Introduction
Total knee arthroplasty (TKA) is a safe and cost-effective musculoskeletal surgical procedure for relieving pain and improving function and health-related quality of life for patients with end-stage knee arthritis.[1] As one of the most commonly performed procedures, the number of TKAs performed each year has exceeded 1.5 million in data collected from ten national joint registers and has been rapidly increasing.[2,3] The increased demands pose a challenge for the health care system from a quality and finance perspective.[4] With the development of enhanced recovery after surgery (ERAS), surgeons and hospitals have made great efforts in reducing the length of stay (LOS) and inpatient charges to alleviate the financial burden without sacrificing the quality of care.[5] Therefore, understanding the patterns of LOS and inpatient charges and identifying their determinants may provide a reference for quality improvement and the relief of economic burden.
With advances in surgical techniques and early mobilization, the LOS has significantly decreased in recent decades.[6] Previous published studies have reported on LOS statistics and its associated factors.[7-9] However, most of these studies were conducted in high-income countries, where fairly large numbers of patients are likely discharged to extended-care facilities after surgery.[2,10] It has been claimed that the decrease in LOS may be due to this type of transfer.[11] Little information is available on LOS and charges of TKA in low- or intermediate-income countries.
In China, the largest low- or intermediate-income country, there are over 150 million Chinese individuals who are 65 years or older.[12] As the rapid aging of China's population continues, the demand for TKA has also been increasing remarkably.[13] Such a situation and its associated costs for hospitalization may place a huge challenge on patients and the health care system. Patients are barely discharged to extended-care facilities due to a shortage of primary care resources and different postoperative rehabilitative care deliveries,[14] which results in the LOS and hospitalization-associated costs of TKA in China being higher than those of high-income countries, while also being more representative of actual resource utilization. In 2016, China began to promote ERAS and price reform for medical services in order to optimize resource utilization.[15,16] To our knowledge, there are no relevant data available on the corresponding effects and changes. Furthermore, there have been no national studies on the LOS and inpatient charges following TKA in China. Therefore, in this study, we used data from a large patient-level national database (the Hospital Quality Monitoring System [HQMS]) to study the patterns and changes of LOS and inpatient charges, as well as to identify their determinants.
Methods
Ethical approval
This study was authorized by the HQMS Committee Board and approved by the ethics committee of Xiangya Hospital (No. 2017121016), with waiver of informed consent. All procedures were conducted in accordance with the Declaration of Helsinki.
Data source
The HQMS database was accessed for this study. The HQMS contained inpatient data from 230.4 million patients from tertiary hospitals across all 31 provincial-level administrative regions in the mainland of China until 2019. From the year 2013, tertiary hospitals have been mandated to automatically submit their inpatient discharge records to HQMS on a daily basis. We combined 7 years of HQMS data from 2013 to 2019. Data in HQMS included demographic factors and hospitalization information. Previous literature had widely discussed the methodology used by HQMS.[17,18]
Identification of TKA
Procedures of primary TKA in the HQMS were identified by using procedure code 81.54 according to the International Classification of Diseases, ninth Revision, Clinical Modification (ICD-9-CM). To minimize the possibility miscode, we also searched other knee-related procedure codes, diagnosis codes, and free texts to verify TKA. The following exclusion criteria were applied: (1) lack of basic demographic information, such as age and sex, (2) patients who received partial knee arthroplasty, (3) patients who received bilateral TKA, (4) patients who received TKA for non-elective indication (i.e., neoplasm, infection, or fracture),[19] (5) lack of information about the LOS and the inpatient charges, and (6) patients who had a LOS longer than 60 days [Supplementary Figure 1, https://links.lww.com/CM9/B286].
Study variables
During each hospitalization, sociodemographic factors (such as age, sex, and marital status) were collected. In addition, clinical care information of hospitalization, including name of hospital, date of hospitalization, primary indication for surgery, health care services that were received, and comorbidities (the ICD-10 diagnostic code for each disease), was also recorded.
Outcome measurements
Our primary outcome was the LOS after the surgical procedure (hereafter referred to as LOS) and inpatient charges. The admission-to-surgery interval, inpatient charges for implants and materials, surgery, anesthesia, nursing, physiotherapy and rehabilitation, medication, laboratory, and radiology were also collected.
