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Assessing the sustainability of the Systems Analysis and Improvement Approach to increase HIV testing in family planning clinics in Mombasa, Kenya: results of a cluster randomized trial

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Background In Kenya, HIV incidence is highest among reproductive-age women. A key HIV mitigation strategy is the integration of HIV testing and counseling (HTC) into family planning services, but successful integration remains problematic. We conducted a cluster-randomized trial using the Systems Analysis and Improvement Approach (SAIA) to identify and address bottlenecks in HTC integration in family planning clinics in Mombasa County, Kenya. This trial (1) assessed the efficacy of this approach and (2) examined if SAIA could be sustainably incorporated into the Department of Health Services (DOHS) programmatic activities. In Stage 1, SAIA was effective at increasing HTC uptake. Here, we present Stage 2, which assessed if SAIA delivery would be sustained when implemented by the Mombasa County DOHS and if high HTC performance would continue to be observed. Methods Twenty-four family planning clinics in Mombasa County were randomized to either the SAIA implementation strategy or standard care. In Stage 1, the study staff conducted all study activities. In Stage 2, we transitioned SAIA implementation to DOHS staff and compared HTC in the intervention versus control clinics 1-year post-transition. Study staff provided training and minimal support to DOHS implementers and collected quarterly HTC outcome data. Interviews were conducted with family planning clinic staff to assess barriers and facilitators to sustaining HTC delivery. Results Only 39% (56/144) of planned SAIA visits were completed, largely due to the COVID-19 pandemic and a prolonged healthcare worker strike. In the final study quarter, 81.6% (160/196) of new clients at intervention facilities received HIV counseling, compared to 22.4% (55/245) in control facilities (prevalence rate ratio [PRR]=3.64, 95% confidence interval [CI]=2.68–4.94). HIV testing was conducted with 60.5% (118/195) of new family planning clients in intervention clinics, compared to 18.8% (45/240) in control clinics (PRR=3.23, 95% CI=2.29–4.55). Interviews with family planning clinic staff suggested institutionalization contributed to sustained HTC delivery, facilitated by low implementation strategy complexity and continued oversight. Conclusions Intervention clinics demonstrated sustained improvement in HTC after SAIA was transitioned to DOHS leadership despite wide-scale healthcare disruptions and incomplete delivery of the implementation strategy. These findings suggest that system interventions may be sustained when integrated into DOHS programmatic activities. Trial registration ClinicalTrials.gov (NCT02994355) registered on 16 December 2016.
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Longetal. Implementation Science (2022) 17:70
https://doi.org/10.1186/s13012-022-01242-3
RESEARCH
Assessing thesustainability oftheSystems
Analysis andImprovement Approach
toincrease HIV testing infamily planning
clinics inMombasa, Kenya: results ofacluster
randomized trial
Jessica E. Long1,2* , McKenna C. Eastment2, George Wanje3, Barbra A. Richardson3,4,5, Emily Mwaringa6,
Mwanakarama Athman Mohamed6, Kenneth Sherr1,3,7, Ruanne V. Barnabas1,2,3, Kishorchandra Mandaliya3,
Walter Jaoko8 and R. Scott McClelland1,2,3,8
Abstract
Background: In Kenya, HIV incidence is highest among reproductive-age women. A key HIV mitigation strategy is
the integration of HIV testing and counseling (HTC) into family planning services, but successful integration remains
problematic. We conducted a cluster-randomized trial using the Systems Analysis and Improvement Approach (SAIA)
to identify and address bottlenecks in HTC integration in family planning clinics in Mombasa County, Kenya. This trial
(1) assessed the efficacy of this approach and (2) examined if SAIA could be sustainably incorporated into the Depart-
ment of Health Services (DOHS) programmatic activities. In Stage 1, SAIA was effective at increasing HTC uptake. Here,
we present Stage 2, which assessed if SAIA delivery would be sustained when implemented by the Mombasa County
DOHS and if high HTC performance would continue to be observed.
Methods: Twenty-four family planning clinics in Mombasa County were randomized to either the SAIA implementa-
tion strategy or standard care. In Stage 1, the study staff conducted all study activities. In Stage 2, we transitioned SAIA
implementation to DOHS staff and compared HTC in the intervention versus control clinics 1-year post-transition.
Study staff provided training and minimal support to DOHS implementers and collected quarterly HTC outcome
data. Interviews were conducted with family planning clinic staff to assess barriers and facilitators to sustaining HTC
delivery.
Results: Only 39% (56/144) of planned SAIA visits were completed, largely due to the COVID-19 pandemic and a
prolonged healthcare worker strike. In the final study quarter, 81.6% (160/196) of new clients at intervention facili-
ties received HIV counseling, compared to 22.4% (55/245) in control facilities (prevalence rate ratio [PRR]=3.64, 95%
confidence interval [CI]=2.68–4.94). HIV testing was conducted with 60.5% (118/195) of new family planning clients
in intervention clinics, compared to 18.8% (45/240) in control clinics (PRR=3.23, 95% CI=2.29–4.55). Interviews with
© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
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Open Access
*Correspondence: jesslong@uw.edu
1 Department of Epidemiology, University of Washington, 325 9th Avenue,
Box 359909, Seattle, WA 98104, USA
Full list of author information is available at the end of the article
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Longetal. Implementation Science (2022) 17:70
Contributions totheliterature
Sustainability is an under-measured aspect of imple-
mentation studies and is critical to understanding the
lasting impact of effective interventions.
We measured the sustainment of both an evidence-
based intervention and an implementation strategy,
and barriers and facilitators to sustainment.
In this setting, where a county-level Department of
Health Services (DOHS) oversees health facilities,
the evidence-based intervention was sustained after
embedding the implementation strategy into DOHS’s
routine programmatic activity.
Institutionalization, or establishment of the evidence-
based intervention as normal practice, was facilitated
by the low complexity of the implementation strategy,
positive implementation climate within facilities, and a
health system structure that allowed DOHS-led over-
sight and cost coverage.
Introduction
Eastern and southern Africa have seen remarkable reduc-
tions in HIV incidence, but gender gaps still remain [1].
In 2019, two in five new infections in this region were
among women, and adolescent girls and young women
(aged 15 to 24 years) were 2.5 times more likely than
male peers to acquire HIV [1]. In Kenya, 6.6% of women
are living with HIV, and the incidence is highest among
young women of reproductive age [2]. Effective outreach,
testing, and linkage to care among women are essential
to reduce the burden and spread of HIV and achieve the
United Nations Joint Program on HIV/AIDS (UNAIDS)
95-95-95 goal of 95% of people living with HIV knowing
their status, 95% antiretroviral therapy (ART) use among
those diagnosed with HIV, and 95% viral load suppres-
sion among those on ART. A key strategy for reaching
women of reproductive age and improving HIV testing
uptake is the integration of HIV testing and counseling
(HTC) into family planning services [35]. However,
while many countries have national guidelines to sup-
port HTC at family planning clinics, implementation of
this intervention varies widely between and within coun-
tries. In Kenya, HTC integration into family planning
services is promoted by Kenya’s National AIDS and STD
Control Program, but successful integration of these ser-
vices remains low in many regions, including Mombasa
County [5, 6].
Implementation strategies, such as the Systems Analy-
sis and Improvement Approach (SAIA), can be used to
systematically identify and address bottlenecks in health-
care delivery systems. SAIA is an evidenced-based multi-
component implementation strategy that is applied at the
facility level to provide staff with tools aimed at improv-
ing care cascades. rough a five-step process (described
below) SAIA provides a system-wide view of a health-
care cascade and uses small tests of change to address
context-specific bottlenecks and barriers to care delivery
[7]. Using this method, SAIA provides healthcare teams
with tools to collaboratively identify problems, prioritize
areas of improvement, implement changes, and evaluate
those changes [8, 9]. is method is theorized to improve
service-delivery outcomes by facilitating communica-
tion, promoting consensus decision-making, and encour-
aging accountability across staff within a care cascade
[8, 10]. SAIA has previously been tested as a strategy to
improve healthcare cascades focused on the preven-
tion of mother-to-child HIV transmission [11], mental
healthcare [8], and integrating hypertension diagnosis
and management into the HIV care cascade [10], among
others. An important topic of the ongoing study is the
sustainability of these interventions and the impact they
have on long-term changes in delivery systems after the
research has ended.
While there is no standard definition of sustainment
in implementation research [12, 13], it is often concep-
tualized as the continued use of program components
and activities to achieve desirable program and popula-
tion outcomes over time [12, 14, 15]. is can encompass
both continued adherence to the implementation strat-
egy (e.g., SAIA) and continued delivery of the evidence-
based intervention (e.g., HTC) [12]. For interventions
delivered within healthcare settings, an important aspect
of sustainability is how well the implementation strategy
family planning clinic staff suggested institutionalization contributed to sustained HTC delivery, facilitated by low
implementation strategy complexity and continued oversight.
