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Table 4 Results of multiple linear regression models for inpatients suffering quota payment diseases and general diseases

From: Effectiveness evaluation of quota payment for specific diseases under global budget: a typical provider payment system reform in rural China

Quota payment diseases

General diseases

Crude model

Adjusted model

Crude model

Adjusted model

Total fee

 2014

0

0

0

0

 2015

−611.66 (−661.33, −561.99) ***

− 631.57 (− 681.15, − 581.99) ***

2128.88 (1873.82, 2383.95) ***

2094.25 (1837.18, 2351.33) ***

 2016

−810.46 (−858.37, −762.55) ***

− 827.06 (− 875.10, − 779.03) ***

2686.53 (2418.57, 2954.50) ***

2567.26 (2294.38, 2840.14) ***

Actual compensation ratio

 2014

0

0

0

0

 2015

20.02 (19.3, 20.74) ***

20.26 (19.55, 20.98) ***

−8.29 (−8.66, −7.92) ***

− 8.57 (− 8.92, − 8.22) ***

 2016

21.47 (20.77, 22.16) ***

21.72 (21.03, 22.42) ***

−10.38 (−10.76, −9.99) ***

− 10.85 (− 11.22, − 10.47) ***

Out-of-pocket ratio

 2014

0

0

0

0

 2015

−7.54 (− 7.73, − 7.36) ***

−7.47 (− 7.65, − 7.28) ***

8.26 (7.89, 8.63) ***

8.54 (8.19, 8.89) ***

 2016

−10.35 (− 10.53, − 10.17) ***

−10.21 (− 10.39, − 10.03) ***

9.84 (9.45, 10.23) ***

10.31 (9.93, 10.68) ***

Constituent ratio of treatment fee

 2014

0

0

0

0

 2015

3.48 (3.22, 3.74) ***

3.62 (3.36, 3.87) ***

4.81 (4.42, 5.19) ***

4.90 (4.51, 5.28) ***

 2016

9.33 (9.08, 9.58) ***

9.45 (9.2, 9.70) ***

9.74 (9.34, 10.15) ***

10.06 (9.65, 10.47) ***

Constituent ratio of inspection and laboratory fee

 2014

0

0

0

0

 2015

0.23 (0.05, 0.41) ***

0.18 (−0.01, 0.36) ***

0.96 (0.71, 1.21) ***

0.93 (0.68, 1.19) ***

 2016

0.22 (0.04, 0.40) **

0.17 (−0.01, 0.35) *

3.44 (3.17, 3.70) ***

3.39 (3.12, 3.66) ***

Length of stay

 2014

0

0

0

0

 2015

−0.77 (−0.91, − 0.63) ***

−0.81 (− 0.95, − 0.67) ***

1.16 (0.93, 1.39) ***

0.93 (0.69, 1.16) ***

 2016

−1.21 (−1.34, −1.07) ***

−1.25 (−1.39, − 1.12) ***

1.80 (1.55, 2.04) ***

1.40 (1.16, 1.65) ***

  1. Data in the table: β (95%CI)
  2. ***p < 0.01; **0.01 ≤ p < 0.05; *p < 0.1
  3. Adjusted model adjusts for sex, age and individual attribute