Introduction
End-stage renal disease (ESRD) incidence and prevalence, necessitating renal replacement therapy, has steadily increased. The number of patients undergoing dialysis in Korea exceeded 100,000 in 2021 and has doubled over the past decade [
1]. Although mortality has declined significantly over the past 20 years, the absolute mortality risk remains higher in hemodialysis (HD) patients than in the general population [
2]. Nevertheless, most patients in Korea receive HD, expensive medical service requiring sophisticated equipment, materials, several drugs, and laboratory tests, and it has significantly impacted health insurance finances [
3]. The Korean health insurance system is a public, single-payer system. Notably, the National Health Insurance Act was enacted in 2000, and all insurers were merged into a single insurer [
4]. Additionally, the government introduced a fixed-payment system for medical aid (MA) beneficiaries receiving HD in 2001 to promote financial stability by managing an increasing number of patients receiving HD. The government established a fixed fee for HD treatment, regardless of the type of medical institution, in order to prevent the burden on patients from increasing as the number of HD patients receiving MA increases. Additionally, the government incorporated all necessary costs, including doctors’ fees, HD fees, materials, dialysate, essential oral medications, and intravenous drugs administered during dialysis, such as erythropoietin, into one single fee and prohibited additional charges. However, there are constant concerns that the fixed-payment system’s cost is lower than the actual medical cost, causing a deficit in medical institutions, and that they may receive unequal medical services compared to National Health Insurance (NHI) beneficiaries [
5]. However, only a few studies have investigated whether a difference in the treatment outcomes and mortality of patients in each group exists due to varying health insurance types, and these studies’ results are usually inconsistent [
6–
8]. Therefore, this study aimed to comprehensively compare the treatment process, treatment outcomes, and mortality rates according to health insurance type using the Korean Renal Data System (KORDS).
Methods
This study was approved by the Institutional Review Board of the Eulji Medical Center (No. EMC 2022-09-014). The requirement for informed consent from patients was waived due to the retrospective design of the study.
Data sources and study population
The ESRD Registry Committee of the Korean Society of Nephrology has registered Korean patients on dialysis and collected dialysis data since 1985. The KORDS is a nationwide ESRD patient registry usually updated annually [
9]. Therefore, we conducted a retrospective analysis using data from patients who underwent HD registered in the KORDS from 2001 (when a fixed-payment system was introduced) to 2017. The study participants included patients with ESRD aged ≥19 and ≤80 years who began HD after 2001. Among these patients in the KORDS, our study’s exclusion criteria were as follows: 1) patients with insufficient or missing data; 2) those whose insurance type did not fulfill the study criteria; 3) those with <2 dialyzes weekly or peritoneal dialysis; 4) patients who started dialysis before 2001; and 5) aged <19 years or >80 years.
Supplementary Fig. 1 (available online) shows a flow diagram of patient selection.
Data collection and variable definition
Patients were categorized into two groups based on the health insurance type as follows: the NHI and MA groups. At the time of enrollment, demographic information was obtained, such as age, sex, cause of ESRD, and comorbidities. Furthermore, data associated with treatment processes and outcomes, including laboratory data, were based on values entered in the KORDS and were extracted using the codebook. Data on the phosphate-binder types used, the types of drugs inhibiting parathyroid hormone (PTH), the types of erythropoiesis-stimulating agents (ESA) in use, the number of HD per week, and the surface area of the dialyzer were collected as the treatment process indicators. Moreover, as treatment outcome indicators, residual renal function, urea reduction rate (URR), HD adequacy (standard Kt/V), weight gain between dialysis, systolic and diastolic blood pressures, and laboratory results such as hemoglobin, albumin, calcium, phosphorus, and PTH were recorded. Furthermore, in analyzing the treatment outcomes, we evaluated the average value and the achievement rate of the target value suggested using the international treatment guidelines [
10–
14].
