were tested using the 𝜒2 test or Monte Carlo exact method, and correlations of information were analysed using Spearman correlation analysis. All P values were two-sided and a difference of p < 0.05 was considered statistically significant. Data were analysed using Excel 2021 and SPSS statistical software (ver 25.0, USA).
This study followed the Declaration of Helsinki and approved by the Medical Ethics Committee of Armed Police Force Hospital of Ningxia (No. WQC-0075). Written informed consent was obtained from all participants upon admission to the hospital. All private patient information was kept strictly confidential.
Results
Demographic information
A total of 27,423 patients were discharged from the Department of Orthopaedic Trauma at our hospital between 2013 and 2022, excluding 2,800 patients who had internal fixation retention and removal surgeries, 1,663 patients with various types of motor system and non-trauma orthopaedic-related diseases, 494 cases of reoperation for non-polar injuries, 375 cases of congenital malformations, and five cases of missing key information, and finally, a total of 22,086 patients were included in the study.
Patient demographic information is shown in Table 1. Between 2013 and 2022, the ratio of male to female patients was 3.84:1 (17524/4562); the median age of the patients was 36 (26–47) years; the age stratification of the patients was highest in the patients aged 40–50 years (29.23%), followed by the patients aged 30–40 years (22.62%); patients’ occupation was highest in heavy labourers such as farmers and labourers, about 63.04% (n = 13923), followed by urban and rural self-employed individuals, about 17.23% (n = 3805); patients’ admissions were mainly in the form of emergencies (n = 16875, 76.41%); the median length of hospitalization of patients was 7 (5, 12) days. Statistically significant differences were observed in gender, age, patient distribution across age groups, comorbidities, occupational status, admission mode, and hospital stay duration from 2013 to 2022 (p < 0.05).
Table 1.
Demographic information.
| Year | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | Total |
|---|---|---|---|---|---|---|---|---|---|---|---|
| N | 3116 | 2961 | 2609 | 2555 | 3239 | 2735 | 2306 | 1074 | 1113 | 378 | 22086 |
| Sex n(%) | |||||||||||
| Male | 2473(79.36) | 2334(78.82) | 2050(78.57) | 2058(80.55) | 2557(78.94) | 2183(79.82) | 1805(78.27) | 869(80.91) | 907(81.49) | 288(76.19) | 17524(79.34) |
| Female | 643(20.64) | 627(21.18) | 559(21.43) | 497(19.45) | 682(21.06) | 552(20.18) | 501(21.73) | 205(19.09) | 206(18.51) | 90(23.81) | 4562(20.66) |
| Age M(IQR) | 33(23–44) | 34(24–45) | 35(25–45) | 36(26–46) | 36(26–47) | 38(27–47) | 39(28–49) | 39(29–49) | 40(29–50) | 41(30–51) | 36(26–47) |
| Age stratification n(%) | |||||||||||
| 0–10 | 235(2.01) | 112(0.97) | 107(1.04) | 116(1.12) | 159(1.21) | 168(1.48) | 80(0.81) | 27(0.58) | 39(0.8) | 9(0.54) | 1052(1.18) |
| 10–20 | 370(6.32) | 364(6.28) | 293(5.72) | 227(4.41) | 280(4.25) | 227(4.01) | 176(3.57) | 85(3.66) | 83(3.42) | 31(3.69) | 2136(4.78) |
| 20–30 | 816(20.9) | 758(19.61) | 670(19.62) | 600(17.45) | 740(16.83) | 507(13.44) | 472(14.38) | 198(12.77) | 194(11.99) | 56(10.01) | 5011(16.81) |
