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HIV Testing at Family Planning Clinics in Mombasa County, Kenya

HIV Testing at Family Planning Clinics in Mombasa County, Kenya: A Cluster-Randomized Trial Comparing the Systems Analysis and Improvement Approach (SAIA) to Usual Procedures

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT02994355
Enrollment
24
Registered
2016-12-15
Start date
2018-06-01
Completion date
2022-12-31
Last updated
2023-11-30

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

HIV

Keywords

Family planning clinics, Implementation Science, Systems Analysis and Improvement Approach (SAIA)

Brief summary

Location: Family Planning Clinics in Mombasa County, Kenya Introduction: Integration of HIV treatment and prevention with family planning (FP) services is a promising approach for optimizing delivery of comprehensive healthcare for HIV-positive women, as well as prevention services for those who are negative. In Mombasa County, the USAID-supported AIDS Population and Health Integrated Assistance II Program revised the FP Clinic Register to capture HIV testing in 2008. However, the rate of HIV testing in FP clinics remains low. Our overarching objective is to assess the effectiveness, costs, and budget impact of implementing the systems analysis and improvement approach (SAIA) to increase HIV testing in FP clinics in Mombasa County. Methods: The investigators aim to conduct a cluster-randomized trial comparing the effect of the SAIA approach versus usual procedures on rates of HIV testing in first-time attendees at 20 intervention versus 20 control FP clinics in Mombasa County. The investigators will compare HIV testing rates for first-time FP clinic attendees in SAIA intervention versus control facilities after an additional year, during which FP clinics in the intervention arm will be encouraged to continue to use the SAIA tools with minimal support from the study team as the Mombasa County Ministry of Health will take ownership of implementation. Lastly, the investigators aim to estimate the incremental cost and budget impact of applying SAIA versus standard of care using an activity-based approach. Anticipated Results: The investigators anticipate that SAIA will produce significant and sustained improvement in HIV-testing rates in first-time FP clinic attendees in intervention clinics compared to control facilities. The use of a rigorous study design will provide strong evidence to guide integration of HIV testing into FP services in a wide range of settings. The inclusion of costing and budget impact analyses will assist policy makers in reaching informed decisions about implementation. Anticipated Conclusion: By addressing the crucial first step in the linkage of HIV and FP services, this research holds considerable promise for improving women's health by opening the gateway to HIV care and prevention.

Detailed description

Integration of HIV treatment and prevention with family planning (FP) services is a promising approach for optimizing delivery of comprehensive healthcare for HIV-positive women, as well as prevention services for those who are negative. The need for integration of services is evident in Africa, which bears a disproportionate burden of HIV, high birth rates, and maternal mortality. A high and increasing proportion of African women use FP services, making this a potentially efficient venue for reaching them. Testing for HIV is the gateway to care and prevention. Integrating HIV testing into FP clinics could open this essential gateway, decreasing stigma associated with seeking HIV testing while reducing costs. The antenatal setting provides a useful example. In many African countries, testing for HIV in antenatal clinics (ANCs) has become routine. Diagnosis of HIV during pregnancy has paved the way to substantial reductions in mother-to-child transmission of HIV and AIDS-related deaths in women of reproductive age. These achievements demonstrate the feasibility and impact of wide-scale HIV testing through existing reproductive health services. In contrast to ANCs, integration of HIV testing into FP services remains at a formative stage in much of Africa. Recent reviews support the feasibility of integrating these services, but invariably conclude that additional research is needed. In Kenya, the National AIDS and STD Control Program (NASCOP) states that the FP clinic is a setting in which, Failure to offer HIV testing and counseling is unacceptable, and will be considered negligent. However, there has been almost no operational assessment of HIV testing in Kenyan FP clinics. In Mombasa County, the USAID-supported AIDS Population and Health Integrated Assistance II Program revised the FP Clinic Register to capture HIV testing in 2008. However, the rate of HIV testing in FP clinics remains low, and the County has requested our assistance in addressing this prevention gap. Colleagues at the University of Washington Department of Global Health have developed a systems analysis and performance enhancement approach, using industrial and systems engineering techniques, that the investigators believe will be useful in this setting. The overarching objective is to assess the effectiveness, costs, and budget impact of implementing this systems analysis and improvement approach (SAIA) to increase HIV testing in FP clinics in Mombasa County. The investigators specific aims are as follows: AIM 1: To conduct a cluster-randomized trial comparing the effect of the SAIA approach versus usual procedures on rates of HIV testing in first-time attendees at 12 intervention versus 12 control FP clinics in Mombasa County, Kenya. HYP 1: After one year of study team support implementing SAIA vs. usual procedures, a higher proportion of first-time FP clinic attendees will be tested for HIV at intervention compared to control facilities AIM 2: To determine whether the SAIA training results in a lasting effect, the investigators will compare HIV testing rates for first-time FP clinic attendees in SAIA intervention versus control facilities after an additional year, during which FP clinics in the intervention arm will be encouraged to continue to use the SAIA tools with minimal support from the study team. The Mombasa County Ministry of Health will take ownership of implementation during this phase. HYP 2: After an additional year with minimal support from the study team, there will continue to be significantly higher rates of HIV testing in first-time FP clinic attendees at intervention compared to control facilities. AIM 3: To estimate the incremental cost and budget impact of applying SAIA versus standard of care. Using an activity-based approach, the investigators will perform a costing analysis, estimating cost per new HIV diagnosis, both during active support from the study team and after a period without active support. The investigators will also estimate cost to scale up, and conduct a budget impact analysis from a Department of Health (DOH) perspective. Expected Outcome and Significance: The investigators anticipate that the SAIA approach will produce significant and sustained improvement in HIV-testing rates in first-time FP clinic attendees in intervention clinics compared to control facilities. The use of a rigorous study design to evaluate this scalable approach will provide strong evidence to guide integration of HIV testing into FP services in a wide range of settings. The inclusion of costing and budget impact analyses will assist policy makers in reaching informed decisions about implementation. By addressing the crucial first step in the linkage of HIV and FP services, this research holds considerable promise for improving women's health by opening the gateway to HIV care and prevention. Preliminary data on linkage to care and prevention services will inform development of future grant proposals.

