Abstract
Background
Previous studies have highlighted the importance of intensive care units (ICUs) in providing specialized care for critically ill patients. However, little is known about the current distribution of ICU resources, medical personnel, and available technologies across hospitals of different levels in Chinese mainland. In response, this study evaluated the distribution of ICU resources, personnel, major diseases, medical techniques, and the relationship between ICU bed availability and economic development to provide an overview of the current state of ICU services in Chinese mainland.
Methods
A comprehensive questionnaire was distributed to intensivists at all levels of hospitals in Chinese mainland via the Questionnaire Starmini-program, a commonly used web-based survey platform in China. The questionnaire covered a wide range of items, including the demographic characteristics of intensivists, ICU type and capacity, composition of medical teams, disease classification, and available medical techniques.
Results
Data were analyzed from 3637 intensivists working in 2005 hospitals throughout Chinese mainland, representing approximately half of all hospitals with ICU settings nationwide. The median number of hospital beds was 1000 (interquartile range [IQR], 547–1800), and the median number of ICU beds was 17 (IQR: 11–25). Overall, 600 (IQR: 300–1091) patients were admitted to the ICU annually at each hospital. The mean number of ICU beds per 100,000 people was 5.31 in 2022. The majority of the surveyed medical groups (ranging from 97.7% to 98.8%) led by chief physicians have experience in treating the eight most common conditions managed in the ICU, including severe pneumonia, cardiogenic shock, hypovolemic shock, sepsis, septic shock, cardiopulmonary resuscitation, acute respiratory distress syndrome, and acute renal injury. Regarding essential medical techniques in the ICU, 98.2%, 86.5%, 71.2%, and 24.1% of surveyed hospitals have implemented invasive mechanical ventilation, continuous blood purification, bedside ultrasound, and extracorporeal membrane oxygenation, respectively.
Conclusions
This survey indicates that, although ICUs in Chinese mainland have advanced significantly to some extent, there are still challenges to address, such as regional disparities and hospital grade differences.
Keywords: Intensive care units, Critical care, Resource, Survey
Introduction
The intensive care unit (ICU) is one of the most complex environments within medical institutions, specializing in the management and treatment of severely ill patients.[1] Its primary objective is to monitor, maintain, and restore the essential physiological functions of patients.[2] As patient numbers rise and medical techniques advance, critical care management and treatment delivery are escalating in many developing countries and areas.[3] By encouraging comprehensive treatment in these settings, the prognosis of critically ill patients has been greatly improved.[4]
Establishing evidence-based and standardized treatment protocols for critically ill patients is a high-priority research area.[5] However, the availability of ICU resources remains scarce in some resource-limited areas in Chinese mainland.[6] In addition, there is a lack of data regarding personnel, major diseases, and medical techniques in ICUs across various grades of hospitals in Chinese mainland. The unclear relationship between ICU bed availability and economic development further complicates the situation, highlighting disparities in ICU capacity across different regions. Therefore, we conducted this survey to identify the status and influencing factors of ICU development in Chinese mainland, which is essential for enhancing clinical practice and advancing the evolution of critical care medicine in Chinese mainland.[7,8]
Methods
Study design
This cross-sectional, multicenter study was conducted between January 19, 2022 and February 23, 2022, covering all provinces in Chinese mainland. A self-developed questionnaire was created by the Chinese Critical Care Resources Investigation Group and distributed to participating intensivists by the Critical Care Medicine Branch of the Chinese Medical Association. To guarantee a good response rate and accuracy of the questionnaire, each provincial region designated a manager (usually the chairman of the provincial critical care society) to be responsible for promoting and managing the survey’s deployment. Provincial managers first evaluated whether the ICUs of hospitals within the province were willing to participate in the investigation, and those ICUs that were unwilling to participate in the survey were excluded. Subsequently, each ICU participating in this survey assigned one or two physicians (with different professional titles) to be specifically responsible for the survey. Considering that some data needed to be gathered by accessing electronic health records, the survey questionnaire was sent to the survey coordinators 1 month in advance for the compilation of various data, including to ensure their accuracy. In the case of a discrepancy between the data provided by the two survey coordinators, the issue was resolved through data verification and discussion. In addition, the number of ICU beds, the number of hospital beds, and the total and per-capita healthcare expenditures in 31 provinces and regions of Chinese mainland were extracted from the China Health Statistics Yearbook 2022. Similarly, the gross domestic product (GDP), Health Development Index, and Human Development Index were derived from the China Statistical Yearbook 2022.
Incision and exclusion criteria
For hospitals to be included in this study, they were required to be either a specialized or a general hospital with an ICU. In addition, the inclusion criteria for intensivists were as follows: (1) a minimum of 1 year of experience working in the designated hospital; (2) currently engaging in clinical medical work; and (3) willingness to participate in this survey. Intensivists who were not familiar with clinical medical work were excluded.
Questionnaire
The study questionnaire was designed by the Chinese Critical Care Resources Investigation Group, an expert team of intensive care physicians, epidemiologists, statisticians, and hospital administrators. After its development, the instrument underwent pre-testing at 10 centers, where it was filled out by relevant professionals to assess clarity, comprehensibility, and relevance. Based on the feedback gleaned from these pre-tests, necessary revisions were made to ensure the instrument met the required standards for its formal distribution. The final questionnaire consisted of four primary sections covering the following: (1) general information about the hospital, including its tier, geographical location, whether it was a teaching hospital or not, type(s) of ICU, total number of hospital beds, total number of ICU beds, average annual patient admissions over the previous 3 years, and the calculation and values of the Case Mix Index (CMI); (2) demographics of the participating intensivists, including age, sex, educational attainment, academic title, years of working experience, and the composition of medical teams; (3) types of diseases treated by the involved medical teams within the previous 3 years, including sepsis, septic shock, cardiogenic shock, hypovolemic shock, acute respiratory distress syndrome (ARDS), acute kidney injury (AKI), acute liver injury, acute gastrointestinal injury, multiple trauma, severe traumatic brain injury, severe pneumonia, and other common ICU conditions; and (4) the implementation of monitoring and therapeutic techniques in ICU, including high-flow oxygen therapy, non-invasive ventilation, invasive mechanical ventilation, continuous blood purification, extracorporeal membrane oxygenation (ECMO), bedside ultrasound monitoring, fiberoptic bronchoscopy, electroencephalogram monitoring, microcirculation monitoring, and other common practices or procedures in the ICU setting. The complete questionnaire is shown in Supplementary Table S1.
