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Erschienen in: BMC Health Services Research 1/2016

Open Access 01.12.2016 | Research article

Mortality and treatment costs of hospitalized chronic kidney disease patients between the three major health insurance schemes in Thailand

verfasst von: Sirirat Anutrakulchai, Pisaln Mairiang, Cholatip Pongskul, Kaewjai Thepsuthammarat, Chitranon Chan-on, Bandit Thinkhamrop

Erschienen in: BMC Health Services Research | Ausgabe 1/2016

Abstract

Background

Thailand has reformed its healthcare to ensure fairness and universality. Previous reports comparing the fairness among the 3 main healthcare schemes, including the Universal Coverage Scheme (UCS), the Civil Servant Medical Benefit Scheme (CSMBS) and the Social Health Insurance (SHI) have been published. They focused mainly on provision of medication for cancers and human immunodeficiency virus infection. Since chronic kidney disease (CKD) patients have a high rate of hospitalization and high risk of death, they also require special care and need more than access to medicine. We, therefore, performed a 1-year, nationwide, evaluation on the clinical outcomes (i.e., mortality rates and complication rates) and treatment costs for hospitalized CKD patients across the 3 main health insurance schemes.

Methods

All adult in-patient CKD medical expense forms in fiscal 2010 were analyzed. The outcomes focused on were clinical outcomes, access to special care and equipment (especially dialysis), and expenses on CKD patients. Factors influencing mortality rates were evaluated by multiple logistic regression.

Results

There were 128,338 CKD patients, accounting for 236,439 admissions. The CSMBS group was older on average, had the most severe co-morbidities, and had the highest hospital charges, while the UCS group had the highest rate of complications. The mortality rates differed among the 3 insurance schemes; the crude odds ratio (OR) for mortality was highest in the CSMBS scheme. After adjustment for biological, economic, and geographic variables, the UCS group had the highest risk of in-hospital death (OR 1.13;95% confidence interval (CI) 1.07–1.20; p < 0.001) while the SHI group had lowest mortality (OR 0.87; 95% CI 0.76–0.99; p = 0.038). The circumscribed healthcare benefits and limited access to specialists and dialysis care in the UCS may account for less favorable comparison with the CSMBS and SHI groups.

Conclusions

Significant differences are observed in mortality rates among CKD patients from among the 3 main healthcare schemes. Improvements in equity of care might minimize the differences.
Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​s12913-016-1792-9) contains supplementary material, which is available to authorized users.
The original version of this article was revised to provide an updated Table 1.
An erratum to this article is available at http://​dx.​doi.​org/​10.​1186/​s12913-016-1874-8.
Abkürzungen
AKI
Acute kidney injury
CAPD
Continuous ambulatory peritoneal dialysis
CI
Confidence interval
CKD
Chronic kidney disease
CSMBS
The Civil Servant Medical Benefit Scheme
DM
Diabetes mellitus
ESA
Erythropoiesis stimulating agent
ESRD
End stage renal disease
GDP
Gross domestic product
GEE
Generalized estimating equation
GFR
Glomerular filtration rate
HIV/AIDS
Human immunodeficiency virus infection and acquired immune deficiency syndrome
HT
Hypertension
ICD
International Statistical Classification of Diseases and Related Health Problems
MLRA
Multiple logistic regression analysis
OR
Odds ratio
SD
Standard deviation
SHI
The Social Health Insurance
UCS
The Universal Coverage Scheme

Background

Thailand implemented healthcare reforms in 2002 to ensure universal healthcare provision [1]. The 4 national healthcare insurance schemes include: (i) the Universal Coverage Scheme (UCS) provides free medical care for persons without any other insurance (i.e., > 70% of the population: the majority of farmers, low-income persons, and the unemployed); (ii) the Civil Servant Medical Benefit Scheme (CSMBS) provides free medical care for government employees and their dependents; (iii) the Social Health Insurance (SHI) scheme for private sector employees; and, (iv) private insurance. The first 3 schemes cover > 96% of the population [2].
The level of healthcare in Thailand depends on the particular hospital type and location. Community hospitals principally provide primary care and have limited resources for treating complex illnesses. Patients from the latter are sent to general (secondary) and tertiary hospitals, as appropriate. The distribution of hospitals in turn depends on economics and geography. The central region—where the capital is located—has the highest gross domestic product (GDP) per capita (~158% of national GDP). By comparison, the respective proportion of national GDP of the Northeast and North is 34 and 45% [3].
Previous reports—comparing the fairness of healthcare provision among the 3 main healthcare schemes—were mainly on the provision of medication for cancers and HIV/AIDS [48]. To our knowledge, there has been no report comparing the different healthcare schemes vis-à-vis chronic diseases (i.e., chronic kidney diseases – CKD) that require medicine, special care teams, special medical equipment, and hospitalization.
Since CKD patients have an increased rate of hospitalization and a high risk for death [9, 10], we evaluated the nationwide healthcare data of hospitalized CKD patients in fiscal year 2010 for practice outcomes of healthcare among the 3 main health insurance schemes. Our particular focus was on differences in (i) clinical outcomes, (ii) access to special care and equipment (notably dialysis), and (iii) budgeting.

