Levels, trends and determinants of technical efficiency of general hospitals in Uganda: data envelopment analysis and Tobit regression analysis

Rogers Ayiko; Paschal N. Mujasi; Joyce Abaliwano; Dickson Turyareeba; Rogers Enyaku; Robert Anguyo; Walter Odoch; Pauline Bakibinga; Tom Aliti

doi:10.1186/s12913-020-05746-w

Levels, trends and determinants of technical efficiency of general hospitals in Uganda: data envelopment analysis and Tobit regression analysis

Rogers Ayiko, Paschal N. Mujasi, Joyce Abaliwano, Dickson Turyareeba, Rogers Enyaku, Robert Anguyo, Walter Odoch, Pauline Bakibinga, Tom Aliti

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

Abstract

General hospitals provide a wide range of primary and secondary healthcare services. They accounted for 38% of government funding to health facilities, 8.8% of outpatient department visits and 28% of admissions in Uganda in the financial year 2016/17. We assessed the levels, trends and determinants of technical efficiency of general hospitals in Uganda from 2012/13 to 2016/17.

Methods

We undertook input-oriented data envelopment analysis to estimate technical efficiency of 78 general hospitals using data abstracted from the Annual Health Sector Performance Reports for 2012/13, 2014/15 and 2016/17. Trends in technical efficiency was analysed using Excel while determinants of technical efficiency were analysed using Tobit Regression Model in STATA 15.1.

Results

The average constant returns to scale, variable returns to scale and scale efficiency of general hospitals for 2016/17 were 49% (95% CI, 44–54%), 69% (95% CI, 65–74%) and 70% (95% CI, 65–75%) respectively. There was no statistically significant difference in the efficiency scores of public and private hospitals. Technical efficiency generally increased from 2012/13 to 2014/15, and dropped by 2016/17. Some hospitals were persistently efficient while others were inefficient over this period. Hospital size, geographical location, training status and average length of stay were statistically significant determinants of efficiency at 5% level of significance.

Conclusion

The 69% average variable returns to scale technical efficiency indicates that the hospitals could generate the same volume of outputs using 31% (3439) less staff and 31% (3539) less beds. Benchmarking performance of the efficient hospitals would help to guide performance improvement in the inefficient ones. There is need to incorporate hospital size, geographical location, training status and average length of stay in the resource allocation formula and adopt annual hospital efficiency assessments.

Original language	English
Article number	916
Pages (from-to)	e916
Journal	BMC Health Services Research
Volume	20
Issue number	1
Early online date	6 Oct 2020
DOIs	https://doi.org/10.1186/s12913-020-05746-w
Publication status	E-pub ahead of print - 6 Oct 2020

Keywords

Data envelopment analysis
General hospital
Technical efficiency
Tobit regression analysis
Uganda

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Ayiko et al-2020-BMC Health Services ResearchFinal published version, 527 KBLicence: CC BY

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Ayiko, R., Mujasi, P. N., Abaliwano, J., Turyareeba, D., Enyaku, R., Anguyo, R., Odoch, W., Bakibinga, P., & Aliti, T. (2020). Levels, trends and determinants of technical efficiency of general hospitals in Uganda: data envelopment analysis and Tobit regression analysis. BMC Health Services Research, 20(1), e916. Article 916. Advance online publication. https://doi.org/10.1186/s12913-020-05746-w

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title = "Levels, trends and determinants of technical efficiency of general hospitals in Uganda: data envelopment analysis and Tobit regression analysis",

abstract = "General hospitals provide a wide range of primary and secondary healthcare services. They accounted for 38\% of government funding to health facilities, 8.8\% of outpatient department visits and 28\% of admissions in Uganda in the financial year 2016/17. We assessed the levels, trends and determinants of technical efficiency of general hospitals in Uganda from 2012/13 to 2016/17.MethodsWe undertook input-oriented data envelopment analysis to estimate technical efficiency of 78 general hospitals using data abstracted from the Annual Health Sector Performance Reports for 2012/13, 2014/15 and 2016/17. Trends in technical efficiency was analysed using Excel while determinants of technical efficiency were analysed using Tobit Regression Model in STATA 15.1.ResultsThe average constant returns to scale, variable returns to scale and scale efficiency of general hospitals for 2016/17 were 49\% (95\% CI, 44–54\%), 69\% (95\% CI, 65–74\%) and 70\% (95\% CI, 65–75\%) respectively. There was no statistically significant difference in the efficiency scores of public and private hospitals. Technical efficiency generally increased from 2012/13 to 2014/15, and dropped by 2016/17. Some hospitals were persistently efficient while others were inefficient over this period. Hospital size, geographical location, training status and average length of stay were statistically significant determinants of efficiency at 5\% level of significance.ConclusionThe 69\% average variable returns to scale technical efficiency indicates that the hospitals could generate the same volume of outputs using 31\% (3439) less staff and 31\% (3539) less beds. Benchmarking performance of the efficient hospitals would help to guide performance improvement in the inefficient ones. There is need to incorporate hospital size, geographical location, training status and average length of stay in the resource allocation formula and adopt annual hospital efficiency assessments.",

keywords = "Data envelopment analysis, General hospital, Technical efficiency, Tobit regression analysis, Uganda",

author = "Rogers Ayiko and Mujasi, \{Paschal N.\} and Joyce Abaliwano and Dickson Turyareeba and Rogers Enyaku and Robert Anguyo and Walter Odoch and Pauline Bakibinga and Tom Aliti",

year = "2020",

month = oct,

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doi = "10.1186/s12913-020-05746-w",