Conclusions: Intervention clinics demonstrated sustained improvement in HTC after SAIA was transitioned to DOHS
leadership despite wide-scale healthcare disruptions and incomplete delivery of the implementation strategy. These
findings suggest that system interventions may be sustained when integrated into DOHS programmatic activities.
Trial registration: ClinicalTrials.gov (NCT02994355) registered on 16 December 2016.
Keywords: HIV counseling and testing, Family planning clinics, Implementation science, System analysis and
improvement approach (SAIA), Sustainability
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Page 3 of 16
Longetal. Implementation Science (2022) 17:70
or evidence-based intervention was integrated into nor-
mal activity.
To assess the effectiveness and sustainability of SAIA as
a strategy to increase uptake of HTC at family planning
clinics, we conducted a two-stage cluster-randomized
trial in Mombasa, Kenya. In the first stage of the trial, the
study staff implemented SAIA at family planning clinics
in the intervention arm for 1 year. At the end of the first
stage, 85% (740/868) of new family planning clients were
counseled about the need to complete opt-out HIV test-
ing in intervention clinics compared to 67% (1036/1542)
in control clinics (prevalence rate ratio [PRR]: 1.27, 95%
confidence interval [CI], 1.15–1.30) [16]. Testing was
conducted among 42% (364/859) of new clients at inter-
vention clinics compared to 32% (485/1521) at control
clinics (PRR: 1.33, 95% CI, 1.16–1.52). ese results
showed that SAIA was effective in increasing rates of
both pre-test counseling and HIV testing at clinics in the
intervention arm compared to control clinics.
Here, we present the results of the second stage of the
trial. At this stage, we were interested in determining the
feasibility of transitioning SAIA to Mombasa County
leadership to integrate SAIA implementation into stand-
ard county oversight of family planning clinics. We
hypothesized that providing continued oversight to fam-
ily planning clinics through an existing county oversight
mechanism would provide structure and motivation to
continue SAIA implementation and that this could con-
tribute to the long-term sustainment of the higher HTC
levels observed in the first stage of the trial. To test this,
we transitioned SAIA implementation and leadership to
the Mombasa County Department of Health Services
(DOHS), tracked the frequency of county-led SAIA vis-
its, and compared HTC in clinics in the intervention arm
versus the control arm of the trial 1 year after this hando-
ver. e aim of this stage of the trial was to assess if both
SAIA delivery, and the observed improvements in uptake
of HTC in family planning clinics would be sustained
when implemented by the county with minimal support
from study staff.
Methods
Study design andrandomization
is study was a two-stage cluster-randomized trial to
evaluate the use of SAIA to improve HTC at family plan-
ning clinics in Mombasa, Kenya. e trial design and
Stage 1 results have been previously reported [16]. In
brief, SAIA is a blended implementation strategy that
iteratively uses a 5-step cycle to improve performance
across care cascades [11]. Twenty-four family planning
clinics in Mombasa were selected for study inclusion and
randomized to either receive the SAIA implementation
strategy (n=12) or to be included as controls receiving
standard care (n=12). Restricted randomization of clinics
(1:1) was conducted based on clinic size and delivery of
HTC services prior to the study start. Due to the nature
of the implementation strategy delivered to clinics in the
intervention arm, participating clinics were not blinded.
Randomization was conducted by an independent statis-
tician at the Center for AIDS Research Biometrics Core
at the University of Washington who did not serve in any
other role in the study.
County DOHS collaborators
Kenya has a decentralized system of government, in
which the national Ministry of Health (MOH) provides
policy, but each county independently operates a County
Department of Health Services. In Mombasa County, an
Executive of Health oversees two branches, Public Health
and Medical Services, which are each led by a Chief
Officer and Director. Under this leadership, the County
Health Management Team (CHMT) operates across both
branches, divided into departments to address impor-
tant health topics. For this research, we worked with
the Reproductive Health (RH) Officer and HIV/Sexu-
ally Transmitted Infections (STI) Officer. ese officers
oversee sub-county RH and STI coordinators, who have
direct oversight over family planning clinics within their
respective sub-counties. e sub-county STI and RH
coordinators are primarily nurses and clinical officers
by training who have risen to a supervisory role through
years of service and professional development. eir pri-
mary role is to supervise the delivery of STI and RH ser-
vices, respectively, in their sub-county jurisdictions. As
part of their standard duties, RH and STI coordinators
visit family planning clinics monthly to address any prob-
lems and track the progress of programmatic activities.
All study activities were conducted in coordination with
collaborators within the Mombasa County DOHS.
Stage 1: Study setting
Trial Stage 1 was conducted from December 2018 to
November 2019. During this time, Mombasa County did
not experience any systematic disruptions to the health-
care system. At the study start, Mombasa had approxi-
mately 170 family planning clinics, including public and
private facilities. All facilities receive HIV-testing sup-
plies at no cost from the Mombasa County DOHS. HIV-
testing commodities are tracked on MOH-provided
registers. Specific training and certification are required
to perform HTC. In the context of this study, the coun-
seling aspect of HTC refers to pre-test counseling, in
which care providers recommend opt-out HIV test-
ing and ask family planning clients if they are willing to
be tested. Anyone who reports a previous HIV-positive
diagnosis is not eligible for HIV testing. For each family
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Longetal. Implementation Science (2022) 17:70
planning client, MOH-provided registers record if they
received this counseling, HIV serostatus at the time of
counseling, and if they received HIV testing. ese data
were used to calculate HTC rates in clinics in the inter-
vention arm versus control clinics, with all new family
planning clients considered eligible for counseling, and
all new clients who did not have a previous HIV-positive
diagnosis eligible for testing.
Stage 1: Procedures
During Stage 1 of the trial, study staff implemented
SAIA at each clinic in the intervention arm. e SAIA
steps and roles played by the clinic staff and facilitators
are explained in Table1. As previously described [16],
this included the creation of a “cascade analysis tool,
an Excel-based system for quantifying and displaying
the number of individuals who complete each step of a
process to identify where improvement may be needed
[9, 17]. e tool also shows the expected impact on HIV
testing when each step of the cascade is optimized to full
performance. Cascade analysis was followed by sequen-
tial process flow mapping, in which study staff helped
clinic staff to map clinic processes to identify modifiable
bottlenecks in their workflow for HTC. Study staff then
worked with clinic staff to conduct plan-do-study-act
(PDSA) cycles, in which they identified workflow modi-
fications that clinic staff would implement during the fol-
lowing month (termed “micro-interventions”) chosen to
address barriers to implementing HTC specific to each
clinic, then evaluate during the following cycle. Study
staff conducted monthly SAIA visits with clinic staff at
facilities in the intervention arm to assess the implemen-
tation and impact of the micro-interventions with real-
time data input into the cascade analysis tool and plan
a micro-intervention for the next month. Micro-inter-
vention activities were enacted by the clinic staff at each
family planning clinic over the following month. Exam-
ples of micro-interventions implemented in Stage 1 have
been previously published [16]. Research staff conducted
monthly SAIA visits for 12 months at each participating
clinic in the intervention arm, during which time study
data on HTC outcomes were also collected.
Control clinics were aware of the study but did not
receive any of the SAIA implementation strategy compo-
nents described above and instead continued with stand-
ard care and delivery of HTC. Kenya MOH National
Guidelines recommend integration of HTC at family
planning clinics, and this is overseen by DOHS RH and
STI coordinators [18]. However, no specific strategies are
in place to promote HTC uptake at these clinics. Study
staff visited control clinics every 3 months to collect data,
but otherwise had no interaction with control clinic staff.
During this stage, the County DOHS leadership were
updated regularly regarding study activities and served in
an advisory role.
At the end of study Stage 1, there was a brief gap in the
trial before Stage 2 was launched. During this time, study
staff continued to actively deliver SAIA at clinics in the
intervention arm.
Power andsample size
Sample size estimates are based on Stage 1 of the trial
and have been described previously [16]. Briefly, sam-
ple size determination was made based on an average of
15 new family planning clients per clinic per 3-month
period, 20% HIV testing among new clients in the control
clinics, and a 50% increase in HTC with the SAIA imple-
mentation strategy. At an alpha level of 0.05 and a two-
sided test, the inclusion of 11 clinics per study arm would
provide 80% power to detect this effect in clinics in the
intervention arm compared to control clinics. To allow
for potential loss to follow up of one clinic per arm, 24
clinics were randomized. Twenty-three clinics remained
in follow-up throughout both stages of the study.
