Objective. The association between high case volumes and better patient outcomes has been demonstrated for many surgical procedures and medical treatments, including surgery for children with congenital heart disease. To simulate the effects of regionalization of pediatric cardiac surgery, we assessed the impact of reducing the number of pediatric cardiac centers on surgical mortality and patient’s travel distance.
Methods. This study used abstracted statewide hospital discharge data from California from 1995 to 1997. Case volume and in-hospital mortality for pediatric cardiac surgeries at each hospital were calculated. All hospitals that performed ≥10 pediatric cardiac surgeries in 1995 to 1997 were included in the analysis. To simulate regionalization, we “closed” the hospital with the lowest case volume and redistributed patients from this hospital to the nearest remaining hospitals. The number of in-hospital deaths was then recalculated using the original mortality rate of each remaining hospital multiplied by its new case volume. A multivariate logistic regression was conducted to determine the odds ratios of mortality of various types of surgery compared with closure of ventricular septal defect. This result was used for adjusting for the case-mix of the hospitals. Regionalization simulation analysis was repeated, and the number of deaths was recalculated using this adjustment of hospital case-mix. We also examined the increase in travel distance of patients to the hospitals as a result of the regionalization simulation.
Results. In California, 6592 children underwent cardiac surgeries in 1995 to 1997 with 352 in-hospital deaths (overall mortality rate: 5.34%). A quadratic regression model demonstrated that a high surgical volume was associated with a low mortality rate. We found demarcations between low- and medium-volume hospitals at 70 cases per year and medium- and high-volume hospitals at 170 cases per year. With adjustment for hospital case-mix, we found that 41 deaths could be avoided when all patients from low-volume hospitals were referred, and 83 deaths could be avoided when all patients from low- and medium-volume hospitals were referred to high-volume hospitals (overall mortality rate decreased to 4.08%). The average travel distance for pediatric cardiac surgery was 45.4 miles, which increased by 12.7 miles when all surgeries were referred to high-volume hospitals. When only the 733 high-risk patients were referred from low- and medium-volume hospitals to high-volume hospitals, 49 deaths could be avoided, yielding an overall mortality rate of 4.60%.
Conclusions. Theoretical regionalization of pediatric cardiac surgery is associated with a reduction in surgical mortality from 5.34% to 4.08% when all cases were referred to high-volume hospitals, or decrease to 4.60% when high-risk cases were referred. Although regionalization is associated with an important decrease in the number of deaths, it also increases the travel distance for patients. Additional studies on the costs and benefits of regionalization are needed to determine the best strategies to improve outcomes for children who undergo cardiac surgery.
Regionalization is a regulatory approach to rationalization of resource allocation, especially for highly specialized medical services or technologies.1 Proposals to encourage regionalization have waxed and waned in popularity over the years.2 A major argument in favor of regionalization is the possibility of achieving better patient outcomes. Experiences in regionalizing perinatal and neonatal care have resulted in improved outcomes for mothers and infants.3,4 For high-risk surgical procedures such as cardiac surgery, regionalization may improve outcomes by consolidating surgical programs and increasing the case volume of surgical centers. The first study to examine the empirical relationship between hospital volume and patient outcomes was published by Luft et al.5 Since then, the direct relation between hospital volume and favorable patient outcomes has been demonstrated by many studies for several surgical procedures and medical treatments.6–14 In 1990, Luft et al reviewed the volume–outcome literature and published the book, Hospital Volume, Physician Volume, and Patient Outcomes.15 More recently, Dudley et al16 conducted a systematic review of the volume–outcome studies published during the past decade.
The first study of the relation between hospital surgical volume and mortality of pediatric cardiac surgeries was conducted by Jenkins et al17 in 1995. Using an administrative database, these authors demonstrated that risk-adjusted, in-hospital mortality rates are lower in centers with higher volumes of pediatric cardiac surgeries. A more recent study by Hannan et al18 used a clinical database from New York to evaluate the effect of the volume of pediatric cardiac surgery at a given hospital or performed by a particular surgeon on in-hospital mortality and reached similar conclusions. It was found that the odds ratio (OR) for mortality for a low-volume hospital (annual case volume <100) was 1.42 when compared with a high-volume hospital (annual case volume ≥100).
