Abstract
Background
The use of coronary artery bypass grafting (CABG) surgery in China is growing, but little is known about hospital-level performance. We sought to characterize the variation in performance across hospitals participating in a national registry in China.
Methods and results
The study sample was drawn from the Chinese Cardiac Surgery Registry (CCSR), a national multi-center database that includes 43 hospitals across 13 provinces and 4 direct-controlled municipalities in China. We assessed consecutive patients undergoing isolated CABG surgery during the period of January 1, 2007 through December 31, 2008. Hierarchical generalized linear models were used to estimate hospital-level risk-standardized in-hospital all-cause mortality rates (RSMR) and major complication rates (RSMCR), which included death, myocardial infarction, reoperation for bleeding, mediastinal infection, stroke, re-intubation, and renal failure. Among 8739 patients who underwent isolated CABG surgery, the mean age was 62.2 years (Standard Deviation [SD]=9.2) and 78% were male. Observed in-hospital mortality and complication rates were 2.2% (95% Confidence Interval [CI], 1.9%–2.5%) and 6.6% (95% CI, 6.1%–7.1%) respectively. The mean RSMR was 1.9% (SD=1.1) with a range of 0.7% to 5.8%, and the mean RSMCR was 6.4% (SD=1.5) with a range of 3.8% to 10.1%. The odds of dying and the odds of having a complication after CABG surgery at a hospital one SD below the average relative to a hospital one SD above the average were 2.06 (95% CI, 1.40–3.04) and 1.53 (95% CI, 1.31–1.79) respectively. The Eastern region had the lowest RSMR and RSMCR (1.6% and 5.8%, respectively), whereas the Central region had the highest RSMR (2.5%) and the Southern region had the highest RSMCR (7.7%).
Conclusions
Mortality and complication rates after CABG surgery in the Chinese Cardiac Surgery Registry are generally low but vary by hospital and region within China. These results suggest that there are opportunities to improve outcomes in some CABG facilities.
Keywords: CABG, outcomes research
INTRODUCTION
Cardiovascular disease is a leading cause of death in China. There are projections of additional substantial increases in its incidence and prevalence as the population ages and the economy grows 1, 2. As the use of coronary artery bypass graft (CABG) surgery increases in China, there is a concomitant need to track the quality of care across hospitals and regions to evaluate performance, and to ensure equity in the access to high quality care. In the United States, the Society for Thoracic Surgeons has documented variation in patient outcomes after CABG 3. Such studies, lacking in China, can reveal whether hospitals across the country are achieving good and uniform results, and if not, may provide insights in how to improve care.
Accordingly, we sought to assess the quality of CABG surgery by examining in-hospital mortality and complication rates for a large sample of hospitals that perform CABG surgery in China. To address this issue we used the Chinese Cardiac Surgery Registry (CCSR) to evaluate CABG outcomes in China. The CCSR, funded by the Chinese government in 2004, is the largest CABG registry in China.
METHODS
Data source
The study sample was drawn from the CCSR, a multicenter registry, launched in 2004, with the primary purpose of evaluating surgical outcomes in patients undergoing cardiac surgery. The registry is overseen by a steering committee that includes cardiac surgeons and researchers from Fuwai Hospital, a hospital affiliated with the Peking Union Medical College in Beijing, China. Funding for the registry comes from the Chinese government as part of the National Science & Technology Pillar Program during the Eleventh Five-Year Plan Period.
At the beginning of the registry a telephone survey sponsored by CCSR committee was conducted to obtain annual surgery volume information of each cardiac center in order to decide which centers should be included. The center address list was provided by Chinese Society for Thoracic and Cardiovascular Surgery. According to the results of CCSR survey, there were 601 hospitals rendering services in the field of cardiac surgery and 268 had an annual cardiac surgery volume of more than 100. These 268 centers were clustered in twenty five provinces and four directly controlled municipalities (of which the administrative ranking is equal to a province). The invitation to take part in the registry was limited to these 268 centers. A total of 43 centers from thirteen provinces and four directly controlled municipalities agreed to participate in the CCSR. Patients were evenly distributed among the thirteen provinces and four directly controlled municipalities representing various stages of economic development. Based on the survey, we estimate that the registry includes about 25% of the total isolated CABG surgeries performed in China. The participating institutions vary by geographic and administrative boundaries in thirteen provinces and four direct controlled municipalities (Figure 1).