Statistical analysis
The analysis of demographic characteristics and treatment-related variables was conducted using the full, original dataset without any matching. Categorical and continuous variables were expressed in numbers and percentages and as mean ± standard deviation, respectively. The chi-square test and t test were used to compare the NHI and MA groups for categorical and continuous variables, respectively. To minimize the potential impact of confounding variables on our subsequent analyses related to mortality, we conducted a one-to-one matching of the NHI and MA groups based on age and sex, comparing both their survival and mortality rates. Crude mortality rates were calculated by dividing the number of patients with a given event by person-years and were expressed as cases per 1,000 person-years. Furthermore, Poisson regression models were employed to estimate the mortality rate ratios between groups, and survival time was calculated using the Kaplan-Meier method. Therefore, to compare the overall survival time between the NHI and MA groups, the log-rank tests were used. Hazard ratios (HRs) with 95% confidence intervals (CIs) for all-cause mortality were also calculated using the Cox proportional hazard regression model. Moreover, we used three different models with increasing adjustment degrees to evaluate the step-by-step adjustment effect of confounding factors. The first, model 1 was adjusted for age and sex. Subsequently, model 2 was further adjusted to determine the ESRD etiology. Finally, model 3 was further adjusted to model 2 for comorbidities. This analysis was conducted using R software, version 4.1.3 (R Foundation for Statistical Computing).
Results
Demographic characteristics
Overall, 52,574 eligible patients were enrolled, with 42,359 (80.6%) and 10,215 patients (19.4%) in the NHI and MA groups, respectively (
Table 1). Both groups had a higher proportion of male than female (approximately 60% male vs. 40% female), and the proportion of those aged ≥65 years was higher in the NHI group than in the MA group (39.0% vs. 19.6%, p < 0.001). However, the dialysis vintage was longer in the MA group (4.4 years vs. 5.4 years). Among the causes of ESRD, the NHI group had more hypertension (20.1% vs. 18.3%, p < 0.001) and renal cysts (2.1% vs. 1.5%, p < 0.001), and less diabetes (49.0% vs. 51.7%, p < 0.001) compared with the MA group. Diabetes and hypertension accounted for approximately 70% of the ESRD cases in both groups. Furthermore, among comorbidities, the MA group showed a higher proportion of heart failure (6.7% vs. 7.8%, p < 0.001), arrhythmia (4.2% vs. 4.7%, p = 0.048), cerebrovascular disease (5.6% vs. 6.0%, p = 0.04), hepatitis B (3.4% vs. 4.8%, p < 0.001), and hepatitis C (1.6% vs. 3.2%, p < 0.001) than the NHI group; however, malignancy (2.4% vs. 1.8%, p = 0.001) was more prevalent in the NHI group than in the MA group (
Table 1).
Comparison of the treatment process and outcomes by groups
Tables 2 and
3 present the comparison results for the treatment process and outcome indicators, respectively. In the drug prescription pattern, the proportion of erythropoietin prescriptions was significantly higher in the MA group (p < 0.001), and the rate of darbepoetin (p < 0.001) or continuous erythropoietin receptor activator (CERA) (p = 0.003) prescriptions was significantly higher in the NHI group. Similarly, the ratio of calcium-based phosphate binder prescriptions was higher in the MA group (p = 0.01); however, that of the non-calcium phosphate binders was higher in the NHI group (p = 0.01). Furthermore, the proportion of patients receiving HD three times weekly was higher in the MA group (p < 0.001), and no significant differences were observed in the dialysis membrane surface area.
The average hemoglobin level was not significantly different between the two groups; however, the number of patients managed in the control target ranging from 10 to 11 g/dL was significantly higher (p < 0.001) in the NHI group. Mean albumin levels were elevated in the MA group, along with a higher percentage of patients achieving the target range of 3.4 to 5.2 mg/dL (p = 0.006). The average calcium level in the MA group was significantly higher than that in the NHI group (p < 0.001), and the number of patients managed in the control target ranging from 8.4 to 9.6 g/dL was significantly higher (p < 0.001) in the NHI group. Furthermore, the mean blood phosphorus level was significantly higher (p < 0.001) in the MA group, and the number of patients managed within the control target ranging from 2.4 to 5.0 mg/dL, was significantly lower in the MA group (p < 0.001). Moreover, the mean PTH level was significantly higher (p < 0.001) in the MA group; however, the proportion of patients managed with the control target ranging from 100 to 300 pg/dL was significantly lower in the MA group (p < 0.001). Among the indicators used to evaluate the adequacy of dialysis, residual renal function was significantly (p < 0.001) higher in the NHI group, and both systolic and diastolic blood pressure were significantly lower in the NHI group (p < 0.001). Additionally, the weight gain during dialysis was higher in the MA group. There was no significant difference in Kt/V and URR between the two groups.
