Bisola Ojikutu and Molly-Higgins Biddle are employed by John Snow Inc. Usman Kolapo is employed by Indepth Precision. Benjamin R. Phelps and Anouk Amzel, are employed by the U.S. Agency for International Development. There are no patents, products in development or marketed products to declare. This does not alter the authors' adherence to all PLOS ONE policies on sharing data and materials.
Conceived and designed the experiments: BO MHB DG BRP AA EO UK HC EC LH. Performed the experiments: BO MHB DG UK EC HC. Analyzed the data: BO MHB DG HC LH. Contributed reagents/materials/analysis tools: BO MHB DG EO UK HC EC LH. Wrote the paper: BO MHB DG EO UK HC LH.
Access to pediatric HIV treatment in resource-limited settings has risen significantly. However, little is known about the quality of care that pediatric or adolescent patients receive. The objective of this study is to explore quality of HIV care and treatment in Nigeria and to determine the association between quality of care, loss-to-follow-up and mortality. A retrospective cohort study was conducted including patients ≤18 years of age who initiated ART between November 2002 and December 2011 at 23 sites across 10 states. 1,516 patients were included. A quality score comprised of 6 process indicators was calculated for each patient. More than half of patients (55.5%) were found to have a high quality score, using the median score as the cut-off. Most patients were screened for tuberculosis at entry into care (81.3%), had adherence measurement and counseling at their last visit (88.7% and 89.7% respectively), and were prescribed co-trimoxazole at some point during enrollment in care (98.8%). Thirty-seven percent received a CD4 count in the six months prior to chart review. Mortality within 90 days of ART initiation was 1.9%. A total of 4.2% of patients died during the period of follow-up (mean: 27 months) with 19.0% lost to follow-up. In multivariate regression analyses, weight for age z-score (Adjusted Hazard Ratio (AHR): 0.90; 95% CI: 0.85, 0.95) and high quality indicator score (compared a low score, AHR: 0.43; 95% CI: 0.26, 0.73) had a protective effect on mortality. Patients with a high quality score were less likely to be lost to follow-up (Adjusted Odds Ratio (AOR): 0.42; 95% CI: 0.32, 0.56), compared to those with low score. These findings indicate that providing high quality care to children and adolescents living with HIV is important to improve outcomes, including lowering loss to follow-up and decreasing mortality in this age group.
Though numerous challenges have limited scale-up of pediatric antiretroviral therapy (ART), significant progress has been made.
The Institute of Medicine defines health care quality as the extent to which health services provided to individuals and populations improve desired health outcomes and are consistent with current professional knowledge.
Moreover, quality assessment of pediatric HIV care and treatment lags far behind that of adults internationally. Several national programs have identified process and outcomes indicators to guide improvement efforts. However, few reports of HIV care quality that focus on pediatric or adolescent services have been published.
Nigeria is home to the second largest number of people living with HIV in the world after South Africa. In 2012, approximately 3,400,000 people in Nigeria were living with HIV, including 430,000 children.
The study protocol and assessment tools were submitted to the National Health Research Ethics Committee of Nigeria (NHREC) and approved on April 9th, 2011. Individual signed, written informed consent from participants was waived by NHREC. Patient information was de-identified prior to analysis. Unique patient identifiers were assigned to each patient to protect patient confidentiality.
A retrospective cohort study was conducted including patients enrolled in care between November 2002 and December 2011. This chart review was a component of a larger assessment of access to pediatric and adolescent treatment services funded by the United States Government/PEPFAR Nigeria Program. [
Charts representing 10% of the total number of patients 0–18 years of age receiving antiretroviral therapy (ART) in the 10 states chosen were selected using random sampling. Each site was asked to provide a list of all enrolled patients 0–18 years of age meeting the inclusion criteria by medical record number. Chart design and contents were standardized in 2008 to include the same variables across all sites throughout the country, and sites maintained either paper or electronic records.
Patients were eligible for inclusion in the study if they were 0–18 years of age and initiated ART during the study period. Follow-up was censored either at the time of the loss to follow-up (as defined below), death or the end of the study period.