| 30–40 | 678(23.15) | 677(23.36) | 595(23.23) | 600(23.26) | 730(22.14) | 647(22.86) | 513(20.83) | 271(23.32) | 254(20.92) | 92(21.92) | 5057(22.62) |
| 40–50 | 657(28.04) | 660(28.46) | 601(29.35) | 626(30.34) | 791(29.98) | 687(30.34) | 577(29.29) | 255(27.42) | 279(28.73) | 94(27.98) | 5227(29.23) |
| 50–60 | 253(12.96) | 279(14.44) | 256(14.99) | 303(17.62) | 410(18.65) | 361(19.13) | 369(22.48) | 172(22.19) | 194(23.97) | 73(26.09) | 2670(17.92) |
| 60–70 | 82(4.9) | 93(5.61) | 77(5.26) | 67(4.55) | 117(6.2) | 119(7.37) | 101(7.18) | 60(9.03) | 66(9.51) | 20(8.34) | 802(6.28) |
| 70–80 | 23(1.57) | 15(1.04) | 9(0.7) | 15(1.16) | 11(0.67) | 17(1.2) | 18(1.46) | 6(1.03) | 4(0.66) | 3(1.43) | 121(1.08) |
| 80–90 | 2(0.15) | 3(0.23) | 1(0.09) | 1(0.09) | 1(0.07) | 1(0.08) | 0(0) | 0(0) | 0(0) | 0(0) | 9(0.09) |
| 90- | 0(0) | 0(0) | 0(0) | 0(0) | 0(0) | 1(0.09) | 0(0) | 0(0) | 0(0) | 0(0) | 1(0.01) |
| Comorbidities n(%) | |||||||||||
| Hypertension | 15(0.48) | 16(0.54) | 33(1.26) | 16(0.63) | 33(1.02) | 41(1.5) | 50(2.17) | 19(1.77) | 40(3.59) | 23(6.08) | 286(1.29) |
| Heart diseases | 2(0.06) | 2(0.07) | 2(0.08) | 5(0.2) | 3(0.09) | 3(0.11) | 3(0.13) | 0(0) | 4(0.36) | 8(2.12) | 32(0.14) |
| Hepatitis | 4(0.13) | 2(0.07) | 15(0.57) | 33(1.29) | 26(0.8) | 43(1.57) | 22(0.95) | 19(1.77) | 27(2.43) | 7(1.85) | 198(0.90) |
| Pulmonary disease | 4(0.13) | 3(0.1) | 2(0.08) | 3(0.12) | 3(0.09) | 7(0.26) | 4(0.17) | 12(1.12) | 9(0.81) | 2(0.53) | 49(0.22) |
| Kidney disease | 4(0.13) | 1(0.03) | 2(0.08) | 1(0.04) | 3(0.09) | 1(0.04) | 3(0.13) | 1(0.09) | 2(0.18) | 8(2.12) | 26(0.12) |
| Diabetes | 10(0.32) | 12(0.41) | 13(0.5) | 6(0.23) | 12(0.37) | 24(0.88) | 17(0.74) | 9(0.84) | 11(0.99) | 5(1.32) | 119(0.54) |
| Occupation n(%) | |||||||||||
| Self-employed individuals | 292(9.37) | 470(15.87) | 472(18.09) | 571(22.35) | 652(20.13) | 461(16.86) | 401(17.39) | 230(21.42) | 198(17.79) | 58(15.34) | 3805(17.23) |
| Farmers/workers | 2091(67.11) | 2019(68.19) | 1602(61.4) | 1533(60) | 1938(59.83) | 1697(62.05) | 1503(65.18) | 580(54) | 711(63.88) | 249(65.87) | 13923(63.04) |
| Students | 171(5.49) | 139(4.69) | 119(4.56) | 100(3.91) | 166(5.13) | 180(6.58) | 106(4.6) | 80(7.45) | 55(4.94) | 14(3.7) | 1130(5.12) |
| Preschool children | 114(3.66) | 35(1.18) | 29(1.11) | 42(1.64) | 50(1.54) | 48(1.76) | 53(2.3) | 15(1.4) | 21(1.89) | 5(1.32) | 412(1.87) |
| Service staff | 173(5.55) | 124(4.19) | 144(5.52) | 128(5.01) | 129(3.98) | 133(4.86) | 107(4.64) | 82(7.64) | 17(1.53) | 15(3.97) | 1052(4.76) |
| Civil servant | 190(6.1) | 148(5) | 200(7.67) | 110(4.31) | 140(4.32) | 148(5.41) | 104(4.51) | 56(5.21) | 67(6.02) | 19(5.03) | 1182(5.35) |
| Other | 85(2.73) | 26(0.88) | 43(1.65) | 71(2.78) | 164(5.06) | 68(2.49) | 32(1.39) | 31(2.89) | 44(3.95) | 18(4.76) | 582(2.64) |
| Mode of admission n(%) | |||||||||||
| Emergency | 2075(66.59) | 2192(74.03) | 2115(81.07) | 1933(75.66) | 2576(79.53) | 1974(72.18) | 1927(83.56) | 891(82.96) | 930(83.56) | 262(69.31) | 16875(76.41) |
| Outpatient | 1039(33.34) | 762(25.73) | 488(18.7) | 617(24.15) | 661(20.41) | 759(27.75) | 379(16.44) | 183(17.04) | 183(16.44) | 116(30.69) | 5187(23.49) |