Comparison of the survival probability and mortality by group
The two groups were matched in a 1:1 nearest neighbor ratio according to age and sex to minimize confounding effects before comparing survival and death. Therefore, 10,215 NHI and 10,215 MA patients were matched.
In total, 2,022 (19.8%) and 1,523 patients (14.9%) died in the NHI and MA groups, respectively, over the study period. The crude death rate was 27 and 31 (per 1,000 person-years) in the NHI and MA groups, respectively, and the mortality rate ratio was 1.2. When stratified by age and sex, the crude mortality rate was higher in participants aged >65 years than in those aged <65 years in all groups (261 vs. 87 cases per 1,000 person-years) in males than in females (188 vs. 160 per 1,000 person-years). Additionally, the group with the highest mortality rate was the male MA group aged ≥65 years (85 per 1,000 person-years), and those with the lowest mortality was the female NHI group aged <65 years (18 per 1,000 person-years) (
Table 4).
Fig. 1 shows the Kaplan-Meier survival curves. Patients’ survival rate in the NHI group was significantly lower than that of those in the MA group (p < 0.001). Additionally, the gap between the two curves widened over time during the first 5 years. The 5-year survival rates were 93.9% and 87.3% in the NHI and MA groups, respectively, and 6.6% higher in the NHI group. Furthermore, when comparing the group of patients aged ≥65 years, the difference in the survival probability between the NHI and MA patient groups significantly increased, and the difference was maintained throughout the observation period (p < 0.001) (
Fig. 2A). Moreover, even when patients aged <65 years were compared, the NHI group also had a higher survival probability than the MA group; however, the difference between the curves was smaller than when the ≥65 years group was compared (p < 0.001) (
Fig. 2B). Finally, when compared based on sex, a significant difference in both males and females was observed, and the overall survival rate of the NHI patient group was higher than that of the MA group (p < 0.001) (
Fig. 2C,
D).
Health insurance types are independently associated with mortality in patients who underwent hemodialysis
All-cause mortality was analyzed using the simple (unadjusted) and multiple (adjusted) Cox regression analyses, adjusting for age, sex, ESRD causes, and comorbidities. Compared with the NHI group, the mortality of the MA group was 1.28 (95% CI, 1.20–1.37; p < 0.001) and 1.39 times higher (95% CI, 1.30–1.49; p < 0.001) in the simple and multiple analyses, respectively. Additionally, when analyzed by sex, the simple analysis result was not significant, but the multiple analysis showed that the risk of death for females was 0.86 times lower (95% CI, 0.80–0.92; p < 0.001). Conversely, when divided by age, the risk of death was 3.18 times higher (95% CI, 2.97–3.41; p < 0.001) in the group aged ≥65 years compared to the group aged <65 years, according to the simple analysis; it was also 3.24 times higher (95% CI, 3.01–3.48) in the multiple analyses (
Table 5).
The risk of each causative disease of ESRD was compared using chronic glomerulonephritis as a reference. Patients with hypertension as the cause of ESRD had 1.76 times higher risk of death (95% CI, 1.50–2.07; p < 0.001) in simple analysis and 1.54 times (95% CI, 1.31–1.80; p = 0.01) in multiple analyses. In contrast, in patients with diabetes as the cause of ESRD, the risk of death was 3.59 times (95% CI, 3.11–4.14; p < 0.001) and 3.17 times (95% CI, 2.74–3.65; p < 0.001) higher in the simple and multiple analyses, respectively. Furthermore, in patients whose other cause was ESRD, the risk of death was 1.66 times (95% CI, 1.42–1.95; p < 0.001) and 1.57 times (95% CI, 1.34–1.84; p < 0.001) higher in the simple and multiple analysis, respectively, compared with the reference (
Table 5).