Figure 1.
Geographic distribution of the 43 heart centers across thirteen provinces and four direct controlled municipalities (The highest level classification for cities used by People’s Republic of China).
BJ=Beijing, nine participant heart centers
FJ=Fujian, two participant heart centers
GD=Guangdong, two participant heart centers
HB1=Hebei, one participant heart centers
HB2=Hubei, two participant heart centers
HN1=Henan, two participant heart centers
HN2=Hunan, one participant heart centers
HLJ=Heilongjiang, one participant heart centers
JS=Jiangsu, three participant heart centers
LN=Liaoning, one participant heart centers
SD=Shandong, seven participant heart centers
SX1=Shanxi, one participant heart centers
SX2=Shanxi, one participant heart centers
SH=Shanghai, six participant heart centers
TJ=Tianjin, two participant heart centers
ZJ=Zhejiang, one participant heart centers
CQ=Chongqing, one participant heart centers
Each participating institution received detailed information on data collection requirements and definitions of variables. A standardized case report form (CRF) containing demographic, preoperative risk factors, operative information, post-operative treatment course, and surgical outcomes was used.
Training for data collection was conducted at each site by the Coordinating Center. All the data were collected by trained clinical research staff including research nurses or residents at local sites. Every site completed a CRF for each hospitalization. The CRFs were then submitted to the data processing center of Chinese Cardiac Surgery Registry and double entered into the database by trained technicians. Two reviewers from the data processing center abstracted a random sample of 5–10% of medical records through on-site auditing at a six-month interval. The data submitted by the hospitals were compared with information in the medical records. When a disagreement occurred, a physician adjudicated the disagreement to determine the correct final value.
Study Sample
The study focused on CCSR patients ≥ 17 years old who underwent isolated CABG surgery from January 1, 2007 through December 31, 2008, either off-pump or on-pump. Although not standard our pre-specified inclusion criteria was age 17 years or older because, although rare in children, the precursors of atherosclerostic cardiovascular diseases are present in the young 4.
Patient and Hospital Characteristics
Several patient risk factors were collected and used for risk-adjustment (Table 1), including demographics, coronary anatomy, comorbidities, and triage status. We used estimated glomerular filtration rate (eGFR, mL/min per 1.73 m2) 5 to measure renal function by the following equation: 186 × (serum creatinine level [mg/dL])−1.154 × (age [y]) −0.203. We also used the “European system for cardiac operative risk evaluation” (EuroSCORE), which is a widely adopted risk model including 19 variables 6, for risk adjustment.
Table 1.