Statistical analysis
Categorical variables are described as n (%), and quantitative variables are expressed as mean ± standard deviation values or median with interquartile range (IQR) values, depending on whether the data are normally distributed. The Kruskal–Wallis test was used for the comparison of continuous variables, whereas the chi-squared test was used to assess categorical data. Data with missing values were excluded from the analysis. P < 0.05 was regarded as statistically significant.
We performed linear regression analyses to evaluate the relationship between the GDP, total healthcare expenditure, healthcare expenditure per capita, Health Development Index, Human Development Index, the number of hospital beds per 100,000 people, and the number of ICU beds per 100,000 people.
A multivariable logistic regression analysis was conducted to evaluate the independent factors associated with the implementation of four major medical techniques in the ICU, including invasive mechanical ventilation, bedside ultrasound, continuous blood purification, and ECMO. The study used a backward elimination method with a significance level of less than 0.05 for variable entry and greater than 0.10 for stepwise removal, respectively. The following variables were adjusted: hospital grade and geographic location, whether the hospital was a teaching hospital or not, the number of hospital beds, the ICU type, the number of ICU beds, the number of patients admitted to the ICU per year, the CMI, and the proportion of patients with an Acute Physiology and Chronic Health Evaluation (APACHE) II score of ≥15 points. The outcomes are presented as odds ratios (OR) with 95% confidence intervals (CI).
Results
Relationship between economic development and ICU bed availability
Table 1 illustrates the economic development and ICU bed availability distribution across the 31 surveyed provinces. The mean number of ICU beds per 100,000 people was 5.31 in 2022. The greatest ICU bed density was observed in Chongqing, which was 6.1 times greater than the lowest recorded in Sichuan, highlighting significant inequalities in health resource distribution across Chinese mainland. In addition, our linear regression analyses showed that, while there was a positive trend between the number of critical care beds per 100,000 people and economic indicators such as the GDP, total healthcare expenditure, health expenditure per capita, Health Development Index, Human Development Index, and hospital beds per 100,000 people, none of these relationships were statistically significant (Figure 1).
Table 1.
The Chinese mainland economic development and medical resource distribution in 2022 at national, regional, and provincial levels.
| Location | GDP (billion RMB) | Total healthcare expenditure (billion RMB) | Health expenditure per capita (RMB) | Health Development Index | Human Development Index | Hospital beds per 100,000 population | ICU beds per 100,000 population |
|---|---|---|---|---|---|---|---|
| Chinese mainland | 121,000 | 7680 | 5443.243 | - | - | 692 | 5.31 |
| Area | |||||||
| Northeast China | 5790 | 486 | 5042.959 | - | - | 792.85 | 4.13 |
| North China | 14,900 | 1060 | 6310.677 | - | - | 643.59 | 5.22 |
| East China | 46,300 | 2520 | 5925.053 | - | - | 656.54 | 5.67 |
| South China | 16,200 | 1060 | 5638.482 | - | - | 540.12 | 4.67 |
| Central China | 16,400 | 1020 | 4563.683 | - | - | 782.7 | 6.22 |
| Northwest China | 7040 | 560 | 5408.303 | - | - | 717.09 | 5.41 |
| Southwest China | 13,700 | 980 | 4782.351 | - | - | 783.36 | 9.73 |
| Provinces | |||||||
| Beijing | 4160 | 335 | 15,347.57 | 96.84 | 0.881 | 613 | 6.74 |
| Tianjin | 1630 | 107 | 7867.938 | 83.41 | 0.838 | 503 | 5.02 |
| Hebei | 4240 | 331 | 4459.057 | 74.75 | 0.721 | 655 | 5.63 |
| Shanxi | 2560 | 157 | 4508.532 | 75.05 | 0.733 | 656 | 4.15 |
| Inner Mongolia | 2320 | 133 | 5541.483 | 74.62 | 0.754 | 698 | 4.24 |
| Liaoning | 2900 | 195 | 4646.676 | 74.25 | 0.76 | 777 | 4.59 |
| Jilin | 1310 | 116 | 4959.455 | 73.08 | 0.75 | 755 | 2.7 |
| Heilongjiang | 1590 | 175 | 5642.917 | 69.4 | 0.732 | 843 | 4.59 |
| Shanghai | 4470 | 333 | 13,440.69 | 100 | 0.854 | 668 | 4.63 |
| Jiangsu | 12,300 | 578 | 6787.293 | 84.81 | 0.784 | 661 | 5.03 |
| Zhejiang | 7770 | 429 | 6523.324 | 88.95 | 0.772 | 580 | 7.99 |
| Anhui | 4500 | 252 | 4106.626 | 77.9 | 0.707 | 725 | 4.84 |
| Fujian | 5310 | 208 | 4958.978 | 80.03 | 0.746 | 555 | 4.37 |
| Jiangxi | 3210 | 186 | 4109.32 | 78.65 | 0.712 | 695 | 4.47 |
| Shandong | 8740 | 537 | 5288.537 | 79.41 | 0.753 | 683 | 6.54 |
| Henan | 6130 | 408 | 4136.629 | 79.48 | 0.714 | 762 | 8.08 |
| Hubei | 5370 | 305 | 5220.756 | 80.1 | 0.746 | 771 | 5.15 |
| Hunan | 4870 | 305 | 4620.609 | 77.27 | 0.737 | 824 | 4.39 |