Stage 2: Study setting
Trial Stage 2 was conducted from February 2020 to Jan-
uary 2021. In March 2020, the first cases of COVID-19
were detected in Kenya. is led to government-man-
dated restrictions beginning March 18, 2020, includ-
ing curfews, travel restrictions, school closures, bans
on gatherings of >15 people, and drastic restrictions on
public transportation. In Mombasa County, a full lock-
down was issued for some areas between May 6 to July
7. In October and November 2020, healthcare workers in
Mombasa began a “go-slow” period, in which healthcare
services were restricted to emergencies only, followed
by a full strike from December 28, 2020, to February 19,
2021. ese events resulted in temporary closures of
some family planning clinics, reduced staff and capacity
at public clinics that remained open, and reduced capac-
ity at the county level to oversee family planning clinics.
While these events were disruptive to care delivery, the
purpose of Stage 2 of the trial was to assess if both SAIA
delivery and higher HTC performance in family planning
clinics would be sustained when implemented by the
County in real-world circumstances, so it did not impact
the timeline of data collection for this study.
Stage 2: Procedures
In study Stage 2, clinics maintained the study arm
that they were randomized to in the first year of the
study. To support the transition of SAIA implementa-
tion to the Mombasa County DOHS, the research team
trained 16 sub-county RH and STI Coordinators who
were appointed by the RH and HIV/STI Officers as
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Longetal. Implementation Science (2022) 17:70
Table 1 Description of the 5-step SAIA cycle conducted with intervention clinics
SAIA step Description Frequency and location FP clinic role Facilitation
Cascade analysis tool Excel-based system for quantifying and
displaying the number of individuals
who complete each step of a process
to identify where improvement may
be needed
Monthly SAIA meetings at clinics in the
intervention arm Clinic managers review the results of
the cascade analysis monthly with
study staff facilitators (Stage 1) or
DOHS facilitators (Stage 2)
Facilitators populate the cascade
analysis tool, and review results with FP
clinic staff. Facilitators were study staff in
Stage 1, DOHS staff in Stage 2.
Sequential process flow mapping Drawn map of clinic processes and
client movement through clinics to
identify modifiable bottlenecks in their
workflow for HTC
At initial training and at monthly SAIA
meetings at clinics in the intervention
arm
FP clinic staff draw the map of their
specific clinic flow Facilitators trained FP clinic staff and
oversaw process mapping.
Micro-intervention setting Identification of workflow modifica-
tions (termed “micro-inter ventions”)
that clinic staff implement during the
following month chosen to address
clinic-specific barriers to implement-
ing HTC
Monthly SAIA meetings at clinics in the
intervention arm FP clinic managers develop a micro-
intervention that addresses a problem
specific to their clinic, then implement
that change over the following month.
Facilitators assist in developing ideas for
feasible micro-interventions.
Micro-intervention assessment Micro-intervention chosen in the previ-
ous monthly SAIA meeting is assessed
to determine if it was (a) successfully
implemented, (b) effective in improv-
ing HTC, and (c) if the micro-interven-
tion should be adapted, adopted, or
abandoned.
Monthly SAIA meetings at clinics in the
intervention arm FP clinic managers report on how suc-
cessfully the micro-intervention was
implemented, and decide if it should
be adapted, adopted, or abandoned.
Facilitators provide HTC updates based
on the Cascade Analysis Tool and assist
FP clinic managers in decision making
on next steps.
Iterative refinement All previous steps are repeated at
monthly SAIA meetings, where previ-
ous micro-interventions are reviewed,
and new ones are chosen.
Monthly SAIA meetings at clinics in the
intervention arm FP clinic managers meet with
facilitators and are prepared to review
previous micro-interventions and set
new ones.
Facilitators arrange SAIA meetings and
attend monthly.
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Longetal. Implementation Science (2022) 17:70
“implementers” to conduct SAIA visits at each clinic in
the intervention arm as part of their normally scheduled
monthly family planning clinic supervision visits. Four
teams of STI and RH Coordinators conducted SAIA vis-
its at all clinics in the intervention arm within their cov-
erage area (between 1 and 6 clinics per team, depending
on coverage area).
Trainings led by study staff provided the sub-county
RH and STI Coordinators with an overview of SAIA,
practice in collecting and recording data, and mock SAIA
visits. e implementers were then responsible for trave-
ling to assigned clinics in the intervention arm for SAIA
visits to conduct or update flow mapping (as necessary),
cascade analysis, and development and assessment of
micro-interventions. e targeted SAIA visit schedule
was one visit per month to each clinic for 12 months. e
initial Stage 2 SAIA cycle at each clinic was conducted by
the County implementers with oversight and mentorship
from the study staff. After this initial mentored hand-off,
study staff were available to answer questions and con-
ducted periodic check-ins to monitor progress. Aside
from the initial mentored cycle, the study staff did not
participate in the implementation of SAIA during Stage
2 of the trial. County implementers were provided tablets
preloaded with training materials that they used for data
collection at sites. No other funding support or incentives
were given by the study to complete these visits. County
implementers reported to study staff when each SAIA
visit was completed to allow study staff to track when
DOHS-led SAIA cycles were conducted at each site. To
avoid behavior changes induced by observation, study
staff did not attend any additional SAIA cycle meetings
after the mentored cycle, and therefore, we were unable
to collect data on potential adaptations made at SAIA
visits led by DOHS staff.
ree types of data were collected during this stage
of the study. First, DOHS-appointed implementers
recorded information about each SAIA visit in a RED-
Cap questionnaire, which provided fidelity data on com-
pletion of SAIA cycles. Second, the clinical outcomes of
interest (number of new family planning clients, number
counseled, number tested) were independently collected
quarterly by study staff directly from register data at each
family planning clinic. ird, interviews were conducted
with clinic staff and managers to assess barriers and facil-
itators to uptake and sustainment of HTC and SAIA, and
reflections on why improvements were or were not sus-
tained at their clinic.
Participants
Data for this study were collected at the clinic level. Fam-
ily planning clinic staff and managers worked with the
STI and RH coordinators to implement SAIA at each
clinic and participated in exit interviews at the end of the
study. is study did not involve direct contact with fam-
ily planning clients, and all client data were de-identified
and aggregated.
Outcomes
Outcomes of interest included sustained delivery of SAIA
and maintenance of improvements in HTC observed in
Stage 1 of the trial. Sustained delivery of SAIA was meas-
ured as the proportion of the planned monthly SAIA vis-
its that were completed. Interviews with clinic staff were
used to provide context for gaps in SAIA delivery. Inter-
views also assessed institutionalization of HTC, as well
as facilitators and barriers that impacted sustainment of
SAIA implementation and HTC at clinics in the interven-
tion arm.
HTC delivery was measured as the proportion of
new family planning clients tested for HIV in the final 3
months of the study, comparing clinics in the interven-
tion arm to control clinics. A secondary measure of con-
tinued HTC was the proportion of new family planning
clients who received pre-test counseling in the final 3
months in clinics in the intervention arm compared to
controls. ese outcome variables were collected quar-
terly even if no SAIA visits had been conducted and were
recorded as zero new family planning clients during tem-
porary clinic closures.
Statistical analysis
e primary analysis followed an intent-to-treat design
based on the arm of the trial each clinic was randomized
to, regardless of participation in SAIA implementation
procedures. Study data were collected each quarter (Q)
of the 2-year study, with Stage 2 data collected in Q5–Q8.
We calculated prevalence rate ratios (PRR) using Poisson
regression with a log link, comparing the rates of HIV
testing in the final 3 months of Stage 2 (Q8) in clinics in
the intervention arm versus control clinics. A second-
ary analysis used the same method to compare rates of
pre-test counseling in the intervention arm compared
to the control. For both outcomes, we also examined if
performance differed between public and private family
planning clinics. Results were stratified by public versus
private family planning clinics if an interaction term p
value was <0.05. As an exploratory analysis, we further
examined HTC rates over the course of Stage 2 using a
difference-in-differences analysis in which we compared
the change in HIV testing and counseling rates from Q5
to Q8 at clinics in the intervention arm versus control
clinics. All analyses used Stata version 15.1 (College Sta-
tion, TX, USA, 2017).
All clinics in the intervention arm (n=12) were invited
to participate in exit interviews after study Stage 2 was
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Longetal. Implementation Science (2022) 17:70
complete. An interview guide was developed using
adapted measures from the Consolidated Framework for
Implementation Research (CFIR) interview guide tool
(https:// cfirg uide. org/) and a psychometrically validated
tool developed by Weiner etal. [19]. Interviews were con-
ducted among family planning clinic staff members who
were involved in SAIA implementation, and were ana-
lyzed using a rapid assessment approach guided by the
CFIR [20] and the Implementation Outcomes Framework
[21]. is analysis includes interview responses focused
on barriers and facilitators of sustaining the implementa-
tion strategy (SAIA) and the evidence-based intervention
(HTC), with a specific focus on CFIR domains of inter-
vention characteristics, inner setting, and process, as well
as concepts specific to sustainability, such as institution-
alization. Interviews were recorded through field notes
and audio recordings (GW). A structured codebook was
created to allow for categorization of elicited constructs
and emergent themes and was populated by two coders
using field notes (GW, JL). Interpretation of coding was
discussed iteratively between the two coders until con-
sensus was reached.
