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

被引：15

作者：

Ayiko, Rogers ^{[1
]}

Mujasi, Paschal N. ^{[2
]}

Abaliwano, Joyce ^{[3
]}

Turyareeba, Dickson ^{[3
]}

Enyaku, Rogers ^{[4
]}

Anguyo, Robert ^{[5
,6
]}

Odoch, Walter ^{[7
]}

Bakibinga, Pauline ^{[8
]}

Aliti, Tom ^{[9
]}

机构：

[1] Fdn African Empowerment, POB 116, Arusha, Tanzania

[2] Univ Pompeu Fabra, Barcelona Sch Management, Dept Econ & Business, Balmes 132, Barcelona 08001, Spain

[3] Makerere Univ, Business Sch, Plot 21 A,Port Bell Rd, Kampala, Uganda

[4] Community Resource Dev Initiat, POB 6653, Kampala, Uganda

[5] Univ Liverpool Liverpool Sch Trop Med, Dept Int Publ Hlth, Pembroke Pl, Liverpool L3 5QA, Merseyside, England

[6] Nile Univ, Fac Hlth Sci, POB 1070, Arua, Uganda

[7] East Cent & Southern Africa Hlth Community, 157 Olorien,Njiro Rd ECSA HC,POB 1009, Arusha, Tanzania

[8] African Populat & Hlth Res Ctr, Off Kirawa Rd,POB 10787-00100, Nairobi, Kenya

[9] Minist Hlth, Plot 6,Lourdel Rd,POB 7272, Kampala, Uganda

来源：

BMC HEALTH SERVICES RESEARCH | 2020年 / 20卷 / 01期

关键词：

Data envelopment analysis; General hospital; Technical efficiency; Tobit regression analysis; Uganda; HEALTH-CARE; TEACHING HOSPITALS; PERFORMANCE;

D O I：

10.1186/s12913-020-05746-w

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

BackgroundGeneral 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.

引用

页数：12