Methods

The data analyzed were from (i) the in-patients total medical expense forms from the UCS fiscal year 2010 from the National Health Security Office; (ii) the in-patient data from the CSMBS from the Comptroller General’s Department; and, (iii) the in-patient data from the SHI from the Social Security Office. The variables included: sex, age, occupation, address, type of hospital, health insurance scheme, co-morbidities, length of hospital stay (days), complications, treatment, clinical outcomes, and medical expenses (costs charged). Additional information obtained from the Nephrology Society of Thailand, the National Statistical Office, and the Office of the National Economic and Social Development Board, Office of the Prime Minister included: ratio of nephrologists to dialysis units/regional population and end-stage renal disease (ESRD) patients, and the reimbursement of renal replacement therapies among the different healthcare schemes.
The in-patient data were first checked for accuracy by examining for (i) overlapping information (ii) visit dates (iii) missing items (iv) incorrect coding and (v) the correct fiscal year. CKD patients were identified in either the primary diagnosis (CKD-primary) or secondary diagnosis (CKD-secondary) as code N18 of the International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10) [11]. Hemodialysis and peritoneal dialysis were identified as code 39.95 and 54.98, respectively (ICD-9-CM 2010 classification of procedures) [12]. The data were analyzed not only on the basis of health insurance scheme but also on the level of care provided (i.e., community/primary, general/secondary or tertiary hospital or private hospital) in order to assess accessibility to appropriate care.

Outcome measures

The differences across the 3 health insurance schemes vis-à-vis in-hospital mortality and high treatment cost were examined. Demographic data, comorbidities and complications were analyzed as to whether they affected the two measures. In addition, policies involving the CKD treatment of the three schemes, budget allocation were explored to facilitate the explanation of the differences of the outcome measures (if any).

Statistical analysis

STATA version 14 was used for the statistical analyses. The means ± SD or medians (25th-75th percentile) and percentages were used to present the continuous and categorical data, respectively. The generalized estimating equation (GEE) and multiple logistic regression analysis (MLRA) were performed to adjust the odds ratios for factors influencing the (i) high cost accounting for multiple admissions within an individual and (ii) mortality rate at individual level.

Results

Demographic data of the patients

In fiscal 2010, the population over 19 years of age numbered 47,966,734—or 74% of Thailand’s total population of 64.7 million. Approximately 96% of the adult population (46,208,964 persons) was covered by one of the 3 health insurance systems. The total number of adult in-patients was 3,876,792 (admitted 4,863,935 times), accounting for 71% of all in-patients. According to the 23 major disease groups in the ICD 10, among the respective causes of hospitalization and mortality, diseases of the genitourinary system ranked 7th among hospitalized patients (298,258 persons, 7.7% of all adults in-patients and 392,498 admissions) and the 7th cause of mortality [13].
CKD was the most common diagnosis of the genitourinary system. The total number of CKD patients was 128,338 (generating 236,439 admissions), and accounting for 4.9% of all adult in-patient admissions (268 persons or 493 visits per 100,000 adult population). Of these, 98,727 persons (185,161 admissions), 24,767 (42,348 admissions) and 4844 (8930 admissions) were covered in the UCS, CSMBS, and SHI groups, respectively.

Characteristics of hospitalized CKD patients under different healthcare schemes

Table 1 presents the characteristics of CKD patients in the UCS, CSMBS, and SHI schemes. The age of subjects in the CSMBS were the oldest while those in the SHI scheme were the youngest. Most of participants in the UCS, CSMBS and SHI scheme were admitted in a community, tertiary and private hospital, respectively. The patients in the CSMBS and SHI scheme comprised the majority from the central region while those in the UCS were from the Northeast region. Highest proportion of CKD patients in the CSMBS group was diagnosed as CKD-secondary. The respective proportion of ESRD among in-patients under the SHI, CSMBS and UCS was 52.1, 31.6, and 24.2%.
Table 1
Characteristics of CKD patients by the main three health schemes
Characteristics
The main three Thai health schemes
Universal Coverage Scheme
Civil Servant Medical Benefit Scheme
Social Health Insurance
Number of adult patients (persons)
98,727
24,767
4844
Number of admissions (times)
185,161
42,348
8930
Age (mean ± SD)
66.55 ± 13.36
72.23 ± 11.46
46.99 ± 12.16
Sex (male/female)
1/1.15
1/0.88
1/0.58
Region (%)
 N/NE/C/S
21.4/46.2/24.2/8.2
17.4/32.6/39.5/10.5
11.6/11.2/71.2/6.1
Hospital levels (%)
 Community hospital
49.95
27.24
1.84
 General hospital
23.58
24.49
16.72
 Tertiary hospital
22.92
48.14
35.61
 Private hospital
3.55
0.13
45.83
Onetime admission/Multiple admission (%)
62.6/37.4
64.8/35.2
60.0/40.0
CKD diagnosed as primary/secondary (%)
24.4/75.6
19.9/80.1
35.1/64.9
Proportion of ESRD ((%)
24.19
31.63
52.06
Common co-morbidities (%)
   
 Hypertension
56.91
67.90
63.79
 Diabetes mellitus
45.08
49.09
36.50
 Hyperlipidemia
17.19
25.05
20.05
 Ischemic heart disease
13.49
21.68
11.91
 Heart failure
14.28
13.95
12.70
 Gout
10.49
13.17
6.44
 Sepsis
12.78
14.71
10.90
 Pneumonia
9.94
12.25
8.20
 Acute kidney injury
8.59
10.26
7.23
 Diarrhea
8.63
8.34
7.51
 Stroke
6.51
11.41
5.66
 Respiratory failure
8.53
7.85
4.81
Complications (%)
   
 Anemia requiring blood transfusion
31.86
23.24
31.32
 Hyperkalemia
15.95
11.56
11.50
 Volume overload
12.44
8.96
14.80
 Metabolic acidosis
9.20
5.04
4.81
Dialysis treatment (% of admissions)
   
 Hemodialysis
6.97
16.64
24.15
 Peritoneal dialysis
2.98
1.86
2.15
Overall mortality rate (%)
10.39
12.44
8.71
Mortality rate in different hospital levels (%)
   
 Community/General/Tertiary/Private
3.7/14.9/17.5/13.2
5.9/14.5/15.1/15.2
7.9/8.04/10.4/7.6
Note: CKD chronic kidney disease, ESRD end stage renal disease, N northern region, NE northeastern region, C central region, S southern region, SD standard deviation

Associated co-morbidities

The top 12 diseases associated with CKD patients were hypertension (HT) (59.3%), diabetes mellitus (DM) (45.5%), hyperlipidemia (18.8%), ischemic heart disease (15.0%), heart failure (14.2%), sepsis (13.1%), gout (10.9%), pneumonia (10.3%), acute kidney injury on top CKD (8.9%), diarrhea (8.5%), respiratory failure (8.3%) and stroke (7.4%). Patients in the CSMBS had the greatest proportion of co-morbidities (Table 1).