Interventions

1. Understanding the cascade from FP clinic enrollment to HIV testing 2. Use process mapping to identify modifiable bottlenecks 3. Define and implement workflow adaptations to eliminate modifiable bottlenecks 4. Monitor change in performance 5. Repeat the analysis and improvement cycle (steps 1-4)

Sponsors

National Institutes of Health (NIH)
CollaboratorNIH
University of Nairobi
CollaboratorOTHER
Kenyatta National Hospital
CollaboratorOTHER_GOV
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)
CollaboratorNIH
Ministry of Health, Mombasa County
CollaboratorOTHER_GOV
University of Washington
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SCREENING
Masking
NONE

Eligibility

Sex/Gender
ALL
Healthy volunteers
No

Inclusion criteria

for in-depth interviews: * Adult family planning clinic staff * If staff younger than 18 are encountered, they will be allowed to participate only if they qualify as emancipated minors in Kenya (14 years or older and married or pregnant). * Able to provide written informed consent for in-depth interviews Inclusion criteria for FP clinics in Mombasa: -Clinics providing assent for participation in both the preliminary review and randomizations

Exclusion criteria

for FP clinics: * Clinics planning to be closed during the study period * Clinics unwilling to be randomized or to participate in the SAIA intervention/approach

Design outcomes

Primary

MeasureTime frame
Percentage of Eligible (Not Known HIV+) New FP Clients Who Are Tested for HIV in the Months 9-12 of the Study in Intervention and Control FacilitiesMonths 9-12 of the study

Secondary

MeasureTime frame
Percentage of New FP Clients Who Are Counseled About HIV Testing in the Months 9-12 of the Study in Intervention and Control Facilities, Adjusted for BaselineMonths 9-12 of the study
Percentage of New FP Clients Who Are Tested for HIV After Year of Minimal SupportMonths 13-24 of the study

Countries

Kenya

Participant flow

Participants by arm

ArmCount
Intervention Clinics
Clinics randomized to the intervention will be introduced to the Systems Analysis and Improvement Approach (SAIA) to understand barriers to HIV testing in family planning clinics. Sequential process flow mapping will be used to highlight areas for improvement and then specific interventions will be implemented for the clinics with the goal of increasing HIV testing rates. Systems Analysis and Improvement Approach: 1. Understanding the cascade from FP clinic enrollment to HIV testing 2. Use process mapping to identify modifiable bottlenecks 3. Define and implement workflow adaptations to eliminate modifiable bottlenecks 4. Monitor change in performance 5. Repeat the analysis and improvement cycle (steps 1-4)
0
Intervention Clinics
Clinics randomized to the intervention will be introduced to the Systems Analysis and Improvement Approach (SAIA) to understand barriers to HIV testing in family planning clinics. Sequential process flow mapping will be used to highlight areas for improvement and then specific interventions will be implemented for the clinics with the goal of increasing HIV testing rates. Systems Analysis and Improvement Approach: 1. Understanding the cascade from FP clinic enrollment to HIV testing 2. Use process mapping to identify modifiable bottlenecks 3. Define and implement workflow adaptations to eliminate modifiable bottlenecks 4. Monitor change in performance 5. Repeat the analysis and improvement cycle (steps 1-4)
12
Control Clinics
Clinics randomized to the control arm of the study will continue HIV testing as per usual procedures.
0
Control Clinics
Clinics randomized to the control arm of the study will continue HIV testing as per usual procedures.
11
Total23