| Transferred | 2(0.06) | 7(0.24) | 6(0.23) | 5(0.2) | 2(0.06) | 2(0.07) | 0(0) | 0(0) | 0(0) | 0(0) | 24(0.11) |
| Length of stay M(IQR) | 7(4,13) | 8(5,13) | 8(5,13) | 7(5,11) | 7(4,11) | 7(5,11) | 7(5,11) | 7(5,11) | 7(6,12) | 8(6,11) | 7(5,12) |
Distribution of causes of injury by year
Over the ten-year period, the highest percentage of injury causes were due to inanimate mechanical forces (75.4%), followed by falls (16.14%), and then traffic accidents (6.49%). The difference in the distribution of injury causes was statistically significant (p < 0.05). From 2019 to 2022, the percentage of injuries caused by falls gradually increased in patients, while the percentage of injuries due to inanimate mechanical forces gradually decreased (Figure 1).
Figure 1.
Distribution of causes of injury by year.
The cause of the patient’s injury was categorized as traffic accidents, inanimate mechanical forces, animal attack, falls, sport injury, thermal energy damage, fight and other. The horizontal coordinate indicates the year. The difference in the distribution of injury causes was statistically significant (P < 0.05).
Distribution of causes of injury by age
Causes of injuries were categorized according to traffic accidents, inanimate mechanical forces, animal attacks, falls, sports injuries, thermal energy injuries, and fights (Figure 2). Statistical testing revealed significant differences in distribution (p < 0.01). In all age groups, the most common cause of injury was exposure to inanimate mechanical forces, followed by falls and traffic accidents. Starting at the 20-30 age group, the percentage of patients with falls increased with age, and the correlation test between the age group of 20-90 years old and the percentage of patients with falls showed a positive correlation between age and the percentage of falls (r = 0.964, p < 0.01).
Figure 2.
Distribution of causes of injury by age.
The cause of the patient’s injury was categorized as traffic accidents, inanimate mechanical forces, animal attack, falls, sport injury, thermal energy damage, fight and other. The horizontal coordinate indicates age. Their distribution was tested statistically and the difference was significant(P < 0.01).
Injury site distribution (according to year)
The patients’ injury sites were categorized as left upper extremity, right upper extremity, both upper extremities, left lower extremity, right lower extremity, both lower extremities, trunk, and multiple injuries (Figure 3). Statistical tests of injury sites distributions showed significant differences(p < 0.01). The highest percentage of patients in different years had injuries to the upper extremities, followed by the lower extremities, and the percentage of patients with injuries to the extremities exceeded 90% in all years.
Figure 3.
Injury site distribution (according to year).
The patients’ injury sites were categorized as left upper extremity, right upper extremity, both upper extremities, left lower extremity, right lower extremity, both lower extremities, trunk, and multiple injuries. The horizontal coordinate indicates the year. Statistical tests of their distributions showed significant differences(P < 0.01).