Baseline Characteristics
| Characteristics | Overall (n=8739) | East (n=2146) | Regions†
|
p value | ||
|---|---|---|---|---|---|---|
| North (n=5489) | South (n=450) | Central (n=654) | ||||
| Age, Mean (SD), years|| | 62.2(9.2) | 64.1(9.1) | 61.7(9.2) | 61.3(9.3) | 61.3(8.8) | <0.001 |
| Female (%)|| | 21.6 | 22.6 | 22.1 | 13.1 | 20.0 | <0.001 |
| BMI, Mean (SD), kg/m2 | 25.3(3.3) | 24.9(3.3) | 25.7(3.2) | 23.5(2.9) | 24.9(2.9) | <0.001 |
| Current smoker (%)|| | 49.6 | 40.7 | 53.3 | 45.1 | 50.3 | <0.001 |
| Diabetes (%)|| | 31.2 | 32.4 | 31.9 | 26.0 | 24.3 | <0.001 |
| Hypertension (%)|| | 64.8 | 68.1 | 64.9 | 51.1 | 63.5 | <0.001 |
| Hyperlipidemia (%) | 64.3 | 59.7 | 67.9 | 52.0 | 57.5 | <0.001 |
| History of stroke (%) | 8.3 | 7.9 | 9.2 | 3.7 | 6.6 | <0.001 |
| Creatinine, Mean (SD), μmol/L|| | 83.9(25.3) | 82.6(22.9) | 83.4(25.6) | 97.6(27.8) | 82.9(25.9) | <0.001 |
| eGFR≤60 ml/min/1.73m2 (%) | 10.6 | 10.0 | 10.1 | 21.3 | 9.3 | <0.001 |
| No. of diseased territories * | <0.001 | |||||
| Single (%) | 4.2 | 6.2 | 3.5 | 5.5 | 3.1 | |
| Double (%) | 13.8 | 15.1 | 12.7 | 20.7 | 15.4 | |
| Triple (%) | 82.9 | 78.8 | 83.8 | 73.8 | 81.5 | |
| Left main stenosis(≥50%) (%) | 31.2 | 32.9 | 30.2 | 38.0 | 29.4 | 0.001 |
| History of MI (%) | 41.6 | 34.1 | 43.3 | 64.2 | 36.7 | <0.001 |
| Congestive heart failure (%)|| | 0.4 | 9.4 | 4.2 | 6.9 | 2.4 | <0.001 |
| Atrial fibrillation (%) | 2.5 | 2.9 | 2.6 | 2.0 | 1.4 | 0.16 |
| COPD (%) | 1.6 | 2.5 | 1.1 | 0.4 | 3.2 | <0.001 |
| PVD (%)|| | 1.3 | 1.5 | 1.4 | 0.1 | 0.9 | 0.06 |
| Ejection fraction, Mean (SD)|| | 58.7(10.2) | 58.8(9.6) | 58.7(10.3) | 58.5(11.9) | 58.5(10.4) | 0.94 |
| Previous open heart surgery (%)|| | 0.8 | 1.2 | 0.7 | 0.9 | 0.6 | 0.14 |
| Used preoperative intra-aortic balloon pump(%) | 4.4 | 7.4 | 3.2 | 5.8 | 3.1 | <0.001 |
| On pump techniques (%) | 40.9 | 44.0 | 39.9 | 16.9 | 56.1 | <0.001 |
| Emergent/urgent surgeries (%) | 2.8 | 2.7 | 2.6 | 6.4 | 2.0 | <0.001 |
| Additive EuroSCORE >6 (%) | 13.7 | 18.1 | 12.7 | 12.7 | 7.8 | <0.001 |
“Territory” refers to the three coronary vessel trees (left anterior descending artery, circumflex artery, and right coronary artery). “diseased territory” refers to those territories with stenosis>70%.
continuous variables were analyzed by, categorical variables were analyzed by
continuous variables were analyzed by, categorical variables were analyzed by
variables in risk adjustment
BMI=body mass index
CAD=coronary artery disease
eGFR=estimated glomerular filtration rate
COPD=chronic obstructive pulmonary disease
PVD=peripheral vascular disease
Key hospital characteristics include teaching status, cardiovascular specialty status, ownership (public versus private), and military affiliation. Cardiovascular specialty hospitals are hospitals in which the faculty is dedicated exclusively to cardiovascular disease support and treatment. Teaching hospitals are those affiliated with medical schools or post-graduate training programs. Hospitals were also categorized into the regions Eastern, Northern, Southern, and Central China according to geographic and administrative boundaries.
