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Table 8 Results of the technical efficiency decomposition

From: Approximating the influence of external factors on the technical efficiency score of hospital care: evidence from the federal states of Germany

DMUs

TTE(CRS)

PTE(VRS)

SE

DMUs

TTE(CRS)

PTE(VRS)

SE

Baden-WĂĽrttemberg

1_2015

0.870

0.986

0.883

1_2018

0.864

1.000

0.864

Bayern

2_2015

0.882

0.941

0.937

2_2018

0.861

0.934

0.921

Berlin (city state)

3_2015

0.996

0.998

0.999

3_2018

0.986

0.997

0.989

Brandenburg

4_2015

1.000

1.000

1.000

4_2018

0.971

1.000

0.971

Bremen (city state)

5_2015

0.943

0.981

0.961

5_2018

0.917

0.929

0.987

Hamburg (city state)

6_2015

0.985

1.000

0.985

6_2018

0.944

0.948

0.996

Hessen

7_2015

0.938

0.986

0.951

7_2018

0.902

0.954

0.945

Mecklenburg-Vorpommern

8_2015

0.914

0.916

0.998

8_2018

0.905

0.913

0.991

Niedersachsen

9_2015

0.917

1.000

0.917

9_2018

0.889

0.996

0.893

Nordrhein-Westfalen

10_2015

0.907

0.921

0.985

10_2018

0.898

0.913

0.983

Rheinland-Pfalz

11_2015

0.899

0.966

0.930

11_2018

0.893

0.948

0.942

Saarland

12_2015

1.000

1.000

1.000

12_2018

0.975

0.996

0.979

Sachsen

13_2015

0.961

0.965

0.995

13_2018

0.942

0.948

0.993

Sachsen-Anhalt

14_2015

0.917

0.932

0.984

14_2018

0.889

0.894

0.994

Schleswig–Holstein

15_2015

0.882

1.000

0.882

15_2018

0.877

1.000

0.877

ThĂĽringen

16_2015

0.946

1.000

0.946

16_2018

0.900

0.914

0.985

Baden-WĂĽrttemberg

1_2016

0.876

0.993

0.882

1_2019

0.861

0.999

0.861

Bayern

2_2016

0.883

0.945

0.934

2_2019

0.864

0.940

0.919

Berlin (city state)

3_2016

1.000

1.000

1.000

3_2019

0.983

0.999

0.984

Brandenburg

4_2016

1.000

1.000

1.000

4_2019

0.964

0.979

0.985

Bremen (city state)

5_2016

0.956

1.000

0.956

5_2019

0.886

0.892

0.994

Hamburg (city state)

6_2016

0.988

1.000

0.988

6_2019

0.936

0.939

0.997

Hessen

7_2016

0.915

0.965

0.949

7_2019

0.895

0.951

0.941

Mecklenburg-Vorpommern

8_2016

0.928

0.929

0.998

8_2019

0.887

0.899

0.986

Niedersachsen

9_2016

0.920

1.000

0.920

9_2019

0.891

1.000

0.891

Nordrhein-Westfalen

10_2016

0.909

0.924

0.984

10_2019

0.892

0.913

0.976

Rheinland-Pfalz

11_2016

0.899

0.946

0.950

11_2019

0.855

0.916

0.933

Saarland

12_2016

1.000

1.000

1.000

12_2019

0.922

0.928

0.994

Sachsen

13_2016

0.957

0.961

0.996

13_2019

0.913

0.928

0.984

Sachsen-Anhalt

14_2016

0.910

0.916

0.993

14_2019

0.885

0.892

0.992

Schleswig–Holstein

15_2016

0.885

0.977

0.905

15_2019

0.884

1.000

0.884

ThĂĽringen

16_2016

0.947

0.993

0.954

16_2019

0.901

0.907

0.993

Baden-WĂĽrttemberg

1_2017

0.868

0.995

0.871

1_2020

0.765

1.000

0.765

Bayern

2_2017

0.868

0.937

0.926

2_2020

0.746

0.874

0.853

Berlin (city state)

3_2017

0.989

0.998

0.991

3_2020

0.860

0.917

0.938

Brandenburg

4_2017

0.988

0.992

0.996

4_2020

0.824

0.951

0.867

Bremen (city state)

5_2017

0.930

0.944

0.986

5_2020

0.794

0.796

0.997

Hamburg (city state)

6_2017

0.974

0.984

0.990

6_2020

0.811

0.824

0.984

Hessen

7_2017

0.911

0.956

0.953

7_2020

0.769

0.912

0.843

Mecklenburg-Vorpommern

8_2017

0.918

0.922

0.996

8_2020

0.776

0.822

0.944

Niedersachsen

9_2017

0.907

0.998

0.909

9_2020

0.774

0.997

0.776

Nordrhein-Westfalen

10_2017

0.904

0.922

0.981

10_2020

0.768

0.826

0.931

Rheinland-Pfalz

11_2017

0.879

0.927

0.949

11_2020

0.730

0.887

0.823

Saarland

12_2017

0.984

0.986

0.998

12_2020

0.763

0.799

0.955

Sachsen

13_2017

0.942

0.949

0.993

13_2020

0.810

0.859

0.942

Sachsen-Anhalt

14_2017

0.903

0.904

0.999

14_2020

0.762

0.802

0.950

Schleswig–Holstein

15_2017

0.897

0.997

0.900

15_2020

0.781

0.989

0.790

ThĂĽringen

16_2017

0.930

0.948

0.980

16_2020

0.769

0.794

0.969