In the study by Dudley et al,16 the results from Hannan’s study were used to calculate potentially avoidable deaths in California, assuming that patients from low-volume hospitals were selectively referred to high-volume hospitals. The authors found that by selective referral to high-volume hospitals, 7 deaths from pediatric cardiac surgery in California in 1997 could be avoided. However, the methodology of this study requires refinement. In addition, the impact of selective referral on factors such as cost and patient preference was not explored.
The purpose of the current study was to evaluate the impact of regionalizing pediatric cardiac surgery on in-hospital mortality and the associated increase in travel distance for patients. Specifically, the aims of this study were to 1) examine the volume–outcome relation in pediatric cardiac surgery and focus on defining the demarcation between high- and low-volume hospitals, 2) use a refined simulation model to assess the impact of regionalization on potential avoidable deaths from pediatric cardiac surgery, and 3) determine the increase in travel distance for patients associated with regionalization of pediatric cardiac surgery.
The study used the California statewide abstracted hospital discharge data from the California Office of Statewide Health Planning and Development (OSHPD). The OSHPD database includes all hospital discharges in California. The 1995, 1996, and 1997 OSHPD data on hospital discharges were used in the current study. The OSHPD data contain International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) discharge diagnosis and procedure codes assigned by California hospitals to each individual discharge during the year. Fields are provided for up to 24 diagnoses and 24 procedures. Routine demographic and administrative information such as age, gender, race, admission type and source, discharge status, length of hospitalization, and total hospital charges are listed in the OSHPD database. This administrative database contains important and valuable information on health care utilization and outcomes and has been used in many health services studies.19–22
We selected children (<21 years of age) with principal procedure codes in the databases indicating cardiac surgery. The principal procedure code in the OSHPD database is based on the ICD-9-CM. We used the following list of pediatric cardiac procedures and the corresponding ICD-9-CM codes for these procedures to select study samples: closure of atrial septal defect (ASD; 3551, 3561, 3571), arterial switch operation (3584), repair of atrioventricular canal defect (3554, 3563, 3573), aortic valve replacement (3521, 3522), atrial switch operation (3591), aortopulmonary shunt (390), cavopulmonary shunt (3921), Fontan operation (3594), mitral valve replacement (3523, 3524), Norwood operation (patients younger than 3 months with a diagnosis of hypoplastic left heart syndrome  and a procedure code indicating cardiopulmonary bypass ), orthotopic heart transplant (375), right ventricle to pulmonary artery conduit (3592), repair of total anomalous pulmonary venous return (TAPVR; 3582), truncus arteriosus repair (3583), repair of tetralogy of Fallot (TOF; 3581), repair or replacement of tricuspid or pulmonary valve (3525–8, 3533–5, 3539), thoracic vessel surgery (3835, 3845, 3959), open valvuloplasty (3510–4), and repair of ventricular septal defect (VSD; 3553, 3562, 3572). These 19 procedure groups were used for case-mix adjustment of in-hospital mortality of the hospitals.
Case Volume, Mortality Rate, and Regression Model
Many hospitals with 1 or 2 pediatric cardiac surgery admissions per year were listed in the OSHPD database. It is possible that small numbers of pediatric surgery cases were listed in these hospitals because of coding errors or because these cases were emergent cases that precluded referral to other hospitals. To avoid possible coding errors and to exclude cases for which selective referral may not have been feasible, we selected hospitals that performed ≥10 pediatric cardiac surgeries in 1995 to 1997. The in-hospital mortality rate of each hospital was calculated. To define the relation between case volume and mortality rate, we conducted a regression analysis. We used a weighted quadratic regression model, found useful to define the volume–outcome relation by many previous studies.15 Each hospital was used as a unit of regression. The independent variable was the case volume of the hospital. The dependent variable was the mortality rate of the hospital. The weight for each regression point, similar to other studies, was as follows: where N = number of patients at a given hospital, and Pi indicates the probability of mortality for the ith patient in that hospital.15 All statistical analyses were performed using SPSS 8.0 for Windows (SPSS Inc, Chicago, IL).