| Guangdong | 12,900 | 806 | 6371.162 | 80.82 | 0.77 | 481 | 4.84 |
| Guangxi | 2630 | 194 | 3847.038 | 75.03 | 0.708 | 677 | 4.42 |
| Hainan | 682 | 55.6 | 5412.463 | 78.89 | 0.733 | 596 | 3.85 |
| Chongqing | 2910 | 169 | 5267.383 | 81.37 | 0.747 | 781 | 13.42 |
| Sichuan | 5670 | 425 | 5080.857 | 77.07 | 0.704 | 817 | 2.21 |
| Guizhou | 2020 | 154 | 3985.737 | 71.84 | 0.665 | 803 | 4.76 |
| Yunnan | 2900 | 207 | 4400.405 | 74.1 | 0.659 | 727 | 3.8 |
| Xizang | 213 | 25.5 | 6996.978 | 70.39 | 0.561 | 549 | 3.16 |
| Shaanxi | 3280 | 215 | 5423.382 | 80.64 | 0.742 | 732 | 4.64 |
| Gansu | 1120 | 111 | 4457.103 | 72.11 | 0.671 | 758 | 5.13 |
| Qinghai | 361 | 38.8 | 6522.185 | 71.97 | 0.667 | 722 | 6.02 |
| Ningxia | 507 | 37.3 | 5122.527 | 73.61 | 0.725 | 574 | 3.78 |
| Xinjiang | 1770 | 158 | 6125.744 | 67.48 | 0.717 | 694 | 7.19 |
GDP: Gross domestic product; ICU: Intensive care unit.
Figure 1.
Linear regression analysis.A: The number of critical care beds per 100,000 people relative to the GDP; B: total healthcare expenditure; C: healthcare expenditure per capita; D: Health Development Index; E: Human Development Index;F: Hospital beds per 100,000 people. Lines represent linear regression analysis with 95% confidence intervals.
Overview of surveyed ICUs and intensivists
A total of 3692 questionnaires were distributed, and 3658 participants responded to the survey (99.1%). Following data deduplication and verification for accuracy, 3637 responses were retained for subsequent analysis. The responders were from 2005 hospitals distributed across 31 provincial areas in the Chinese mainland, representing approximately half of all hospitals with ICU settings nationwide (Figure 2). Of the surveyed hospitals, 1389 were classified as class III general hospitals, 175 were classified as class III specialized hospitals, 434 were classified as class II hospitals, and 7 were classified as other types of hospitals. Among these 1564 class III hospitals, 803 (51.3%) were teaching hospitals. The median number of hospital beds was 1000 (IQR: 547–1800), and the median number of ICU beds was 17 (IQR: 11–25). On average, 600 (IQR: 300–1091) patients were admitted to the ICU in each hospital per year, with 65.0% (IQR: 45.0%–80.0%) of these patients having an APACHE II score of ≥15 points. A total of 432 (21.5%) ICUs calculated CMI values, and the median CMI value was 3.43 (IQR: 2.60–4.70). Of note, class III general hospitals were more likely to be teaching hospitals, to calculate CMI values, to have more ICU beds, and to have more annual ICU admissions than other types of hospitals (Table 2).
Figure 2.
The number of surveyed hospitals across different provinces in the Chinese mainland.
Table 2.
Basic characteristics of the investigated hospitals (n = 2005).
| Variable | All | Class II hospital | Class III specialized hospital | Class III general hospital | Other | P value overall |
|---|---|---|---|---|---|---|
| (n = 2005) | (n = 434) | (n = 175) | (n = 1389) | (n = 7) | ||
| Area | ||||||
| Northeast China | 208 (10.4) | 22 (5.07) | 17 (9.7) | 168 (12.1) | 1 (14.3) | |
| North China | 273 (13.6) | 73 (16.8) | 20 (11.4) | 179 (12.9) | 1 (14.3) | |
| East China | 494 (24.6) | 91 (21.0) | 52 (29.7) | 350 (25.2) | 1 (14.3) | |
| South China | 225 (11.2) | 47 (10.8) | 16 (9.1) | 162 (11.7) | 0 | |
| Central China | 251 (12.5) | 60 (13.8) | 24 (13.7) | 167 (12.0) | 0 | |
| Northwest China | 180 (9.0) | 49 (11.3) | 18 (10.3) | 113 (8.14) | 0 | |
| Southwest China | 374 (18.7) | 92 (21.2) | 28 (16.0) | 250 (18.0) | 4 (57.1) | |
| Teaching hospital | <0.001 | |||||
| No | 1202 (60.0) | 370 (85.3) | 103 (58.9) | 724 (52.1) | 5 (71.4) | |
| Yes | 803 (40.0) | 64 (14.7) | 72 (41.1) | 665 (47.9) | 2 (28.6) | |
| Hospital bed number | 1000 (547–1800) | 500 (300–740) | 800 (500–1200) | 1300 (800–2000) | 520 (500–1050) | <0.001 |
| ICU type: | <0.001 | |||||
| Specialized ICU | 155 (7.7) | 12 (2.8) | 57 (32.6) | 85 (6.12) | 1 (14.3) | |
| General ICU | 1850 (92.3) | 422 (97.2) | 118 (67.4) | 1304 (93.9) | 6 (85.7) | |
| ICU bed Number | 17.0 (11.0–25.0) | 11.0 (8.0–15.0) | 13.0 (9.0–20.0) | 20.0 (14.0–30.0) | 15.0 (11.0–18.0) | <0.001 |
| Number of patients admitted to ICU per year | 600 (300–1091) | 400 (200–700) | 450 (252–900) | 750 (380–1200) | 450 (160–950) | <0.001 |
| CMI assessment: | <0.001 | |||||
| No | 1573 (78.5) | 385 (88.7) | 151 (86.3) | 1030 (74.2) | 7 (100.0) | |
| Yes | 432 (21.5) | 49 (11.3) | 24 (13.7) | 359 (25.8) | 0 | |
| CMI value | 3.43 (2.60–4.70) | 3.26 (2.50–4.20) | 3.10 (2.25–3.60) | 3.50 (2.69–4.70) | 0.416 | |
| APACHE II≥15 | 65.0 (45.0–80.0) | 60.0 (40.0–80.0) | 50.0 (28.8–75.0) | 67.0 (50.0–80.0) | 70.0 (56.0–70.0) | <0.001 |
Data presented as n (%) and median (interquartile range).
