Although the United Republic of
Tanzania has made remarkable progress in scaling up HIV services, substantial gaps in pediatric coverage remain ( ). Joint United Nations Programme on HIV/AIDS, 2013 Tanzania is among the countries with the world's lowest pediatric antiretroviral therapy coverage ( ), and the Ministry of Health (MOH), Community, Development, Gender, Elderly and Children has prioritized expanding access to HIV testing, care, and treatment for children ( Joint United Nations Programme on HIV/AIDS, 2013 ). United Republic of Tanzania Ministry of Health and Social Welfare, 2012
Improving the identification of children living with HIV is a critical first step to expanding treatment coverage. In countries with generalized HIV epidemics, ill children presenting to health facilities have a higher HIV prevalence than the general pediatric population (
Cohn, Whitehouse, Tuttle, Lueck, & Tran, 2016 ; Kankasa et al., 2009 ; Preidis, 2013 ; ). Offering routine opt-out HIV testing to at-risk pediatric subpopulations (those presenting to health care with signs of illness or for admission, malnutrition, or tuberculosis treatment) is a high-yield identification strategy ( Wagner et al., 2015 ). Because these children and their caregivers are actively seeking health services and are easy to reach, they present a unique opportunity to identify those most in need of HIV care and to initiate treatment rapidly. Mutanga et al., 2012
Tanzania's National AIDS Control Program (NACP) has recommended provider-initiated HIV testing and counseling (PITC) services for all children attending health facilities. National guidelines recommend rapid antibody testing using Determine HIV 1/2 and Unigold HIV1/2 for children ages 18 months and older and early infant virologic diagnostic HIV testing through DNA polymerase chain reaction analysis for children younger than 18 months. National PITC training, guidelines, and strategies have been developed, and national targets aim for 80% of attendees at any service delivery point in the health facility to receive PITC ( ). United Republic of Tanzania Ministry of Health and Social Welfare, 2012
However, HIV testing coverage in children attending health facilities frequently falls well below this target. On-site quality assessments and supportive supervision activities conducted by ICAP at Columbia University (ICAP) and other implementing partners revealed health system barriers such as staff workload, test kit stock outs, provider role confusion, unclear workflow processes, process breakdowns, and system failures.
These observations were consistent with barriers to pediatric PITC identified by other implementers and researchers. For example, in a study conducted at six primary care clinics in Harare, Zimbabwe,
identified numerous challenges to routine PITC adherence for children ages 6–15 years, despite high positivity rates. The main reasons expressed by health care workers (HCW) included perceived unsuitability of the accompanying guardian to provide consent for HIV testing on behalf of the child, lack of staff availability, and shortage of HIV testing kits. Additional facility- and provider-level barriers can include HCW concerns about privacy and disclosure in crowded inpatient spaces, perceptions of increased workloads due to pre- and posttest counseling, and limited task shifting policies that might enable more professions to conduct testing ( Kranzer et al. (2014) Ahmed et al., 2013 ; Horwood, Voce, Vermaak, Rollins, & Qazi, 2010 ; Kapologwe, Kabengula, & Msuya, 2011 ; ). MacPherson et al., 2012
The “know-do” gap between established standards of care (what we know) and the ability of health systems to produce improved outcomes (what we do) occurs in both resource-rich and resource-poor settings (
) Haines, Kuruvilla, & Borchert, 2004 . Modern quality improvement (QI) methods help HCW bridge this gap by enabling them to use a team approach to design and implement locally appropriate process-focused change interventions that lead to sustained system improvements ( ). Although the NACP launched a national HIV program QI strategy, tools, and training curriculum in 2010, site-level staff had little experience actually implementing QI methods ( Heiby, 2014 ). The purpose of our project was to build QI capacity and improve pediatric PITC coverage by designing and supporting a QI Collaborative (QIC) to catalyze swift improvement in PITC performance for pediatric inpatients. United Republic of Tanzania Ministry of Health and Social Welfare, 2010 Methods
Collaborative Quality Improvement Collaborative Design
The QIC approach is a well-defined improvement method, in which health care facilities partner to address a quality challenge over a specified period, often 12–18 months (
Catsambas et al., 2008 ; ). A quality challenge is identified, along with a problem statement, an aim statement, and shared indicators. Multiprofessional QI teams are established at each facility. After baseline training and orientation, each site is supported to identify contextually appropriate interventions and conduct rapid iterative tests of change using the Model for Improvement and its plan-do-study-act (PDSA) cycles ( Franco & Marquez, 2011 ). Facilities then come together for quarterly meetings, in which they compare progress and share interventions and innovations. Between learning sessions, facilities receive monthly site support and QI coaching visits. In addition to building QI capacity and improving outcomes, QICs also generally develop a “change package” of tools and approaches that can then be disseminated to additional facilities ( Catsambas et al., 2008 Catsambas et al., 2008 ; ). Franco & Marquez, 2011
ICAP worked with NACP, regional and district health teams, the Centers for Disease Control and Prevention, the Ariel Glaser Pediatric AIDS Health Care Initiative (AGPAHI), and the Christian Social Services Commission (CSSC) to design and implement the QIC. Preparations began in August 2014, and the project included stakeholder engagement, identification of site selection criteria, development of aim statements and indicators, and baseline data collection and analysis. It focused on children between the ages of 18 months and 15 years, following the national definitions of “pediatric” and “child” as persons younger than 15 years of age and excluding children younger than 18 months who required early infant virologic testing via DNA polymerase chain reaction (
). Baseline data were collected for the period between January and March 2015, and the QIC was implemented between May 2015 and March 2016. United Republic of Tanzania Ministry of Health and Social Welfare, 2012
The project was conducted at 24 health facilities supported by the U.S. President's Emergency Fund for AIDS Relief in Simiyu and Geita Regions, 2 high HIV prevalence areas in northern
Tanzania. The sites included 7 district hospitals, 16 health centers, and 1 dispensary. Each facility met site selection criteria, including the presence of a pre-existing QI team consisting of nursing and medical staff, laboratory staff, child health nurses and clinical officers, PITC focal nurses, and HIV counseling and testing nurses and counselors.