The two main outcomes were lost to follow-up and death. Loss to follow-up was defined as no evidence of a visit to the clinic or drug pick up for 90 days following the last scheduled appointment as documented in the chart. Death was only counted if verified by the patient's family or if death occurred within the hospital.
The primary independent variable of interest was a quality score comprised of six process indicators: (1) screening for tuberculosis at entry into care, (2) adherence measurement at last visit, (3) adherence counseling at last visit, (4) prescription of co-trimoxazole at any time since enrollment, (5) at least one CD4 count in the last six months, and (6) documented weight at last visit. These indicators are recommended by the World Health Organization and should be standard components of clinical practice as outlined by the 2005 and 2010 National Guidelines on Paediatric HIV and AIDS Treatment and Care in Nigeria.
Additional patient characteristics and clinical variables related to the outcomes of interest were also collected including: gender, age at ART initiation, CD4 count/percentage (baseline and most recent value), baseline weight/height (to determine age-for-weight z-score), current ART regimen, and facility type (rural, peri-urban and urban). Viral load measurement was not standard of care during the study period, and therefore was not included as an outcome measure.
Baseline immunosuppression at entry into care was calculated using patient age and either initial CD4 count or initial CD4 percentage. For patients less than two years of age, “severe immunosuppression” was defined as an initial CD4 count less than 750 cells/mm3 or a percentage less than 15%, while “moderate immunosuppression” was defined as CD4 count between 750 and 1500 cells/mm3 or a percentage of between 15% and 25%. “No immunosuppression” was defined as an initial CD4 count of 1500 cells/mm3 or more or a percentage of 25% or more. For patients between two and five years of age, “severe immunosuppression” was defined as an initial CD4 count less than 500 cells/mm3 or percentage less than 15%, “moderate immunosuppression” as an initial CD4 count of between 500 and 1000 cells/mm3 or percentage of between 15% and 25%, and “no immunosuppression” as an initial CD4 count of 1000 cells/mm3 or more or percentage of 25% or more. For patients five years of age or older, “severe immunosuppression” was defined as an initial CD4 count less than 200 cells/mm3 or percentage less than 15%, “moderate immunosuppression” as an initial CD4 count of between 200 and 500 cells/mm3 or percentage of between 15% and 25%, and “no immunosuppression” as an initial CD4 count of 500 cells/mm3 or more or percentage of 25% or more.
Means and standard deviations were computed for continuous variables and counts with percentages for categorical variables. Differences in mortality and loss to follow-up by age group and differences in quality indicators by year of initial visit were compared using chi-square statistics. Bivariate methods were used to examine the relationships of individual independent variables with the primary outcomes of survival and loss-to-follow up, including Kaplan-Meier estimation with log rank testing. One predictor Cox proportional hazards regression models were used for survival and one predictor logistic regression models for loss to follow-up.
In survival analyses, associations were estimated using hazard ratios (HR) with 95 percent confidence intervals (CI). In the analysis of loss to follow-up, associations were estimated using odds ratios (OR) with 95 percent CIs. The multivariate logistic regression models included independent variables that were significant in the bivariate models defined as p<0.05 and/or were potential confounders of the relationship between the quality score and the outcomes (e.g., weight for age (z-score) and age at ART initiation). The multivariate Cox regression model was limited to four predictors due to the number of deaths in the sample, using a guide of ten events or deaths required per predictor.
The proportional hazards assumption was checked by graphical methods and by testing interaction terms that included the log of follow-up time. The discrimination ability of the logistic models was measured by c-statistics with calibration assessed using Hosmer-Lemeshow chi-square statistics and their associated p-values. Where data were sufficient, we tested for interactions among the independent variables in these models. Patient-level variability across sites was investigated using the intra-cluster correlation coefficient (ICC). The ICC was close to zero, indicating similarity between within-site variability and variability across sites. We employed an alpha of 0.05 in all statistical tests to determine statistical significance. All data management and statistical analyses were performed using SAS for Windows version 9.2.