Travel distance, measured as the number of miles between a patient’s home and the hospital where surgery was performed, was calculated for each patient using the listed zip codes in the OSHPD data set. We used a computer program MapPoint 2000 (Microsoft Corp, Redmond, WA) to calculate the distances between the geographic centers of the zip codes. The distances calculated represent the shortest street and highway distance selected by the program.
Because high surgical volume is associated with low mortality rate, we created a model to simulate regionalization by “referring” patients from low-volume hospitals to high-volume hospitals. To conduct this analysis, we made an assumption that the in-hospital mortality rates for high-volume hospitals remain unchanged as their case volumes are increased by referrals from low-volume hospitals.
The flow diagram of the regionalization simulation is presented in Fig 1. We first ranked the 20 hospitals by number of cases of pediatric cardiac surgery for the years 1995 to 1997. The hospital with the lowest number of cases was hypothetically closed for pediatric cardiac surgery services. Patients from this lowest volume hospital were referred to the remaining hospitals nearest to their homes (judged by zip code). The number of deaths for each remaining hospital was recalculated using the new number of cases (including original cases plus patients referred from the lowest volume hospital) at each hospital multiplied by the original mortality rate at that hospital. Travel distances for patients referred from the lowest volume hospital to the nearest remaining hospitals were recalculated, and the mean travel distance for all patients was recorded. After this process was completed, the lowest volume hospital among the remaining hospitals was then hypothetically closed and the patients from this hospital were referred to the nearest remaining hospitals. The number of deaths and travel distance were recalculated. The process of closing the lowest volume hospital, selective referral of patients to the nearest remaining hospitals, and recalculation of number of deaths and patient travel distance was repeated until only 2 hospitals were left providing pediatric cardiac surgery services in California.
We define the number of avoidable deaths as the difference between the original number of deaths (before simulation of regionalization) and the number of deaths after each step of regionalization. The number of avoidable deaths was calculated after each lowest volume hospital was closed and its patients were redistributed during the regionalization simulation. The results of this analysis were used to divide the hospitals into 3 groups: low-, medium-, and high-volume hospitals. The regionalization simulation analysis was first conducted without adjustment for hospital case-mix. This analysis was then repeated with adjustment for hospital case-mix.
Adjustment for Hospital Case Mix
In contrast to adults who undergo coronary artery bypass graft surgery, children with various forms of congenital heart defects undergo a wide variety of surgical procedures to palliate or repair cardiac defects. Although there is no consensus among researchers regarding 1 best approach for case-mix adjustment, previous studies have attempted risk stratification by grouping various surgical procedures. In the present study, we chose to categorize pediatric cardiac surgical procedures into 19 procedure groups, as described in the Case Selection section. To calculate the OR for mortality of various procedure groups using VSD closure as the reference group (OR = 1), we conducted a logistic regression to control for the following variables: age (neonate <1 month, infant ≥1 month and <1 year, and child ≥1 year; child ≥1 year as reference group), gender (male and female; male as reference group), race and ethnicity (white, black, nonwhite and nonblack Hispanic, Asian and Pacific Islander, and others; white as reference group), type of insurance (private insurance, managed care, public insurance and others; private insurance as reference group), and family income (using median household income of home zip code; income >$60 000 as reference group), type of admission (elective or nonelective; elective as reference group), and surgical volume of the hospital (low, medium, and high; high as reference group). In addition, the logistic regression also controlled for the following comorbidity conditions listed in the diagnosis code: prematurity, failure to thrive, Down syndrome, and pulmonary hypertension.