Complications

Complications for all CKD patients comprised significant anemia requiring blood transfusion (30.2%), hyperkalemia (14.9%), volume overload (11.9%), and metabolic acidosis (8.2%). The rate of complications was highest in the UCS (Table 1).

Dialysis treatment

CKD patients needed dialysis, accounting for 15,684 (12.2%) patients. The mode of dialysis included hemodialysis (n = 12,175; 77.6%) and peritoneal dialysis (n = 3509; 23.4%). The percentage of those needing hemodialysis was greater under the SHI and CSMBS than the UCS (Table 1). The respective proportion of ESRD patients receiving both types of dialysis during admission under the UCS, SHI and CSMBS was 41.1, 50.5, and 58.5%.
The characteristics of CKD patients defined as CKD-primary or CKD-secondary and admitted in different hospital levels are presented in the Additional file 1: Table S1 and Additional file 2: Table S2. Subjects in the CKD-secondary group were older, stayed in hospital longer, were more likely from the central region and were admitted to a tertiary hospital. The CKD-secondary group also had more co-morbidities, incurred a higher hospital cost, and had higher mortality rate than the CKD-primary group. In contrast, the rate of complications was higher in the CKD-primary group. Patients treated in tertiary hospitals had more comorbidities; particularly cardiovascular disease, pneumonia, acute on top CKD, and sepsis. By region, hospitals admitting the greatest proportion of CKD patients were in the North and Northeast in community hospitals. By comparison, patients in the central region were admitted to tertiary hospitals. Most of the private hospitals are also located in the central region, where a significant number of patients in the SHI group were admitted.

Length of hospital stay

The longest hospital stay among CKD patients was in the central region at tertiary hospitals under the CSMBS (Table 2).
Table 2
Length of hospital stay and hospital charges for CKD patients by region, hospital level and healthcare scheme
 
Length of hospital stays (Days)
Hospital charges (Baht)
Mean ± SD
Median (25th-75th percentile)
Mean ± SD
Median (25th-75th percentile)
Insurance
 UCS
5.14 ± 8.01
3.00 (2.00–6.00)
16,040 ± 131,052
6506 (3599–13,562)
 CSMBS
9.40 ± 17.81
5.00 (3.00–10.00)
39,401 ± 113,206
12,685 (5694–31,169)
 SHI
7.49 ± 11.11
4.00 (3.00–8.00)
36,053 ± 87,854
14,745 (6773–33,588)
Region
 Northern
5.46 ± 7.41
3.00 (2.00–6.00)
15,626 ± 38,605
6796 (3660–14,335)
 Northeast
4.56 ± 7.21
3.00 (2.00–5.00)
13,292 ± 164,746
5827 (3378–11,507)
 Central
8.50 ± 15.74
5.00 (2.00–9.00)
37,717 ± 114,169
12,549 (5747–30,348)
 Southern
6.61 ± 10.91
4.00 (2.00–7.00)
19,443 ± 47,700
7847 (4111–17,058)
Hospital levels
 Community (All schemes)
4.02 ± 4.93
3.00 (2.00–5.00)
7683 ± 144,783
4482 (2830–7548)
  - UCS
3.78 ± 4.43
3.00 (1.00–5.00)
7196 ± 154,018
4349 (2775–7196)
  - CSMBS
5.85 ± 7.36
4.00 (3.00–7.00)
11,150 ± 24,473
5816 (3387–10,636)
  - SHI
6.89 ± 10.35
4.00 (3.00–8.00)
19,013 ± 35,546
8594 (4922–20,042
 General (All schemes)
6.56 ± 9.52
4.00 (2.00–7.00)
19,556 ± 119,149
9251 (4967–18,832)
  - UCS
5.97 ± 8.77
4.00 (2.00–7.00)
17,969 ± 130,809
8807 (4808–17,531)
  - CSMBS
9.08 ± 12.05
6.00 (3.00–10.00)
26,606 ± 56,668
12,179 (6162–25,407)
  - SHI
6.85 ± 8.56
4.00 (3.00–8.00)
18,754 ± 45,335
7823 (4152–17,042)
 Tertiary (All schemes)
8.64 ± 16.35
5.00 (2.00–9.00)
38,758 ± 102,610
14,404 (6998–32,997)
  - UCS
7.21 ± 11.68
4.00 (2.00–8.00)
28,033 ± 65,349
12,043 (6312–25,825)
  - CSMBS
11.71 ± 23.47
6.00 (3.00–12.00)
62,964 ± 154,866
22,389 (10,214–54,582)
  - SHI
8.65 ± 12.90
5.00 (3.00–9.00)
31,367 ± 71,631
12,724 (5761–28,578)
 Private (All schemes)
5.57 ± 8.85
3.00 (2.00–6.00)
43,915 ± 104,269
20,608 (9725–37,617)
  - UCS
4.83 ± 7.71
2.00 (1.00–5.00)
42,401 ± 101,864
20,611 (9415–33,539)
  - CSMBS
8.46 ± 13.55
5.00 (3.00–7.00)
30,826 ± 71,164
11,732 (7139–24,025)
  - SHI
6.86 ± 10.40
4.00 (3.00–7.00)
46,805 ± 108,756
20,820 (10,395–44,565)
Note: CKD chronic kidney disease, UCS Universal Coverage Scheme, CSMBS Civil Servant Medical Benefit Scheme, SHI Social Health Insurance, SD standard deviation