A total of 1,516 patients were sampled from 23 sites. Most patients (73.6%) received care at urban facilities (
N | Mean (SD) or % | |
Age at ART initiation | ||
0–24 months | 363 | 24.0% |
25–71 months | 605 | 40.0% |
6–9 years | 318 | 21.1% |
10–18 years | 225 | 14.9% |
Gender (Male) | 799 | 52.8% |
Baseline immunosuppression |
||
Severe | 666 | 46.3% |
0–24 months | 165 | 24.8% |
25–71 months | 256 | 38.4% |
6–9 years | 124 | 18.6% |
10–18 years | 121 | 18.2% |
Moderate | 468 | 32.5% |
0–24 months | 106 | 22.7% |
25–71 months | 202 | 43.3% |
6–9 years | 92 | 19.7% |
10–18 years | 67 | 14.4% |
No suppression | 306 | 21.3% |
0–24 months | 47 | 15.4% |
25–71 months | 126 | 41.3% |
6–9 years | 97 | 31.8% |
10–18 years | 35 | 11.5% |
Weight for age (z-score) | 1382 | −1.08 ( |
Most recent CD4 count among those alive | ||
<350 cells/mm3 | 369 | 27.3% |
≥350 cells/mm3 | 983 | 72.7% |
Duration of follow-up in months | 1511 | 27.7 ( |
Current ART regimens | ||
AZT/3TC/NVP | 1236 | 81.5% |
Regimens containing d4T | 81 | 5.3% |
Other regimen | 196 | 13.0% |
Rural | 199 | 13.1% |
Peri-urban | 201 | 13.3% |
Urban | 1116 | 73.6% |
Screened for tuberculosis at entry into care | 1115 | 81.3% |
Adherence counseling documented at last visit | 1311 | 89.7% |
Adherence measured at last visit | 1296 | 88.7% |
Ever prescribed co-trimoxazole | 1482 | 98.8% |
Alive and not lost to follow up with at least one CD4 count in last six months | 518 | 37.0% |
Weight documented in chart at patient's last visit | 1049 | 72.2% |
High quality indicator score |
842 | 55.5% |
For patients less than two years of age, severe immunosuppression was defined as an initial CD4 count less than 750 cells/mm3 or percentage less than 15%, moderate immunosuppression as an initial CD4 count of between 750 and 1500 cells/mm3 or percentage of between 15% and 25%, and no immunosuppression as an initial CD4 count of 1500 cells/mm3 or more, or percentage of 25% or more. For patients between two and five years of age, severe immunosuppression was defined as an initial CD4 count less than 500 cells/mm3 or percentage less than 15%, moderate immunosuppression as an initial CD4 count of between 500 and 1000 cells/mm3 or percentage of between 15% and 25%, and no immunosuppression as an initial CD4 count of 1000 cells/mm3 or more, or percentage of 25% or more. For patients between five years of age or older, severe immunosuppression was defined as an initial CD4 count less than 200 cells/mm3 or percentage less than 15%, moderate immunosuppression as an initial CD4 count of between 200 and 500 cells/mm3 or percentage of between 15% and 25%, and no immunosuppression as an initial CD4 count of 500 cells/mm3 or more, or percentage of 25% or more.
1 point assigned for each service received (screened for tuberculosis, adherence counseling at last visit, adherence measured by patient/caregiver self-report at last visit, ever prescribed co-trimoxazole, alive and not lost to follow-up with at least one CD4 count in the last six months, and weight documented in chart at patient's last visit, and 0 points assigned if the service was not received, for a total of 6 points. A high score was defined as having the median score or above (>4 points).
The mean duration of follow-up time was 27.7 months (±19.7). Most patients were on an ART regimen comprised of AZT/3TC/NVP (81.5%) at the time of chart review. For those on regimens containing d4T, the mean length of time on the regimen was 36.7 months (±18.5).