Statistical analysis
We divided the age at the time of TKA into four categories: <60 years, 60 to 69 years, 70 to 79 years, and ≥80 years. Marital status was grouped into two categories: married and single (i.e., never married, divorced, or widowed). We divided the indications for TKA into two categories: osteoarthritis and non-osteoarthritis (e.g., rheumatoid arthritis, osteonecrosis, and other knee disorders). Based on the recorded comorbidities, we calculated the Charlson comorbidity index (CCI)[20] for each patient and divided it into three categories: 0, 1 to 2, and ≥3.[7,18] The geographic regions of the hospitals where TKA was performed were as follows: North, East, North-East, South-Central, South-West, and North-West regions.[21] The hospitals were grouped into two types: provincial and non-provincial. Furthermore, according to the procedures performed every year, the hospital volume for TKA (cases/year) was categorized into three groups: <250 cases/year, 250 to 500 cases/year, and >500 cases/year.[22]
We described the characteristics of patients according to the year in which TKA was performed. Furthermore, we calculated LOS and inpatient charges according to sociodemographic factors, indications for TKA, comorbidities, hospital geographic regions, hospital types, and hospital volume.
LOS and inpatient charges were log-transformed to account for the skewed nature of the distributions and to stabilize the variance of residuals, and it was analyzed with linear regression models with an absorbed variable. The coefficients were converted to odds ratios (ORs) using an exponential transformation.[23] In the multivariable-adjusted linear regression model, we first adjusted for age and sex and subsequently added other covariates, including marital status, primary indication, comorbidity, geographic location, hospital type, and hospital volume, into the regression model.
All statistical analyzes were performed using SAS 9.4 (SAS Institute Inc., Cary, NC, USA), and a P value <0.05 was considered statistically significant.
Results
In total, 220,557 knee arthroplasty procedures were recorded in the HQMS. Of them, 1634 procedures were excluded due to missing sex or age data. A total of 12,311 partial knee arthroplasties were excluded. Moreover, 4921 were excluded due to non-elective surgeries, and 11,752 had received bilateral TKA. A total of 2621 procedures were unable to calculate the LOS, 2775 were unable to extract charge information, and 180 had a LOS longer than 60 days. Therefore, the final sample in the analysis consisted of 184,363 TKAs. The patients’ characteristics are summarized in Table 1.
Table 1 -
Characteristics of 184,363 TKA procedures in HQMS in
China, 2013 to 2019.
| Characteristics |
2013 |
2014 |
2015 |
2016 |
2017 |
2018 |
2019 |
Total |
| Number of procedures |
16,835 |
23,561 |
25,581 |
28,263 |
30,017 |
30,233 |
29,873 |
184,363 |
| Age, mean (SD) (years) |
66.2 (8.5) |
66.2 (8.5) |
66.7 (8.2) |
66.9 (8.1) |
67.2 (8.0) |
67.1 (7.8) |
67.3 (7.8) |
66.9 (8.1) |
| Age (year) (%) |
|  <60 |
20.6 |
19.9 |
17.5 |
16.2 |
14.7 |
14.4 |
14.4 |
16.4 |
|  60–69 |
42.2 |
43.5 |
44.1 |
45.2 |
46.1 |
47.9 |
46.5 |
45.4 |