Factors influencing the high treatment cost of in-patient

Hospital charges for CKD patients were highest in (i) the central region compared with other regions (ii) at private hospitals compared with community, general and tertiary hospitals, and (iii) covered by CSMBS compared with UCS and SHI (Table 2). Comparing hospital charges of the 3 health schemes with the same hospital levels revealed that hospital charge of the SHI was significantly highest at community hospitals while the CSMBS was the highest at general and tertiary hospitals. No significant differences in hospital charges between the 3 health schemes treated at private hospitals were observed (Table 2).
After adjustment with the factors affecting high hospital charges (>50,000 baht or ~1470 USD per admission)—sex, hospital level, region, co-morbidities, complications, and dialysis treatment—the UCS and SHI groups had a respective 62 and 55% lower hospital charges than the CSMBS (Table 3).
Table 3
Factors influencing high hospital charges (>50,000 baht/1470 USD) among hospitalized, Thai, adult, CKD patients
Variables
No. of admission (times)
No. of high cost admission (%)
Crude odds ratio (95% CI)
p-value
Adjusted odds ratio (95% CI)
p-value
Sex
 Female
126,027
8490 (6.7)
1
<0.001
1
<0.001
 Male
110,412
9662 (8.8)
1.31 (1.27–1.36)
 
1.16 (1.12–1.20)
 
Age
 19–30
4376
405 (9.3)
1
 
1
 
 31–40
8392
715 (8.5)
0.92 (0.80–1.06)
0.24
1.03 (0.88–1.20)
0.70
 41–50
22,172
1682 (7.6)
0.81 (0.72–0.92)
0.001
1.08 (0.94–1.24)
0.26
 51–60
46,571
3408 (7.3)
0.77 (0.68–0.86)
<0.001
1.05 (0.92–1.20)
0.49
 61–70
62,672
4324 (6.9)
0.72 (0.64–0.81)
<0.001
1.01 (0.89–1.16)
0.85
 71–80
64,288
5065 (7.9)
0.82 (0.72–0.92)
0.001
1.02 (0.89–1.16)
0.82
  > 80
27,968
2553 (9.1)
0.95 (0.84–1.07)
0.40
1.01 (0.88–1.17)
0.85
Insurance
 CSMBS
42,348
6923 (16.4)
1
 
1
 
 SHI
8930
1441 (16.1)
0.99 (0.93–1.06)
0.85
0.45 (0.41–0.49)
<0.001
 UCS
185,161
9788 (5.3)
0.29 (0.28–0.30)
<0.001
0.38 (0.36–0.39)
<0.001
Hospital level
 Community
102,251
977 (1.0)
1
 
1
 
 General
56,525
4049 (7.2)
7.54 (7.03–8.10)
<0.001
3.58 (3.32–3.87)
<0.001
 Tertiary
66,150
10,974 (16.6)
19.36 (18.11–20.70)
<0.001
7.17 (6.67–7.70)
<0.001
 Private
11,513
2152 (18.7)
23.09 (21.28–25.05)
<0.001
13.82 (12.58–15.19)
<0.001
Region
 Northern
48,110
2645 (5.5)
1
 
1
 
 Northeast
104,067
3703 (3.6)
0.63 (0.60–0.66)
<0.001
0.74 (0.70–0.78)
<0.001
 Central
64,962
10,360 (16.0)
3.23 (3.08–3.39)
<0.001
1.83 (1.74–1.94)
<0.001
 Southern
19,300
1444 (7.5)
1.36 (1.27–1.46)
<0.001
1.21 (1.12–1.31)
<0.001
Co–morbidities
 Hypertension (yes/no)
125,565/110,874
11,037 (8.8)/7115 (6.4)
1.38 (1.34–1.42)
<0.001
1.00 (0.96–1.04)
0.96
 Diabetes mellitus (yes/no)
101,664/134,775
8775 (8.6)/9377 (7.0)
1.27 (1.23–1.31)
<0.001
1.12 (1.08–1.17)
<0.001
 Hyperlipidemia (yes/no)
31,229/205,210
3449 (11.0)/14,703 (7.2)
1.51 (1.45–1.57)
<0.001
1.06 (1.01–1.12)
0.016
 Ischemic heart disease (yes/no)
29,272/207,167
4406 (15.1)/13,746 (6.6)
2.42 (2.33–2.51)
<0.001
1.75 (1.67–1.84)
<0.001
 Heart failure (yes/no)
24,915/211,524
2679 (10.8)/15,473 (7.3)
1.53 (1.46–1.60)
<0.001
1.11 (1.05–1.17)
<0.001
 Gout (yes/no)
19,640/216,799
1407 (7.2)/16,745 (7.7)
0.92 (0.87–0.98)
0.005
0.99 (0.93–1.06)
0.76
 Sepsis (yes/no)
18,528/217,911
4586 (24.8)/13,566 (6.2)
4.62 (4.44–4.79)
<0.001
2.75 (2.62–2.88)
<0.001
 Pneumonia (yes/no)
14,732/221,707
4004 (27.2)/14,148 (6.4)
5.18 (4.98–5.40)
<0.001
3.27 (3.10–3.45)
<0.001
 Acute renal failure (yes/no)
12,133/224,306
3351 (27.6)/14,801 (6.6)
5.09 (4.88–5.31)
<0.001
2.35 (2.23–2.48)
<0.001
 Diarrhea (yes/no)
12,085/224,354
774 (6.4)/17,378 (7.75)
0.82 (0.76–0.88)
<0.001
0.98 (0.90–1.07)
0.69
 Stroke (yes/no)
11,886/224,553
2313 (19.5)/15,839 (7.1)
2.97 (2.83–3.12)
<0.001
1.82 (1.72–1.94)
<0.001
 Respiratory failure (yes/no)
11,347/225,092
3080 (27.1)/15,072 (6.7)
5.02 (4.80–5.25)
<0.001
2.30 (2.17–2.44)
<0.001
Complications
 Anemia requiring blood
57,727/178,712
7442 (12.9)/10,710 (6.0)
2.38 (2.31–2.46)
<0.001
2.25 (2.17–2.34)
<0.001
  Transfusion (yes/no)
 Hyperkalemia (yes/no)
23,505/212,934
2532 (10.8)/15,620 (7.3)
1.57 (1.51–1.64)
<0.001
1.17 (1.11–1.23)
<0.001
 Volume overload (yes/no)
22,091/214,348
1966 (8.9)/16,186 (7.55)
1.30 (1.24–1.36)
<0.001
0.99 (0.93–1.05)
0.67
 Metabolic acidosis (yes/no)
11,897/224,542
1549 (13.0)/16,603 (7.4)
1.90 (1.80–2.00)
<0.001
1.11 (1.04–1.19)
0.003
Mode of dialysis
 Hemodialysis
17,143/219,296
5239 (30.6)/12,913 (5.9)
6.45 (6.22–6.70)
<0.001
3.14 (3.00–3.28)
<0.001
 Peritoneal dialysis
4584/231,855
1170 (25.5)/16,982 (7.3)
4.16 (3.89–4.46)
<0.001
3.30 (3.04–3.59)
<0.001
Note: CKD chronic kidney disease, UCS Universal Coverage Scheme, CSMBS Civil Servant Medical Benefit Scheme, SHI Social Health Insurance, CI confidence interval