Most patients were screened for tuberculosis at entry into care (81.3%) and had adherence counseling at their last visit (89.7%) (
Two quality indicators improved over time. The percentage of patients with a CD4 count in the last six months (p<0.0001) and weight for age documented at the last visit (p = 0.0034) was higher for those with an initial visit in more recent years (2008 to 2011) than for those who enrolled in care prior to 2008.
Documented mortality within 90 days of ART initiation was 1.9% (
Within 90 days of ART Initiation | 30 | 1.9% | |
During period of follow-up | 64 | 4.2% | |
By age at ART initiation | |||
0–24 months | 23 | 35.9% | NS |
25–71 months | 20 | 31.3% | |
6–9 years | 13 | 20.3% | |
10–18 years | 8 | 12.5% | |
Within 6 months of ART Initiation | 52 | 3.6% | |
Within 12 months of ART Initiation | 100 | 6.9% | |
During period of follow-up | 276 | 19.0% | |
By age at ART initiation | |||
0–24 months | 83 | 30.4% | p = 0.0130 |
25–71 months | 98 | 35.9% | |
6–9 years | 48 | 17.6% | |
10–18 years | 44 | 16.1% |
Differences between age groups significant at p<0.05.
NS, not significant.
Patients with a high quality score were more likely to survive over time (p = 0.0011) and less likely to be loss to follow-up (p<0.0001) than patients with a low quality indicator score (
Mortality | Mortality (n = 1315) | Loss to Follow-up | Loss to Follow-up (n = 1386) | |||||||
N | HR (95% CI) | p-value | AHR (95% CI) | p-value | N | OR (95% CI) | p-value | AOR (95% CI) | p-value | |
Male (Ref: Female) | 1509 | 1.50 (0.90, 2.49) | NS | — | — | 1450 | 1.00 (0.77, 1.30) | NS | — | — |
Weight for age (z-score) | 1379 | 0.90 (0.85, 0.95) | 0.0003 | 0.92 (0.87, 0.98) | 0.0121 | 1328 | 0.99 (0.96, 1.03) | NS | — | — |
Age at ART initiation ≤24 months (Ref: >24) | 1506 | 1.76 (1.06, 2.94) | 0.0297 | 1.00 (0.51, 1.99) | NS | 1447 | 1.56 (1.16, 2.09) | 0.0029 | 1.36 (0.99, 1.87) | NS |
Baseline immunosuppression |
1435 | 1388 | ||||||||
Severe | 6.11 (1.89, 19.76) | 0.0025 | 7.21 (1.72, 30.21) | 0.0068 | 1.48 (1.02, 2.14) | 0.0374 | 1.45 (0.99, 2.11) | NS | ||
Moderate | 1.95 (0.53, 7.19) | NS | 2.88 (0.62, 13.39) | NS | 1.14 (0.77, 1.70) | NS | 1.13 (0.75, 1.70) | NS | ||
No suppression | ||||||||||
High quality indicator score |
1511 | 0.43 (0.26, 0.73) | 0.0015 | 0.47 (0.26, 0.87) | 0.0165 | 1452 | 0.40 (0.31, 0.53) | <0.0001 | 0.42 (0.32, 0.56) | <0.0001 |
HR, hazard ratio; AHR, adjusted hazard ratio; OR, odds ratio; AOR, adjusted odds ratio; CI, confidence interval; NS, not significant
For patients less than two years of age, severe immunosuppression was defined as an initial CD4 count less than 750 cells/mm3 or percentage less than 15%, moderate immunosuppression as an initial CD4 count of between 750 and 1500 cells/mm3 or percentage of between 15% and 25%, and no immunosuppression as an initial CD4 count of 1500 cells/mm3 or more, or percentage of 25% or more. For patients between two and five years of age, severe immunosuppression was defined as an initial CD4 count less than 500 cells/mm3 or percentage less than 15%, moderate immunosuppression as an initial CD4 count of between 500 and 1000 cells/mm3 or percentage of between 15% and 25%, and no immunosuppression as an initial CD4 count of 1000 cells/mm3 or more, or percentage of 25% or more. For patients between five years of age or older, severe immunosuppression was defined as an initial CD4 count less than 200 cells/mm3 or percentage less than 15%, moderate immunosuppression as an initial CD4 count of between 200 and 500 cells/mm3 or percentage of between 15% and 25%, and no immunosuppression as an initial CD4 count of 500 cells/mm3 or more, or percentage of 25% or more.