|  70–79 |
33.5 |
32.6 |
33.9 |
33.8 |
34.1 |
32.9 |
34.1 |
33.6 |
|  ≥80 |
3.8 |
4.1 |
4.6 |
4.8 |
5.1 |
4.8 |
5.0 |
4.7 |
| Sex (%) |
|  Female |
79.3 |
79.0 |
78.6 |
78.3 |
76.7 |
77.2 |
77.1 |
77.9 |
|  Male |
20.7 |
21.0 |
21.4 |
21.7 |
23.3 |
22.8 |
22.9 |
22.1 |
| Marital status (%) |
|  Married |
92.2 |
93.1 |
92.3 |
91.4 |
92.0 |
92.5 |
93.0 |
92.4 |
|  Single |
4.7 |
4.6 |
5.0 |
5.7 |
4.7 |
5.3 |
5.4 |
5.1 |
|  Unknown |
3.1 |
2.3 |
2.7 |
2.9 |
3.2 |
2.1 |
1.6 |
2.5 |
| Primary indication (%) |
|  Osteoarthritis |
92.6 |
93.1 |
93.4 |
93.9 |
93.7 |
93.8 |
93.8 |
93.5 |
|  Non-osteoarthritis |
7.4 |
6.9 |
6.6 |
6.1 |
6.3 |
6.2 |
6.2 |
6.5 |
| CCI (%) |
|  0 |
76.3 |
76.9 |
75.4 |
74.7 |
77.1 |
74.7 |
72.9 |
75.3 |
|  1–2 |
22.7 |
21.9 |
23.3 |
24.3 |
21.9 |
23.6 |
25.3 |
23.4 |
|  ≥3 |
1.0 |
1.3 |
1.3 |
1.0 |
1.1 |
1.7 |
1.9 |
1.3 |
| Geographic region (%) |
|  North |
31.4 |
22.9 |
20.3 |
21.6 |
17.6 |
18.9 |
20.4 |
21.2 |
|  East |
35.3 |
38.9 |
40.4 |
40.8 |
45.7 |
44.8 |
38.6 |
41.1 |
|  North-East |
5.1 |
5.7 |
5.4 |
4.7 |
4.3 |
3.9 |
2.6 |
4.4 |
|  South-Central |
14.8 |
18.4 |
20.0 |
17.8 |
18.2 |
19.2 |
22.2 |
18.9 |
|  South-West |
6.7 |
7.8 |
7.2 |
8.2 |
9.2 |
5.8 |
6.8 |
7.4 |
|  North-West |
6.7 |
6.4 |
6.7 |
6.9 |
4.9 |
7.4 |
9.5 |
7.0 |
| Hospital type (%) |
|  Provincial |
72.2 |
63.4 |
63.0 |
62.3 |
56.8 |
58.4 |
51.8 |
60.2 |
|  Non-provincial |
27.8 |
36.6 |
37.0 |
37.7 |
43.2 |
41.6 |
48.3 |
39.8 |
| Hospital volume∗ (cases/year) (%) |
|  >500 |
34.7 |
26.2 |
24.9 |
25.0 |
22.8 |
19.5 |
14.3 |
23.0 |
|  250–500 |
20.8 |
19.2 |
19.6 |
20.5 |
19.6 |
21.5 |
22.7 |
20.6 |
|  <250 |
44.5 |
54.7 |
55.5 |
54.5 |
57.6 |
59.0 |
63.0 |
56.4 |
∗Annual hospital volume for TKA procedures.CCI: Charlson comorbidity index; HQMS: Hospital Quality Monitoring System; SD: Standard deviation; TKA: Total knee arthroplasty.
LOS
The mean LOS of all the TKAs was 10.3 days. The LOS decreased from 10.8 days in 2013 to 9.3 days in 2019 (P for trend <0.001). The mean admission-to-surgery interval decreased from 4.6 days in 2013 to 4.2 days in 2019 (P for trend <0.001) [Figure 1]. The results of the multi-regression analysis on the association of perioperative factors with LOS are shown in Table 2. Single patients more easily had longer LOS than married patients (OR: 1.02, 95% confidence interval [CI]: 1.01–1.02). As the CCI increased, patients had longer LOS (P for trend <0.001). Furthermore, patients who received TKA for non-osteoarthritis disease had a higher risk of longer LOS (OR: 1.05, 95% CI: 1.05–1.06). Regarding hospital-related factors, we found that the hospital's geographic region contributed greatly to the distribution of LOS. Patients in North and East regions had the shortest LOS (9.2 and 9.4 days, respectively), and patients in South-Central region had the longest LOS (12.8 days). Patients in non-provincial hospitals had a longer LOS (OR: 1.19, 95% CI: 1.18–1.19). As the hospital volume increased, patients had shorter LOS (P for trend <0.001).
;)
Figure 1: LOS and admission-to-surgery interval of TKA from 2013 to 2019. LOS: Length of stay; TKA: Total knee arthroplasty.
Table 2 -
LOS and its associated factors of TKA.