Factors associated with mortality

Table 4 presents patient characteristics. After adjustment for age, sex, region, hospital level, hospital charge, co-morbidities, complications, and mode of dialysis, the multiple logistic regression analysis revealed that the highest mortality rate was for patients under the UCS while the lowest was for those under the SHI. Patients under the SHI and CSMBS had a respective 23.0 and 11.5% reduction of mortality rates compared to the UCS group. Patients who received dialysis had a reduced mortality (hemodialysis; OR 0.90, 95% CI 0.85–0.96, p = 0.002, peritoneal dialysis; OR 0.87, 95% CI 0.78–0.96, p = 0.006). Other factors influencing the mortality rate included (i) elderly age (ii) level of care (i.e., tertiary hospitals had higher mortality rates than general and private hospitals while community hospital had lowest rate); (iii) presence of ESRD; (iv) co-morbidities (viz., sepsis, respiratory failure, stroke, pneumonia, acute on top CKD, ischemic heart disease, heart failure, and DM); and (v) complications of CKD (i.e., metabolic acidosis, hyperkalemia and volume overload) (Table 5).
Table 4
Characteristics of dead and alive hospitalized CKD patients
Characteristics
Discharge status of CKD patients
Dead CKD patients
Alive CKD patients
p-value
Number of patients (persons)
13,755
114,583
 
Age (years; mean ± SD)
67.89 ± 14.04
66.79 ± 13.70
<0.001
Sex (male/female)
1/0.98
1/1.07
<0.001
Health scheme (%)
   
UCS/CSMBS/SHI
74.5/22.4/3.1
77.2/18.9/3.9
<0.001
Hospital levels (%)
 Community/General/Tertiary/Private
   
  First admission
24.6/29.7/41.0/4.7
46.1/22.7/26.7/4.5
<0.001
  Frequent admission
17.3/33.0/44.9/4.8
42.7/24.2/28.5/4.5
<0.001
  Last admission
14.9/34.6/45.9/4.6
43.4/24.2/28.0/4.4
<0.001
Onetime admission/Multiple admission (%)
54.6/45.4
63.9/36.1
<0.001
CKD diagnosed as primary/secondary (%)
21.7/78.3
24.2/75.8
<0.001
Proportion of ESRD ((%)
39.29
25.16
<0.001
Common co-morbidities (%)
   
 Hypertension
59.54
59.26
0.52
 Diabetes mellitus
49.40
45.06
<0.001
 Hyperlipidemia
17.43
18.98
<0.001
 Ischemic heart disease
23.10
14.04
<0.001
 Heart failure
23.82
13.00
<0.001
 Gout
10.12
10.94
0.003
 Sepsis
44.68
9.29
<0.001
 Pneumonia
28.06
8.19
<0.001
 Acute kidney injury
21.61
7.33
<0.001
 Diarrhea
8.30
8.56
0.31
 Stroke
15.06
6.51
<0.001
 Respiratory failure
34.22
5.14
<0.001
Complications (%)
   
 Anemia requiring blood transfusion
43.01
28.64
<0.001
 Hyperkalemia
27.10
13.47
<0.001
 Volume overload
20.58
10.81
<0.001
 Metabolic acidosis
20.35
6.77
<0.001
Dialysis treatment (%)
   