Furthermore, in the analysis based on comorbidities, patients with coronary artery disease had no significant difference in the simple analysis; however, the risk of death was significantly lower at 0.86 times (95% CI, 0.78–0.94; p = 0.001) in the multiple analysis. The risk of death in patients with arrhythmia was 0.78 times (95% CI, 0.68–0.89; p < 0.001) and 0.77 times (95% CI, 0.67–0.88; p < 0.001) lower in the simple and multiple analyses, respectively. However, no significant differences among the patients with heart failure were observed. In patients with cerebrovascular disease, the risk of death was significantly higher at 1.22 times (95% CI, 1.09–1.36; p < 0.001) and 1.08 times (95% CI, 0.96–1.21; p = 0.19) in the simple and multiple analyses, respectively, showing no significant difference. Furthermore, patients with hepatitis B had a significantly lower risk of death at 0.74 times (95% CI, 0.64–0.86; p < 0.001) and 0.92 times (95% CI, 0.79–1.07; p = 0.27) in the simple analysis and multiple analyses, respectively, with no significant difference. Conversely, in patients with hepatitis C, the risk of death was significantly lower by 0.74 times (95% CI, 0.60–0.90; p = 0.002) and 0.72 times (95% CI, 0.59–0.88; p = 0.001) in the simple and multiple analyses, respectively. Additionally, patients with liver cirrhosis exhibited no significant difference in the simple analysis; however, the risk of death was significantly higher at 2.02 times (95% CI, 1.27–3.23; p = 0.002) in the multiple analysis. Moreover, in patients with malignancy, the risk of death was 1.10 (95% CI, 0.87–1.26; p = 0.60) and 1.10 (95% CI, 0.91–1.32; p = 0.32) in the simple and multiple analyses, indicating no statistical significance.
We conducted an analysis where the model included dialysis vintage as an additional covariate, along with age and sex (
Supplementary Table 1, available online). After further adjustments for dialysis vintage, causes of ESRD, and comorbidities, the mortality HR remained significantly higher in the MA group than in the NHI group, although there was a considerable reduction in HR after adjusting for dialysis vintage. Adjusting for the underlying cause of ESRD did not eliminate the difference in HR between the two groups. However, when comorbidities were added to the model, statistical significance was no longer observed in the HR difference (adjusted HR, 1.07; 95% CI, 1.00–1.14).
Comparison of the causes of death between two groups
The cause of death was analyzed in 3,525 patients who died during the observation period, and no significant difference was found in the cause of death between the two groups. However, heart disease was the most prevalent cause of death in both groups, with heart attack being the most common. The second cause of death was an infectious disease, and the third was from causes other than those found in the general population (
Supplementary Table 2, available online) [
15].
Discussion
Using nationwide ESRD patient registry data from 2001 to 2017, we categorized NHI and MA beneficiaries based on health insurance type and compared demographics, treatment processes and outcomes, and mortality.
We confirmed differences between the two groups regarding demographic characteristics, age, ESRD causes, and comorbidities. The population aged ≥65 years was more prevalent in the NHI group, which was analyzed similarly in a previous study [
8]. However, the dialysis vintage was longer in the MA group, indicating earlier initiation of dialysis in the MA group. Diabetes was the most prevalent cause of ESRD in both groups, followed by hypertension and chronic glomerulonephritis. Since these three diseases account for most of the diseases causing ESRD, it was possible to reaffirm the significance of managing these three diseases to prevent ESRD. Additionally, comorbidities were common in the MA group, excluding malignancy. Although there was no difference in coronary artery disease (the most prevalent cause of heart failure) between the two groups, the higher proportion of heart failure in the MA group implies that MA beneficiaries require additional management after coronary artery disease.