| Preoperative factors |
LOS (mean, days) |
Crude OR (95% CI) |
Age- and sex-adjusted OR (95% CI) |
Multivariable adjusted OR (95% CI)∗
|
| Calendar year |
|  2013 |
10.8 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  2014 |
11.2 |
1.06 (1.05, 1.07) |
1.06 (1.05, 1.07) |
0.98 (0.98, 0.99) |
|  2015 |
10.9 |
1.03 (1.02, 1.04) |
1.03 (1.02, 1.04) |
0.95 (0.95, 0.96) |
|  2016 |
10.3 |
0.98 (0.97, 0.99) |
0.98 (0.97, 0.99) |
0.91 (0.90, 0.91) |
|  2017 |
10.0 |
0.95 (0.94, 0.96) |
0.95 (0.94, 0.96) |
0.85 (0.85, 0.86) |
|  2018 |
9.6 |
0.92 (0.91, 0.93) |
0.92 (0.91, 0.93) |
0.82 (0.81, 0.82) |
|  2019 |
9.3 |
0.89 (0.88, 0.89) |
0.89 (0.88, 0.89) |
0.75 (0.75, 0.76) |
|  
P for trend |
– |
<0.001 |
<0.001 |
<0.001 |
| Sex |
|  Female |
10.2 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  Male |
10.3 |
1.00 (1.00, 1.01) |
1.01 (1.00, 1.01) |
1.00 (1.00, 1.01) |
| Age (year) |
|  <60 |
10.5 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  60–69 |
10.2 |
0.97 (0.97, 0.98) |
0.97 (0.97, 0.98) |
0.98 (0.97, 0.98) |
|  70–79 |
10.2 |
0.97 (0.96, 0.97) |
0.97 (0.96, 0.97) |
0.98 (0.98, 0.99) |
|  ≥80 |
10.8 |
1.01 (1.00, 1.02) |
1.01 (0.99, 1.02) |
1.01 (1.00, 1.02) |
|  
P for trend |
– |
<0.001 |
<0.001 |
0.321 |
| Marital status |
|  Married |
10.3 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  Single |
10.5 |
1.01 (1.00, 1.02) |
1.01 (1.00, 1.02) |
1.02 (1.01, 1.02) |
| Primary indication |
|  Osteoarthritis |
10.2 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  Non-osteoarthritis |
11.2 |
1.08 (1.07, 1.09) |
1.08 (1.07, 1.09) |
1.05 (1.05, 1.06) |
| CCI |
|
|
|
|
|  0 |
10.1 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  1–2 |
10.8 |
1.07 (1.06, 1.07) |
1.07 (1.06, 1.08) |
1.03 (1.02, 1.03) |
|  ≥3 |
12.2 |
1.19 (1.17, 1.22) |
1.20 (1.18, 1.22) |
1.06 (1.04, 1.08) |
|  
P for trend |
|
<0.001 |
<0.001 |
<0.001 |
| Geographic region |
|  North |
9.2 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  East |
9.4 |
1.03 (1.02, 1.04) |
1.03 (1.02, 1.04) |
0.97 (0.97, 0.97) |
|  North–East |
11.6 |
1.28 (1.26, 1.29) |
1.28 (1.26, 1.29) |
1.05 (1.04, 1.06) |
|  South–Central |
12.8 |
1.41 (1.41, 1.42) |
1.41 (1.41, 1.42) |
1.08 (1.07, 1.08) |
|  South–West |
10.6 |
1.13 (1.12, 1.14) |
1.13 (1.12, 1.14) |
1.00 (0.99, 1.00) |
|  North–West |
10.4 |
1.15 (1.14, 1.16) |
1.15 (1.14, 1.16) |
1.00 (0.99, 1.01) |
|  
P-value |
– |
<0.001 |
<0.001 |
<0.001 |
| Hospital type |
|  Provincial |
8.5 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  Non-provincial |
13.0 |
1.54 (1.53, 1.54) |
1.54 (1.53, 1.54) |
1.19 (1.18, 1.19) |
| Hospital volume†(cases/year) |
|
|
|
|
|  >500 |
5.5 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  250–500 |
9.3 |
1.55 (1.54, 1.56) |
1.55 (1.54, 1.56) |
1.47 (1.46, 1.48) |
|  <250 |
12.6 |
2.06 (2.05, 2.06) |
2.05 (2.05, 2.06) |
1.79 (1.78, 1.80) |
|  
P for trend |
– |
<0.001 |
<0.001 |
<0.001 |
∗Adjusted for age, sex, marital status, primary indication, CCI, geographic region, hospital type, and hospital volume.
†Annual hospital volume for TKA procedures.CCI: Charlson comorbidity index; CI: Confidence interval; LOS: Length of stay; OR: Odds ratio; TKA: Total knee arthroplasty.
Inpatient charges
The mean inpatient charges were 61,208.3 Chinese Yuan (CNY), and implant and material charges (40,578.9 CNY) accounted for nearly two-thirds of all the inpatient charges. Inpatient charges reached a peak in 2016, after which they showed a trend of gradual decrease (P for trend <0.001). Similarly, implant and material charges, as well as medication charges, also showed a significant downward trend since 2016 [Figure 2A,B]. Labor-related charges (surgery, anesthesia, nursing, physiotherapy, and rehabilitation) accounted for a lower percentage of the total charges but exhibited a gradual increase (P for trend all <0.001) [Figure 2B].