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T1 - Levels, trends and determinants of technical efficiency of general hospitals in Uganda: data envelopment analysis and Tobit regression analysis

AU - Ayiko, Rogers

AU - Mujasi, Paschal N.

AU - Abaliwano, Joyce

AU - Turyareeba, Dickson

AU - Enyaku, Rogers

AU - Anguyo, Robert

AU - Odoch, Walter

AU - Bakibinga, Pauline

AU - Aliti, Tom

PY - 2020/10/6

Y1 - 2020/10/6

N2 - General hospitals provide a wide range of primary and secondary healthcare services. They accounted for 38% of government funding to health facilities, 8.8% of outpatient department visits and 28% of admissions in Uganda in the financial year 2016/17. We assessed the levels, trends and determinants of technical efficiency of general hospitals in Uganda from 2012/13 to 2016/17.MethodsWe undertook input-oriented data envelopment analysis to estimate technical efficiency of 78 general hospitals using data abstracted from the Annual Health Sector Performance Reports for 2012/13, 2014/15 and 2016/17. Trends in technical efficiency was analysed using Excel while determinants of technical efficiency were analysed using Tobit Regression Model in STATA 15.1.ResultsThe average constant returns to scale, variable returns to scale and scale efficiency of general hospitals for 2016/17 were 49% (95% CI, 44–54%), 69% (95% CI, 65–74%) and 70% (95% CI, 65–75%) respectively. There was no statistically significant difference in the efficiency scores of public and private hospitals. Technical efficiency generally increased from 2012/13 to 2014/15, and dropped by 2016/17. Some hospitals were persistently efficient while others were inefficient over this period. Hospital size, geographical location, training status and average length of stay were statistically significant determinants of efficiency at 5% level of significance.ConclusionThe 69% average variable returns to scale technical efficiency indicates that the hospitals could generate the same volume of outputs using 31% (3439) less staff and 31% (3539) less beds. Benchmarking performance of the efficient hospitals would help to guide performance improvement in the inefficient ones. There is need to incorporate hospital size, geographical location, training status and average length of stay in the resource allocation formula and adopt annual hospital efficiency assessments.

AB - General hospitals provide a wide range of primary and secondary healthcare services. They accounted for 38% of government funding to health facilities, 8.8% of outpatient department visits and 28% of admissions in Uganda in the financial year 2016/17. We assessed the levels, trends and determinants of technical efficiency of general hospitals in Uganda from 2012/13 to 2016/17.MethodsWe undertook input-oriented data envelopment analysis to estimate technical efficiency of 78 general hospitals using data abstracted from the Annual Health Sector Performance Reports for 2012/13, 2014/15 and 2016/17. Trends in technical efficiency was analysed using Excel while determinants of technical efficiency were analysed using Tobit Regression Model in STATA 15.1.ResultsThe average constant returns to scale, variable returns to scale and scale efficiency of general hospitals for 2016/17 were 49% (95% CI, 44–54%), 69% (95% CI, 65–74%) and 70% (95% CI, 65–75%) respectively. There was no statistically significant difference in the efficiency scores of public and private hospitals. Technical efficiency generally increased from 2012/13 to 2014/15, and dropped by 2016/17. Some hospitals were persistently efficient while others were inefficient over this period. Hospital size, geographical location, training status and average length of stay were statistically significant determinants of efficiency at 5% level of significance.ConclusionThe 69% average variable returns to scale technical efficiency indicates that the hospitals could generate the same volume of outputs using 31% (3439) less staff and 31% (3539) less beds. Benchmarking performance of the efficient hospitals would help to guide performance improvement in the inefficient ones. There is need to incorporate hospital size, geographical location, training status and average length of stay in the resource allocation formula and adopt annual hospital efficiency assessments.

KW - Data envelopment analysis

KW - General hospital

KW - Technical efficiency

KW - Tobit regression analysis

KW - Uganda

U2 - 10.1186/s12913-020-05746-w

DO - 10.1186/s12913-020-05746-w

M3 - Article

SN - 1472-6963

VL - 20

SP - e916

JO - BMC Health Services Research

JF - BMC Health Services Research

IS - 1

M1 - 916

ER -

Levels, trends and determinants of technical efficiency of general hospitals in Uganda: data envelopment analysis and Tobit regression analysis

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Keywords

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