Baseline characteristics

CharacteristicIntervention ClinicsControl ClinicsTotal
Age, Categorical
<=18 years
NA Family Planning ClinicsNA Family Planning ClinicsNA Family Planning Clinics
Age, Categorical
>=65 years
NA Family Planning ClinicsNA Family Planning ClinicsNA Family Planning Clinics
Age, Categorical
Between 18 and 65 years
NA Family Planning ClinicsNA Family Planning ClinicsNA Family Planning Clinics
Clients required to pay for HIV testing2 Family Planning Clinics3 Family Planning Clinics5 Family Planning Clinics
Complete auditory privacy7 Family Planning Clinics7 Family Planning Clinics14 Family Planning Clinics
Complete visual privacy8 Family Planning Clinics6 Family Planning Clinics14 Family Planning Clinics
FP clinic manager aware of most recent National HIV Guidelines6 Family Planning Clinics9 Family Planning Clinics15 Family Planning Clinics
Number of FP providers trained in HTC1 Family Planning Clinics1 Family Planning Clinics1 Family Planning Clinics
Public Clinic6 Family Planning Clinics6 Family Planning Clinics12 Family Planning Clinics
Race (NIH/OMB)
American Indian or Alaska Native
NA Family Planning ClinicsNA Family Planning ClinicsNA Family Planning Clinics
Race (NIH/OMB)
Asian
NA Family Planning ClinicsNA Family Planning ClinicsNA Family Planning Clinics
Race (NIH/OMB)
Black or African American
NA Family Planning ClinicsNA Family Planning ClinicsNA Family Planning Clinics
Race (NIH/OMB)
More than one race
NA Family Planning ClinicsNA Family Planning ClinicsNA Family Planning Clinics
Race (NIH/OMB)
Native Hawaiian or Other Pacific Islander
NA Family Planning ClinicsNA Family Planning ClinicsNA Family Planning Clinics
Race (NIH/OMB)
Unknown or Not Reported
NA Family Planning ClinicsNA Family Planning ClinicsNA Family Planning Clinics
Race (NIH/OMB)
White
NA Family Planning ClinicsNA Family Planning ClinicsNA Family Planning Clinics
Sex: Female, Male
Female
NA Family Planning ClinicsNA Family Planning ClinicsNA Family Planning Clinics
Sex: Female, Male
Male
NA Family Planning ClinicsNA Family Planning ClinicsNA Family Planning Clinics
Urban Clinic4 Family Planning Clinics4 Family Planning Clinics8 Family Planning Clinics

Adverse events

Event typeEG000
affected / at risk
EG001
affected / at risk
deaths
Total, all-cause mortality
0 / 00 / 0
other
Total, other adverse events
0 / 120 / 12
serious
Total, serious adverse events
0 / 120 / 12

Outcome results

Primary

Percentage of Eligible (Not Known HIV+) New FP Clients Who Are Tested for HIV in the Months 9-12 of the Study in Intervention and Control Facilities

Time frame: Months 9-12 of the study

Population: Data was collected at the clinic level.

ArmMeasureValue (MEAN)Dispersion
Intervention ClinicsPercentage of Eligible (Not Known HIV+) New FP Clients Who Are Tested for HIV in the Months 9-12 of the Study in Intervention and Control Facilities42 Percentage tested for HIVStandard Deviation 26
Control ClinicsPercentage of Eligible (Not Known HIV+) New FP Clients Who Are Tested for HIV in the Months 9-12 of the Study in Intervention and Control Facilities32 Percentage tested for HIVStandard Deviation 15
p-value: <0.0595% CI: [1.16, 1.52]Poisson Regression
Secondary

Percentage of New FP Clients Who Are Counseled About HIV Testing in the Months 9-12 of the Study in Intervention and Control Facilities, Adjusted for Baseline

Time frame: Months 9-12 of the study

Population: Data was collected at the clinic level.

ArmMeasureValue (MEAN)Dispersion
Intervention ClinicsPercentage of New FP Clients Who Are Counseled About HIV Testing in the Months 9-12 of the Study in Intervention and Control Facilities, Adjusted for Baseline85 Percentage counseled for HIVStandard Deviation 27
Control ClinicsPercentage of New FP Clients Who Are Counseled About HIV Testing in the Months 9-12 of the Study in Intervention and Control Facilities, Adjusted for Baseline67 Percentage counseled for HIVStandard Deviation 34
p-value: <0.0595% CI: [1.15, 1.3]Poisson regression
Secondary

Percentage of New FP Clients Who Are Tested for HIV After Year of Minimal Support

Time frame: Months 13-24 of the study

Population: Data was collected at the clinic level.

ArmMeasureValue (MEAN)Dispersion
Intervention ClinicsPercentage of New FP Clients Who Are Tested for HIV After Year of Minimal Support61 % tested for HIVStandard Error 7
Control ClinicsPercentage of New FP Clients Who Are Tested for HIV After Year of Minimal Support19 % tested for HIVStandard Error 6
p-value: <0.0595% CI: [2.29, 4.55]Poisson regression

Source: ClinicalTrials.gov · Data processed: Feb 13, 2026