Figure 2: Specific inpatient charges of TKA from 2013 to 2019. (A) Total charges and charges for implant and material; (B) Other specific charges. TKA: Total knee arthroplasty.
Male (OR: 0.99, 95% CI: 0.98–0.99) was associated with lower inpatient charges. Younger age (P for trend <0.001) and single marital status (OR: 1.01, 95% CI: 1.01–1.02) were associated with higher inpatient charges. Non-osteoarthritis indications were associated with higher inpatient charges (OR: 1.04, 95% CI: 1.03–1.04). As the CCI increased, patients had higher inpatient charges (P for trend <0.001). In terms of hospital-related factors, we found that there was also an apparent variety between different hospital geographic regions. The East region had the lowest inpatient charges (57,890.4 CNY), and North-East region had the highest charges (73,844.4 CNY). Compared with hospital volume of >500 cases/year, lower hospital volume was associated with more inpatient charges (P for trend = 0.001). Furthermore, non-provincial hospitals were associated with lower inpatient charges (OR: 0.86, 95% CI: 0.86–0.87) [Table 3].
Table 3 -
Inpatient charges and its associated factors of TKA.
| Preoperative factors |
Inpatient charges (mean, CNY) |
Crude OR (95% CI) |
Age- and sex-adjusted OR (95% CI) |
Multivariable adjusted OR (95% CI)∗
|
| Calendar year |
|  2013 |
60,618.5 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  2014 |
62,317.7 |
1.02 (1.01, 1.03) |
1.02 (1.01, 1.03) |
1.03 (1.02, 1.03) |
|  2015 |
62,717.4 |
1.03 (1.02, 1.04) |
1.03 (1.02, 1.04) |
1.04 (1.03, 1.05) |
|  2016 |
63,039.1 |
1.04 (1.03, 1.04) |
1.04 (1.03, 1.04) |
1.05 (1.04, 1.06) |
|  2017 |
60,534.6 |
0.99 (0.98, 1.00) |
0.99 (0.98, 1.00) |
1.01 (1.00, 1.02) |
|  2018 |
59,132.8 |
0.96 (0.95, 0.97) |
0.96 (0.96, 0.97) |
0.98 (0.97, 0.98) |
|  2019 |
60,418.7 |
0.98 (0.98, 0.99) |
0.99 (0.98, 0.99) |
1.00 (1.00, 1.01) |
|  
P for trend |
|
<0.001 |
<0.001 |
<0.001 |
| Sex |
|  Female |
61,440.2 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  Male |
60,391.3 |
0.98 (0.98, 0.98) |
0.98 (0.98, 0.99) |
0.98 (0.98, 0.99) |
| Age (year) |
|  <60 |
63,604.5 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  60–69 |
60,998.3 |
0.97 (0.96, 0.97) |
0.97 (0.96, 0.97) |
0.98 (0.98, 0.98) |
|  70–79 |
60,415.1 |
0.96 (0.96, 0.97) |
0.97 (0.96, 0.97) |
0.98 (0.97, 0.98) |
|  ≥80 |
60,515.5 |
0.97 (0.96, 0.98) |
0.98 (0.97, 0.98) |
0.99 (0.98, 0.99) |
|  
P for trend |
|
<0.001 |
<0.001 |
<0.001 |
| Marital status |
|  Married |
61,085.8 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  Single |
63,510.0 |
1.03 (1.03, 1.04) |
1.04 (1.03, 1.04) |
1.02 (1.01, 1.02) |
| Primary indication |
|
|
|
|
|  Osteoarthritis |
60,961.7 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  Non-osteoarthritis |
64,776.2 |
1.05 (1.04, 1.05) |
1.04 (1.03, 1.05) |
1.04 (1.03, 1.04) |
| CCI |
|  0 |
61,150.6 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  1–2 |
61,229.6 |
1.00 (1.00, 1.01) |
1.00 (1.00, 1.01) |
1.00 (1.00, 1.00) |
|  ≥3 |
64,113.4 |
1.04 (1.03, 1.06) |
1.05 (1.04, 1.07) |
1.05 (1.04, 1.07) |
|  
P for trend |
|
<0.001 |
<0.001 |
<0.001 |
| Geographic region |
|  North |
62,682.1 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  East |
57,890.4 |
0.93 (0.93, 0.94) |
0.93 (0.93, 0.94) |
0.94 (0.93, 0.94) |
|  North–East |
73,844.4 |
1.17 (1.16, 1.18) |
1.17 (1.16, 1.18) |
1.10 (1.09, 1.11) |
|  South–Central |
64,424.0 |
1.02 (1.01, 1.02) |
1.02 (1.01, 1.02) |
1.02 (1.02, 1.03) |
|  South–West |
59,483.6 |
0.95 (0.94, 0.96) |
0.95 (0.94, 0.95) |
0.95 (0.94, 0.95) |
|  North–West |
61,352.8 |
0.95 (0.94, 0.96) |
0.95 (0.94, 0.96) |
0.91 (0.90, 0.91) |
|  
P-value |
|
<0.001 |
<0.001 |
<0.001 |
| Hospital type |
