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Table 6 Malmquist index of medical services in 31 provinces between 2007 and 2019

From: The impact of human resources for health on the health outcomes of Chinese people

DMU

effch

techch

pech

sech

tfpch

Beijing

1.081

0.851

1.034

1.045

0.919

Tianjin

1.000

0.866

1.000

1.000

0.866

Hebei

0.979

0.969

1.029

0.952

0.949

Shanxi

1.030

0.947

1.029

1.001

0.975

Inner Mongolia

1.018

0.915

1.012

1.006

0.931

Liaoning

0.981

0.946

0.980

1.001

0.928

Jilin

1.073

0.890

1.083

0.991

0.954

Heilongjiang

1.002

0.937

1.002

1.000

0.939

Shanghai

1.029

0.865

1.000

1.029

0.891

Jiangsu

0.973

0.963

0.946

1.029

0.937

Zhejiang

0.996

0.943

0.947

1.051

0.940

Anhui

0.971

0.946

0.997

0.974

0.918

Fujian

1.016

0.957

1.020

0.996

0.973

Jiangxi

1.002

0.951

1.038

0.966

0.953

Shandong

0.960

0.956

0.937

1.024

0.918

Henan

0.982

0.949

0.954

1.030

0.933

Hubei

0.998

0.951

0.968

1.031

0.949

Hunan

1.013

0.930

1.007

1.005

0.942

Guangdong

1.002

0.955

0.990

1.012

0.957

Guangxi

0.989

0.956

0.991

0.998

0.946

Hainan

1.000

0.966

1.000

1.000

0.966

Chongqing

0.985

0.922

0.919

1.072

0.908

Sichuan

0.997

0.937

0.997

1.000

0.934

Guizhou

0.978

0.932

0.967

1.011

0.911

Yunnan

0.998

0.950

1.000

0.997

0.948

Tibet

1.000

0.918

1.000

1.000

0.918

shaanxi

1.021

0.942

1.044

0.978

0.961

Gansu

1.040

0.918

1.036

1.004

0.955

Qinghai

1.016

0.941

1.014

1.002

0.956

Ningxia

1.035

0.912

1.034

1.001

0.944

Sinkiang

1.054

0.930

1.050

1.004

0.980

mean

1.007

0.932

1.000

1.006

0.938

  1. DMU Decision Making Unit, effch Technical efficiency change, techch Technological change, pech Pure efficiency changem sech Scale efficiency change, tfpch total factor productivity change