Characteristics of the distribution of injury sites by age group
Injury sites of patients of different age groups were categorized as upper extremity, lower extremity, trunk, and multiple injuries (Figure 4), and their distribution was statistically tested for significant differences (p < 0.01). The distribution of injury sites was highest in the upper extremities in all age groups. The proportion of lower extremities and trunk increased with age. Correlations between age groups and lower limb and trunk injuries were analyzed. Comparing different age groups from 0 to 90 years was not significantly correlated with lower extremity injuries (p < 0.01) and positively correlated with trunk injuries (r = 0.469, p = 0.203).
Figure 4.
Characteristics of the distribution of injury sites by age group.
Injury sites of patients of different age groups were categorized as upper extremity, lower extremity, trunk, and multiple injuries, and their distribution was statistically tested for significant differences (P < 0.01). The horizontal coordinate indicates age.
Hospitalization costs
Median hospitalization costs for patients ranged from $766 in 2020 to $1293.5 in 2016, with statistically significant year-to-year variations (p < 0.01). Figure 5 shows patient hospitalization costs.
Figure 5.
Hospitalization costs.
Figure shows the median cost (dollars) of hospitalization for patients between 2013-2022. The difference in costs by year is statistically significant (P < 0.01).
Discussion
Trauma is a leading cause of death and disability globally, placing an enormous burden on patients and society [2]. Orthopaedic-related patients make up a large proportion of trauma patients [13]. Epidemiologic studies of local orthopaedic trauma patients are crucial, as their characteristics can vary by study, region, and economic development [5]. In this study, we analysed the demographic information of local patients, the distribution of causes of injuries, the distribution of injury sites, and so on. Our study found a higher percentage of male patients compared to females, with the peak age distribution between 40 and 50 years. The majority of patients were manual labourers, and the causes of injury were mainly mechanical injuries.
Among the 22,086 orthopaedic trauma patients in this study, the male-to-female ratio was 3.84:1. The gender ratio among orthopaedic trauma patients varied across studies and even within this study, with significant differences in the distribution of male and female patients across different years (p < 0.05). However, it is noteworthy that male patients consistently made up the highest percentage across different years. A study noted that approximately 70% of trauma patients are male (2.3:1 male-to-female ratio) [16]. Some studies have also reported a male-to-female ratio of 2.4:1 in orthopaedic trauma patients [17]. A Chinese study puts the male-to-female ratio of trauma patients at 2.7:1 [18]. In an Iranian study, the male-to-female ratio of traumatized orthopaedic patients was even as high as 4:1 [19]. This may be due to the fact that men tend to engage in activities with a higher risk of injury, such as sports and manual labour, leading to an increase in the proportion of male patients in orthopaedic cases of trauma [19].
The age distribution of orthopaedic trauma patients also varied across studies. The highest percentage of patients (29.23%) were in the 40–50 years age group in the trauma orthopaedics department during the 10 years of this study. Despite variations in age distribution among different years (p < 0.05), the 40–50 age group consistently had the highest percentage of patients. Additionally, the 25–44 age group had the highest frequency of trauma, representing approximately 31.9% of the study population (824/2582) [20]. Popovic et al. found that the majority of traumatized orthopaedic patients were between 30 and 50 years old [21], a finding that aligns with our results. The predominance of middle-aged patients with traumatic injuries may reflect their higher engagement in socially productive work [22].
Hypertension was the most common comorbidity among patients in this study, affecting 1.29% of the population. However, the percentage of patients with hypertension varied significantly across years, ranging from 0.48% to 6.08%. Data from previous years indicate a consistent annual increase in the percentage of hypertensive patients (Table 1). A study reported an increase in hypertension prevalence in China from 40.8/1000 person-years in 1993 to 48.6/1000 person-years in 201522. Among 1,738,886 patients aged 35 to 75 years in a study, 44.7% had hypertension [23]. China’s large hypertensive patient base may contribute to the high prevalence of hypertension among patients with comorbidities in this study. Additionally, hepatitis was more prevalent (0.9%) among patients with concurrent underlying diseases [24, 25]. Over half (63.04%) of the patients were farmers and labourers, as observed in the occupational distribution over the 10-year period. Although the difference in the occupational distribution of patients was statistically significant (p < 0.05), the percentage of workers and farmers was more than 60% in all years. Studies suggest that trauma victims are predominantly from sectors like agriculture/forestry/fishing, manufacturing, and transportation/postal/warehousing [26]. Bahman et al. found that construction, general and industrial workers comprised up to 70% of traumatized orthopaedic patients [27]. Farmers and workers often operate machinery, have close contact with animals, and face variable environmental conditions [28]. Hence, they are more prone to injuries from livestock, machinery, and hand tools [29]. Furthermore, on some small farms, workers and farmers are more likely to be injured due to a lack of safety supervision and enforcement [30]. We also noted a significant proportion of trauma patients were self-employed individuals (17.23%). Self-employed individuals, often small business operators, face high occupational hazards, a high prevalence of occupational diseases, and low occupational health and safety coverage, as indicated by a national survey [31]. In addition, their flexible working styles and the frequent lack of effective regulatory oversight may account for their greater vulnerability.