Ethical considerations
is research was approved by the Kenyatta National
Hospital-University of Nairobi Ethics and Research
Committee, the Human Subjects Research Institutional
Review Board at the University of Washington, and the
Mombasa County DOHS. is trial is registered at Clini-
calTrials.gov (NCT02994355). All Mombasa County
DOHS implementers verbally agreed to participate in
the trial, and clinic staff and managers who participated
in interviews provided written informed consent prior to
COVID-19 and verbal assent for remote interviews dur-
ing the pandemic.
Results
Of the 24 randomized clinics, 23 contributed data to
Stage 2 outcomes (Fig.1); one control clinic closed prior
to the start of the trial. In each arm of the trial, 6 clinics
(50%) were public, and 4 clinics (33%) were in an urban
location. In both control arm and intervention arm clin-
ics, a median of 1 (interquartile range [IQR] 0–2) provid-
ers were trained in HTC at study baseline. In both study
arms, a median of 1 (IQR 0–2) family planning clinic
manager reported awareness of the most recent National
HIV Guidelines at study baseline.
e COVID-19 pandemic and subsequent healthcare
worker strike caused short-term clinic closures in some
participating clinics. One control clinic was unable to
contribute Q5 data due to temporary closure, and two
clinics in the intervention arm were closed and unable
to contribute data during Q7 and Q8. Additionally, one
clinic in the intervention arm declined participation in
SAIA implementation but allowed data collection and is
included in analyses.
HIV testing andcounseling
Stage 1 results reviewed in the introduction of this paper
have been previously published [14] and are incorporated
in Figs.2 and 3 to provide context. In Stage 2, 5232 new
family planning clients were seen at all clinics during the
Fig. 1 Flow diagram of family planning clinics. Flow diagram of family planning clinics assessed for eligibility, randomized, participated, and
included in final intent-to-treat analysis in the first and second year of the study
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Longetal. Implementation Science (2022) 17:70
12 months of data collection, with a precipitous drop in
new clients observed in Q8 resulting from the healthcare
worker strike and subsequent clinic closures (Fig.2, bot-
tom row). Clinics in the intervention arm (n=10) saw a
median of 18 (IQR 11–20) new family planning clients
per clinic in Q8, compared to a median of 7 (IQR 5–30)
in control clinics (n=11).
In Q8, pre-test counseling was conducted with 81.6%
(160/196) of new family planning clients at interven-
tion arm facilities compared to 22.4% (55/245) in control
arm facilities (PRR 3.64, 95% CI 2.68–4.94) (Fig.2). is
effect was modified by clinic type, with a strong effect of
the SAIA implementation strategy found in private clin-
ics (PRR 8.26, 95% CI 3.38–20.17) and a smaller but still
highly significant effect in public clinics (PRR 2.75, 95%
CI 1.71–4.42) (Fig.4). A difference-in-differences analy-
sis showed a significant difference between clinics in the
intervention arm compared to control clinics from Q5 to
Q8. Clinics in the intervention arm saw a 0.5% increase
in HIV counseling comparing Q5 to Q8, while pre-test
counseling decreased in control clinics by 54% during
the same time period, for a difference in differences of
54.5% between intervention arm and control arm clinics
(p<0.05).
In Q8, 60.5% (118/195) of new family planning clients
were tested for HIV in clinics in the intervention arm,
compared to 18.8% (45/240) in clinics in the control arm
(PRR 3.23, 95% CI 2.29–4.55) (Fig.3). Similar to coun-
seling, this effect was strongly modified by clinic type;
private clinics in the intervention arm had a significantly
higher rate of HIV testing in new family planning clients
compared to private clinics in the control arm (PRR 6.64,
95% CI 2.71–16.27) (Fig.4). In contrast, no effect of the
SAIA implementation strategy was seen in the compari-
son of public intervention arm versus control arm clinics
(PRR 1.07, 95% CI 0.50–2.28). A difference-in-differences
analysis comparing the difference in HIV testing rates
from Q5 to Q8 in each study arm found that HIV testing
increased 7% in clinics in the intervention arm, while it
decreased 10% in control clinics, corresponding to a dif-
ference in differences of 17% (p<0.05).
In Stage 2 of the study, there were 3/2105 (0.14%)
new HIV diagnoses at intervention clinics, compared to
3/3127 (0.10%) at control facilities.
Fig. 2 Proportion of eligible family planning clients receiving pre-test HIV counseling. Pre-test HIV counseling by quarter for the entire duration of
the study. Results from Stage 1 have been previously published [16] and are re-presented here for context. Error bars reflect the standard error. (FP
family planning, Int. intervention arm, Con. control arm)
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Longetal. Implementation Science (2022) 17:70
SAIA delity
Optimal delivery of the SAIA implementation strategy
would require monthly visits at each clinic in the inter-
vention arm, for a total of 144 visits performed by STI
and RH Coordinators. However, due to the COVID-19
pandemic and healthcare worker strike, formal SAIA
cycles with oversight from DOHS supervisors were not
completed monthly at all family planning clinics in the
study. Overall, 39% (56/144) of DOHS-led SAIA visits
occurred, and no clinic completed all DOHS-led SAIA
visits (Fig.5). STI and RH coordinators reported at least
one visit to oversee a SAIA cycle at 12 clinics in Q5, 6 in
Q6, 11 in Q7, and 4 in Q8. Due to the nature of this phase
of the research, study staff did not have contact with clin-
ics, and therefore, they were unable to assess the degree
to which clinics in the intervention arm conducted ele-
ments of the SAIA implementation strategy (e.g., imple-
menting micro-interventions) in the months that the
County was not available to oversee visits. Study staff
were also unable to assess if County implementers made
adaptations to the SAIA approach when they conducted
SAIA visits.
Barriers andfacilitators tosustainment
Participants from seven clinics in the intervention arm
took part in the interviews; five intervention arm clin-
ics were unable to participate due to the timing of the
interviews during the COVID-19 pandemic. During
exit interviews, staff at clinics in the intervention arm
provided insight into why they believed their clinics
maintained high levels of HTC despite healthcare inter-
ruptions and inconsistent implementation of SAIA. Insti-
tutionalization of HTC due to the routine use of SAIA
was a common theme in all interviews. Reported barriers
and facilitators of SAIA implementation mapped to the
CFIR constructions of complexity, implementation cli-
mate, and leadership engagement. In addition, emergent
themes were well aligned with recently proposed new
constructs to adapt CFIR to research in low- and middle-
income countries [22]. ese themes included systems
architecture and perceived sustainability.
Several responses from interviewed staff suggested
institutionalization of HTC, which they attribute to the
impact of SAIA. ese responses suggested that HTC
was conducted by all staff within facilities as a part of
Fig. 3 Proportion of eligible family planning clients tested for HIV. HIV testing by quarter for the entire duration of the study. Results from Stage 1
have been previously published [16] and are re-presented here for context. Error bars reflect the standard error. (FP family planning, Int. intervention
arm, Con. control arm)
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Page 10 of 16
Longetal. Implementation Science (2022) 17:70
their regular work stream, and SAIA was viewed as an
ongoing activity to promote continued HTC:
It is everyday work. Now we are doing what is
expected of us. e guidelines say we counsel and
test. Most people [at other facilities] are not doing
that. SAIA helped reach testing targets... We will
continue with SAIA because it helps reach our tar-
gets for the facility. Nurse in-charge, Rural public
clinic
We encourage nowadays all our FP clients to know
their status. Every staff is doing that from [clini-
cal officer] CO to me in the lab. No woman passes
without getting information. ... We know what we
are doing. Even our percent right now, we are high.
We want it that way. Our documentation is all
complete. Any new staff is trained on SAIA. Lab
tech, Peri-urban private clinic
A commonly cited facilitator of maintaining SAIA
was the low complexity of the intervention. While sev-
eral clinics identified early barriers, such as difficulties
in documenting HTC, by the second year of the study
clinic staff expressed that SAIA was easy to conduct.
It is easy. Daily work operations. [We] just did
Fig. 4 Proportion of eligible family planning clients receiving HTC in public versus private clinics. A Proportion of eligible family planning clients at
private health facilities (n=11) receiving pre-test HIV counseling from Q5 to Q8 of the trial in intervention and control clinics. B Proportion of eligible
family planning clients at public health facilities (n=12) receiving pre-test HIV counseling from Q5 to Q8 of the trial in intervention and control
clinics. C Proportion of eligible family planning clients at private health facilities (n=11) tested for HIV from Q5 to Q8 of the trial in intervention
and control clinics. D Proportion of eligible family planning clients at public health facilities (n=12) tested for HIV from Q5 to Q8 of the trial in
intervention and control clinics. Error bars reflect the standard error. (FP family planning, PRR, prevalence rate ratio)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 11 of 16
Longetal. Implementation Science (2022) 17:70
work we’re supposed to do ... When you hear about
SAIA, you think it’s big. It’s not. Just knowing your
work and doing it for better outcomes. Nurse in-
charge, Peri-urban public clinic
Implementation climate was also a facilitator to SAIA
continuation. Most clinic staff discussed a willingness
among staff to conduct SAIA and satisfaction in seeing
positive improvements in HTC as a result.
