Tools
Tools
Ayiko, Rogers, Mujasi, Paschal N., Abaliwano, Joyce, Turyareeba, Dickson, Enyaku, Rogers, Anguyo, Robert, Odoch, Walter, Bakibinga, Pauline and Aliti, Tom (2020) 'Levels, trends and determinants of technical efficiency of general hospitals in Uganda: data envelopment analysis and Tobit regression analysis'. BMC Health Services Research, Vol 20, e916.
|
Text
Ayiko_et_al-2020-BMC_Health_Services_Research.pdf - Published Version Available under License Creative Commons Attribution. Download (539kB) | Preview |
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.
| Item Type: | Article |
|---|---|
| Subjects: | W General Medicine. Health Professions > Health Services. Patients and Patient Advocacy > W 84.4 Quality of Health Care WA Public Health > WA 100 General works WA Public Health > WA 20.5 Research (General) WA Public Health > Health Problems of Special Population Groups > WA 395 Health in developing countries WX Hospitals and Other Health Facilities > WX 20 Research (General) |
| Faculty: Department: | Clinical Sciences & International Health > International Public Health Department |
| Digital Object Identifer (DOI): | https://doi.org/10.1186/s12913-020-05746-w |
| Depositing User: | Helen Fletcher |
| Date Deposited: | 16 Oct 2020 14:50 |
| Last Modified: | 11 Nov 2020 11:25 |
| URI: | https://archive.lstmed.ac.uk/id/eprint/15839 |
Statistics
Actions (login required)
 |
Edit Item |