|  Provincial |
63,755.2 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  Non-provincial |
57,358.0 |
0.89 (0.88, 0.89) |
0.89 (0.88, 0.89) |
0.86 (0.86, 0.87) |
| Hospital volume†(cases/year) |
|  >500 |
59,555.4 |
1.00 (Reference) |
1.00 (Reference) |
1.00 (Reference) |
|  250–500 |
63,999.4 |
1.05 (1.05, 1.06) |
1.05 (1.05, 1.06) |
1.08 (1.07, 1.08) |
|  <250 |
60,864.2 |
1.00 (0.99, 1.00) |
1.00 (0.99, 1.00) |
1.07 (1.06, 1.08) |
|  
P for trend |
|
<0.001 |
<0.001 |
0.001 |
∗Adjusted for age, sex, marital status, primary indication, CCI, geographic region, hospital type, and hospital volume.
†Annual hospital volume for TKA procedures.CCI: Charlson comorbidity index; CI: Confidence interval; OR: Odds ratio; TKA: Total knee arthroplasty.
Sub-analysis
In a sub-analysis [Supplementary Tables 1, https://links.lww.com/CM9/B286 and 2, https://links.lww.com/CM9/B286] of age range, geographic region, hospital type, and hospital volume in every year by the same models, the results were generally similar.
Discussion
By using data collected from the HQMS (a comprehensive Chinese national database), we observed that the mean LOS following TKA in China was relatively long, as well as the fact that implant and material charges accounted for the majority of the inpatient charges. Additionally, as time went by, the LOS showed a decreasing trend, and the implant and material charges were within a descending channel. Both patient and hospital characteristics had effects on LOS and inpatient charges.
Compared with previous studies in developed countries,[1,7,8,10] the LOS in China was relatively long. In China, rehabilitative care is limited only to clinical settings,[14] and primary care (such as residential care facilities) are not as prevalent as they are in high-income countries.[24,25] From the patients’ perspectives, they are more willing to stay longer in hospital rather than be referred to primary health-care institutions, due to the tendency for more professional care in that setting.[25] With the rising incidence of TKA, considerable efforts have been made to optimize perioperative management in China. From the year 2016, China has been heavily promoting ERAS.[15] Accordingly, we were encouraged to observe that LOS and the admission-to-surgery interval had been steadily decreasing.
We observed that the mean inpatient charges were 61,208 CNY, which were roughly close to the GDP per capita in China in recent years (65,534 CNY in 2018).[26] Fortunately, inpatient charges have been exhibiting a downward trend alongside the decreasing LOS since 2016, as reducing LOS has been proven to be a successful approach to slowing the pace of the increase in costs for joint arthroplasty.[4] In addition to the merit of decreased LOS, another crucial reason may be the downregulation of orthopedic implants, as the charges for implants and materials accounted for approximately 60% to 70% of the total inpatient charges, and the changing trend from 2013 to 2019 was exactly coincided with the total inpatient charges. Moreover, medication charges also showed a downward trend, whereas charges for surgery, anesthesia, nursing, physiotherapy, and rehabilitation gradually increased. The previously mentioned changes were particularly pronounced during the time period from 2016 to 2017, which reflected the price reform for medical services that was implemented in 2016.[16] The reform aimed to reduce the prices of implants and medication, thus raising the relative proportion of labor charges. However, charges for surgery and nursing still accounted for only a small proportion of the total charges, while implants and materials accounted for nearly two-thirds of the total charges in 2019.