Staff like it when you see results. e dedication of
staff is amazing. ... We know as a facility we want
to be champions of … SAIA. Lab tech, Peri-urban
private clinic
Staff are dedicated to make SAIA work. Nurse in-
charge, Peri-urban public clinic
For some clinics, this sense of commitment extended
to leader engagement, with clinic leaders reporting their
commitment to SAIA and their involvement to ensure
that all staff are properly trained on SAIA components.
In contrast, lack of strong engagement from leadership
appeared to act as a barrier to sustainability. A clinic that
had low HTC performance during Stage 2 reported:
Staff are ready to work if given the tools. We see no
problem. … Admin needs to put [in] more effort. We
have mentioned about getting [HIV testing] kits but
it takes forever to make decisions. Sister in-charge,
Urban private clinic
An emerging theme was the systems’ architecture,
and the critical role that the Mombasa County DOHS
played in successful implementation. Even among high-
performing clinics, issues with obtaining HIV-testing kits
were prevalent. Testing kits come from the DOHS, and
these findings suggest a systems-level issue with provi-
sion of commodities. Similarly, staff turnover was cited
as a barrier to sustainability. Staff turnover in public
facilities is often a result of DOHS-wide reassignments of
staff, and this makes it difficult to maintain institutional
knowledge of SAIA. However, some aspects of the sys-
tem were seen as facilitators of continuation, particularly
Fig. 5 Schedule of SAIA monthly visits that were completed by the supervising sub-county implementer during Stage 2 follow-up, from February
2020 to January 2021. Green indicates when visits did occur and red indicates that a supervising sub-county STI or RH coordinator did not visit
the clinic. This visit schedule reflects the context in Mombasa County at the time of the study. In February 2020, before any COVID-19 cases were
reported in Kenya, the sub-county Coordinators completed supervised hand-off visits with study staff. In March 2020, the COVID-19 pandemic
reached Kenya, and restrictions were put in place that impacted government-run services. Beginning in July, normal operations returned to a
certain extent, and SAIA supervision visits resumed. However, the healthcare worker go-slow began in October 2020, followed by a full healthcare
worker strike beginning in December 2020 that lasted through the end of the study and resulted in disruption of study activities.
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Page 12 of 16
Longetal. Implementation Science (2022) 17:70
relating to oversight. Sub-county RH and STI coordina-
tors visit the clinics as part of their normal workflow, and
embedding SAIA oversight into this structure was seen
as a motivator by clinic staff:
Frequent supervision will help, especially from
MOH, like they usually do … supervision from [sub-
county RH and STI coordinators] really helped to
keep us on [our] toes. Nurse in-charge, Per-urban
private clinic
Interview responses indicated that at some facilities,
SAIA had become part of routine internal operations,
suggesting clinics were able to sustain at least some com-
ponents of SAIA delivery on their own with occasional
oversight from DOHS implementers:
We meet every month twice and ensure that all our
work including FP clinic and SAIA is meeting objec-
tives. Lab tech, Peri-urban private clinic
Finally, the perceived longer-term sustainability of the
SAIA implementation strategy was apparent in many of
the responses from clinic staff. Due largely to the facilita-
tors described above, staff expressed the belief that SAIA
was effective, easy, and some suggested that it should
even be implemented in other settings or with other
health outcomes. One staff member stated:
e results are good, and we shall continue doing
it even as you say the study is over. Lab tech, Peri-
urban private clinic
Discussion
In Stage 2 of this cluster-randomized controlled trial,
39% of planned DOHS-led SAIA visits occurred, show-
ing moderate ability to sustain supervised SAIA delivery
once it was transitioned to County DOHS leadership
with minimal support from study staff. is result was
influenced by the timing of the study, which was con-
ducted in the context of multiple widespread disruptions
in healthcare and short-term clinic closures resulting
from the COVID-19 pandemic and a healthcare worker
strike. Despite these disruptions, the positive effect of
SAIA on HTC rates in family planning clinics enrolled
in the intervention arm of the trial was sustained dur-
ing implementation by the County DOHS. Clinics in the
intervention arm consistently sustained high levels of
HTC, while control clinics saw declines in both pre-test
counseling and testing.
Integration of HTC into family planning clinics has
been found to be an effective means of reaching women
of childbearing age [3, 4]. A recent systematic review
assessing HTC integration into family planning services
found an overall increase in HIV testing as a result of
integration [3]. In Kenya, a pre-post study in 23 fam-
ily planning clinics reported success in increasing HTC
using a clinic-based implementation strategy targeting
provider training [23]. A later study using a non-rand-
omized comparison design to test a similar implemen-
tation strategy found an increase in HTC at the clinics
implementing the strategy over the course of study fol-
low-up [24]. e results of this two stage trial demon-
strate that SAIA could be an effective and sustainable
means of increasing HIV testing coverage and knowledge
of HIV status among reproductive age women [16].
is study provided valuable insight on the sustain-
ment of the SAIA implementation strategy in the context
of family planning clinics in Mombasa County. While
DOHS implementers only completed 39% of SAIA over-
sight visits, interviews with clinic staff suggest that HTC
remained high in Stage 2 due to HTC becoming a nor-
malized part of clinic visits, and SAIA becoming a rou-
tine activity for some clinics. is suggests successful
institutionalization of HTC, likely resulting from the reg-
ular implementation of SAIA during Stage 1 of the trial.
Institutionalization can occur when the intervention
becomes embedded in a system [12, 14, 25]. While there
are other pathways to sustainment [26], institutionaliza-
tion is an effective means to ensure the continuation of
programs after the initial research or funding stage has
ended. e maintenance of a high level of HTC seen in
our study, as well as the results of the family planning
staff interviews, suggest effective institutionalization. e
patterns observed in pre-test counseling serve as a poten-
tial example of this. While there was a significant drop
off in counseling in the control clinics during the strike,
clinics in the intervention arm maintained their high
counseling rate, suggesting that counseling had become
a routine part of care even when minimal services were
provided.
In addition to the facilitators identified by family
planning staff, such as low complexity and a favorable
implementation climate, structural aspects of the SAIA
implementation strategy and HTC evidence-based inter-
vention were likely important drivers of institutionaliza-
tion. Previous studies have found that institutionalization
is facilitated by permanent funding, repeated reinforce-
ment, and integration into subsystems at the facilities
[12, 14, 25]. Both HTC provision and DOHS oversight
are funded through Mombasa County. Further, the itera-
tive nature of SAIA allowed for repeated reinforcement.
While cost and repetition were not explicitly addressed
in staff interviews, they likely played a role in sustain-
ment of the SAIA implementation strategy and the HTC
that it targeted in this trial.
Interestingly, our results differed significantly between
private and public clinics. At the time of Q8 data
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Page 13 of 16
Longetal. Implementation Science (2022) 17:70
collection, the healthcare worker strike was ongoing,
impacting public clinics but not private ones. A number
of health services offered through public facilities were
interrupted due to the strike, including HIV programs,
family planning services, cervical cancer screening, and
tuberculosis treatment. Within this study, for pre-test
counseling, both public and private clinics saw a decline
in counseling during Q8 among control clinics, while
counseling remained steady at clinics in the interven-
tion arm. is same pattern was observed for HIV test-
ing in private clinics. However, in public clinics, those in
the intervention arm experienced a substantial drop in
HIV testing during Q8, matching the testing rates of the
control clinics. erefore, when clinics were at a reduced
capacity, clinics in which SAIA was an integrated strategy
were able to maintain counseling but not HIV testing.
is could be driven by clinic-level factors (e.g., reduced
capacity to provide testing) or client-level factors (e.g.,
reduced willingness due to longer wait times). Further
research is needed to understand how interruptions
in delivery of implementation strategies and the inter-
ventions that they target, particularly interruptions
resulting from factors outside of the control of the
clinic, may impact institutionalization and long-term
sustainability.
e timing of this study during the COVID-19 pan-
demic and healthcare worker strike provided a natural
experiment of the sustainment of the SAIA implemen-
tation strategy and family planning clinic-based HTC
under increased stress on the healthcare system. Dur-
ing the West African Ebola epidemic in 2014, evidence
from Sierra Leone and Guinea suggested decreases in
HTC, both generally and among women of childbearing
age [27, 28]. Moreover, emerging evidence suggests that
the COVID-19 pandemic has resulted in interruptions to
HIV testing in sub-Saharan Africa [29, 30]. In the present
study, a steep drop in number of new family planning cli-
ents in Q8 led to a small denominator and reduced power
in our sample. However, despite the reduced number of
eligible family planning clients, the proportion of HTC
uptake remained high in clinics in the intervention arm
and starkly contrasted with the drop-off in HTC seen
in control clinics, particularly in HIV counseling. ese
results provide important evidence of the sustainment
of the SAIA implementation strategy and its beneficial
effect on HTC in the context of multiple major health-
care disruptions. e results suggest that a data-driven
approach to systems analysis and improvement may
create greater health systems resilience. Future work is
needed to directly test this hypothesis and to understand
the mechanisms of the effects observed.