APACHE II: Acute physiology and chronic health evaluation II; CMI: Case Mix Index; ICU: Intensive care unit.
The demographic characteristics of the participating intensivists are summarized in Table 3 and Supplementary Tables S2–S4. Of the 3637 responders (65.9% males), 2406 (66.2%) were from class III general hospitals, 264 (7.3%) were from class III specialized hospitals, 959 (26.4%) were from class II hospitals, and eight (0.2%) were from other hospitals. The majority (91.9%) of intensivists were older than 31 years, with a median of 10.0 (IQR: 5.00–13.0) years of experience working in the ICU. The most common professional titles among participants were attending physician (35.1%) and associate chief physician (34.1%), followed by chief physician (16.6%) and resident physician (14.2%). Most participants (61.7%) had a bachelor’s degree as their highest level of education, while only a small proportion (5.4%) had a doctoral degree.
Table 3.
The demographics of the participating intensivists.
| Variable | All (n = 3637) | Class II hospital (n = 959) | Class III specialized hospital (n = 264) | Class III general hospital (n = 2406) | Other (n = 8) | P value overall |
|---|---|---|---|---|---|---|
| Sex | <0.001 | |||||
| Male | 2395 (65.9) | 705 (73.5) | 161 (61.0) | 1523 (63.3) | 6 (75.0) | |
| Female | 1242 (34.1) | 254 (26.5) | 103 (39.0) | 883 (36.7) | 2 (25.0) | |
| Age (years) | <0.001 | |||||
| ≤30 | 296 (8.1) | 65 (6.8) | 17 (6.4) | 213 (8.9) | 1 (12.5) | |
| 31–39 | 1525 (41.9) | 370 (38.6) | 109 (41.3) | 1045 (43.4) | 1 (12.5) | |
| ≥40 | 1816 (49.9) | 524 (54.6) | 138 (52.3) | 1148 (47.7) | 6 (75.0) | |
| Education | <0.001 | |||||
| Bachelor’s degree and below | 2244 (61.7) | 870 (90.7) | 129 (48.9) | 1237 (51.4) | 8 (100.0) | |
| Doctor’s degree | 198 (5.4) | 0 | 20 (7.6) | 178 (7.4) | 0 | |
| Master's Degree | 1195 (32.9) | 89 (9.3) | 115 (43.6) | 991 (41.2) | 0 | |
| Work year | 10.0 (5.0–13.0) | 8.0 (5.0–11.0) | 10.0 (5.5–13.0) | 10.0 (6.0–15.0) | 9.0 (6.3–12.5) | <0.001 |
| Academic title | <0.001 | |||||
| Associate chief physicians | 1242 (34.1) | 362 (37.7) | 93 (35.2) | 782 (32.5) | 5 (62.5) | |
| Chief physicians | 602 (16.6) | 116 (12.1) | 54 (20.5) | 432 (18.0) | 0 | |
| Attending physicians | 1275 (35.1) | 360 (37.5) | 84 (31.8) | 829 (34.5) | 2 (25.0) | |
| Resident physicians | 518 (14.2) | 121 (12.6) | 33 (12.5) | 363 (15.1) | 1 (12.5) |
Data presented as n (%) and median (interquartile range).
Disease spectrum and implementation of medical techniques in the ICU
The common causes of ICU admission and the number of cases received by different hierarchies of medical groups are presented in Table 4 and Supplementary Tables S5–S7. The majority of the surveyed medical groups (97.7%–98.8%) led by chief physicians have experience in treating the eight most common conditions seen in the ICU, including severe pneumonia, cardiogenic shock, hypovolemic shock, sepsis, septic shock, the need for cardiopulmonary resuscitation, ARDS, and AKI, whereas there is a slight variation in the proportion of treating these conditions among medical groups led by associated physicians (97.1%–99.4%) or attending physicians (95.1%–99.1%). Supplementary Tables S8–S10 present the essential medical techniques used for diagnosing, monitoring, and administering treatment to patients in the ICU, along with the distribution of cases treated with these techniques across various medical groups. High-flow oxygen therapy and non-invasive ventilation, invasive mechanical ventilation, tracheal intubation, central venous catheterization, thoracentesis, enteral nutrition, parenteral nutrition, and sedation and analgesia were the eight most commonly used techniques in ICU settings.
Table 4.
