Table 1.
Sample profile for the baseline study in the three BHOMA districts.
Table 2.
Summary of indicators used to calculate Service coverage score in the household survey.
Table 3.
Baseline demographic characteristics of the health facilities in the BHOMA study.
Table 4.
Baseline District Performance in Six Health System Domains.
Table 5.
Baseline Performance Stratified by Residence in the Six Health System Domains.
Figure 1.
District balanced Scorecard stratified by domain.
This figure shows district scores stratified by domain. The domain comprised six indices, each made up from an aggregate of indicators. Across the three study districts the basic infrastructure score was similar at 76%. Basic equipment and laboratory capacity scores showed major variation with Kafue and Luangwa having lower scores when compared to Chongwe. For basic equipment Luangwa scored lowest (65%), followed by Kafue (67%). Chongwe had the highest basic equipment score of 84%, and the laboratory capacity score was lowest in Kafue (63%) and highest in Chongwe (77%). Infection control scores were highest in Luangwa (90%) and lowest in Kafue (80%).
Figure 2.
Health facility scorecard stratified by area of residence.
This figure shows residential scores which are stratified by domains. It shows that basic infrastructure and basic equipment scores were lowest in hospital-based health facilities (73% and 70% respectively), and the highest scores for basic infrastructure were in the peri-urban health facilities (78%) and rural health facilities for basic equipment (76%). Laboratory capacity had a lower score in rural (68%) and hospital-based health facilities (69%) and was highest in peri-urban health facilities. Infection control was best in hospital-based health facilities (100%) and worst in peri-urban health facilities (76%).Tracer drugs had high scores across the three residential areas (all above 87%).
Table 6.
Linear regression model of determinants for Adult service satisfaction score.
Table 7.
Linear regression analysis of the association between the different measures of quality of care.