In the present study, fidelity was measured as the fre-
quency of SAIA visits led by DOHS staff. One limitation
of this analysis is the lack of more granular measures of
fidelity, such as adherence to each step of SAIA, adapta-
tions made, and reasons for adaptations. Studies in other
contexts provide more detailed insight into SAIA fidelity,
as well as the core components of SAIA and how clinics
may adapt the strategy [7]. e original SAIA trial was
conducted in Mozambique, Kenya, and Cote d’Ivoire to
improve PMTCT of HIV. In these contexts, flow map-
ping and continued quality improvement (CQI) cycles
were considered core components of the intervention,
while the cascade analysis tool was identified in some set-
tings as being overly complex and nonessential in places
with low HIV burden [31]. Similarly, a study that piloted
SAIA to improve the pediatric and adolescent HIV care
cascade in Kenya found that flow mapping and CQI were
compatible with existing workflows, but that the cascade
analysis was difficult to use [32]. Building on these find-
ings, several SAIA studies are providing more detailed
data on fidelity and adaptation to SAIA designs. e
SAIA-SCALE study, testing SAIA for PMTCT services in
Mozambique, measured fidelity through a tablet-based
survey completed by clinic staff to track number of SAIA
cycles, attendants at each cycle meeting, and the number,
content, and results of micro-interventions tested [33].
Two additional studies in Mozambique using SAIA for
hypertension and mental health services assessed fidelity
as number and frequency of SAIA cycles completed [10]
and adherence to the 5-step SAIA cycle [34]. All three
studies then categorized clinics as high or low performing
and used focus group data to assess features of successful
implementation. Results of these studies are forthcoming
and will provide important evidence about adaptations to
SAIA designs in a variety of healthcare settings.
is study had several strengths. e use of a cluster-
randomized trial design provides strong causal evi-
dence of the effectiveness of SAIA. Incorporating both
private and public institutions allowed for compari-
son in different types of facilities. e incorporation
of a second year of data collection to formally test and
measure sustainment of SAIA and HTC was a novel
aspect of this study and allowed for rigorous data col-
lection and a combination of both quantitative and
qualitative metrics to assess these outcomes. Finally,
the timing of this study unintentionally provided the
opportunity to test the sustainment of the SAIA imple-
mentation strategy and performance of HTC in family
planning clinics in the context of widespread healthcare
disruptions, which provided a unique perspective on
sustainability under extraordinary conditions.
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Page 14 of 16
Longetal. Implementation Science (2022) 17:70
e results should be interpreted in light of a num-
ber of limitations. Data on HTC was collected through
registries completed by clinic staff, and the delivery
of HTC was not independently verified by study staff.
Data on the micro-interventions implemented in Stage
2 were not collected, so this could not be analyzed. Our
study design did not include an arm that received SAIA
in Stage 1 but no DOHS oversight in Stage 2, so we are
unable to distinguish how Stage 2 activities impacted
sustainment of high HTC in intervention clinics, versus
the extent to which this would have occurred regardless
of continued SAIA delivery due to institutionalization
of HTC established in Stage 1. While we know when
SAIA visits were completed, we have limited informa-
tion about what was done by County DOHS imple-
menters at the SAIA visits, or if clinics conducted SAIA
activities (meetings, cascade analysis, flow mapping,
and implementation of micro-interventions) in the
absence of County implementers. As discussed above,
this limits our understanding of SAIA fidelity and what
adaptations may have occurred. If SAIA cycles were
implemented with low fidelity to the core SAIA com-
ponents, these unknown adaptations could partially
account for the continued high levels of HTC. However,
both DOHS implementers and the staff in the family
planning clinics were trained in SAIA, and qualitative
responses from family planning clinic staff suggest that
SAIA was well understood and implemented within
clinics. Further, the use of County DOHS implementers
could potentially have led to contamination, as these
same coordinators were visiting and overseeing control
facilities as part of their regular programmatic activi-
ties. Finally, due to the healthcare interruptions, fewer
new family planning clients attended clinics during the
final quarter of analysis, reducing our power to detect
associations.
ere are a number of future directions for this
research. A large scale-up of the SAIA implementation
strategy is planned and will provide important evidence
of whether these results can be replicated at a program-
matic scale. Incorporating data on linkage to care and
ART retention could provide valuable insight into the
ways in which this implementation strategy impacts the
downstream steps of the HIV care cascade and where
further efforts to improve implementation are still
needed. Expanding the SAIA implementation strategy
to also include screening and linkage to pre-exposure
prophylaxis (PrEP) could provide added value toward
HIV prevention. Further research on sustainability, par-
ticularly focused on core components and adaptability,
could provide important evidence on what aspects of the
SAIA implementation strategy are most critical and how
to best integrate them into routine clinical operations.
Conclusions
ese findings show that clinics receiving SAIA sustained
improvements in HTC after one year under DOHS
leadership, even in the context of wide-scale healthcare
disruptions and incomplete maintenance of the imple-
mentation strategy. ese findings demonstrate promis-
ing evidence of the sustainability of systems interventions
and provide an example of successful integration of an
implementation strategy into DOHS programmatic
activities.
Acknowledgements
We would like to thank the Ganjoni clinic staff, the Mombasa County family
planning clinic staff, the Mombasa County sub-county RH and STI coordina-
tors, and all other Mombasa County Department of Health Services staff who
collaborated on this project.
Authors’ contributions
JEL completed all analyses and was the primary author on this manuscript
with significant editing by RSM. RSM, RVB, KS, KM, EM, and WJ conceived of
the study design. MCE, JEL, and GW contributed to study coordination. EM
and MAM provided partnership and implementation support from the Mom-
basa County DOHS. BAR and MCE contributed to data analysis. RSM secured
funding for the study. All authors contributed to study implementation and
approved the final submitted version of the manuscript.
Funding
This research was supported by a grant from the National Institutes of Health/
National Institute for Child Health and Human Development K24-HD88229.
MCE received support through K08-CA228761. The research site has received
infrastructure support from the University of Washington/Fred Hutch Center
for AIDS Research, an NIH-funded program under award number AI027757
which is supported by the following NIH Institutes and Centers: NIAID, NCI,
NIMH, NIDA, NICHD, NHLBI, NIA, NIGMS, and NIDDK. The funders had no role in
study design, data collection and analysis, decision to publish, or preparation
of the manuscript.
Availability of data and materials
This study was conducted with approval from the Kenyatta National
Hospital—University of Nairobi Ethics and Research Committee (KNH-UON
ERC), which requires that we release data from Kenyan studies (including
de-identified data) only after they have provided their written approval for
additional analyses. As such, data for this study will be available from the
authors upon request, with written approval for the proposed analysis from
the KNH/UON ERC. Their application forms and guidelines can be accessed at
http:// erc. uonbi. ac. ke/. To request these data, please contact KRTC administra-
tor at kenya res@ uw. edu
Declarations
Ethics approval and consent to participate
This research was approved by the Kenyatta National Hospital-University
of Nairobi Ethics and Research Committee, the Human Subjects Research
Institutional Review Board at the University of Washington, and the Mombasa
County DOHS. This trial is registered at ClinicalTrials.gov (NCT02994355). All
Mombasa County DOHS implementers verbally agreed to participate in the
trial, and clinic staff and managers who participated in interviews provided
written informed consent prior to COVID-19 and verbal assent for remote
interviews during the pandemic.
Consent for publication
Not applicable.
Competing interests
RSM has received research funding, paid to the University of Washington from
Hologic Corporation. The other authors declare that they have no competing
interests.
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 15 of 16
Longetal. Implementation Science (2022) 17:70
Author details
1 Department of Epidemiology, University of Washington, 325 9th Avenue,
Box 359909, Seattle, WA 98104, USA. 2 Present Address: Department of Medi-
cine, University of Washington, Seattle, WA, USA. 3 Department of Global
Health, University of Washington, Seattle, WA, USA. 4 Department of Biosta-
tistics, University of Washington, Seattle, WA, USA. 5 Fred Hutchinson Cancer
Research Center, Vaccine and Infectious Disease Division, Seattle, WA, USA.