Outcome measures
The primary hospital-level outcomes were in-hospital risk-standardized mortality (RSMR) and risk-standardized major complication rate (RSMCR). A major complication was defined as the occurrence of any of the following events: all-cause death, myocardial infarction, reoperation for bleeding, mediastinal infection, stroke, re-intubation, and renal failure. Myocardial infarction was those newly occurred postoperatively and was defined as any one of the following: documented in the medical record or EKG documented Q waves which are 0.03 seconds in width and/or ≥ one third of the total QRS complex in two or more contiguous leads. Reoperation for bleeding was defined as chest tube drainage ≥ 200ml/hour for at least 3 hours. Mediastinal infection was defined as a documented debridement within the medical record. Stroke was defined as central neurologic deficit persisting more than 72 hours (i.e. extremity weakness or loss of motion, loss of consciousness, loss of speech, visual field cuts). Renal failure was defined as increase of serum creatinine to >2mg/dL, or 2×most recent preoperative creatinine level, or a new requirement for dialysis postoperatively. Additionally, we assessed the length of stay, defined as the difference between discharge and admission dates plus 1 day.
Statistical analysis
We conducted bivariate analyses to compare the differences in patient characteristics across regions using Chi-square tests for categorical variables and t-tests for continuous variables.
A few variables had missing values in the CCSR, with patient-level data completion ranging from 97%–100% (see Supplemental Table 1). When there were missing values, we created an additional binary variable that assigned a value of 1 if missing and 0 otherwise. We then set the missing values with the median of observed values for a continuous variable with missing values, and added an additional level that indicated a variable has missing values for a categorical or binary variable. We included the additional binary variable and its corresponding variable in the model. This method of modeling missing data assumes data are missing at random and permits inclusion of all available cases, although it is not as efficient as multiple imputation procedures.
Using hierarchical logistic regression modeling 7, we estimated a random intercept risk model relating the log-odds of in-hospital mortality to patient risk factors for the study sample. The candidate variables used for risk-adjustment were selected based on clinical knowledge and previous studies (footnoted in Table 1). The model provides information to compute standardized hospital-specific estimates as well as quantitative summaries of between-hospital variation after adjusting for case mix. Using the regression coefficients from the risk model, we calculated a standardized mortality ratio (SMR), defined as hospital-specific mortality divided by the hospital expected mortality 7 for each hospital included in the study sample. We then multiplied the SMR by the average observed mortality rate of the 43 hospitals to obtain an RSMR for each hospital. We used the nonparametric bootstrapping method to generate 1,000 samples with replacement to estimate a 95% confident interval (CI) for each hospital RSMR and to determine which hospitals had RSMRs that were lower than the average mortality rate of the 43 hospitals 8. We classified hospitals into three mutually exclusive groups: 1) better, if the upper limit of a hospital’s 95% CI is less than the average mortality, 2) worse, if the lower limit of a hospital’s 95% CI is higher than the average mortality, and 3) as-expected, if a hospital’s 95% CI overlaps with the average. Using bootstrapping samples, we also calculated the probability of a RSMR below than the average for each hospital. We used the same approach to calculate a standardized complication ratio (SCR), RSMCR, 95% CI of RSMCR, and the probability of RSMCR below than the average for each hospital and classified them into the better, worse, and as-expected groups.
We estimated between-hospital variations in mortality and complication rates to quantify differences in hospital quality of care for CABG. We calculated the odds of dying or having a major complication if a patient was treated at a hospital 1 SD above the average of mortality or complication rate of 43 hospitals relative to the odds of dying or having a major complication if a patient was treated at a hospital 1 SD below the average. We classified hospitals into regions based on their locations and calculated the region-specific aggregated weighted RSMRs and RSMCRs. All statistical testing was 2-sided, at a significance level of 0.05, and all analyses using SAS version 9.1.3 (SAS Institute Inc, Cary, North Carolina) and estimated the hierarchical models using the GLIMMIX procedure in SAS.
The authors had full access to and take full responsibility for the integrity of the data. All authors have read and agree to the manuscript as written. The Fuwai Hospital Institutional Review Board has reviewed and approved the study.