In a subsequent analysis, surgical procedures were classified as low-risk procedures for those procedure groups with OR for mortality that were statistically equal to or lower than mortality for VSD and as high-risk procedures for those procedure groups with OR for mortality that were statistically higher than mortality for VSD. For low-risk procedures, we conducted a logistic regression analysis to calculate the OR for mortality when low- and medium-volume hospitals were compared with high-volume hospitals when all other variables (eg, age, gender) were controlled. This process was repeated for the high-risk procedures to calculate the OR for mortality when low- and medium-volume hospitals were compared with high-volume hospitals.
The regionalization simulation process was then repeated using case-mix adjustment for the hospitals. For each patient who was referred from a low-volume hospital to a medium-volume hospital, the risk for mortality was adjusted using the OR for mortality of low-volume hospital compared with the medium-volume hospital for that procedure (low- or high-risk procedure). Similar adjustments were conducted when patients from the low-volume hospitals were referred to the high-volume hospitals or when patients from the medium-volume hospitals were referred to the high-volume hospitals. After all patients from the low-volume hospitals were referred, the overall number of deaths and the number of avoidable deaths were calculated. Then the regionalization process was repeated until 2 hospitals were left in California.
Different regionalization scenarios were considered: 1) all hospitals with initial case volume <100 cases/year were closed (as proposed by Hannan et al18 and used by Dudley et al16), 2) all low-volume hospitals (<70 case/year) were closed, 3) all low- and medium-volume hospitals (<170 case/year) were closed, and 4) hospitals were sequentially closed until only 2 highest volume hospitals were providing pediatric cardiac surgery services. The purpose of this analysis was to determine the relation between the reduction of mortality and increase in travel distance associated with regionalization for the different scenarios.
After determining the OR for mortality by low- and high-risk procedures comparing low-, medium-, and high-volume hospitals, we created another regionalization scenario by referring only patients who were undergoing high-risk procedures from the low- and medium-volume hospitals to high-volume hospitals. This was done to test the hypothesis that selective referral of only patients who are undergoing high-risk procedures to high-volume hospitals can increase the number of avoidable deaths without the need to close many low- and medium-volume hospitals, mitigating the effect of regionalization on a patient’s travel distance.
We identified 6972 children who underwent congenital heart disease surgeries at 65 hospitals in California between 1995 and 1997. Although the surgeries were performed at 65 hospitals, nearly half (30 hospitals) had only 1 pediatric cardiac surgery case during the 3-year period. After excluding surgeries performed in centers with <10 cases and cases with missing information, 6592 cases of surgery from 20 hospitals were entered into the analysis. There were 1088 neonates (16.5%), 1869 infants (28.4%), and 3635 children (55.1%). The overall in-hospital mortality was 352, yielding a mortality rate of 5.34%.
Figure 2 demonstrates the case volume versus in-hospital mortality rate for the 20 hospitals included in the analysis. As has been demonstrated by previous studies, mortality rates for low-volume hospitals tend to have a wide range of distribution. It is apparent that the variance in mortality rates among hospitals decreases as the case volume of hospitals increases to approximately an average case volume of 170 per year. The variance in mortality rates was 0.136% for hospitals with <170 cases per year and 0.004% for hospitals with ≥170 case per year. It is also apparent from the regression curve that when the case volume of hospitals is ≥170 cases/year, the curve becomes almost flat and the decrease in mortality rate with increasing case volume becomes minimal.
Hannan et al18 used a case volume of 100 per year as a discriminator between high-volume and low-volume hospitals because it “yielded the largest differential in risk-adjusted mortality rates between the 2 groups while maintaining reasonably large volumes in the 2 groups.” However, we found the largest differential at a case volume of 170 cases/year: the mortality rate was 4.91% for hospitals with ≥170 cases/year compared with a mortality rate of 6.23% for hospitals with <170 cases/year in our study group.
The quadratic regression model using case volume as the independent variable and mortality rate as the dependent variable is also shown in Fig 2. The R2 value for the regression model is 0.14 (P < .01).