 Hemodialysis
18.29
8.43
<0.001
 Peritoneal dialysis
5.21
2.44
<0.001
Length of stay (days; mean ± SD)
11.4 ± 24.8
5.8 ± 8.8
<0.001
Hospital charges (baht; mean ± SD)
61,662 ± 164,842
18,656 ± 55,546
<0.001
Note: ESRD end stage renal disease, CKD chronic kidney disease, ESRD end stage renal disease, UCS Universal Coverage Scheme, CSMBSCivil Servant Medical Benefit Scheme, SHI Social Health Insurance, SD standard deviation
Table 5
Prognostic factors influencing mortality rates among hospitalized, Thai, adult, CKD patients
Variables
No. of patients (persons)
Dead persons and mortality rate (%)
Crude odds ratio (95% CI)
p-value
Adjusted odds ratio (95% CI)
p-value
Sex
 Female
66,134
6814 (10.3)
1
 
1
 
 Male
62,204
6941 (11.2)
1.09 (1.06–1.13)
<0.001
1.03 (0.99–1.07)
0.17
Age
 19–30
1869
189 (10.1)
1
 
1
 
 31–40
4135
400 (9.7)
0.95 (0.79–1.14)
0.60
1.16 (0.95–1.42)
0.15
 41–50
10,556
1127 (10.7)
1.06 (0.90–1.25)
0.47
1.28 (1.07–1.54)
0.008
 51–60
23,073
2318 (10.0)
0.99 (0.85–1.16)
0.93
1.21 (1.01–1.44)
0.039
 61–70
32,837
3277 (10.0)
0.99 (0.84–1.15)
0.85
1.25 (1.05–1.50)
0.013
 71–80
37,727
4039 (10.7)
1.07 (0.91–1.24)
0.42
1.40 (1.18–1.68)
<0.001
  > 80
18,141
2405 (13.3)
1.36 (1.16–1.59)
<0.001
1.82 (1.52–2.19)
<0.001
Insurance
 CSMBS
24,767
3080 (12.4)
1
 
1
 
 UCS
98,727
10,253 (10.4)
0.82 (0.78–0.85)
<0.001
1.13 (1.07–1.20)
<0.001
 SHI
4844
422 (8.7)
0.67 (0.60–0.75)
<0.001
0.87 (0.76–0.99)
0.038
Hospital level
 Community
56,151
3384 (6.0)
1
 
1
 
 General
30,156
4091 (13.6)
2.45 (2.33–2.57)
<0.001
1.58 (1.50–1.68)
<0.001
 Tertiary
36,274
5634 (15.5)
2.87 (2.74–3.00)
<0.001
1.62 (1.53–1.71)
<0.001
 Private
5757
646 (11.2)
1.97 (1.80–2.15)
<0.001
1.51 (1.35–1.68)
<0.001
Hospital charges (Baht/USD)
 First quartile (<5550/< 163)
32,090
701 (2.2)
1
 
1
 
 Second quartile (5550–13,271/163–390)
32,079
2028 (6.3)
3.02 (2.77–3.30)
<0.001
2.08 (1.90–2.28)
<0.001
 Third quartile (13,272–34,502/390–1015)
32,085
3680 (11.5)
5.80 (5.34–6.30)
<0.001
2.98 (2.72–3.26)
<0.001
 Fourth quartile (>34,502/> 1015)
32,084
7346 (22.9)
13.30 (12.28–14.39)
<0.001
4.43 (4.03–4.88)
<0.001
Onetime admission/Multiple admission
80,764/47,574
7514 (9.3)/6241 (13.1)
1.47 (1.42–1.53)
<0.001
0.64 (0.61–0.68)
<0.001
CKD diagnosed as primary/secondary
30,731/97,607
2991 (9.7)/10,764 (11.0)
1.15 (1.10–1.20)
<0.001
0.95 (0.90–1.01)
0.11
ESRD (yes/no)
34,234/94,104
5405 (15.8)/8350 (8.9)
1.93 (1.86–2.00)
<0.001
1.49 (1.42–1.57)
<0.001
Co-morbidities
 Diabetes mellitus (yes/no)
58,427/69,911
6795 (11.6)/6960 (10.0)
1.19 (1.15–1.23)
<0.001
1.12 (1.08–1.17)
<0.001
 Ischemic heart disease (yes/no)
19,264/109,074
3178 (16.5)/10,577 (9.7)
1.84 (1.76–1.92)
<0.001
1.43 (1.35–1.51)
<0.001
 Heart failure (yes/no)
18,174/110,164
3277 (18.0)/10,478 (9.5)
2.09 (2.01–2.18)
<0.001
1.38 (1.31–1.46)
<0.001
 Sepsis (yes/no)
16,792/111,546
6146 (36.6)/7609 (6.8)
7.89 (7.58–8.20)
<0.001
4.28 (4.09–4.48)
<0.001
 Pneumonia (yes/no)
13,247/115,091
3860 (29.1)/9895 (8.6)
4.37 (4.19–4.56)
<0.001
1.59 (1.51–1.68)
<0.001
 Acute renal failure (yes/no)
11,367/116,971
2972 (26.1)/10,783 (9.2)
3.49 (3.33–3.65)
<0.001
1.44 (1.36–1.52)
<0.001
 Stroke (yes/no)
9527/118,811
2071 (21.7)/11,684 (9.8)
2.55 (2.42–2.68)
<0.001
1.85 (1.73–1.96)
<0.001
 Respiratory failure (yes/no)
10,596/117,742
4707 (44.4)/9048 (7.7)
9.60 (9.19–10.03)
<0.001
3.64 (3.45–3.83)
<0.001
Complications
 Anemia requiring blood
 Transfusion (yes/no)
38,730/89,608
5916 (15.3)/7839 (8.7)
1.88 (1.81–1.95)
<0.001
1.03 (0.98–1.07)
0.28
 Hyperkalemia (yes/no)
19,165/109,173
3728 (19.5)/10,027 (9.2)
2.39 (2.29–2.49)
<0.001
1.48 (1.40–1.55)
<0.001
 Volume overload (yes/no)
15,213/113,125
2,831 (18.6)/10,924 (9.7)
2.14 (2.04–2.24)
<0.001
1.23 (1.16–1.31)
<0.001
 Metabolic acidosis (yes/no)
10,561/117,777
2,799 (26.5)/10,956 (9.3)
3.52 (3.35–3.69)
<0.001
1.72 (1.62–1.82)
<0.001
Mode of dialysis
 Hemodialysis (yes/no)
12,175/116,163
2,516 (20.7)/11,239 (9.7)
2.43 (2.32–2.55)
<0.001
0.90 (0.85–0.96)
0.002
 Peritoneal dialysis (yes/no)
3,509/124,829
717 (20.4)/13,038 (10.4)
2.20 (2.02–2.39)
<0.001
0.87 (0.78–0.96)
0.006
Note: CKD chronic kidney disease, ESRD end stage renal disease, UCS Universal Coverage Scheme, CSMBS Civil Servant Medical Benefit Scheme, SHI Social Health Insurance, CI confidence interval
In addition to the factors associated with mortality, health policies among the health schemes differed (Table 6). Patients in the UCS trended to have fewer benefits than patients in the other healthcare schemes. Patients under the UCS were not able to choose the hospitals with full-scale CKD care. They had to be referred by a primary care hospital. The limited distribution of nephrologists and dialysis units outside major urban centres might be a barrier for patients under the UCS who live mainly in the North and Northeast (Table 7).
Table 6
Comparison the health policies on the health care providing and reimbursement among the three schemes
Issues
SHI
UCS
CSMBS
Financial barriers to equitable access
Acute complications occurred, the patients had access to special care without barrier by referral system.
Administrative efficiency
Three health care schemes applied the same clinical practice guidelines
Patient and provider autonomy
The patients received the care from only the self-registry hospitals (either private or public hospitals). Treatment of ESRD was hemodialysis or CAPD depended on facility of the self-registry hospitals.
The patients received care only the public hospitals in their casement areas, mostly community or general hospitals. The patients were referred to higher facility hospital whenever the complications occurred. CAPD was the first treatment for ESRD patients.
The patients freely chosen the public or tertiary care hospital that they preferred. Physicians had autonomy to choose hemodialysis or CAPD for treatment of ESRD.
Non-financial barriers to equitable access
Most of the patients worked in the big cities in Bangkok and central region of Thailand which had better population/nephrologist ratio than UCS
Most of the patients were in the rural area that had least population/nephrologist ratio
Most of the patient chosen to be care in the tertiary care hospitals and medical school hospitals which had best population/nephrologist ratio
Reimbursement of erythropoietin administration
   
