Technical efficiency of public clinics in Kwazulu-Natal Province of South Africa.
BACKGROUND
In sub-Saharan Africa (SSA) much of the attention of policy makers, health care managers, health systems researchers and donors is focussed almost solely on mobilising additional resources and not on efficiency in their use.


OBJECTIVE
To investigate the technical inefficiencies among 155 primary health care clinics in Kwazulu-Natal Province of South Africa; and to draw policy implications.


METHODS
Cross-sectional provincial health clinic survey. SELLING: Kwazulu-Natal Provincial Department of Health Clinics survey, 1996.


METHODS
The analysis is based on 155 public clinics.


METHODS
Non-intervention Data Envelopment Analysis (DEA) study.


METHODS
Technical and scale efficiency scores.


RESULTS
Forty seven (30%) were found to be technically efficient. Among the 108 (70%) technically inefficient facilities, 16% had an efficiency score of 50% or less. The presence of inefficiencies indicates that a clinic has excess inputs or insufficient outputs compared to those clinics on the efficiency frontier. To achieve technical efficiency, Kwazulu-Natal clinics would, in total have to decrease inputs by 417 nurses and 457 general staff. Alternatively, outputs would have to be increased by 115,534 antenatal visits, 1,010 births (deliveries), 179,075 child care visits, 5,702 dental visits, 121,658 family planning visits, 36,032 psychiatric visits, 56,068 sexually transmitted disease visits and 34,270 tuberculosis visits.


CONCLUSIONS
There is need for more detailed studies in a number of the relativdy efficient clinics to determine why they are efficient with a view of documenting attributes of 'best practise' that other clinics can emulate. The potential benefit of replicating this kind of study in other provinces, and indeed, other SSA countries cannot be overemphasised.
Kirigia
J M
JM
WHO Regional Office for Africa, Harare. KIRIGIAJ@WHOAFR.ORG
Sambo
L G
LG
Scheel
H
H
D003151:Community Health Centers / Q000458:organization & administration* / Q000706:statistics & numerical data; D003430:Cross-Sectional Studies; D017598:Efficiency, Organizational / Q000706:statistics & numerical data*; D019538:Health Care Surveys; D006291:Health Policy; D006801:Humans; D016015:Logistic Models; D011320:Primary Health Care / Q000458:organization & administration* / Q000706:statistics & numerical data; D011382:Programming, Linear; D011635:Public Health Administration / Q000592:standards*; D011785:Quality Assurance, Health Care / Q000379:methods; D013019:South Africa