In our simulated regionalization, closing hospitals one at a time as described in “Methods”, we found that as the number of hospitals was reduced from 20 to 13, the number of avoidable deaths fluctuated between −4 and +4. Figure 3 shows a graph of the number of remaining hospitals with regionalization (x axis) versus the number of avoidable deaths for that number of remaining hospitals (y axis). It is obvious that there are 2 inflection points in the graph of the number of avoidable deaths versus remaining hospitals, indicating 2 sharp rises in the number of avoidable deaths. The first sharp rise in the number of avoidable deaths occurred when the number of hospitals was decreased to 11. Therefore, we defined the first 9 hospitals with average annual case volume of <70 as low-volume hospitals. The second sharp rise in the number of avoidable deaths occurred when 5 hospitals remained. Therefore, we defined the 6 hospitals (hospital 11 to hospital 6) with average annual case volume between 70 and 170 as medium-volume hospitals and the largest 5 hospitals with an annual case volume of ≥170 as high-volume hospitals. As shown in Fig 3, closing the low-volume hospitals has a minimal effect on reducing the number of deaths. Of note, the decrease in number of deaths became consistently positive and significant when all remaining hospitals had an original case volume of ≥70 cases/year.
Adjustment for Hospital Case Mix
We used VSD closure (overall mortality rate: 2.15%) as the reference group to calculate the OR for mortality in the multivariate logistic regression model. As shown in Fig 4, the mortality OR for atrioventricular canal repair, TAPVR repair, TOF repair, truncus arteriosus repair, open valvuloplasty, aortic valve replacement, mitral valve replacement, right ventricle to pulmonary artery conduit, Fontan operation, atrial switch operation, and Norwood operation were significantly greater than 1 (compared with VSD closure) and were therefore defined as high-risk procedures. The mortality OR for thoracic vessel procedures, orthotopic heart transplant, tricuspid or pulmonary valve procedures, arterial switch operation, aortopulmonary shunt, and Glenn shunt were not statistically different from 1, and the OR for ASD closure was significantly lower than 1. These procedures with similar or lower OR for mortality compared with VSD closure were defined as the low-risk procedures.
Table 1 lists the case-mix adjustment results when the type of surgery was categorized by high and low risk and the hospitals were stratified to low-, medium-, and high-volume hospitals. When patients were transferred from low-volume hospitals to medium-volume hospitals, there was no statistical difference in OR for mortality in either low- or high-risk procedures. When patients were transferred from low-volume hospitals to high-volume hospitals, there was no statistical significance in the OR for mortality of low-risk procedures, but the odds of mortality decreased by 2.67-fold (P < .01) for high-risk procedures. When patients were transferred from medium-volume hospitals to high-volume hospitals, the odds for mortality decreased by 1.54 (P < .05) for low-risk procedures and by 2.54 (P < .01) for high-risk procedures. In an additional analysis to adjust for case mix of the hospitals, these OR comparing low-risk and high-risk procedures, respectively, among low-, medium-, and high-volume hospitals were used to recalculate the changes in the number of deaths in the regionalization simulation.
Figure 5 shows the results of regionalization simulation analysis with adjustment for case-mix of the hospitals. As expected, the curve in Fig 5 appears smoother with less fluctuation compared with the curve in Fig 3 without case-mix adjustment. There was essentially no change in the number of deaths when the number of hospitals decreased from 20 to 15; after that, the number of avoidable deaths began to rise. The number of avoidable deaths reached a plateau when 5 hospitals were left in California, and no significant change was noted as the number of hospitals decreased below 5.
Table 2 lists the results of various regionalization scenarios, with and without adjustment for hospital case-mix. When 9 low-volume hospitals were closed (11 hospitals remained), the number of avoidable deaths with case-mix adjustment was 41 and the overall mortality rate decreased from 5.34% to 4.72%. When 12 hospitals with an average annual case volume of <100 were closed (8 hospitals remained), the number of avoidable deaths was 61 and the overall mortality rate decreased to 4.41%. The highest number of avoidable deaths, 83, and the lowest mortality rate, 4.08%, occurred when only 5 high-volume hospitals with an average annual case volume of ≥170 remained. Decreasing the number of hospitals further to 2 hospitals did not result in a significant increase in the number of avoidable deaths or decrease in overall mortality rate, but the mean travel distance increased steeply.