Details of the eight most common diseases and four essential medical techniques in the past 3 years among the medical groups led by chief physicians.
| Variable | All (n = 602) | Class II hospital (n = 116) | Class III specialized hospital (n = 54) | Class III general hospital (n = 432) | P value overall |
|---|---|---|---|---|---|
| Whether received patients with sepsis | 0.008 | ||||
| No | 8 (1.3) | 5 (4.3) | 1 (1.9) | 2 (0.5) | |
| Yes | 594 (98.7) | 111 (95.7) | 53 (98.1) | 430 (99.5) | |
| Number of patients with sepsis per year | 90.0 (30.0–200.0) | 30.0 (14.0–80.0) | 60.0 (30.0–120.0) | 100.0 (50.0–200.0) | <0.001 |
| Whether received patients with septic shock | 0.003 | ||||
| No | 9 (1.5) | 5 (4.3) | 2 (3.7) | 2 (0.5) | |
| Yes | 593 (98.5) | 111 (95.7) | 52 (96.3) | 430 (99.5) | |
| Number of septic shock patients per year | 50.0 (20.0–100.0) | 20.0 (10.0–51.0) | 28.0 (15.0–85.8) | 60.0 (30.0–110.0) | <0.001 |
| Whether received patients with cardiogenic shock | <0.001 | ||||
| No | 13 (2.2) | 5 (4.3) | 6 (11.1) | 2 (0.5) | |
| Yes | 589 (97.8) | 111 (95.7) | 48 (88.9) | 430 (99.5) | |
| Number of patients with cardiogenic shock per year | 29.0 (10.0–50.0) | 15.0 (8.0–38.0) | 15.0 (8.0–30.0) | 30.0 (15.0–56.0) | <0.001 |
| Whether received patients with hypovolemic shock | 0.816 | ||||
| No | 7 (1.2) | 2 (1.7) | 0 | 5 (1.2) | |
| Yes | 595 (98.8) | 114 (98.3) | 54 (100) | 427 (98.8) | |
| Number of hypovolemic shock patients per year | 40.0 (20.0-100) | 25.0 (11.2-50.0) | 20.0 (10.0-50.0) | 50.0 (25.0-100) | 0.001 |
| Whether received patients with ARDS | 0.009 | ||||
| No | 12 (2.0) | 6 (5.2) | 2 (3.7) | 4 (0.9) | |
| Yes | 590 (98.0) | 110 (94.8) | 52 (96.3) | 428 (99.1) | |
| Number of patients with ARDS per year | 37.5 (20.0–100.0) | 20.0 (10.0–38.8) | 30.0 (10.0–46.2) | 50.0 (21.8–100) | <0.001 |
| Whether received patients with AKI | <0.001 | ||||
| No | 14 (2.3) | 9 (7.8) | 2 (3.7) | 3 (0.7) | |
| Yes | 588 (97.7) | 107 (92.2) | 52 (96.3) | 429 (99.3) | |
| Number of patients with AKI per year | 50.0 (25.0–123) | 20.0 (8.00–42.5) | 35.0 (12.0–50.0) | 70.0 (30.0–180) | <0.001 |
| Whether received patients with severe pneumonia | 0.036 | ||||
| No | 7 (1.2) | 1 (0.9) | 3 (5.6) | 3 (0.7) | |
| Yes | 595 (98.8) | 115 (99.1) | 51 (94.4) | 429 (99.3) | |
| Number of severe pneumonia per year | 50.0 (25.0–100.0) | 30.0 (10.0–55.5) | 50.0 (20.0–100.0) | 60.0 (30.0–150.0) | <0.001 |
| No | 31 (5.1) | 3 (2.6) | 10 (18.5) | 18 (4.2) | |
| Yes | 571 (94.9) | 113 (97.4) | 44 (81.5) | 414 (95.8) | |
| Whether received patients with CPR | 0.018 | ||||
| No | 12 (2.0) | 2 (1.7) | 4 (7.4) | 6 (1.4) | |
| Yes | 590 (98.0) | 114 (98.3) | 50 (92.6) | 426 (98.6) | |
| Number of patients with CPR per year | 16.5 (10.0–30.0) | 10.0 (5.00–20.0) | 14.0 (5.00–20.0) | 20.0 (10.0–34.0) | <0.001 |
| Whether received patients underwent invasive mechanical ventilation | |||||
| No | 6 (1.0) | 0 | 1 (1.9) | 5 (1.2) | |
| Yes | 596 (99.0) | 116 (100.0) | 53 (98.1) | 427 (98.8) | |
| Number of patients underwent invasive mechanical ventilation per year | 200 (100–400) | 100 (50.0–260) | 100 (40.0–200) | 250 (106–490) | |
| Whether received patients underwent bedside ultrasound | |||||
| No | 149 (24.8) | 44 (37.9) | 17 (31.5) | 88 (20.4) | |
| Yes | 453 (75.2) | 72 (62.1) | 37 (68.5) | 344 (79.6) | |
| Number of patients underwent bedside ultrasound per year | 100 (42.0–300) | 75.0 (20.0–200) | 50.0 (20.0–200) | 122 (50.0–300) | |
| Whether received patients underwent CBP | |||||
| No | 57 (9.5) | 23 (19.8) | 6 (11.1) | 28 (6.5) | |
| Yes | 545 (90.5) | 93 (80.2) | 48 (88.9) | 404 (93.5) | |
| Number of patients underwent CBP per year | 50.0 (25.0–150) | 26.0 (10.0–60.0) | 30.0 (10.0–55.5) | 78.0 (30.0–161) | |
| Whether received patients underwent ECMO | |||||
| No | 406 (67.4) | 115 (99.1) | 38 (70.4) | 253 (58.6) | |
| Yes | 196 (32.6) | 1 (0.9) | 16 (29.6) | 179 (41.4) | |
| Number of patients underwent ECMO per year | 5.00 (2.00–10.0) | 1.00 (1.00–1.00) | 8.00 (3.25–10.0) | 4.00 (2.00–10.0) |
Data presented as n (%) and median (interquartile range).
AKI: Acute kidney injury; ARDS: Acute respiratory distress syndrome; CBP: Continuous blood purification; CPR: Cardiopulmonary resuscitation; ECMO: Extracorporeal membrane oxygenation.