 - Pre-dialysis
No
No
Yes
 - Dialysis
Yes
Yes
Yes
Reimbursement of dialysis for ESRD patients
   
 - CAPD
Yes
Yes
Yes
 - Hemodyalysis
Not more than 1,500 bahts (44 USD)/session and not more than 4,500 bahts (132USD)/week.
Hemodialysis was allowed only CAPD was contraindication or having complications. Not more than 1,500–1,700 bahts (44–50 USD)/session and not more than 3,000–3,400 bahts (88–100 USD)/week.
As the actual expenses
Note: ESRD end stage renal disease, CAPD continuous ambulatory peritoneal dialysis, SHI Social Health Insurance, UCS Universal Coverage Scheme, CSMBS Civil Servant Medical Benefit Scheme
Table 7
Comparing the ratio of population and ESRD patients per one nephrologists and one dialysis unit in different regions
Regional health care
Population/nephrologist (n)
Population/dialysis unit (n)
ESRD patients/nephrologist (n)
ESRD patients/dialysis unit (n)
Bangkok
44,177
51,585
71
83
Central part
204,307
152,801
99
74
Northern
529,820
233,121
221
97
Northeastern
592,690
197,563
229
76
Southern
422,429
173,941
144
59
Note: ESRD end stage renal disease

Discussion

CKD is defined as abnormalities in the kidney structure or function and/or a decreased glomerular filtration rate for more than 3 months (GFR < 60 ml/min/1.73 m2) [14]. Code N18 in the ICD-10 represents an older nomenclature for chronic renal failure as a decrease in GFR comparable to stage 3a-5 CKD patients (estimated GFR < 60 ml/min/1.73 m2). Our study revealed that 45–60% of admitted CKD patients also had hypertension and diabetes. The co-morbidities associated with mortality and high hospital charges were sepsis, pneumonia, respiratory failure followed by cardiovascular diseases and AKI on pre-existing CKD. This finding agrees with previous studies that demonstrated the severity of CKD increased in-hospital mortality among patients with acute coronary syndrome [1520], heart failure [2123], cardiac surgery [24], and stroke [25]. Early optimum therapeutic interventions and appropriate medications might improve clinical outcomes and reduce the cost of hospitalization.
After the Thai healthcare reforms were implemented in 2002, the poor indeed had wider access to medical services. Equity of health financing, health workers and healthcare infrastructure have been studied and an improving trend in equity was reported [2629]. Notwithstanding, differences in access to hospital types persist among the 3 insurance schemes. The population under UCS must be registered at a community hospital near home. When necessary, there is a line of referrals. Any patient who does not follow the referral process and attempts to go directly to a tertiary care center will have to pay all costs by themselves. By comparison, under the CSMBS, a government employee can register at any public hospital according to their preference [2] while an employee covered by SHI must register at the contracted public or private hospital [30]. If a referral is required, the employee must go to one of the hospitals in the designated network. Only in an emergency may persons covered by SHI or UCS be exempted from paying; however, they must be transferred to their registered hospital as soon as possible. These vagaries in regulations provide an explanation as to why those on UCS go to community hospitals and government employees go to tertiary care hospitals [2]. Since the UCS group comprises a higher proportion of low socio-economic patients, mainly located in rural region, they experience delayed hospital accessibility. Furthermore, our study revealed differences in clinical outcomes of hospitalized CKD patients that might represent residual inequality that needs addressing.
Mortality rates of hospitalized CKD patients differed among the 3 insurance schemes: the crude odd ratios revealed the highest mortality under the CSMBS. Patients admitted under the CSMBS had more severe or complicated disease than the other schemes; as indicated by the highest (i) percentage of life-threatening co-morbidities, (ii) length of stay, and (iii) hospital charges. After adjusting for biological and economic geographic variables, the multivariable analysis demonstrated that the UCS group had the highest risk of in-hospital death while the SHI group had the lowest mortality. The explanation may be related to the limited health care benefits under the UCS compared to the CSMBS and SHI. Table 6 presents a comparison of the health policies among the 3 schemes. The CSMBS appears to have better benefits than the other schemes; such as free access to specialist care, free service without capitation, and better chances of getting kidney replacement therapy (either hemodialysis or CAPD) for ESRD patients. Furthermore, the ratios of population and ESRD patients per nephrologist and dialysis unit were the best in Bangkok and the central region: that is, the regions where a higher proportion of patients are under either the CSMBS or SHI. On the other hand, in the other regions where most patients are under the UCS, poorer ratios prevail. The insufficiency of medical personnel and equipment might be the reasons for higher CKD complications and less dialysis treatment in the UCS group. Previous studies confirmed that remote CKD patients were less likely to receive specialist care, to receive laboratory testing, and to get appropriate medications, and were more likely to die or be hospitalized compared with those living closer to a nephrologist [31, 32].