The median hospital stay for patients in this study was 7 days. Although lengths of stay varied by year (p < 0.05), they generally centred around 7 days. William et al. reported a median hospital stay of approximately 6 days, which is comparable to our findings [32]. Brice et al. reported an average hospital stay of about 9 days for trauma patients [33]. Hospital stays vary by injury site, with spinal injuries typically requiring longer stays [34], our study focused on extremity injuries, which tend to have shorter stays.
Furthermore, a significant decrease in trauma admissions in 2022 may correlate with the COVID-19 pandemic and subsequent public health and disease control measures. The pandemic prompted people to reduce outdoor activities, and closures of some factories may have contributed to a decrease in trauma cases. Consistent with our findings, other hospitals reported a 48% decline in trauma inpatient admissions attributed to the COVID-19 pandemic [35].
In this study, we found that exposure to inanimate mechanical forces (75.4%) accounted for the highest proportion of patient injury causes between 2013 and 2022. The annual distribution of patient injury causes significantly differed (p < 0.05), with the highest incidence due to inanimate mechanical forces. Consistent with our findings, Kezhi et al. reported that mechanical injuries constituted up to 60% of cases [31]. Falls (16.14%) and traffic accidents (6.49%) were also significant causes of orthopaedic trauma. This is similar to the findings of the study by Marc, Alberdi et al. [36, 37] Over 60% of patients were farmers and labourers, likely contributing to the high incidence of mechanical force injuries due to their work with agricultural equipment.
Variations in injury causes among different age groups were statistically significant (p < 0.01). The highest percentage of cause of injury in all age groups was inanimate mechanical force, followed by falls and traffic accidents. Analysis revealed an age-related increase in fall-related injuries, commencing at 20–30 years. Due to the limited number of patients >90 years of age (only 1 case), we excluded this subgroup from further analysis, as they may have been potential outliers. A correlation test was performed between the age subgroups of 20-90 years and the percentage of patients with falls. The results demonstrated a positive correlation between age and the percentage of falls (r = 0.964, p < 0.01). Falls are the most common cause of injury in older patients, resulting in millions of emergency room visits and hip fractures each year in the United States [38]. Similar to our results, many studies have noted that the incidence of falls in traumatic orthopaedic patients increases with age [39–42]. Falls in older adults can be caused by a variety of factors, such as decreased movement, balance and gait problems, decreased muscle mass, and medication overuse [43]. While elderly individuals are prone to falls, regular physical activity, including strength training, endurance training, and balance and mobility exercises, as well as adequate nutrition, is essential for their prevention. Meanwhile, we can also urge seniors to engage in improved balance training to reduce the risk of falls and fractures [44].
Statistically significant annual variations in injury site distribution were noted (P < 0.01). However, it is worth noting that the proportion of injured parts of patients in different years was highest in the upper limbs, followed by the lower limbs, and limb injuries constituted over 90% of cases annually. The study by Ahmed et al. noted that extremity injuries accounted for the vast majority (98%) of orthopaedic and major extremity trauma cases treated in hospitals, which is similar to our findings [45]. It has also been noted that limb injuries accounted for only 33% of orthopaedic trauma cases [46]. This suggests that the site of injury in our patients is related to factors such as, study population, and region.