Formal aim statements were developed for the QIC, with all sites working to achieve the following between May 2015 and March 2016: (a) increase pediatric inpatient PITC coverage rates (proportion of admitted children and adolescents offered HIV testing) to 80% or higher and (b) ensure that at least 90% of children and adolescents living with HIV are referred to care and treatment. Shared performance indicators and operational definitions were developed for the QIC and included the following:
The percentage of children and adolescents admitted to adult inpatient departments who were tested for HIV and received their test results;
The percentage of children and adolescents admitted to pediatric inpatient department who were tested for HIV and received their test results;
The percentage of newly diagnosed children living with HIV diagnosed through opt-out testing enrolled at care and treatment clinics; and
The number of days of test kit stock outs per month/number of days per month.
Baseline Data Collection
In May 2015, the 24 project teams convened for an initial learning session, at which they reviewed retrospective data from the 24 participating facilities to assess performance over the prior 3 months (January–March 2015). These aggregate monthly data were abstracted from health facility registers by facility staff using a standardized paper-based tool. ICAP staff then entered the data into an EXCEL database and conducted descriptive analyses.
Quality Improvement Collaborative Implementation
As above, teams from the 24 project sites attended an initial 1-week learning session in May 2015. The workshop provided refresher training using the MOH national QI curriculum, which outlined the NACP QI approach, including the Model for Improvement and its PDSA methods (
), enabling participants to apply QI methods to the challenge of improving inpatient pediatric PITC. Facility teams conducted root cause analyses using process maps and fishbone diagrams to identify process gaps, system weak points, and system breakdowns related to pediatric inpatient PITC coverage. Using a brainstorming process, teams then selected appropriate change ideas that were logically linked to the gaps and breakdowns identified during root cause analysis. Teams then returned to their facilities and used PDSA methods to test their initial change ideas. Catsambas et al., 2008
Following the initial learning session, AGPAHI and CSSC provided ongoing, site-level, supportive supervision and mentoring on QI methods and data quality assurance to the QI facility teams. AGPAHI and CSSC staff visited sites monthly; ICAP and MOH staff joined these site visits quarterly. Each month, site QI teams reviewed performance and challenges with the implementing partners and MOH staff providing supportive supervision, brainstormed about which changes were or were not working, and made decisions about which interventions to initiate, continue, or drop.
ICAP facilitated quarterly follow-up learning sessions, convening facility QI teams to present their progress toward their aims, describe change ideas and PDSA cycles, and share lessons learned about service delivery barriers, outcomes, and best practices. The quarterly meetings provided site-level staff with the opportunity to publicly compare their progress with that of peer health facilities and to share promising practices and tools with one another.
On completion of the QIC in March 2016, project results were shared at a final stakeholder meeting that included MOH, NACP, regional and district health leaders, implementing partners, and U.S. President's Emergency Fund for AIDS Relief agency representatives. During this final dissemination meeting, higher-performing facilities were invited to present their data, change innovations, lessons learned, and plans for sustainability. The presentations to high-level leadership were designed to promote QIC facility staff recognition and reward higher performance and innovations.
Data Collection, Management, and Analysis
During the intervention period (May 2015–March 2016), site-level QI teams collected aggregate performance data each month; AGPAHI and CSSC shared it with ICAP using standardized paper forms and plotted it on annotated run charts during monthly team meetings. ICAP staff entered the data into a Microsoft Excel spreadsheet that was systematically reviewed on a monthly basis for data quality. If errors were identified, facilities were contacted to obtain correct information. Microsoft Excel 2010 was used to generate monthly descriptive statistics and graphs showing progress toward aim statements for each participating facility as well as performance of the collaborative as a whole.
Aggregate data were analyzed quarterly and at the conclusion of the project. QIC indicator performance was assessed for each participating facility during the 11-month period (May 2015–March 2016), and the range, mean, and median across facilities were calculated. For months where the denominator was zero (for instance, no children were identified as HIV infected), it was assumed that the aim was met.
