Distribution of scores by survey
The sample size varied greatly by country, with the smallest number of facilities that provide curative services for children and the sample of sick child / health worker interactions observed in Senegal and the greatest in Tanzania (Table 1). In Malawi and Haiti, the SPA included a census of health facilities offering child curative services. Between 10% (Malawi) to 42% (Haiti) of sick child observations were excluded because the child was either admitted or sent elsewhere in the facility for care (e.g., lab), preventing complete observation of the care received. In total, we included data from 3,149 health facilities and 11,159 sick child observations in the analysis.
Table 1
Description of Service Provision Assessments (SPAs) included in the analysis
Country | Survey Year | Number of facilities that treat sick children | Number of facilities with at least one sick child observation meeting inclusion criteria | Number of sick child observations | Number of sick child observations meeting inclusion criteria |
Haiti | 2013 | 848 | 515 | 2450 | 1422 |
Malawi | 2013/2014 | 920 | 739 | 3437 | 3083 |
Nepal | 2015 | 907 | 654 | 2229 | 1866 |
Senegal | 2012/2013 | 413 | 320 | 1307 | 1075 |
Tanzania | 2014/2015 | 1154 | 921 | 4959 | 3713 |
Figure 1 shows the distribution of facility-level readiness and provision of care scores by country. Facilities with at least one sick child observation that met the inclusion criteria and were included in the analysis had slightly better readiness scores than the full sample of facilities that treat sick children. Among those facilities included in the analysis, Fig. 2 shows the distribution of facility readiness and average facility provision of care by category of health facility. In general, both government and non-government referral facilities offered greater readiness than first-level facilities within a country. However, on average, first-level facilities provided a slightly better provision of care than referral facilities. Figure 3 shows the distribution of readiness and provision of care domains by country. Over half of all facilities in each country had amenities and commodities scores above 70% (i.e., 7 out of 10 items or better). The readiness domain with the worst performance was “human resources,” where three-quarters of facilities in each country had scores below 65%. Among the provision of care domains, most facilities performed poorly on assessment, counseling, and integrated care, with 75% of facilities on average performing fewer than half of the actions in each domain. Except for Haiti, most facilities had high ratings on the treatment domain. However, the variability in treatment was high, with an interquartile range exceeding 50 percentage points in every country except for Malawi. For most children, only one or two treatment actions were recommended based on their diagnosis, or there was no assessable treatment action because the diagnosis did not align with a treatment action included in the observation protocol. This resulted in individual treatment scores that were heavily skewed to 0 or 1, or were absent entirely, contrary to the other domain values (Supplemental Fig. 1).
Association between readiness and provision of care at the individual level
We first assessed the overall association between facility readiness and provision of care for individual sick children with and without adjusting for other factors. Figure 4 shows the unadjusted correlation between facility readiness and the quality of individual care provided. Without adjusting for any other covariates, only Tanzania demonstrated a significant association between readiness and provision of care (0.146; 95% CI: 0.079–0.214), with each 10 percentage point increase in readiness associated with a 1.46 percentage point increase in provision of care (Table 2). After adjusting for facility type and managing authority, the magnitude of association between readiness and provision of care increased marginally in each of the five countries, and the association was significant in Haiti, Nepal, and Tanzania. For example, in Tanzania a 10 percentage point increase in readiness was associated with a 1.62 percentage point increase in provision of care after adjusting for facility type and managing authority.
Table 2
Association between readiness and provision of care, with and without adjusting for other covariates
Country | Unadjusted | Adjusting for facility type and managing authority | Adjusting for all covariates |
| Coef (95% CI) | Coef (95% CI) | Coef (95% CI) |
Haiti | 0.04 (-0.020-0.099) | 0.088 (0.022–0.155) | 0.068 (0.005–0.132) |
Malawi | -0.038 (-0.107-0.031) | 0.034 (-0.042-0.110) | 0.056 (-0.014-0.126) |
Nepal | 0.068 (-0.003-0.138) | 0.106 (0.035–0.177) | 0.083 (0.003–0.164) |
Senegal | 0.087 (-0.003-0.178) | 0.094 (-0.003-0.191) | 0.123 (0.015–0.23) |
Tanzania | 0.146 (0.079–0.214) | 0.162 (0.085–0.238) | 0.112 (0.043–0.181) |
Table 3 shows the unadjusted bivariate associations and adjusted association between provision of care and characteristics of the health facility (including readiness), health worker, client, and careseeking episode. Covariates with categories that differed by country (i.e., region, facility type, and managing authority) are presented in Supplemental Table 1. After adjusting for characteristics of the facility, health worker, child, caretaker, and episode, every country except Malawi demonstrated a significant positive association between readiness and provision of care, ranging from 0.068 (95% CI: 0.005–0.132) in Haiti to 0.123 (95% CI: 0.015–0.23) in Senegal. In addition, a limited number of other factors were also associated with provision of care in multiple countries. In all five countries, increasing child age was associated with decreasing quality of care provided when adjusting for other factors. Additionally, having a diagnosis other than respiratory, digestive, or febrile illness was associated with poorer provision of care. A diagnosis of malaria and multiple diagnoses were both associated with better provision of care in three of the five countries. In Malawi, Senegal, and Tanzania, increased cost of the visit was associated with better provision of care. Less consistently, caretaker education, health worker cadre, and region were associated the quality of care provided. These variables together, controlling for random effects, accounted for between 9% (Haiti) and 32% (Malawi) of the variation in provision of care scores (Supplemental Table 2).