Regarding the treatment process, the proportion of patients using non–calcium-based phosphate inhibitors, which is a relatively expensive drug among phosphate inhibitors, was lower in the MA group than in the NHI patient group. Similarly, this prescription pattern was observed in the ESA selection. In the MA group, the erythropoietin prescription rate was high; however, darbepoetin and CERA, which are expensive drugs with high potency, were high in the NHI group. Additionally, the MA group had lower treatment goals than the NHI patient group in most treatment outcome indicators. Interestingly, considering the treatment process and treatment outcomes comprehensively, the more aggressive use of newly developed drugs may be the reason for achieving higher treatment goals in the NHI group than in the MA group. The cause of the difference in drug prescription patterns between the two groups appears to be a cost-saving measure for medical institutions. Meanwhile, there were more patients in the MA group who received dialysis three times a week. After the implementation of the fixed-payment system, medical expenses decreased by 4.7%; however, there was an increase in hospital visits per patient by 9.5%. One study analyzed that the cause of this change was a shift in medical providers’ behavior to compensate for the loss of income due to the fixed-payment system by increasing the amount of treatment [
7]. Furthermore, the lower residual renal function, earlier initiation of dialysis, and longer duration of dialysis treatment among the MA group may be contributing factors. Nonetheless, these findings highlight the necessity for increased medical support in caring for this specific patient population. In response to this, the medical community has consistently argued that the government reimbursement costs are insufficient compared to the actual cost of providing better medical treatment in the MA group, and thus, the government should make additional efforts to address this constraint.
Furthermore, it was found that the MA patient group had a lower survival probability when analyzing survival between the groups, with a significant difference even when categorized by age and sex (p < 0.001). Among them, the survival rate difference between the groups was the largest in the group aged ≥65 years, which implies that healthcare intervention is crucial for those aged ≥65 years receiving HD. Conversely, when the survival probabilities of all patients were compared (
Fig. 1), the difference between the two groups gradually decreased 5 years after starting dialysis, which decreased after 5 years. Furthermore, the survival probabilities converged after approximately 13 years and then reversed, considered to be affected by the survival probabilities of male patients (
Fig. 2C). Therefore, additional studies are required on the factors that reduce the difference in survival probabilities, particularly the effect in male patients.
Over the past 20 years, the mortality rate of patients with ESRD has decreased to approximately one-third, with a steadily increased 5-year survival rate. However, when analyzed in this study using the health insurance type, it was confirmed that a large gap existed between the two groups. Therefore, these findings create awareness of the need to improve HD treatment quality and health equity in the MA group receiving HD and the need for active policy intervention in the MA group to reduce this difference. In general, health insurance type reflects socioeconomic status (SES), and low SES taken for granted as a risk factor for all-cause mortality in patients receiving HD [
16–
18]. However, the public health care system, including the MA program, exists to protect these vulnerable patients; therefore, government authorities should try to improve these issues reported.
This study had some limitations. First, because only the KORDS registry data were used to investigate demographic factors, income level, or major socioeconomic factors were excluded in this analysis. Therefore, this can be considered a limitation of the registry data; it is expected that the registration project will have to overcome this obstacle by linking it with health insurance claim data. Second, hospitals participating in the data registration project accounted for approximately 72.8% of all dialysis medical institutions. This trend occurs because there is a limit to voluntary participation in the registration project, not mandatory. Additionally, because of the investigation report’s nature, the survival rate may have been overestimated compared to the actual rate caused by factors including the death omission [
19]. Third, we used the last input value as the laboratory test result. Although using a one-time test result may limit the interpretation, it was used because it could be determined that the final test value was the result that received the most medical management. Finally, this study was analyzed using data from 2001 to 2017. However, the fixed-payment system has been partially improved twice more in 2018 and 2021. In 2018, it was amended to allow separate claims even when receiving treatment for a disease other than ESRD-related complications. As a result, HD patients have improved access to medical care by eliminating the inconvenience of having to visit a medical institution again or another medical institution. Recently, in 2021, the flat-payment system was partially changed to the relative value scale system to enable rate hikes. Therefore, further research is needed to examine the impact of institutional improvements since 2018 on outcomes.
The significance of this study is as follows: First, it is the first study to comprehensively compare and analyze the treatment process, outcomes, survival, and death by groups based on the health insurance type employing the representative KORDS data of Korean patients who received HD. Second, whereas the treatment indicators between the two groups were compared only with a simple average value in the previous study, we evaluated the overall patient management status between the two groups by further comparing the goal achievement rate suggested using international guidelines. Third, the prescription patterns of specific HD-related drugs in domestic patients undergoing HD were analyzed and compared between groups according to health insurance type. Therefore, this study is meaningful because it was possible to confirm the difference in the prescription for each type of drug between the two groups in the actual clinical field. Finally, this study has important significance by providing evidence for improving healthcare policies and systems to enhance health equity among MA beneficiaries.