6 Mombasa County Department of Health, Mombasa, Kenya. 7 Industrial &
Systems Engineering, University of Washington, Seattle, WA, USA. 8 Medical
Microbiology, University of Nairobi, Nairobi, Kenya.
Received: 20 December 2021 Accepted: 23 September 2022
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Background Children and adolescents living with HIV have poorer rates of HIV testing, treatment, and virologic suppression than adults. Strategies that use a systems approach to optimize these multiple, linked steps simultaneously are critical to close these gaps. Methods The Systems Analysis and Improvement Approach (SAIA) was adapted and piloted for the pediatric and adolescent HIV care and treatment cascade (SAIA-PEDS) at 6 facilities in Kenya. SAIA-PEDS includes three tools: continuous quality improvement (CQI), flow mapping, and pediatric cascade analysis (PedCAT). A predominately qualitative evaluation utilizing focus group discussions ( N = 6) and in-depth interviews ( N = 19) was conducted with healthcare workers after implementation to identify determinants of implementation. Data collection and analysis were grounded in the Consolidated Framework for Implementation Research (CFIR). Results Overall, the adapted SAIA-PEDS strategy was acceptable, and the three tools complemented one another and provided a relative advantage over existing processes. The flow mapping and CQI tools were compatible with existing workflows and resonated with team priorities and goals while providing a structure for group problem solving that transcended a single department’s focus. The PedCAT was overly complex, making it difficult to use. Leadership and hierarchy were complex determinants. All teams reported supportive leadership, with some describing in detail how their leadership was engaged and enthusiastic about the SAIA-PEDS process, by providing recognition, time, and resources. Hierarchy was similarly complex: in some facilities, leadership stifled rapid innovation by insisting on approving each change, while at other facilities, leadership had strong and supportive oversight of processes, checking on the progress frequently and empowering teams to test innovative ideas. Conclusion CQI and flow mapping were core components of SAIA-PEDS, with high acceptability and consistent use, but the PedCAT was too complex. Leadership and hierarchy had a nuanced role in implementation. Future SAIA-PEDS testing should address PedCAT complexity and further explore the modifiability of leadership engagement to maximize implementation.
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Article
Background Significant investments are being made to close the mental health (MH) treatment gap, which often exceeds 90% in many low- and middle-income countries (LMICs). However, limited attention has been paid to patient quality of care in nascent and evolving LMIC MH systems. In system assessments across sub-Saharan Africa, MH loss-to-follow-up often exceeds 50% and sub-optimal medication adherence often exceeds 60%. This study aims to fill a gap of evidence-based implementation strategies targeting the optimization of MH treatment cascades in LMICs by testing a low-cost multicomponent implementation strategy integrated into routine government MH care in Mozambique. Methods Using a cluster-randomized trial design, 16 clinics (8 intervention and 8 control) providing primary MH care will be randomized to the Systems Analysis and Improvement Approach for Mental Health (SAIA-MH) or an attentional placebo control. SAIA-MH is a multicomponent implementation strategy blending external facilitation, clinical consultation, and provider team meetings with system-engineering tools in an overall continuous quality improvement framework. Following a 6-month baseline period, intervention facilities will implement the SAIA-MH strategy for a 2-year intensive implementation period, followed by a 1-year sustainment phase. Primary outcomes will be the proportion of all patients diagnosed with a MH condition and receiving pharmaceutical-based treatment who achieve functional improvement, adherence to medication, and retention in MH care. The Consolidated Framework for Implementation Research (CFIR) will be used to assess determinants of implementation success. Specific Aim 1b will include the evaluation of mechanisms of the SAIA-MH strategy using longitudinal structural equation modeling as well as specific aim 2 estimating cost and cost-effectiveness of scaling-up SAIA-MH in Mozambique to provincial and national levels. Discussion This study is innovative in being the first, to our knowledge, to test a multicomponent implementation strategy for MH care cascade optimization in LMICs. By design, SAIA-MH is a low-cost strategy to generate contextually relevant solutions to barriers to effective primary MH care, and thus focuses on system improvements that can be sustained over the long term. Since SAIA-MH is integrated into routine government MH service delivery, this pragmatic trial has the potential to inform potential SAIA-MH scale-up in Mozambique and other similar LMICs. Trial registration ClinicalTrials.gov; NCT05103033 ; 11/2/2021.
Full-text available
Article
Objective: To test an implementation strategy, the Systems Analysis and Improvement Approach (SAIA), to increase rates of HIV testing and counseling (HTC) in family planning (FP) clinics in Mombasa, Kenya. Design: Cluster randomized trial. Methods: Twenty-four FP clinics were randomized 1:1 to implementing SAIA versus usual procedures. Study staff implemented monthly SAIA cycles with FP clinic staff for 12 months. SAIA has five steps. Step 1 uses a "cascade analysis" tool to quantify the number of individuals who complete each step of a process. Step 2 involves sequential process flow mapping to identify modifiable bottlenecks in the system. Step 3 develops and implements workflow modifications to address bottlenecks. Step 4 assesses impact of the modification by recalculating the cascade analysis. Step 5 repeats the cycle. The primary outcome was the proportion of new FP clients tested for HIV during the last quarter of the trial. Results: During the last three months of the trial, 85% (740/868) of new FP clients were counseled for HIV in intervention clinics compared to 67% (1036/1542) in control clinics (prevalence rate ratio [PRR] 1.27, 95% confidence interval [CI] 1.15-1.30). Forty-two percent (364/859) of FP clients were tested for HIV at intervention clinics compared to 32% (485/1521) at control clinics (PRR 1.33, 95%CI 1.16-1.52). Conclusion: SAIA led to a significant increase in HIV testing in FP clinics in Mombasa. Integrating routine HTC into FP clinics is a promising strategy to achieve the UNAIDS goal of 95% of people living with HIV being aware of their status.
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Background The effect of the COVID-19 pandemic on HIV outcomes in low-income and middle-income countries is poorly described. We aimed to measure the impact of the 2020 national COVID-19 lockdown on HIV testing and treatment in KwaZulu-Natal, South Africa, where 1·7 million people are living with HIV. Methods In this interrupted time series analysis, we analysed anonymised programmatic data from 65 primary care clinics in KwaZulu-Natal province, South Africa. We included data from people testing for HIV, initiating antiretroviral therapy (ART), and collecting ART at participating clinics during the study period, with no age restrictions. We used descriptive statistics to summarise demographic and clinical data, and present crude summaries of the main outcomes of numbers of HIV tests per month, ART initiations per week, and ART collection visits per week, before and after the national lockdown that began on March 27, 2020. We used Poisson segmented regression models to estimate the immediate impact of the lockdown on these outcomes, as well as post-lockdown trends. Findings Between Jan 1, 2018, and July 31, 2020, we recorded 1 315 439 HIV tests. Between Jan 1, 2018, and June 15, 2020, we recorded 71 142 ART initiations and 2 319 992 ART collection visits. We recorded a median of 41 926 HIV tests per month before lockdown (January, 2018, to March, 2020; IQR 37 838–51 069) and a median of 38 911 HIV tests per month after lockdown (April, 2020, to July, 2020; IQR 32 699–42 756). In the Poisson regression model, taking into account long-term trends, lockdown was associated with an estimated 47·6% decrease in HIV testing in April, 2020 (incidence rate ratio [IRR] 0·524, 95% CI 0·446–0·615). ART initiations decreased from a median of 571 per week before lockdown (IQR 498–678), to 375 per week after lockdown (331–399), with an estimated 46·2% decrease in the Poisson regression model in the first week of lockdown (March 30, 2020, to April 5, 2020; IRR 0·538, 0·459–0·630). There was no marked change in the number of ART collection visits (median 18 519 visits per week before lockdown [IQR 17 074–19 922] vs 17 863 visits per week after lockdown [17 509–18 995]; estimated effect in the first week of lockdown IRR 0·932, 95% CI 0·794–1·093). As restrictions eased, HIV testing and ART initiations gradually improved towards pre-lockdown levels (slope change 1·183/month, 95% CI 1·113–1·256 for HIV testing; 1·156/month, 1·085–1·230 for ART initiations). Interpretation ART provision was generally maintained during the 2020 COVID-19 lockdown, but HIV testing and ART initiations were heavily impacted. Strategies to increase testing and treatment initiation should be implemented.