In addition to descriptive statistics, performance during the 3-month baseline period (January–March 2015) was compared to that during the final 3 months (January–March 2016) of the intervention period using the chi-squared test of independence. Due to a national HIV test kit stock out in April 2015, this month was excluded from this analysis.
The project received nonresearch determination from the Columbia University Institutional Review Board (protocol: IRB-AAAP4519), the Centers for Disease Control and Prevention Center for Global Health Office of the Associate Director for Science, and the
Tanzania National Institute for Medical Research. Results
In the 3 months prior to QIC initiation (January–March 2015), the 24 sites admitted 7,020 children; of whom, 2,671 (38%) received PITC services. This rate was considered to be the performance baseline for Aim 1. Of the 2,671 children tested, 47 (1.8%) were found to be infected, and 45 (96%) of these were linked to care, the performance baseline for Aim 2.
All sites participated in the QIC throughout the 11-month intervention period, had active QI teams, and received supportive supervision and QI coaching as planned. The QIC learning sessions were well attended, with 80–88 participants attending each of the four learning sessions. QI teams used the PDSA method to identify and test a wide array of facility-driven change ideas, including improvements in staff and client education, staffing patterns, workflow, commodity management, documentation, HIV test kit management, and referrals (
Table 1). Table 1.:
PITC Facility Change Ideas
PITC Facility Change Ideas
PITC Facility Change Ideas
By the end of the QIC, each of the participating health facilities met or surpassed the 80% coverage target for Aim 1 at least once, taking a median of 3 months to achieve the target (
Figure 1; Table 2) and meeting the performance target for a median of 5 months ( Figure 1; Table 2). In the final 3 months of the QIC (January–March 2016), the sites admitted 6,172 children; of whom, 4,662 (76%) were tested; this difference was statistically significant from the 38% found at baseline ( p < .001). There were no differences observed between regions or types of facilities. Figure 1.:
Aggregate achievement of aim statements and rapid test kit stock out over time.
Note. *The country experienced a stock out of rapid test kits in March and April 2015. LS = learning session; PITC = provider-initiated testing and counseling for HIV; RTK = HIV rapid test kit; <15 = younger than 15 years of age. Table 2.:
Improvements in PITC Coverage With Sustained Linkage to Care
The proportion of children testing positive for HIV infection remained stable over time, at 1.8% (47/2,671) during the baseline period and 1.9% (88/4,662) during the final months of the intervention period. Linkage (Aim 2) remained high throughout, with 45 of 47 children living with HIV (96%) linked to care at baseline and 88 of 88 (100%) linked to care in the final months of the intervention period (
Figure 1; Table 2). These stable prevalence and linkage rates combined with an increased PITC coverage resulted in a 96% increase in the number of children living with HIV linked to care.
HIV rapid test kit supply improved during the intervention, with the number of days per month per facility in which test kit stock outs occurred falling from 8.8 during baseline to 1.5 at the end of the project.
The QIC enabled QI teams at the 24 health facilities to double coverage of inpatient pediatric PITC from 38% to 76% while maintaining high linkage rates and reducing HIV test kit stock outs. Facility staff identified and tested contextually appropriate change ideas, focusing on interventions that were feasible at the site level, such as training, supervision, and management of staff, workflow processes, and documentation. The net impact was a 96% increase in the number of children living with HIV who were identified and linked to care, from 45 at baseline to 88 at endline. These were children who might otherwise not have been diagnosed with HIV and started on life-saving antiretroviral therapy.
Our study supports the literature, which has suggested that the QIC approach empowers facility-level teams to achieve and sustain rapid improvement via peer-to-peer learning and fostering of friendly competition and innovation (
Catsambas et al., 2008 ; ). In our program, QICs were used to address a critical need in the pediatric HIV cascade and improve the identification of children living with HIV who had been previously undiagnosed. Franco & Marquez, 2011
Limitations of our analyses include the fact that the coverage indicator for Aim 1 included all pediatric inpatients, but not all children admitted to inpatient wards were eligible for HIV testing. For example, children already known to be living with HIV would not need to be retested. Although this could have caused an underestimate of PITC performance, it should have affected both baseline and endline data equally. Another limitation was that Aim 2 was established via consensus before baseline data were available; when baseline performance was assessed, sites discovered that their referral rates were already extremely high. Monitoring of this indicator continued, but emphasis was placed on maintenance rather than improvement. As is usual for QI projects, there was no control group, so results at these 24 health facilities could not be compared to sites not participating in the QIC and cannot be generalized to other health care facilities.
The magnitude of improvement in our study confirms that the QIC approach holds promise as a method with which to close the know-do gap, improve pediatric PITC, achieve national HIV program targets, and improve health outcomes.
The authors report no real or perceived vested interests related to this article that could be construed as a conflict of interest.
The project was supported by the President's Emergency Plan for AIDS Relief through the U.S. Centers for Disease Control and Prevention under the terms of Cooperative Agreement U2GGH000994-02. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the funding agency.
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