1 point assigned for each service received (screened for tuberculosis, adherence counseling at last visit, adherence measured by patient/caregiver self-report at last visit, ever prescribed co-trimoxazole, alive and not lost to follow-up with at least one CD4 count in the last six months, and weight documented in chart at patient's last visit and 0 points assigned if the service was not received, for a total of 6 points. A high score was defined as having the median score or above (>4 points).
In multivariate Cox regression analyses, adjusting for other factors, weight for age z-score (AHR: 0.92; 95% CI: 0.87, 0.98) and high quality score (compared a low score, AHR: 0.47; 95% CI: 0.26, 0.87) had a protective effect on mortality. Patients with severe baseline immunosuppression were more likely to die than those with no immunosuppression (AHR: 7.21; 95% CI: 1.72, 30.21) (
To our knowledge, this is the first report of a pediatric and adolescent HIV care and treatment quality assessment in Nigeria. Our findings suggest that providing high quality care to children and adolescents living with HIV is associated with lower loss to follow-up and mortality, providing compelling evidence that investing in quality has the potential to retain this age group in care and save lives.
In this study, six process indicators were selected to measure quality. Overall, receipt of services was high. More than 80% of patients were screened for TB at entry into care. However, a higher percentage of adolescents were screened for TB compared to pediatric patients. Though the World Health Organization recommends screening for TB in pediatric patients as described, under-diagnosis and diagnostic delays are common.
The quality score devised for this study was significantly correlated with both loss to follow-up and mortality, with a higher score associated with decreased loss to follow-up and increased survival. This finding correlates with limited data from studies in the US demonstrating the association between quality of HIV care and clinical outcomes.
Very limited clinical outcomes data are currently available from the Nigerian pediatric and adolescent HIV treatment program. Though the focus of this study was not solely on clinical outcomes, this study provides a reasonable estimate of loss to follow-up and mortality within the Nigerian national program. Early mortality was 1.9% across all age groups, while mortality during the period of follow-up was noted to be 4.2%. Compared to data from similar pediatric and adolescent cohorts in sub-Saharan Africa, mortality was lower in the Nigerian program.
This study has several limitations. Sites were not randomly selected because we wanted to include a geographically diverse sample. Furthermore, we were limited to certain states due to safety concerns. We did not measure all site characteristics that may have impacted the process indicators included in the quality score in this study. This was because our goal was to focus on process, not structure. Furthermore, we knew from a larger assessment that all the sites had similar resource availability. [
Pediatric and adolescent access to antiretroviral therapy in Nigeria is expanding. Since 2013, the number of facilities across the country that provide ART to children and adolescents has increased significantly. In order to expedite access to treatment, decentralization or down-referral of pediatric care to primary health clinics has been initiated. Efforts are also underway to standardize services across facilities and to ensure that quality improvement is incorporated into regular in service training. [Federal Ministry of Health of Nigeria, Personal Communication, January 15, 2013] As pediatric and adolescent ART access continues to expand in Nigeria and in similar resource limited settings, ensuring the quality of care that patients receive will be essential to reducing mortality and loss to follow-up. The next logical step toward achieving this goal in the Nigerian treatment program would be to use these data to inform a quality improvement intervention. Quality improvement studies are infrequently published in the medical literature. However, a few studies have demonstrated the efficacy of quality improvement in HIV care and treatment in resource limited settings.
Greeson D, Ojikutu B, Kolapo U, Higgins Biddle M, Cabral H, et al. (2012) Rapid assessment of pediatric HIV treatment in Nigeria. Arlington, VA: USAID's AIDS Support and Technical Assistance Resources, AIDSTAR-One, Task Order 1. Available at:
(PDF)