Full-text available
Article
Substantial investments are being made to scale-up access to mental healthcare in low- and middle-income countries, but less attention has been paid to quality and performance of nascent public-sector mental healthcare systems. This study tested the initial effectiveness of an implementation strategy to optimize routine outpatient mental healthcare cascade performance in Mozambique [the Systems Analysis and Improvement Approach for Mental Health (SAIA-MH)]. This study employed a pre–post design from September 2018 to August 2019 across four Ministry of Health clinics among 810 patients and 3234 outpatient mental health visits. Effectiveness outcomes evaluated progression through the care cascade, including: (1) initial diagnosis and medication selection; (2) enrolling in follow-up care; (3) returning after initial consultation within 60 days; (4) returning for follow-up visits on time; (5) returning for follow-up visits adherent to medication and (6) achieving function improvement. Clustered generalized linear models evaluated odds of completing cascade steps pre- vs post-intervention. Facilities prioritized improvements focused on the follow-up cascade, with 62.5% (10 of 16) monthly system modifications targeting medication adherence. At baseline, only 4.2% of patient visits achieved function improvement; during the 6 months of SAIA-MH implementation, this improved to 13.1% of patient visits. Multilevel logistic regression found increased odds of returning on time and adherent [aOR = 1.53, 95% CI (1.21, 1.94), P = 0.0004] and returning on time, adherent and with function improvement [aOR = 3.68, 95% CI (2.57, 5.44), P < 0.0001] after SAIA-MH implementation. No significant differences were observed regarding other cascade steps. The SAIA-MH implementation strategy shows promise for rapidly and significantly improving mental healthcare cascade outcomes, including the ultimate goal of patient function improvement. Given poor baseline mental healthcare cascade performance, there is an urgent need for evidence-based implementation strategies to optimize the performance of mental healthcare cascades in low- and middle-income countries.
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Background: The Consolidated Framework for Implementation Research (CFIR) is a determinants framework that may require adaptation or contextualization to fit the needs of implementation scientists in low- and middle-income countries (LMICs). The purpose of this review is to characterize how the CFIR has been applied in LMIC contexts, to evaluate the utility of specific constructs to global implementation science research, and to identify opportunities to refine the CFIR to optimize utility in LMIC settings. Methods: A systematic literature review was performed to evaluate the use of the CFIR in LMICs. Citation searches were conducted in Medline, CINAHL, PsycINFO, CINAHL, SCOPUS, and Web of Science. Data abstraction included study location, study design, phase of implementation, manner of implementation (ex., data analysis), domains and constructs used, and justifications for use, among other variables. A standardized questionnaire was sent to the corresponding authors of included studies to determine which CFIR domains and constructs authors found to be compatible with use in LMICs and to solicit feedback regarding ways in which CFIR performance could be improved for use in LMICs. Results: Our database search yielded 504 articles, of which 34 met final inclusion criteria. The studies took place across 21 countries and focused on 18 different health topics. The studies primarily used qualitative study designs (68%). Over half (59%) of the studies applied the CFIR at study endline, primarily to guide data analysis or to contextualize study findings. Nineteen (59%) of the contacted authors participated in the survey. Authors unanimously identified culture and engaging as compatible with use in global implementation research. Only two constructs, patient needs and resources and individual stages of change were commonly identified as incompatible with use. Author feedback centered on team level influences on implementation, as well as systems characteristics, such as health system architecture. We propose a "Characteristics of Systems" domain and eleven novel constructs be added to the CFIR to increase its compatibility for use in LMICs. Conclusions: These additions provide global implementation science practitioners opportunities to account for systems-level determinants operating independently of the implementing organization. Newly proposed constructs require further reliability and validity assessments. Trial registration: PROSPERO, CRD42018095762.
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Article
Background: Across sub-Saharan Africa, evidence-based clinical guidelines to screen and manage hypertension exist; however, country level application is low due to lack of service readiness, uneven health worker motivation, weak accountability of health worker performance, and poor integration of hypertension screening and management with chronic care services. The systems analysis and improvement approach (SAIA) is an evidence-based implementation strategy that combines systems engineering tools into a five-step, facility-level package to improve understanding of gaps (cascade analysis), guide identification and prioritization of low-cost workflow modifications (process mapping), and iteratively test and redesign these modifications (continuous quality improvement). As hypertension screening and management are integrated into chronic care services in sub-Saharan Africa, an opportunity exists to test whether SAIA interventions shown to be effective in improving efficiency and coverage of HIV services can be effective when applied to the non-communicable disease services that leverage the same platform. We hypothesize that SAIA-hypertension (SAIA-HTN) will be effective as an adaptable, scalable model for broad implementation. Methods: We will deploy a hybrid type III cluster randomized trial to evaluate the impact of SAIA-HTN on hypertension management in eight intervention and eight control facilities in central Mozambique. Effectiveness outcomes include hypertension cascade flow measures (screening, diagnosis, management, control), as well as hypertension and HIV clinical outcomes among people living with HIV. Cost-effectiveness will be estimated as the incremental costs per additional patient passing through the hypertension cascade steps and the cost per additional disability-adjusted life year averted, from the payer perspective (Ministry of Health). SAIA-HTN implementation fidelity will be measured, and the Consolidated Framework for Implementation Research will guide qualitative evaluation of the implementation process in high- and low-performing facilities to identify determinants of intervention success and failure, and define core and adaptable components of the SAIA-HTN intervention. The Organizational Readiness for Implementing Change scale will measure facility-level readiness for adopting SAIA-HTN. Discussion: SAIA packages user-friendly systems engineering tools to guide decision-making by front-line health workers to identify low-cost, contextually appropriate chronic care improvement strategies. By integrating SAIA into routine hypertension screening and management structures, this pragmatic trial is designed to test a model for national scale-up. Trial registration: ClinicalTrials.gov NCT04088656 (registered 09/13/2019; https://clinicaltrials.gov/ct2/show/NCT04088656).
Full-text available
Article
Background: Cascades have been used to characterize sequential steps within a complex health system and are used in diverse disease areas and across prevention, testing, and treatment. Routine data have great potential to inform prioritization within a system, but are often inaccessible to frontline health care workers (HCWs) who may have the greatest opportunity to innovate health system improvement. Methods: The cascade analysis tool (CAT) is an Excel-based, simple simulation model with an optimization function. It identifies the step within a cascade that could most improve the system. The original CAT was developed for HIV treatment and the prevention of mother-to-child transmission of HIV. Results: CAT has been adapted 7 times: to a mobile application for prevention of mother-to-child transmission; for hypertension screening and management and for mental health outpatient services in Mozambique; for pediatric and adolescent HIV testing and treatment, HIV testing in family planning, and cervical cancer screening and treatment in Kenya; and for naloxone distribution and opioid overdose reversal in the United States. The main domains of adaptation have been technical-estimating denominators and structuring steps to be binary sequential steps-as well as logistical-identifying acceptable approaches for data abstraction and aggregation, and not overburdening HCW. Discussion: CAT allows for prompt feedback to HCWs, increases HCW autonomy, and allows managers to allocate resources and time in an equitable manner. CAT is an effective, feasible, and acceptable implementation strategy to prioritize areas most requiring improvement within complex health systems, although adaptations are being currently evaluated.
Full-text available
Article
Background: A high proportion of African women utilize family planning (FP) services. Accordingly, incorporating HIV testing into FP services may strategically target the first WHO 90-90-90 goal of 90% of people living with HIV knowing their status. Methods: The objective of this analysis was to determine the proportion of new FP clients counseled and tested for HIV, as well as correlates of HIV testing, in a random sample of 58 FP clinics in Mombasa County, Kenya. Structured interviews of FP clinic managers collected data on characteristics of FP clinics and staff. Study staff performed a 3-month review of FP registers, summarizing new client HIV testing and counseling (HTC). Because overall rates of HTC were quite low, a binary variable was created comparing clinics performing any HIV counseling and/or testing to clinics performing none. Generalized linear models were used to calculate prevalence ratios (PR) and identify correlates of HTC. Factors associated with any HTC with a p-value < 0.10 in univariate analysis were included in a multivariate analysis. Results: Of the 58 FP clinics, 26 (45%) performed any counseling for HIV testing, and 23 (40%) performed any HIV testing. Counseling for HIV testing was conducted for 815/4389 (19%) new clients, and HIV testing was performed for 420/4389 (10%). Clinics without trained HIV testing providers uniformly did not conduct HIV counseling and/or testing (0/12 [0%]), while 27/46 (59%) of clinics with ≥1 provider performed some HTC (p < 0.001). In the subset of 46 clinics with ≥1 trained HIV testing provider, correlates of performing HTC included being a public versus non-public clinic (PR 1.70 95%CI 1.01-2.88), and having an HIV comprehensive care center (CCC) onsite (PR 2.05, 95%CI 1.04-4.06). Conclusion: Trained HIV testing providers are crucial for FP clinics to perform any HTC. Approaches are needed to increase routine HTC in FP clinics including staffing changes and/or linkages with other testing services (in standalone VCT services or lab facilities) in order to improve the implementation of existing national guidelines. A future cluster randomized trial is planned to test an implementation strategy, the Systems Analysis and Improvement Approach (SAIA) to increase HTC in FP clinics.