In the United States, implants accounted for 23% to 40% of the total costs of TKA and personnel costs accounted for over a half of all costs.[27,28] The relatively high implant and material charges and low labor charges in China may be due to several reasons. First, the personnel costs in the United States and other Western countries are relatively higher than those in China. Second, most of the prostheses used in China are imported prostheses, which are accompanied by high taxes, and there are no similar volume pricing and negotiated discounts as in the United States. With the development of domestic prostheses, the increasing procedure volume, and the implementation of centralized procurement,[29] it is foreseeable that the mean expenditures of prostheses will continue to decline. Moreover, implant and medication charges were attributed to most of the substantial out-of-pocket costs in China.[24] In this case, patients’ financial burden will be evidently relieved if implant and material charges are substantially reduced.
Age has been a frequently investigated factor.[7,8,10] In this study, older age was associated with lower inpatient charges. We speculate that older patients pose a lower demand for durability and function than younger patients.[30] They may prefer implants with lower costs, as joint arthroplasty is still an expensive operation in China, and the out-of-pocket costs are higher than those in most industrialized countries.[24] Similar to previous studies, we also found that female sex, single marital status, high CCI, and non-osteoarthritis were associated with increased resource utilization.[9,31] We observed that the prevalence of some risk factors, such as single marital status and CCI, appeared to increase during the study period. Thus, it is important to identify patients with those risk factors and to allocate them to targeted care pathways in advance.
Patients in very high-volume hospitals tend to have shorter LOS and lower inpatient charges. As previously reported, provider-level characteristics, particularly hospital volume, had a greater impact on LOS.[9] Generally, a short LOS is always associated with ideal outcomes, fewer complications and higher patient satisfaction.[7,32] Hospitals with strong specialization usually provide more trained surgeons and comprehensive medical care, which results in better outcomes.[33,34] With the prevalence of those hospitals consistently increasing, the hospitals have been forced to adopt various measures to shorten LOS, in order to release bed capacity.[35] Further, we were glad to observe that the proportion of patients receiving TKA in non-provincial and low-volume hospitals was increasing gradually, which manifested that TKA utilization had expanded during recent years and patients’ access to professional TKA resources was improved.
Moreover, geographical disparities in resource utilization have been observed to exist, which have also been documented in other previous studies.[7,9] China's rapid economic development has been accompanied by a considerable increase in regional inequalities, which includes disparities in health care. This disparity has eventually resulted in differences in supply-side inputs into the health system and health care access for the residents.[36] Our findings indicated that it is also of great importance to reduce the regional gap while also promoting overall resource utilization to realize the regional sharing of health care resource growth dividends.
Several strengths of our study are noteworthy. This is the first study that assessed the LOS and inpatient charges for hospitalization of TKA by using a national database in China. Moreover, we observed that the LOS, overall inpatient charges, and implant charges gradually decreased, which was consistent with current policies. Third, due to the fact that patients in China are rarely discharged to extended care facilities, the LOS and associated charges were more representative of the actual resource utilization of TKA. Finally, we further explored the potentially influential factors that were associated with LOS and inpatient charges. These findings were expected to provide evidence-based implications for relative policy-making and practice improvements to ensure efficient health care utilization.
Admittedly, this study had several limitations. First, when considering the general defect of administrative databases, there may be the possibility of errors in data entry during encoding. However, the accuracy of administrative codes for identifying joint arthroplasty has been well validated.[37] Second, there was no detailed information regarding the specific brand or type of implants, thus limiting us from assessing the relative charges of different types of implants. Third, further exploration of potentially influential clinical factors, such as laboratory data, imaging results, and detailed surgical procedures, was limited, as they were not accessible in HQMS.
By using a national database, we found that the LOS following TKA in China appeared to be long but had been decreasing during the time period from 2013 to 2019. The inpatient charges dominated by implant and material charges were observed to be in a downward trend. However, there were apparent sociodemographic and hospital-related discrepancies of resource utilization. The observed statistics can lead to a more efficient resource utilization of TKA in China.
Funding
This work was supported by grants from the National Natural Science Foundation of China (No.81930071), the Project Program of National Clinical Research Center for Geriatric Disorders (Xiangya Hospital, No.2020LNJJ03), the Science and Technology Program of Hunan Province (No.2019RS2010), and the Fundamental Research Funds for the Central Universities of Central South University (No.2019zzts351).
Conflicts of interest
None.
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