Factors influencing the implementation of medical techniques in the ICU
Over the past two decades, four essential medical techniques, including invasive mechanical ventilation, continuous blood purification, bedside ultrasound, and ECMO, have experienced rapid development and become increasingly adopted in ICU settings in Chinese mainland. The factors that independently influenced the implementation of the four techniques are listed in Supplementary Tables S11–S14. After excluding 7 unclassified hospitals from the total of 2005, the analysis included 1998 hospitals. Among these, invasive mechanical ventilation was available in 1963 (98.2%) hospitals.Factors associated with an increased likelihood of implementation of invasive mechanical ventilation were classification as a class III general hospital, location in the East China, the total number of hospital beds, classification as a general ICU, and having a high proportion of admitted patients with APACHE II scores of ≥15 points (Supplementary points Table S11). Separately, continuous blood purification has been implemented in 1728 of 1998 (86.5%) surveyed hospitals. Factors associated with an increased likelihood of implementation of this treatment included classification as a class III general hospital; location in the East China, South China, or North China; classification as a teaching hospital; classification as a general ICU; being an ICU that calculates CMI values; the total number of hospital beds; the total number of ICU beds; the number of annual ICU admissions and having a high proportion of admitted patients with APACHE II scores of ≥15 points (Supplementary Table S12). Bedside ultrasound has been carried out in 1423 of 1998 (71.2%) surveyed hospitals. Class III general hospital status; location in the East China, South China, or North China; being a teaching hospital; having a greater number of hospital beds; having a greater number of ICU beds; having a higher number of annual ICU admissions; and being an ICU that calculates CMI values were associated with a greater likelihood of bedside ultrasound implementation in the ICU (Supplementary Table S13). Finally, ECMO has been performed in 481 of 1998 (24.1%) surveyed hospitals. Class III general hospitals and specialized hospitals, hospitals located in theEast China or South China, teaching hospitals, hospitals with a greater number of beds, ICUs with a greater number of beds and higher annual ICU admissions, and ICUs that calculated CMI values were associated with a higher likelihood of ECMO implementation in the ICU, whereas hospitals located in the North China were associated with a lower likelihood of ECMO implementation in the ICU (Supplementary Table S14).
Discussion
To our knowledge, this is the first comprehensive survey to investigate the current condition of ICUs in Chinese mainland, which considers general information about the investigated hospitals and ICUs, the relationship between ICU bed availability and economic development, the characteristics of intensivists, the spectrum of diseases treated in ICUs, the medical techniques available in ICUs, and the factors that influence the implementation of medical techniques in ICU settings.
The availability of ICU beds is essential for the management of critically ill patients.[9] In 2024, eight Chinese ministries, including the National Health Commission, collaboratively released a statement on enhancing the capacity of critical care medical services. The document stated that, by the end of 2025, the number of ICU beds for critically ill patients in Chinese mainland should reach 15 per 100,000 people. In addition, the proportion of general ICU beds, specialized ICU beds, and convertible ICU beds in tertiary general hospitals, traditional Chinese medicine hospitals, infectious disease hospitals, and children’s specialized hospitals should not be less than 4%, 2%, and 4%, respectively. A study conducted by Yuan et al.[10] revealed that the number of ICU beds and the proportion of ICU beds to hospital beds have significantly increased during the past 15 years in Chinese mainland. Our survey determined that the proportion of ICU beds to hospital beds in Chinese mainland is about 1.7%, which is still far below the minimum level of national standards and the proportion observed in developed nations.[11,12] Consequently, there remains a need for hospitals at all tiers in Chinese mainland to increase the capacity of ICUs. Moreover, although previous studies have suggested a correlation between ICU bed availability and economic factors, our findings show no significant association between the number of critical care beds per 100,000 people and variables such as the GDP, total healthcare expenditure, healthcare expenditure per capita, Health Development Index, or hospital beds per 100,000 people.[13] This suggests that economic factors may have a less substantial impact on the availability of ICU beds than previously reported. Instead, other factors – such as the size of the older population; local healthcare policies; and the uneven distribution of the aging population, where regions with a greater proportion of older individuals experience increased demand for ICU resources – are likely to play a more decisive role.[[14], [15], [16]]
In our study, the allocation of class III general hospitals and critical care resources in Chinese mainland demonstrated a regional imbalance. Economically developed regions in east China have a greater number of class III general hospitals compared with underdeveloped areas like northwest China. Typically, class III general hospitals in Chinese mainland have higher standards for teaching, research, and ICU quality. In line with a previous survey, our survey showed that class III general hospitals were more likely to be teaching hospitals, to calculate CMI values, to have more ICU beds, and to have more annual ICU admissions than other types of hospitals.[17] In addition, the medical teams led by the chief physicians in class III general hospitals typically consist of a greater number of physicians compared with those in class III specialized hospitals or class II hospitals. This staffing arrangement aligns with the requirements that class III general hospitals usually receive more patients with more complex medical conditions. Moreover, our survey revealed that intensivists with doctorates were more likely to work in class III general hospitals. All the above mentioned factors contributed to the imbalance of critical care resources in Chinese mainland. This phenomenon is also present in other Asian countries and regions.[9,13] Therefore, the National Health Commission of China has proposed the “Thousand County Project” to improve critical care services at the county level, potentially mitigating the inequality in the allocation of critical care resources.