Table 3
Association between provision of care and characteristics of the facility, health worker, patient, and illness episode
| Haiti | Malawi | Nepal | Senegal | Tanzania |
| Unadjusted | Adjusted | Unadjusted | Adjusted | Unadjusted | Adjusted | Unadjusted | Adjusted | Unadjusted | Adjusted |
Variable | Coef (95% CI) | Coef (95% CI) | Coef (95% CI) | Coef (95% CI) | Coef (95% CI) | Coef (95% CI) | Coef (95% CI) | Coef (95% CI) | Coef (95% CI) | Coef (95% CI) |
Readiness | 0.038 (-0.025-0.101) | 0.068 (0.005–0.132) | -0.038 (-0.107-0.031) | 0.056 (-0.014-0.126) | 0.068 (-0.003-0.138) | 0.083 (0.003–0.164) | 0.087 (-0.003-0.178) | 0.123 (0.015–0.23) | 0.146 (0.079–0.214) | 0.112 (0.043–0.181) |
Facility level factors | | | | | | | | | | |
Urbanicity | | | | | | | | | | |
Urban | Ref | Ref | Ref | Ref | - | - | Ref | Ref | Ref | Ref |
Rural | 0.009 (-0.008-0.027) | -0.008 (-0.027-0.011) | 0.016 (-0.003-0.035) | 0.015 (-0.008-0.039) | - | - | 0.024 (0.001–0.047) | 0.013 (-0.016-0.043) | 0.007 (-0.009-0.023) | -0.004 (-0.023-0.015) |
Region (Sup T1) | | | | | | | | | | |
Facility level (Sup T1) | | | | | | | | | | |
Managing authority (Sup T1) | | | | | | | | | | |
Health worker factors | | | | | | | | | | |
Qualification | | | | | | | | | | |
Nurse | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref |
Medical officer | - | - | -0.003 (-0.023-0.018) | -0.004 (-0.026-0.018) | -0.104 (-0.391-0.182) | -0.104 (-0.369-0.161) | - | - | 0.033 (0.015–0.052) | 0.034 (0.013–0.054) |
Doctor | -0.025 (-0.041–0.01) | -0.019 (-0.041-0.004) | 0.028 (0.002–0.055) | 0.016 (-0.013-0.045) | -0.027 (-0.063-0.008) | 0. (-0.071-0.07) | -0.006 (-0.037-0.025) | 0.03 (-0.012-0.073) | 0.029 (0.004–0.055) | 0.054 (0.024–0.084) |
Health Assistant | - | - | 0.2 (-0.012-0.411) | 0.268 (0.076–0.46) | -0.017 (-0.045-0.011) | 0.004 (-0.032-0.041) | - | - | - | - |
Other | 0.089 (-0.106-0.284) | 0.043 (-0.145-0.23) | - | - | -0.007 (-0.162-0.148) | 0.039 (-0.099-0.177) | -0.007 (-0.061-0.046) | -0.012 (-0.065-0.041) | -0.137 (-0.338-0.065) | -0.108 (-0.288-0.073) |
Sex | | | | | | | | | | |
Male | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref |
Female | 0.006 (-0.011-0.023) | -0.01 (-0.028-0.008) | -0.033 (-0.051–0.016) | -0.017 (-0.035-0.001) | 0.013 (-0.006-0.032) | 0.005 (-0.024-0.034) | -0.010 (-0.032-0.013) | -0.006 (-0.028-0.017) | -0.008 (-0.024-0.008) | 0.008 (-0.007-0.023) |
Observation factors | | | | | | | | | | |
Child age (year) | -0.011 (-0.015–0.007) | -0.011 (-0.016–0.007) | 0.002 (-0.001-0.006) | -0.004 (-0.008–0.001) | -0.017 (-0.022–0.012) | -0.014 (-0.019–0.008) | -0.004 (-0.010-0.002) | -0.006 (-0.012-0.) | -0.001 (-0.005-0.002) | -0.005 (-0.008–0.001) |
Chidl sex | | | | | | | | | | |
Male | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref |
Female | 0.005 (-0.006-0.016) | 0.004 (-0.007-0.015) | 0.004 (-0.005-0.013) | 0.001 (-0.007-0.009) | -0.003 (-0.015-0.009) | -0.007 (-0.02-0.006) | -0.004 (-0.018-0.011) | -0.006 (-0.021-0.008) | 0.002 (-0.007-0.011) | 0.002 (-0.006-0.011) |