The mean travel distance for children who were undergoing cardiac surgery in California was 45.4 miles. The mean travel distance increased by only 3.9 miles when the number of hospitals was reduced from 20 to 11. When all hospitals with a case volume of <100 cases/year were closed (ie, all patients were sent to the 8 hospitals with an annual case volume of ≥100), the increase in mean travel distance was 6.9 miles. When the maximum reduction of the number of deaths was achieved (5 hospitals remained in California), the mean travel distance increased by 12.7 miles. When only 2 hospitals were left to provide pediatric cardiac surgery services, there was very little additional reduction in the number of deaths; however, the mean travel distance increased by 33.6 miles. As listed in Table 2, the average travel distance among patients who were referred was 66.9 miles when the number of hospitals decreased to 11 and was 98.2 miles when the number of hospitals decreased to 5.
A total of 733 patients underwent high-risk procedures at the low- and medium-volume hospitals, accounting for 27.2% of all surgeries performed in these hospitals or 38.1% of all high-risk surgery cases in 1995 to 1997. When only high-risk surgery patients were selectively referred from low- and medium-volume hospitals to high-volume hospitals, the number of avoidable deaths was 49. Thus, the overall mortality decreased to 4.60% when all high-risk surgeries were selectively referred to high-volume hospitals.
Jenkins et al17 reported a significant volume-outcome relation in pediatric cardiac surgery using the 1989 California data. In the present study, we found similar volume-outcome relations for pediatric cardiac surgery performed in 1995 to 1997. Unlike previous studies that used 100 cases/year as the demarcation for high-volume and low-volume hospitals, we found that there are 3 groups of hospitals defined by average case volumes of <70, 70 to 170, and ≥170 cases per year. In a theoretical analysis, we found that as the number of hospitals decreased, the number of avoidable deaths did not become significant until all low-volume hospitals (case volume of <70 per year) were closed. When the number of avoidable deaths reached a plateau, 83 deaths (or an average of 28 deaths per year) could be avoided when surgeries were regionalized to 5 hospitals. However, to achieve this maximum benefit of regionalization requires closure of three quarters of current pediatric cardiac centers and an associated increase in mean travel distance of 12.7 miles for all patients, or 52.8 miles for patients who are transferred.
Surgical mortality rates of the hospitals in our study became more stable and predictable when the annual case volume was ≥170 cases/year (Fig 2). In addition, it has been shown that for adult open-heart surgery and cardiac catheterization, an economy of scale is achieved at an annual case volume of 200 to 300.23 We believe that this conclusion may also apply to pediatric cardiac surgery. Therefore, we found it preferable to use case volume of approximately 200 per year (instead of 100 per year used by Hannan et al) to define high- and low-volume hospitals in pediatric cardiac surgery. This is consistent with the federal health planning guidelines for cardiac surgery centers and the recommendation by the Inter-Society Commission for Heart Disease Resources.24,25 In addition, based on the simulation analysis, we found categorizing the hospitals into 3 case volume levels (low, medium, and high) is a better approach than the high- and low-volume dichotomy used by previous studies.
The number of in-hospital deaths did not change significantly or increased slightly when all patients from low-volume hospitals were transferred to medium- and high-volume hospitals (number of hospitals decreased to 13 in Figs 3 and 5). This is probably because of the relatively small number of patients in the low-volume hospitals and higher mortality rates in some medium-volume hospitals. However, when all low- and medium-volume hospitals were closed, the number of avoidable deaths increased significantly. Although we found the highest number of avoidable deaths when all pediatric cardiac surgery in California was regionalized to 2 hospitals, this extreme level of regionalization seems to be impractical and may be ineffective in relation to costs. When pediatric cardiac surgery was regionalized to a more practical scenario of 5 hospitals with case volume of ≥170/year, 83 avoidable deaths could be achieved with a more reasonable cost from increase in travel distance (12.7 miles per patient on average).
