Determinants of Inpatient Expenditure for Chronic Kidney Failure Patients in Guangzhou, China

Transcription

1 Determinants of Inpatient Expenditure for Chronic Kidney Failure Patients in Guangzhou, China Dr. Hui Zhang (Vivienne)* Professor Peter P. Yuen Dr. Yuan Huang 11 January 2016 *

2 Outline Introduction Objectives Methodology Results Conclusions

3 Introduction Information concerning the treatment costs of Chronic Kidney Failure (CKF) is scarce in China. Two health insurance schemes for urban population in China now. --UEBMI: Urban Employee Basic Medical Insurance --URBMI: Urban Resident Basic Medical Insurance

4 Objectives Investigate the direct medical costs for inpatient services of Chronic Kidney Failure Explore determinants of inpatient expenditure for Chronic Kidney Failure (CKF) patients in Guangzhou, China

5 Methodology Data Sources: Reimbursement claim database cover entire enrollees of UEBMI and URBMI in Guangzhou. Chronic Kidney Failure patients in hospitals between 2010 January and 2012 December were all included. Total 5,823 hospitalization records were analyzed.

6 Econometric Model Methodology Extended Estimating Equations (EEE) model (Extended Generalized Linear Model) --Factors associated with total inpatient expenses OLS model --Factors associated with % of out-of-pocket expenses for inpatient treatment of CKF

7 Results: Descriptive Statistics Table 1. Social demographics, clinical characteristics and healthcare utilization of hospitalized patients with chronic kidney failure All cases UEBMI cases URBMI cases Number of cases Social demographics Gender: Male (%) Age (Mean±SD, years) 60.24± ± ±18.75 <60 (%) (%) >70 (%) Clinical characteristics (%) Renal Compensation (ICD10: N18.003) Azotemia (ICD10: N18.001) Uremia (ICD10: N18.002) Unspecified Uremia (ICD10: N19 02) Hospital level (%) Primary Secondary Tertiary Length of stay (Mean±SD, days) 14.69± ± ±12.96 Referred from other hospital (%) Readmission in 15 days (%) ICU admission (%) Transplant surgery (%) Year Year Year

8 Results: Descriptive Statistics Table 2. Hospitalization financial costs of patients with chronic kidney failure All cases UEBMI cases URBMI cases Number of cases All cases Medical expenditure per visit (Mean±SD, yuan) ± ± ± Medical expenditure per visit (Median, yuan) Medication (%) Out-of-pocket (%) Renal Compensation (ICD10: N18.003) Medical expenditure per visit (Mean±SD, yuan) ± ± ± Medical expenditure per visit (Median, yuan) Medication (%) Out-of-pocket (%) Azotemia (ICD10: N18.001) Medical expenditure per visit (Mean±SD, yuan) ± ± ± Medical expenditure per visit (Median, yuan) Medication (%) Out-of-pocket (%) Uremia (ICD10: N18.002) Medical expenditure per visit (Mean±SD, yuan) ± ± ± Medical expenditure per visit (Median, yuan) Medication (%) Out-of-pocket (%) Unspecified Uremia (ICD10: N19 02) Medical expenditure per visit (Mean±SD, yuan) ± ± ± Medical expenditure per visit (Median, yuan) Medication (%) Out-of-pocket (%)

9 Figure 1 The composition of total medical expenditure (UEBMI patients) 4.95% 23.36% Examination 36.24% Treatment Medication Beds 35.45%

10 Figure 2 The composition of total medical expenditure (URBMI patients) 4.65% 24.16% Examination 37.29% Treatment Medication 33.90% Beds

11 Results: EEE Model Table 3. Factors associated with total medical expenses per inpatient visit of chronic kidney failure (EEE model) (1) All cases (2) UEBMI cases (3) URBMI cases (N=5823) (N=5234) (N=589) Coef. Std. Err. Marginal Coef. Std. Err. Marginal Coef. Std. Err. Effect Effect Marginal Effect Male [0.011] [0.011] [0.026] Age [0.000]*** [0.000]*** <0.001 [0.001] UEBMI [0.016]*** Hospital level: primary [0.043]*** [0.048]*** [0.068]*** Hospital level: secondary [0.013]*** [0.014]*** [0.037]*** Referred from other hospital [0.060]*** [0.063]*** [0.094] Readmission in 15 days [0.053] [0.053] [0.180] ICU admission [0.244]*** [0.244]*** Transplant surgery [0.079]*** [0.079]*** Length of stay [0.001]*** [0.001]*** [0.003]*** Renal Compensation (ICD10: N18.003) [0.018]*** [0.019]*** [0.040]*** Azotemia (ICD10: N18.001) [0.016]*** [0.017]*** [0.046] Unspecified Uremia (ICD10: N19 02) [0.011]*** [0.012]*** [0.030] Year [0.016] [0.018]* [0.032] Year [0.016]* [0.017]* [0.036] λ [0.025]*** [0.027]*** [0.071]*** θ [0.038]*** [0.042]*** [0.042]*** θ [0.107]*** [0.117]*** [0.188]*** Note: Standard errors in brackets. *** p<0.01, ** p<0.05, * p<0.1. EEE - extended generalized linear model.

12 Results: OLS Model Table 4. Factors associated with % of out-of-pocket expenses for inpatient treatment of chronic kidney failure (OLS model) (1) All cases (2) UEBMI cases (3) URBMI cases (N=5823) (N=5234) (N=589) Coef. Std. Err. Coef. Std. Err. Coef. Std. Err. Male [0.003]*** [0.003]*** [0.011]* Age [0.000]*** [0.000]*** [0.000]** UEBMI [0.005]*** Hospital level: primary [0.016] [0.018] [0.040]*** Hospital level: secondary [0.004]*** [0.004]*** [0.013]*** Referred from other hospital [0.012]*** [0.012]* [0.051]*** Readmission in 15 days [0.010]* [0.010] [0.031] ICU admission [0.020] [0.019] Transplant surgery [0.011] <0.001 [0.010] Length of stay [0.000]*** [0.000]*** [0.000]*** Renal Compensation (ICD10: N18.003) [0.008]*** [0.008]*** [0.024] Azotemia (ICD10: N18.001) [0.004]*** [0.004]*** [0.016] Unspecified Uremia (ICD10: N19 02) [0.003] < [0.003] [0.012]*** Year [0.004]*** [0.004]*** [0.016]*** Year [0.005]*** [0.004]*** [0.015]*** R-squared Note: Standard errors in brackets. *** p<0.01, ** p<0.05, * p<0.1. OLS - ordinary least square.

13 Conclusions Both demand and supply side factors were significantly associated with the direct inpatient services costs of Chronic Kidney Failure. The establishment of urban medical insurance schemes has reduced some financial burden for the insured urban population.

14 Conclusions However, Medication spending remains high. (More than 35% of total inpatient expenditure) The insured urban enrollees are NOT completely free from the risk of large out-ofpocket payments. (Especially for URBMI enrollees)

15 Thank you very much!