RESULTS
Sample
Over the study period a total of 9844 consecutive patients underwent CABG surgery across 43 centers. Of the 9844 patients, 8739 (88.8%) underwent isolated CABG and were included in the study (Figure 2). The mean age was 62.2±9.2 years and 78.4% were males. On-pump CABG accounted for 40.9% of all the procedures in the current study. Patient characteristics varied greatly by region (Table 1). The patients in the East were the oldest and had the highest proportion of diabetes, hypertension, congestive heart failure, peripheral vessel diseases, and EuroSCORE>6. In contrast, patients from Central China had the lowest proportion of diabetes, good renal function (eGFR less than 60 ml/min/1.73m2), left main stenosis, congestive heart failure, emergent/urgent surgeries, and EuroSCORE > 6. Moreover, patients from Central China had the highest proportion of on-pump CABG.
Figure 2.
flowchart of patient selection in the current study
CCSR=Chinese Cardiac Surgery Registry
Of the 43 hospitals, 90.7% (39/43) were teaching hospitals, 14.0% (6/43) were specialty hospitals, 7.0% (3/43) were military hospitals, and 2.3% (1/43) were private hospitals. Overall, CCSR had seventeen hospitals from Eastern China, sixteen from Northern China, five from Southern China, and another five from Central China. The characteristics of the hospitals within regions are shown in Table 2. Centers in Central China had the lowest proportion of teaching hospitals (60.0%). The median annual CABG volume varied from 30 in Southern China to 128 in Northern China. The ratio of CABG to cardiac surgery volume was significantly different with the highest ratio in North China and the lowest in South China (Table 2, p=0.002).
Table 2.
Hospital characteristics
| Characteristics | Overall (n=43) | Regions‡
|
p value | |||
|---|---|---|---|---|---|---|
| East (n=17) | North (n=16) | South (n=5) | Central (n=5) | |||
| Teaching hospital* | 90.7% | 100.0% | 87.5% | 100.0% | 60.0% | 0.05 |
| Military hospital* | 7.0% | 5.9% | 6.3% | 20.0% | 0 | 0.64 |
| Private hospital* | 2.3% | 0 | 0 | 0 | 20% | 0.06 |
| Specialty hospital‡ | 14.0% | 5.9% | 25.0% | 0 | 20.0% | 0.33 |
| Total No. of beds† | 1759 (1100,2000) | 1800 (1350,2000) | 1432 (864,1872) | 2000 (1830,2240) | 2500 (807,2850) | 0.18 |
| Average beds for cardiac surgery† | 57 (35, 103) | 50 (34,69) | 43 (31, 86) | 180 (101,212) | 128 (76,279) | 0.002 |
| Ratio of cardiac surgery beds /total beds† | 0.04 (0.03, 0.06) | 0.03 (0.02,0.05) | 0.03 (0.02, 0.08) | 0.09 (0.05,0.10) | 0.06 (0.04,0.26) | 0.16 |
| Average No. of cardiac surgeons† | 18 (10, 27) | 17 (9,25) | 14 (8, 22) | 27 (21,51) | 27 (16,85) | 0.49 |
| Average No. of cardiac nurses† | 32 (20, 60) | 30 (25,53) | 26 (17, 50) | 70 (43,167) | 92 (40,235) | 0.21 |
| Ratio of cardiac surgeons /cardiac nurses† | 0.48 (0.32, 0.65) | 0.53 (0.41,0.69) | 0.50 (0.32, 0.64) | 0.39 (0.30,0.49) | 0.35 (0.28,0.70) | 0.47 |
| Average annual cardiac surgery volume† | 850 (350, 1650) | 700 (425, 1150) | 575 (235, 1300) | 1887 (1501, 2609) | 2000 (650, 3352) | 0.03 |
| Average annual CABG volume† | 99 (59, 202) | 87 (41, 198) | 128 (74, 320) | 30 (9, 201) | 116 (95, 174) | 0.15 |