When the type of procedures were divided into high-risk and low-risk, it was clear that low- and medium-volume hospitals had much higher mortality for high-risk procedures compared with high-volume hospitals (Table 1). Even for low-risk procedures, low- and medium-volume hospitals had higher mortality (OR: 1.24 and 1.54, respectively) compared with high-volume hospitals. Furthermore, there were 34 avoidable deaths (total: 83 avoidable deaths; subtract 49 from high-risk procedures) or 40% of all avoidable deaths from low-risk procedures when patients were transferred to high-volume hospitals. The cause of higher mortality in low- and medium-volume hospitals for low-risk procedures requires additional investigation.
The increase in travel distance was small even when more than two thirds of the hospitals were closed. This is largely because in California, most patients live in metropolitan areas where the pediatric cardiac centers are located. In addition, most pediatric cardiac centers are located in population-dense areas and many are in close proximity to one another. Although we did not conduct a cost-benefit analysis in the current study, we do not believe that an average increase in travel distance of 12.7 miles will result in significant additional cost to the patients or to society. On the benefit side, regionalization has been shown to reduce utilization of hospital beds and overall health care costs.26,27 A truly comprehensive consideration of the economics of regionalization may be complex and is beyond the scope of the current analysis.
When patients are referred to different hospitals, patient preference must also be taken into account. Finlayson et al28 found that 45% of patients would prefer surgery at a local hospital instead of a regional referral center 4 hours away even if the local hospital’s operative mortality risk was twice as high (6% vs 3%). It is difficult to extrapolate the results of Finlayson’s study on adults to pediatric patients. Future studies on parent decision making with regard to medical care for their children will help to clarify patient preference issues and the feasibility of selective referral.
In our study, we conducted a theoretical analysis of regionalization using hypothetical scenarios in which hospitals were “closed” for pediatric cardiac surgery services. This analysis was based on data from California, a very large, competitive, and saturated health care market. The results from our analysis in California may not be applicable to other areas of the United States or other countries where the demographic, geographic, and health care market characteristics are different from California. For example, Sweden experienced a dramatic decrease in surgical mortality for pediatric heart surgery after centralizing surgery services from 4 centers to 2 centers.29
The Swedish experience also indicates that the process of achieving regionalization is long (20 years) and “difficult” when the number of pediatric cardiac centers was reduced from 4 to 2.29 In our simulation analysis, the maximum benefit of regionalization would reduce the overall surgical mortality to 4.08%, but this requires closing pediatric cardiac surgery services in three fourths of current hospitals and referring 40.8% of all patients to high-volume hospitals. A more practical approach might be to refer only high-risk patients (11.1% of all patients) to high-volume hospitals. This approach would reduce the overall mortality rate to 4.60% with a much smaller increase in travel distance.
Although regionalization decreases mortality and may have a favorable cost-benefit ratio, it may not be the most feasible and cost-effective way to reduce mortality for pediatric cardiac surgery. Alternative strategies for improving outcomes of children who are undergoing cardiac surgery include implementation of quality assurance programs, selective use of clinical pathways, and education and training of physicians and supporting staff at low- or medium-volume hospitals with high mortality rates. These strategies may also improve overall surgical outcomes and may have a lower cost to the health care system as a whole than regionalization. More studies are needed to explore these speculations further.
A major limitation of this study comes from errors related to miscoding and missing data in an administrative database.30–32 In the present study, we attempted to minimize the effect of errors from miscoding by restricting our case selections to hospitals with ≥10 cases/year of pediatric cardiac surgery. However, missing data and miscoding of patients selected for our study may still exist and potentially bias our findings.