Caretaker age (10 years) | 0.001 (-0.006-0.007) | 0.004 (-0.004-0.012) | 0.000 (-0.007-0.007) | 0.002 (-0.005-0.009) | -0.010 (-0.017–0.002) | 0.003 (-0.009-0.015) | 0.003 (-0.006-0.011) | 0.009 (-0.002-0.02) | 0.001 (-0.004-0.007) | 0. (-0.006-0.006) |
Caretaker education | | | | | | | | | | |
None | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref |
Primary | -0.011 (-0.027-0.006) | -0.008 (-0.025-0.008) | -0.011 (-0.026-0.003) | -0.003 (-0.017-0.01) | 0.019 (-0.002-0.039) | 0.005 (-0.017-0.027) | -0.022 (-0.041–0.003) | -0.021 (-0.04–0.002) | -0.009 (-0.021-0.004) | -0.009 (-0.021-0.003) |
Secondary+ | -0.024 (-0.040–0.008) | -0.018 (-0.035–0.001) | -0.019 (-0.036–0.003) | -0.009 (-0.025-0.006) | 0.005 (-0.009-0.019) | 0.007 (-0.01-0.024) | -0.018 (-0.037-0.001) | -0.017 (-0.037-0.003) | -0.025 (-0.041–0.010) | -0.023 (-0.038–0.008) |
Caretaker’s relationship to child | | | | | | | | | | |
Mother | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref |
Father | -0.007 (-0.033-0.019) | -0.003 (-0.029-0.023) | 0.003 (-0.021-0.027) | -0.015 (-0.037-0.006) | -0.012 (-0.034-0.009) | 0.005 (-0.02-0.029) | -0.018 (-0.047-0.010) | -0.026 (-0.057-0.005) | 0.001 (-0.019-0.020) | 0.009 (-0.01-0.028) |
Sibling | -0.032 (-0.095-0.030) | -0.015 (-0.077-0.046) | 0.007 (-0.008-0.023) | 0.003 (-0.011-0.017) | -0.049 (-0.099-0.001) | -0.013 (-0.064-0.038) | -0.040 (-0.091-0.012) | -0.017 (-0.069-0.034) | -0.035 (-0.070-0.000) | -0.023 (-0.055-0.009) |
Aunt/Uncle | 0.005 (-0.022-0.032) | 0.006 (-0.021-0.032) | -0.001 (-0.046-0.044) | -0.007 (-0.046-0.033) | -0.023 (-0.071-0.026) | -0.021 (-0.067-0.025) | -0.017 (-0.049-0.016) | -0.013 (-0.045-0.02) | -0.036 (-0.084-0.011) | -0.026 (-0.069-0.017) |
Grandparent | -0.007 (-0.033-0.019) | -0.018 (-0.051-0.015) | -0.003 (-0.036-0.031) | -0.007 (-0.042-0.029) | -0.046 (-0.074–0.018) | -0.032 (-0.075-0.011) | -0.026 (-0.057-0.005) | -0.042 (-0.086-0.003) | -0.001 (-0.030-0.028) | 0.004 (-0.027-0.035) |
Other | -0.001 (-0.038-0.035) | 0.006 (-0.03-0.043) | 0.020 (-0.012-0.052) | 0.009 (-0.019-0.038) | -0.012 (-0.138-0.115) | 0.043 (-0.073-0.158) | 0.005 (-0.146-0.156) | 0.059 (-0.086-0.204) | 0.020 (-0.033-0.072) | 0.02 (-0.029-0.068) |
Diagnosis | | | | | | | | | | |
Respiratory illness | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref |
Digestive illness | -0.029 (-0.054–0.003) | -0.02 (-0.045-0.006) | 0.033 (0.017–0.049) | 0.035 (0.019–0.052) | 0.044 (0.025–0.062) | 0.025 (0.004–0.045) | -0.019 (-0.045-0.007) | -0.023 (-0.052-0.006) | 0.008 (-0.007-0.024) | 0.01 (-0.005-0.026) |
Malaria | -0.006 (-0.045-0.033) | 0.011 (-0.028-0.05) | 0.152 (0.140–0.164) | 0.156 (0.143–0.169) | -0.115 (-0.232-0.003) | -0.139 (-0.275–0.003) | 0.122 (0.072–0.172) | 0.142 (0.087–0.197) | 0.131 (0.115–0.147) | 0.133 (0.117–0.149) |
Fever | -0.026 (-0.064-0.011) | -0.025 (-0.062-0.012) | -0.045 (-0.064–0.026) | -0.041 (-0.061–0.022) | -0.048 (-0.067–0.029) | -0.048 (-0.071–0.026) | -0.027 (-0.093-0.038) | -0.031 (-0.101-0.039) | 0.049 (0.028–0.070) | 0.049 (0.028–0.069) |