| Ratio of CABG volume / cardiac surgery volume† | 0.17 (0.05, 0.31) | 0.17 (0.08, 0.25) | 0.31 (0.15, 0.36) | 0.01 (0, 0.07) | 0.06 (0.04, 0.21) | 0.002 |
expressed as percentages
expressed as median (25th, 75th)
continuous variables were expressed by, categorical variables were expressed by
continuous variables were analyzed by, categorical variables were analyzed by
Overall RSMR and RSMCR
The observed in-hospital mortality and complication rates were 2.2% (95% CI, 1.9–2.5) and 6.6% (95% CI, 6.1–7.1), respectively (Table 3). The volume-weighted correlation between RSMR and RSMCR (with death) was 0.58 (p<0.001) and the volume-weighted correlation between RSMR and RSMCR without death was 0.27 (p<0.001). The SMR ranged from 0.33 to 2.70, and the SCR ranged from 0.57 to 1.54. The mean (SD) RSMR was 1.9% (1.1) and varied from 0.7% to 5.8%, mean (SD) RSMCR was 6.4% (1.5) and ranged from 3.8% to 10.1% (see Supplemental Table 2 for details of the risk adjusted model). Among these 43 hospitals, there was one hospital with a RSMR statistically lower than average (RSMR=0.7%) and four hospitals with RSMRs statistically higher than average (RSMRs between 4.2% and 5.8%) (Figure 3). Similarly, there were two hospitals with RSMCRs statistically lower than average (RSMCRs of 4.3% and 4.6%) and one hospital with a RSMCR statistically higher than average (RSMCR=10.1%) (Figure 4). The risk-standardized odds of mortality and odds of a major complication when undergoing isolated CABG at a hospital one SD below average relative to a hospital one SD above average were 2.06 (95% CI, 1.40–3.04) and 1.53 (95% CI, 1.31–1.79), respectively. The overall median (25 th,75th percentiles) length of stay (LOS) was 22 days (16–30), excluding 50 patients who had LOS>100 days.
Table 3.
Outcomes by Region
| Statistics | Hospital level | Region level
|
p value | |||
|---|---|---|---|---|---|---|
| East (n=2146) | North (n=5489) | South (n=450) | Central (n=654) | |||
| Observed clinical outcomes (%) | ||||||
| Mortality | 2.2 | 2.1 | 2.2 | 1.6 | 2.4 | 0.98 |
| Myocardial infarction | 0.7 | 0.6 | 0.8 | 0.7 | 0.3 | 0.16 |
| Reoperation for bleeding | 2.0 | 1.8 | 2.0 | 3.6 | 1.7 | 0.82 |
| Mediastinal infection | 0.2 | 0.2 | 0.2 | 0.4 | 0.2 | 0.64 |
| Stroke | 0.4 | 0.3 | 0.4 | 0.2 | 0.6 | 0.77 |
| Re-intubation | 2.5 | 3.6 | 1.9 | 2.7 | 3.2 | 0.002 |
| Renal failure* | 0.7 | 0.8 | 0.7 | 0.9 | 0.5 | 0.75 |
| Combined complications† | 6.6 | 6.5 | 6.4 | 9.1 | 6.0 | 0.05 |
| Risk standardized mortality rate (%) | P<0.001 | |||||
| Mean (SD) | 1.9 (1.1) | 1.6 (0.6) | 2.0 (1.1) | 1.7 (1.8) | 2.5 (1.8) | |
| Min – Max | 0.7–5.8 | 0.9–3.4 | 1.4–5.4 | 0.7–5.8 | 1.2–4.2 | |
| Risk-standardized major complication rate (%) | P<0.001 | |||||
| Mean (SD) | 6.4 (1.5) | 5.8 (1.5) | 6.5 (1.5) | 7.7 (0.2) | 6.5 (1.8) | |
| Min-Max | 3.8–10.13 | 4.2–9.5 | 4.3–10.1 | 7.0–8.3 | 3.8–8.6 | |
Renal failure requiring dialysis
A combination of mortality, myocardial infarction, reoperation for bleeding, Mediastinal infection, stroke, re-intubation, and renal failure
RSMR=risk-standardized mortality rate
RSMCR=risk-standardized major complication rate
Figure 3.