In addition, we examined the effects of regionalizing all pediatric cardiac surgery to high-volume hospitals. Importantly, we also attempted to adjust for the case-mix of the hospitals using different levels of risk involved in various types of surgery for pediatric heart disease. Although there is no well-accepted risk adjustment methodology for pediatric cardiac surgeries, categorizing the risk levels for various types of surgical procedures has been used by previous researchers. In the present study, we adopted and expanded this approach by increasing the number of the procedure groups to 19 and added 4 comorbidity conditions. However, it is possible that other important medical variables, such as medical history, or other cardiac and noncardiac conditions are not adequately accounted for using this approach. Future studies using detailed clinical databases are needed to refine the risk adjustment strategy used in this study.
Regionalization of pediatric cardiac surgery in California had no apparent effect on reducing surgical mortality until more than one third of current hospitals (with a case volume of <70 per year) were “closed.” At maximum, the mortality rate decreased from 5.34% to 4.08% when all cases were referred to high-volume hospitals. However, this requires closure of three fourths of the current pediatric cardiac centers. When only high-risk surgeries were selectively referred to high-volume hospitals, the overall mortality rate decreased to 4.6%. Although regionalization is associated with an important decrease in the number of deaths, it also increases the travel distance for patients. Additional studies on the cost-effectiveness of regionalization are needed to determine the best strategies to improve outcomes of children who undergo cardiac surgery.
R-K.R.C. was a postdoctoral fellow of the Agency for Healthcare Research and Quality and received an institutional research grant from the Harbor-UCLA Research and Education Institute.
- Received August 30, 2000.
- Accepted August 28, 2001.
- Reprint requests to (R-K.R.C.) Division of Cardiology, Department of Pediatrics, Harbor-UCLA Medical Center, 1000 W Carson St, Torrance, CA 90509. E-mail:
The abstract of this study was presented, in part, at the Association of Health Services Research Meetings; June 25, 2000; Los Angeles, CA.
- ↵Ginzburg E. Regionalization & Health Policy. US Department of Health Education and Welfare. Washington, DC: US Government Printing Office;1977. DHEW Publ. No. [HRA]77– 623
- ↵Rudolph CS, Borker SR. Regionalization. Issues in Intensive Care for High Risk Newborns and Their Families. New York, NY: Praeger Publishers;1987
- ↵Luft HS, Garnick DW, Mark DH, McPhee SJ. Hospital Volume, Physician Volume, and Patient Outcomes. Assessing the Evidence. Ann Arbor, MI: Health Administration Press Perspectives;1990
- ↵Jenkins KJ, Newburger JW, Lock JE, et al. In-hospital mortality for surgical repair of congenital heart defects: preliminary observations of variation by hospital caseload. Pediatrics.1995;95 :323– 330
- ↵Hannan EL, Racz M, Kavey RE, Quaegebeur JM, Williams R. Pediatric cardiac surgery: the effect of hospital and surgeon volume on in-hospital mortality. Pediatrics.1998;101 :963– 969
- ↵Chernew M, Haywood R, Scanlon D. Managed care and open-heart surgery facilities in California. Health Aff (Milwood).1996;15 :191– 201
- Calmes D, Leake BD, Carlisle DM. Adverse asthma outcomes among children hospitalized with asthma in California. Pediatrics.1998;101 :845– 850
- Chang R-KR, Chen AY, Klitzner TS. Factors associated with age at operation for children with congenital heart disease. Pediatrics.2000;105 :1073– 1081
- ↵Erickson LC, Wise PH, Cook EF, Beiser A, Newburger JW. The impact of managed care insurance on use of lower-mortality hospitals by children undergoing cardiac surgery in California. Pediatrics.2000;105 :1271– 1278
- ↵US Department of Health, Education, and Welfare. Health planning: national guidelines. Fed Reg.1978;43 :1304– 1350
- ↵Scannel JG, Brown GE, Buckley MJ. Report of the Inter-Society Commission for the Heart Disease Resources: optimal resources for cardiac surgery: guideline for program planning and evaluation. Circulation.1975;53 :A1– A37
- Copyright © 2002 by the American Academy of Pediatrics