Other | -0.039 (-0.057–0.020) | -0.03 (-0.048–0.011) | -0.059 (-0.071–0.047) | -0.059 (-0.071–0.046) | -0.087 (-0.102–0.073) | -0.089 (-0.106–0.072) | -0.052 (-0.071–0.034) | -0.056 (-0.075–0.036) | -0.075 (-0.088–0.062) | -0.075 (-0.088–0.063) |
Multiple illnesses | -0.009 (-0.028-0.010) | -0.003 (-0.022-0.016) | 0.075 (0.064–0.086) | 0.076 (0.064–0.087) | 0.032 (0.010–0.054) | 0.027 (0.-0.054) | 0.011 (-0.011-0.033) | 0.014 (-0.009-0.038) | 0.032 (0.021–0.044) | 0.032 (0.02–0.043) |
Cost of visit | 0.405 (-0.410-1.221) | 0.47 (-0.331-1.271) | 0.016 (0.010–0.022) | 0.01 (0.004–0.015) | 0.002 (-0.007-0.010) | 0. (-0.012-0.011) | 0.015 (0.006–0.024) | 0.017 (0.008–0.026) | 0.011 (0.005–0.018) | 0.01 (0.004–0.016) |
Green shading notes a significant positive association, orange shading notes a significant negative association
We further examined the relationship between readiness and provision of care within health facility categories. Adjusting for finer delineations of type of provider and managing authority, we found a positive association between readiness and provision of care among first level government health facilities, the most common type of facility, in Nepal, Senegal, and Tanzania (Supplemental Table 3). This association ranged from 0.120 (95% CI: 0.014–0.227) in Senegal to 0.130 (95% CI: 0.033–0.226) in Tanzania. Additionally, in Tanzania, the magnitude of association between readiness and provision of care among non-government facilities was almost twice that observed in government facilities.
We looked for a possible non-linear association between readiness and provision of care. Binning each facility into their relative readiness quintile by category of provider, we found limited evidence of a consistent non-linear association between readiness and provision of care (Fig. 5, Supplementary Table 4). In some countries, the association in the two upper or two lower quintiles did not increase linearly but instead plateaued. We also found no difference in the associations when considering absolute cut-offs for readiness, including readiness above and below 25%, 50%, and joints at each 20%, 40%, 60%, and 80% (data not shown).
Among domains of readiness (Table 4), we observed clear trends in the association with provision of care after adjusting for facility type and managing authority. In all countries except Malawi, the human resources domain was positively associated with the quality of care observed. The association ranged from 0.050 (95% CI: 0.013–0.087) in Senegal to 0.100 (95% CI: 0.067–0.132) in Tanzania, or about half of the magnitude to the total observed association between readiness and provision of care in those countries. Among the provision of care domains (Table 5), the quality of the assessment was significantly positively associated with readiness in four of the five countries, followed by quality of counseling and integrated care which both were significantly positively associated with readiness in three of the five countries. The treatment domain, however, was not significantly associated with readiness in any of the countries.