With regard to disease spectrum, sepsis or septic shock, severe pneumonia, ARDS, and AKI are common causes of ICU admission both in Chinese mainland and other countries and regions worldwide.[[18], [19], [20]] Nevertheless, Chinese ICUs tend to admit a greater proportion of patients presenting with hypovolemic shock or cardiogenic shock compared with ICUs in other international settings.[18] Conversely, alcohol withdrawal is a more frequent reason for ICU admission in other countries and regions, but not in China.[18] Such diversity in disease spectrum can be attributed to variations in regional economic development, ICU type, and demographics of the population. Similar variations in critical care services are also present in both North America and Western Europe, as previously reported.[11]
Compared with earlier data, more recent data suggest there has been a substantial increase in the implementation of medical techniques in the ICU.[21] Even for advanced techniques such as ECMO, the availability rate has increased from 13.5% in 2015 to 24.1% in 2021.[21] We subsequently studied factors influencing the implementation of four essential medical techniques, including invasive mechanical ventilation, continuous blood purification, bedside ultrasound, and ECMO. Findings revealed that class III general hospitals, located in the East China, and hospitals with a greater number of beds were common drivers of the use of these techniques. This finding aligns with prior research indicating a strong correlation between the availability of ICU equipment and the regional economic level.[21,22] Regions with higher levels of economic development tend to have a greater number of class III general hospitals, which in turn are associated with a higher ICU capacity. Compared to underdeveloped regions such as northwest China, the sustained economic growth and healthcare investment in east China have resulted in the provision of relatively adequate facilities and technologies, resulting in an unequal distribution of medical resources and access to essential medical techniques. In addition, even in the most economically developed areas of Chinese mainland, some ICUs are still not able to use advanced medical devices such as ECMO and intra-aortic balloon pumps, which severely hinders patient rescue. In the future,the accessibility of facility resources and essential medical techniques within ICUs in China is expected to improve.
Strengths and limitations
This study has the following strengths. First, it attained a response rate of 99.1% from intensivists with whom we had established connections. Second, we collected comprehensive descriptive data on the demographic characteristics of surveyed intensivists, the type and capacity of ICUs, the composition of medical teams, disease classification, and available medical techniques, thereby adding new knowledge to previous surveys regarding the status of ICUs in Chinese mainland.[21,23,24] Third, the survey covered 31 provincial regions of Chinese mainland, and its findings are likely representative of the nationwide situation. Such insights may provide valuable implications for China and other countries with similar medical circumstances.
However, there are also several limitations of this study. First, the cross-sectional design of our study precludes the establishment of causal relationships between variables. Subsequent longitudinal and prospective studies are necessary to further investigate the relationships among variables like hospital grade, type, physician team composition, and medical technology availability. Second, since this is the first systematic survey on critical care medicine in Chinese mainland, longitudinal comparative data to elucidate the developmental trajectory of critical care medicine in Chinese mainland are currently lacking. Third, due to the nature of our sampling survey, data on the total number of ICU beds within a specific region were not available. Consequently, calculations of metrics such as per-capita ICU beds were not feasible. Finally, our study only focuses on resource mapping without examining patient-level clinical outcomes or mortality rates, which limits the clinical relevance of the observed disparities. Future studies could incorporate longitudinal data from national health registries to assess how resource disparities impact clinical outcomes over time.
Conclusions
Our study offers an overview of the current state of ICUs in Chinese mainland and thus promotes the full and rational use of our critical care resources. Although there have been notable advancements in Chinese ICUs, persistent challenges related to regional disparities and variations in hospital grades persist.
CRediT authorship contribution statement
Sheng Zhang: Supervision, Investigation, Conceptualization. Jiao Liu: Conceptualization. Hang Qian: Formal analysis, Data curation, Conceptualization. Weifeng Shang: Software, Resources. Xijing Zhang: Project administration, Methodology. Bo Hu: Formal analysis, Conceptualization. Yi Yang: Investigation, Formal analysis. Yuan Xu: Funding acquisition, Formal analysis. Ling Liu: Visualization, Validation. Xiaoting Wang: Methodology, Investigation. Xiuling Shang: Formal analysis, Data curation. Jianfeng Wu: Methodology, Investigation. Xuelian Liao: Validation, Supervision. Fen Liu: Investigation, Formal analysis. Jinglun Liu: Writing – original draft, Visualization, Validation. Changsong Wang: Writing – review & editing, Validation. Qianghong Xu: Validation, Supervision. Yonghao Xu: Methodology, Investigation. Kaijiang Yu: Visualization, Validation. Xiangdong Guan: Visualization, Validation, Supervision. Dechang Chen: Supervision, Funding acquisition.
Acknowledgments
The authors thank all intensivists involved in the study.
Funding
This study was supported by grants from the National Natural Science Foundation of China (grant numbers 82102244, 82172152, 82241044, and 82172154) and the Fundamental Research Funds for the Central Universities (grant number YG2023LC01).
Ethical Statement
Not applicable.
Conflict of Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Given his role as Editor-in-Chief, Associate Editor and Editorial Board Member, Dechang Chen, Jiao Liu, Yi yang and Ling Liu were not involved in the editorial review or the decision to publish this article.
Data Availability
The data sets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.
Managing Editor: Jingling Bao/ Zhiyu Wang
Footnotes
Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.jointm.2025.08.011.
Contributor Information
Kaijiang Yu, Email: drkaijiang@163.com.
Xiangdong Guan, Email: guanxd@mail.sysu.edu.cn.
Dechang Chen, Email: 18918520002@189.cn.