Risk standardized mortality rate (RSMR) of 43 centers which are divided by regions and then ranked within regions. Note: probability of RSMR>average for each center is listed beside the corresponding center.
RSMR=risk-standardized mortality rate
Figure 4.
Risk standardized complication rate (RSMCR) of 43 centers which are divided by regions and then ranked within regions. Note: probability of RSMCR>average for each center is listed beside the corresponding center.
RSMCR=risk-standardized major complication rate
Regional variation
Variation in outcomes was observed across regions when hospitals were grouped into Eastern China, Northern China, Southern China and Central China regions. The means (SD) RSMRs of above regions were East: 1.6% (0.6), North: 2.0% (1.1), South: 1.7% (1.8), and Central: 2.5% (1.8) (p<0.001), respectively; the means (SD) RSMCR was East: 5.8% (1.5), North: 6.5% (1.5), South: 7.7% (0.2), and Central: 6.5% (1.8) (p<0.001), respectively (Table 3).
DISCUSSION
In this contemporary report of CABG surgery in China, we assessed in-hospital mortality and complication rates and demonstrated modest differences among sites, with some sites performing significantly better and worse than the overall average. Our findings provide evidence-based information about the performance of CABG among these hospitals and indicate the sites where there may be opportunities for improvement. To the best of our knowledge, this is the first study to report CABG outcomes in China.
Worldwide, despite increased worsening risk profiles, the short-term outcomes following CABG continue to improve. Research using the he STS database from the United States has demonstrated that the observed operative mortality for isolated CABG decreased from 3.9% in 1990 to 2.3% in 2006 9, 10. Similar observations have been reported using region or nationwide databases from other countries. The observed mortality for isolated CABG was around 2.0% in northwest England 11 and in the database of Australian Society of Cardiac and Thoracic Surgeons (ASCTS) 12. In the CCSR database involving 43 leading heart centers around China, the observed mortality for isolated CABG was 2.2%, suggesting that the elite Chinese heart centers have the potential to achieve a comparable level of performance as measured by mortality.
In China, variations in outcomes may also exist and depend upon site of treatment 13. China has undergone rapid advances in technological capabilities over the past 30 years and it is uncertain if they are achieving results at their best centers that are comparable to Western countries. Cardiac surgery is an ideal place to start measuring performance and outcomes in China because of the history of performance measurement in the field and the existence of a robust registry of a large number of Chinese centers that was based, in part, on the U.S. Society of Thoracic Surgeons’example 10.
An interesting finding from the current study is that hospital’s mortality performance and hospital’s complications performance were correlated but did vary. Prior studies have suggested that factors related to complications may not be the same as those associated with mortality 14, 15. Building on the previous evidence, a study involving 84,730 patients from the American College of Surgeons National Surgical Quality Improvement Program further suggested that successful management of complications may be equally important as avoiding complications after surgery 16. Therefore, hospital rankings according to single performance measures should be cautious and multiple measures are needed to better characterize hospital performance17.
Our study has limitations that warrant discussion. First, the 43 centers included in our study are large CABG centers in China and thus are not representative of the CABG centers that did not submit data to CCSR. Nevertheless, most registries studies have limitations with regard to representativeness. The CCSR registry represents a diverse group of hospitals and a high percentage of provinces with large cardiac surgery centers and representing various stages of economic development were included. All the participating centers are prominent surgical centers and this report provides a perspective on their performance. Therefore, we are confident that we capture the variation among sophisticated cardiac surgery centers in China. Second, the data were collected at each center, instead of centrally collected.. However, we randomly checked and audited the data for accuracy, and we had a system in place to centralize and standardize the data collection process. Third, in this study we assessed in-hospital mortality. It would have been preferable to assess a standardized period of time, such as 30-days, but this information was not available in the CCSR. But it should be noted that the median length of stay was 22 days, mitigating some concerns about not having longer follow-up to 30 days. Finally, there may be unmeasured case mix differences between the participating centers. Because our data was based on medical records, this unmeasured case mix effects seem to be small.