Age group differences in injury site distribution were statistically significant (p < 0.01). However, it is not difficult to find that upper extremity injuries are the most prevalent among different age groups. The proportion of lower limbs and trunk gradually increases with age, which may be related to the higher proportion of falls in elderly patients [47]. Correlation analysis of age group with lower extremity injuries and trunk injuries was performed (we did not include the >90-year-old group for comparison because there was only one patient in that group), and it was found that there was a positive correlation with trunk injuries as the age group increased (r = 0.469, p = 0.203). Similarly, Maria, Ayça et al. noted that older patients are more likely to have spinal injuries and trunk injuries [48]. This could be related to decreased spinal stability, increased rigidity, and altered bone metabolism in the elderly [49].
Median hospitalization costs ranged from $766 in 2020 to $1293.5 in 2016, averaging $1100 over the decade. A study noted that the median hospitalization cost for trauma orthopaedic patients in China was about $3,056 [49]. And in the United States, the median cost of hospitalization for orthopaedic trauma patients was $6,544 [47]. The cost of hospitalization is related to the severity of the injury, the medical institution and the level of economic development of the region. For this reason, we are unable to make a simplistic comparison. Although the median cost of hospitalization at our hospital is only $1,100, it is still a huge burden for some patients and society.
Given the prevalence of extremity injuries, increasing on-call hand and foot surgeons could enhance patient disposition efficiency. Because most hand trauma requires emergency surgery, understaffed hospitals may delay patient treatment. Thus, it is also necessary to appropriately increase the proportion of hand and foot surgeons recruited. The elderly tend to be injured primarily in the lower extremities and trunk, and these patients usually do not require urgent surgical intervention. However, they have a relatively high prevalence of comorbidities and relatively poor general health. As a result, there is often a need for multidisciplinary physician collaboration in order to prevent deterioration. This puts high demands on the various departments of the hospital. For elderly patients in poor health, if the hospital lacks comprehensive treatment capabilities, prompt transfer to higher-level hospitals is necessary to prevent condition deterioration.In our study, the patients were mainly manual workers. At the societal level, safety education should be strengthened to increase people’s safety awareness. This may help reduce unnecessary injuries. Similarly, by analyzing the epidemiologic characteristics of local patients, other hospitals may be able to improve the allocation of healthcare resources and increase the success rate of patient treatment.
This study also has the following shortcoming: this study is a single-center retrospective study, which can only reflect the characteristics of the disease in a limited local area. By expanding the scope of the study and conducting a multicenter prospective study in the future, the credibility of the study can be improved, and the epidemiological characteristics of the disease can be provided as a reference for a wider area.
Conclusions
This study provides an epidemiological profile of local orthopaedic trauma patients from 2013 to 2022. Our analysis informs the development of targeted prevention and intervention strategies and guides the optimization of healthcare resource allocation. Furthermore, this will facilitate the enhancement of the efficacy of treatment in healthcare facilities.
Acknowledgements
We would like to thank other engineers in the Information Section for their great support in data extraction for this paper, such as Yu Fu. The authors thank American Journal Experts (AJE) for professional English editing.
Acknowledgments
Written informed consent was obtained from all participants upon admission to the hospital.
Authors’ contributions
All authors contributed to the design of the study. ZY, ZZX, ZL, WT, ZFN and CGC take responsibility for the integrity of the data and accuracy of the data analysis. ZY wrote the manuscript and LY, YW helped revise the manuscript. ZY, MX, CWJ, XS, NYL directly participated in the planning, execution, and analysis of the study. IT support was provided by ZXD. All authors read and approved the final manuscript.
Ethics approval and consent to participate
This study followed the Declaration of Helsinki and approved by the Medical Ethics Committee of Armed Police Force Hospital of Ningxia (No. WQC-0075). Written informed consent was obtained from all participants upon admission to the hospital. All private patient information was kept strictly confidential.
Informed consent statement
Written informed consent was obtained from all participants upon admission to the hospital.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The data used to support the findings of this study are available upon reasonable request from the authors.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data used to support the findings of this study are available upon reasonable request from the authors.