Improving CKD care might be achieved by implementing policies that ensure fairness by providing a comparable budget allocation among the healthcare schemes. The “PD First” policy in Thailand launched in 2008 initiated CAPD as renal replacement therapy for ESRD patients under the UCS [33]. This policy represents an effective strategy for correcting the inadequate distribution of hemodialysis machines and insufficient numbers of nephrologists in rural areas and to underprivileged groups.
Anemia is one of the complications seen in CKD patients, and this can be corrected by injection of erythropoiesis stimulating agent (ESA). ESA is relatively costly and is only reimbursed during the pre-dialysis period under the CSMBS scheme. Our data revealed that there was a lower proportion of patients with anemia requiring blood transfusion under the CSMBS than the UCS or SHI groups. More intensive, high-cost medication support by the 3 main health schemes might reduce morbidity and hospitalization.
The strength of this study is that almost all of the subjects were hospitalized adult, Thai, CKD patients. The results, therefore, provide a clear overview of the situation vis-à-vis these adult patients; however, some limitations existed. Lack of a registered nationwide laboratory system means that there is no standardized staging of CKD patients, which might influence the clinical outcomes. The present study analyzed the administrative claim data, therefore socio-economic status of patients was not available. In addition, we are not able to generate an area locator as a proxy for socio-economic status of individual patients due to lack of data. Insufficient data of these demand-side characteristics observed at the individual level made some limitations in comparison of equity among the three health insurance schemes. The record of charges for each group represents an average and this might not wholly characterize the severity of individual patients nor include details of the procedures and medical instruments needed for each patient. Moreover, the mortality focused in this study was outcome at discharge which may be different with mortality after discharge because some patients died at home.

Conclusions

Concerning the treatment of hospitalized CKD patients, the UCS group had the poorest healthcare benefits compared to the other healthcare schemes—e.g., less budget for hospital care (charge cost), poorer access to specialist care, and treatment options that depended on variable healthcare policies. These might explain the greater mortality rate of those under the UCS compared to those under the CSMBS or SHI. In order to improve health outcomes among hospitalized CKD patients, new healthcare policies are needed to improve budget allocations, accessibility to specialist care, and distribution of resources.

Acknowledgements

We thank (a) Assoc. Prof. Sumitr Sutra for providing the data (b) Mr. Bryan Roderick Hamman for assistance with the English-language presentation of the manuscript through the Publishing Clinic, Research Affairs, Faculty of Medicine, Khon Kaen University.

Funding

The study was supported by funding from the Faculty of Medicine, Khon Kaen University and the Thailand Research Fund (IRG #5780016).

Availability of data and materials

The additional data for characteristics of CKD patients are available in the Additional files 1 and 2.

Authors’ contributions

All authors were involved in the conception and study design. CP and CC have collected and clarified data from the three health-scheme offices. Acquisition of data, analysis and interpretation of data were done by SA and KT under the supervision of BT. SA, PM, and BT drafted the manuscript. All authors reviewed and approved the final version of the manuscript.

Competing interests

The authors declare that they have no competing interests.
Not applicable.
The Khon Kaen University Ethics Committee for Human Research (KKUEC) reviewed and approved our protocols based on the Helsinki Declaration and the ICH Good Clinical Practice Guidelines. The reference number was HE541036. Since all of the data in the study were from hospital records, written informed consent was not possible. Participants’ confidentiality was ensured by data protection and privacy legislation.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.
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Metadaten
Titel
Mortality and treatment costs of hospitalized chronic kidney disease patients between the three major health insurance schemes in Thailand
verfasst von
Sirirat Anutrakulchai
Pisaln Mairiang
Cholatip Pongskul
Kaewjai Thepsuthammarat
Chitranon Chan-on
Bandit Thinkhamrop
Publikationsdatum
01.12.2016
Verlag
BioMed Central
Erschienen in
BMC Health Services Research / Ausgabe 1/2016
Elektronische ISSN: 1472-6963
DOI
https://doi.org/10.1186/s12913-016-1792-9

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