Outcome measurement provides key information about performance and is necessary to creating an accountable health care system dedicated to continual improvement 17. A first step is assembling the data that allows for an assessment of performance and an evaluation of variation among centers 18. In the United States several states, including New York, Massachusetts, New Jersey, California and Pennsylvania, have publicly reported hospital-level outcomes for patients undergoing CABG. This transparency of performance and commitment to identifying and addressing differences is a sign of a high functioning system. The effort to characterize performance is not intended to stigmatize programs with worse performance, but to illuminate the differences and to use the information as a basis for quality improvement 19. In addition, the identification of hospitals with better than average performance provides the opportunity to learn what processes may be responsible for their success 20–22. In China, measuring hospital performance is gaining importance among Chinese healthcare leaders. Although this study reported mortality and complication rates across only 43 CABG centers, going forward, the CCSR aims to measure and report all large CABG centers in China.
CONCLUSIONS
This study represents a new era of accountability among hospitals performing CABG surgery in China. For the first time, Chinese hospitals are collecting data to evaluate their performance and are publishing the results. The findings indicate that the large CABG centers in China are achieving results that are similar to the United States. Moreover, like the United States, China also has variation in performance among CABG sites. Our findings can inform practitioners and policymakers about what is being achieved and what can be done better. The mortality and complication rates from the 43 centers can be used as benchmarks to evaluate other CABG centers’ performance. The ability and willingness to measure performance is an important milestone towards integrating improvement into the Chinese health care system.
What is Known
In the United States, variation in patient outcomes after CABG has been documented.
What this Article Adds
The current study can reveal whether Chinese hospitals are achieving good and uniform results, and if not, may provide insights in how to improve care.
Our findings can inform practitioners and policymakers about what is being achieved and what can be done better.
The mortality and complication rates from the 43 centers can be used as benchmarks to evaluate other Chinese CABG centers’ performance.
The ability and willingness to measure performance is an important milestone towards integrating improvement into the Chinese health care system.
Acknowledgments
This study was conducted on behalf of the Chinese Cardiac Surgery Registry (CCSR, see details of the participating centers in Supplemental Table 3). We thank the colleagues from CCSR coordinating board for their excellent work on data management and all the members from the 43 participated hospitals. We thank the colleagues at Fuwai-Oxford Collaborative Research Center for their assistance with long-term follow-up and data entry of the study.
FUNDING RESOURCES
The current study and Drs. Hu, Zheng, and Yuan were supported by International Science & Technology Cooperation Program of China (2010DFB33140), Public Specialty Fund of Health Ministry(200902001)and Program for New Century Excellent Talents in University. Dr. Krumholz is supported by grant U01 HL105270 (Center for Cardiovascular Outcomes Research at Yale University) from the National Heart, Lung, and Blood Institute. Dr. Ross is currently supported by the National Institute on Aging (K08 AG032886) and by the American Federation of Aging Research through the Paul B. Beeson Career Development Award Program.
Footnotes
DISCLOSURES
Dr. Krumholz discloses that he chairs a cardiac scientific advisory board for United Health and is the recipient of a research grant from Medtronic, Inc. through Yale University. Dr. Normand discloses that she is Director of Mass-DAC, a data coordinating center that monitors the quality of CABG surgery and percutaneous coronary intervention in all non-federal acute care hospitals in Massachusetts.
None of the other authors declared conflict of interest.
References
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