Table 4
Association between readiness domains and provision of care, adjusting for facility type and managing authority
Readiness Domain | Haiti | Malawi | Nepal | Senegal | Tanzania |
| Coef (95% CI) | Coef (95% CI) | Coef (95% CI) | Coef (95% CI) | Coef (95% CI) |
Amenities | -0.001 (-0.037-0.035) | 0.001 (-0.044-0.045) | -0.007 (-0.055-0.042) | 0.016 (-0.054-0.086) | -0.018 (-0.057-0.021) |
Equipment | 0.062 (0.008–0.117) | 0.047 (-0.011-0.106) | -0.007 (-0.058-0.045) | -0.031 (-0.117-0.054) | 0.057 (0.008–0.105) |
Medicines / Commodities | -0.009 (-0.057-0.039) | -0.010 (-0.081-0.061) | 0.008 (-0.045-0.060) | 0.011 (-0.046-0.069) | 0.043 (-0.015-0.102) |
Human Resources | 0.056 (0.028–0.083) | 0.009 (-0.019-0.038) | 0.075 (0.045–0.105) | 0.050 (0.013–0.087) | 0.100 (0.067–0.132) |
Table 5
Association between readiness and provision of care domains, adjusting for facility type and managing authority
Provision of care Domain | Haiti | Malawi | Nepal | Senegal | Tanzania |
| Coef (95% CI) | Coef (95% CI) | Coef (95% CI) | Coef (95% CI) | Coef (95% CI) |
Examination / Assessment | 0.120 (0.045–0.195) | 0.082 (0.001–0.163) | 0.129 (0.049–0.208) | 0.082 (-0.011-0.174) | 0.223 (0.144–0.302) |
Treatment | -0.012 (-0.293-0.270) | 0.081 (-0.110-0.272) | 0.002 (-0.335-0.340) | -0.047 (-0.528-0.435) | -0.103 (-0.297-0.091) |
Counselling | 0.048 (-0.045-0.141) | 0.068 (-0.037-0.174) | 0.134 (0.031–0.236) | 0.167 (0.038–0.297) | 0.237 (0.131–0.343) |
Integrated Care | 0.126 (0.034–0.219) | 0.007 (-0.071-0.086) | 0.076 (0.022–0.131) | 0.132 (-0.001-0.265) | 0.145 (0.061–0.229) |
Association between readiness and provision of care (dropping treatment domain)
Without the treatment domain, we observed a significant positive association between readiness and provision of care in Nepal, Senegal, and Tanzania without adjusting for other factors (Supplemental Table 5). After adjusting for provider category, and fully adjusting for all covariates, we found a significant positive association between readiness and provision of care in all countries except for Malawi. We also observed a small increase (on average + 0.02) in the magnitude of the association when compared to the association using the provision of care score inclusive of the treatment domain.
Similar effects were observed when looking at the association by category of provider, with slight increases in the magnitude of association over those observed with the treatment-inclusive provision of care scores (Supplemental Table 6). Additional significant positive associations between readiness and provision of care, excluding the treatment domain, was observed among first-level government facilities and first-level non-government facilities in Malawi and Haiti, respectively.
Beyond the association between provision of care and facility readiness, we observed that most associations between characteristics of the facility, health worker, and provision of care remained stable when removing the treatment domain (Sup Tables 7 & 8). However, the association between the child’s diagnosis (reported by the provider) and provision of care was reduced when compared to the initial analysis, with many associations no longer significant or reduced in magnitude. The overall amount of variation in provision of care explained by the characteristics was also substantially reduced (Supplemental Table 9).
Exclusion of the treatment domain did not alter the lack of evidence for a non-linear association between readiness and provision of care (Supplemental Table 10). It also did not change how domains of readiness were associated with provision of care, with human resources maintaining the same significant positive association with provision of care (Supplemental Table 11).
Association between readiness and provision of care at the facility level
The results of the facility-level analysis did not vary greatly from the primary individual-level analysis (Supplemental Table 12). Without adjusting for other covariates, both Senegal and Tanzania showed a significant positive association between readiness and average provision of care at the facility level. After adjusting for facility type and managing authority, all countries other than Malawi showed a significant positive association. The magnitude of the association was slightly larger than that observed at the individual level in Senegal and Tanzania, and slightly lower in Haiti and Nepal. Further adjusting for region and urbanicity reduced the magnitude of association, so that only Tanzania maintained a significant association between readiness and provision of care.
Similar results were seen when assessing association by provider category, with Senegal and Tanzania showing a greater magnitude of association among government first level providers compared to the individual assessment and weaker associations observed in Nepal (Supplemental Table 13).
The association at the domain level was not notably different from the individual level association, with the readiness “human resources” domain exhibiting the only significant association with provision of care (Supplemental Table 14), and the provision of care “treatment” domain lacking an association with readiness in all countries (Supplemental Table 15).