Appendix. Supplementary materials
References
- 1.Martinez R.H., Liu K.D., Aldrich J.M. Overview of the medical management of the critically ill patient. Clin J Am Soc Nephrol. 2022;17(12):1805–1813. doi: 10.2215/CJN.07130622. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Hang Y., Liu L., Chen R., Fan X., Sha F., Wu D., et al. Predicting mortality risk in the intensive care unit using a Hierarchical Inception Network for heterogeneous time series. Biomed Signal Process Control. 2025;107 doi: 10.1016/j.bspc.2025.107759. [DOI] [Google Scholar]
- 3.Phua J., Kulkarni A.P., Mizota T., Hashemian S.M.R., Lee W.Y., Permpikul C., et al. Critical care bed capacity in Asian countries and regions before and during the COVID-19 pandemic: an observational study. Lancet Reg Health West Pac. 2024;44 doi: 10.1016/j.lanwpc.2023.100982. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Yuan L., Xu S., Xu J., Cao J., Qian Z. Variation in intensive care unit beds capacity in China from 2007 to 2021. Intens Care Med. 2024;50(3):472–474. doi: 10.1007/s00134-024-07347-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Sevransky J.E., Agarwal A., Jabaley C.S., Rochwerg B. Standardized care is better than individualized care for the majority of critically ill patients. Crit Care Med. 2021;49(1):151–155. doi: 10.1097/CCM.0000000000004676. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Phua J., Weng L., Ling L., Egi M., Lim C.M., Divatia J.V., et al. Intensive care management of coronavirus disease 2019 (COVID-19): challenges and recommendations. Lancet Respir Med. 2020;8(5):506–517. doi: 10.1016/S2213-2600(20)30161-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.CRIT Care Asia Establishing a critical care network in Asia to improve care for critically ill patients in low- and middle-income countries. Crit Care. 2020;24(1):608. doi: 10.1186/s13054-020-03321-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Donovan A.L., Aldrich J.M., Gross A.K., Barchas D.M., Thornton K.C., Schell-Chaple H.M., et al. Interprofessional care and teamwork in the ICU. Crit Care Med. 2018;46(6):980–990. doi: 10.1097/CCM.0000000000003067. [DOI] [PubMed] [Google Scholar]
- 9.Phua J., Faruq M.O., Kulkarni A.P., Redjeki I.S., Detleuxay K., Mendsaikhan N., et al. Critical care bed capacity in Asian countries and regions. Crit Care Med. 2020;48(5):654–662. doi: 10.1097/CCM.0000000000004222. [DOI] [PubMed] [Google Scholar]
- 10.Yuan L., Xu S., Xu J., Cao J., Qian Z. Variation in intensive care unit beds capacity in China from 2007 to 2021. Intensive Care Med. 2024;50(3):472–474. doi: 10.1007/s00134-024-07347-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Wunsch H., Angus D.C., Harrison D.A., Collange O., Fowler R., Hoste E.A., et al. Variation in critical care services across North America and Western Europe. Crit Care Med. 2008;36(10) doi: 10.1097/CCM.0b013e318186aec8. 2787-93.e1-9. [DOI] [PubMed] [Google Scholar]
- 12.Arabi Y.M., Phua J., Koh Y., Du B., Faruq M.O., Nishimura M., et al. Structure, organization, and delivery of critical care in Asian ICUs. Crit Care Med. 2016;44(10):e940–e948. doi: 10.1097/CCM.0000000000001854. [DOI] [PubMed] [Google Scholar]
- 13.Phua J., Faruq M.O., Kulkarni A.P., Redjeki I.S., Detleuxay K., Mendsaikhan N., et al. Critical care bed capacity in Asian countries and regions. Crit Care Med. 2020;48(5):654–662. doi: 10.1097/CCM.0000000000004222. [DOI] [PubMed] [Google Scholar]
- 14.Luo F., Huang Y., Jiang L., Fan Q., Gou Z. Ethnic disparities and temporal trends in health resource allocation: a retrospective decadal analysis in Sichuan, a multi-ethnic Province of Southwest China (2009-2019) BMC Health Serv Res. 2024;24(1):541. doi: 10.1186/s12913-024-11036-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Zhou Y., Zhao K., Han J., Zhao S., Cao J. Geographical pattern evolution of health resources in China: spatio-temporal dynamics and spatial mismatch. Trop Med Infect Dis. 2022;7(10):292. doi: 10.3390/tropicalmed7100292. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Leon-Villapalos C., Wells M., Brett S. Exploratory study of staff perceptions of shift safety in the critical care unit and routinely available data on workforce, patient and organisational factors. BMJ Open. 2020;10(6) doi: 10.1136/bmjopen-2019-034101. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Li Z., Ma X., Gao S., Li Q., Luo H., Sun J., et al. Association between hospital and ICU structural factors and patient outcomes in China: a secondary analysis of the National Clinical Improvement System Data in 2019. Crit Care. 2022;26(1):24. doi: 10.1186/s13054-022-03892-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Nawaz F.A., Deo N., Surani S., Maynard W., Gibbs M.L., Kashyap R. Critical care practices in the world: results of the global intensive care unit need assessment survey 2020. World J Crit Care Med. 2022;11(3):169–177. doi: 10.5492/wjccm.v11.i3.169. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Li M., Huang P., Xu W., Zhou Z., Xie Y., Chen C., et al. Risk factors and a prediction model for sepsis: a multicenter retrospective study in China. J Intensive Med. 2022;2(3):183–188. doi: 10.1016/j.jointm.2022.02.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Coopersmith C.M. Future directions in sepsis research. J Intensive Med. 2025;5(3):211–213. doi: 10.1016/j.jointm.2025.03.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Yin H., Wang S., Zhu Y., Zhang R., Ye X., Wei J., et al. The development of critical care medicine in China: from SARS to COVID-19 pandemic. Crit Care Res Pract. 2020;2020 doi: 10.1155/2020/3956732. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Vincent J-L. Critical care - where have we been and where are we going? Crit Care. 2013;17(1):S2. doi: 10.1186/cc11500. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Rui X., Dong F., Ma X., Su L., Shan G., Guo Y., et al. Quality metrics and outcomes among critically ill patients in China: results of the national clinical quality control indicators for critical care medicine survey 2015-2019. Chin Med J (Engl) 2022;135(9):1064–1075. doi: 10.1097/CM9.0000000000001933. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Liu H., Tian Y., Jiang B., Song Y., Du A., Ji S. Early mobilisation practice in intensive care units: a large-scale cross-sectional survey in China. Nurs Crit Care. 2023;28(4):510–518. doi: 10.1111/nicc.12896. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data sets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.