Systems Analysis and Improvement Approach Archives

✪ Systems analysis and improvement to optimize opioid use disorder care quality and continuity for patients exiting jail (SAIA-MOUD)

Abstract:

Background

Between 2012–2022 opioid-related overdose deaths in the United States, including Washington State, have risen dramatically. Opioid use disorder (OUD) is a complex, chronic, and criminalized illness with biological, environmental, and social causes. One-fifth of people with OUD have recent criminal-legal system involvement; > 50% pass through WA jails annually.

Medications for Opioid Use Disorder (MOUD) can effectively treat OUD. WA has prioritized improving access to MOUD, including for those in jails. As patients in jail settings are systematically marginalized due to incarceration, it is critical to foster connections to MOUD services upon release, an acknowledged period of high overdose risk. Currently, there is insufficient focus on developing strategies to foster linkages between jail-based MOUD and referral services.

The Systems Analysis and Improvement Approach (SAIA), an evidence-based implementation strategy, may optimize complex care cascades like MOUD provision and improve linkages between jail- and community-based providers. SAIA bundles systems engineering tools into an iterative process to guide care teams to visualize cascade drop-offs and prioritize steps for improvement; identify modifiable organization-level bottlenecks; and propose, implement, and evaluate modifications to overall cascade performance. The SAIA-MOUD study aims to strengthen the quality and continuity of MOUD care across jail and referral clinics in King County, WA, and ultimately reduce recidivism and mortality.

Methods

We will conduct a quasi-experimental evaluation of SAIA effectiveness on improving MOUD care cascade quality and continuity for patients receiving care in jail and exiting to referral clinics; examine determinants of SAIA-MOUD adoption, implementation, and sustainment; and determine SAIA-MOUD’s cost and cost-effectiveness. Clinic teams with study team support will deliver the SAIA-MOUD intervention at the jail-based MOUD program and three referral clinics over a two-year intensive phase, followed by a one-year sustainment phase where SAIA implementation will be led by King County Jail MOUD staff without study support to enable pragmatic evaluation of sustained implementation.

Discussion

SAIA packages user-friendly systems engineering tools to guide decision-making by front-line care providers to identify low-cost, contextually appropriate health care improvement strategies. By integrating SAIA into MOUD care provision in jail and linked services, this pragmatic trial is designed to test a model for national scale-up.

Trial registration

ClinicalTrials.gov NCT06593353 (registered 09/06/2024).

Contributions to the literature

Our study examines whether the introduction of an evidence-based, user-friendly, low-cost package of systems engineering tools can optimize investments in providing medications for opioid use disorder for individuals during the high-risk period immediately after exiting jail.
This is the first application of the Systems Analysis and Improvement Approach (SAIA) across health system levels to optimize both care delivery and continuity of care.
Our study is designed to provide decision-makers with evidence they need to decide whether to invest in systems engineering approaches during the expansion of MOUD in jail settings, including information on acceptability, feasibility, effectiveness and cost.

^{**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**}

Peer Review reports

✪ Systems analysis and improvement approach to optimize tuberculosis (SAIA-TB) screening, treatment, and prevention in South Africa: a stepped-wedge cluster randomized trial

Abstract:

Background

The use of systems engineering tools, including the development and use of care cascades using routinely collected data, process mapping, and continuous quality improvement, is used for frontline healthcare workers to devise systems level change. South Africa experiences high rates of tuberculosis (TB) infection and disease as well as HIV co-infection. The Department of Health has made significant gains in HIV services over the last two decades, reaching their set “90–90-90” targets for HIV. However, TB services, although robust, have lagged in comparison for both disease and infection. The Systems Analysis and Improvement Approach (SAIA) is a five-step implementation science method, drawn from systems engineering, to identify, define, and implement workflow modifications using cascade analysis, process mapping, and repeated quality improvement cycles within healthcare facilities.

Methods

This stepped-wedge cluster randomized trial will evaluate the effectiveness of SAIA on TB (SAIA-TB) cascade optimization for patients with TB and high-risk contacts across 16 clinics in four local municipalities in the Sarah Baartman district, Eastern Cape, South Africa. We hypothesize that SAIA-TB implementation will lead to a 20% increase in each of: TB screening, TB preventive treatment initiation, and TB disease treatment initiation during the 18-month intervention period. Focus group discussions and key informant interviews with clinic staff will also be conducted to determine drivers of implementation variability across clinics.

Discussion

This study has the potential to improve TB screening, treatment initiation, and completion for both active disease and preventive measures among individuals with and without HIV in a high burden setting. SAIA-TB provides frontline health care workers with a systems-level view of their care delivery system with the aim of sustainable systems-level improvements.

Trial registration

Clinicaltrials.gov, NCT06314386. Registered 18 March 2024, https://clinicaltrials.gov/study/NCT06314386. NCT06314386.

^{**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**}

✪ A structured approach to applying systems analysis methods for examining implementation mechanisms

Abstract:

Background

It is challenging to identify and understand the specific mechanisms through which an implementation strategy affects implementation outcomes, as implementation happens in the context of complex, multi-level systems. These systems and the mechanisms within each level have their own dynamic environments that change frequently. For instance, sequencing may matter in that a mechanism may only be activated indirectly by a strategy through another mechanism. The dosage or strength of a mechanism may vary over time or across different health care system levels. To elucidate the mechanisms relevant to successful implementation amidst this complexity, systems analysis methods are needed to model and manage complexity.

Methods

The fields of systems engineering and systems science offer methods—which we refer to as systems analysis methods—to help explain the interdependent relationships between and within systems, as well as dynamic changes to systems over time. When applied to studying implementation mechanisms, systems analysis methods can help (i) better identify and manage unknown conditions that may or may not activate mechanisms (both expected mechanisms targeted by a strategy and unexpected mechanisms that the methods help detect) and (ii) flexibly guide strategy adaptations to address contextual influences that emerge after the strategy is selected and used.

Results

In this paper, we delineate a structured approach to applying systems analysis methods for examining implementation mechanisms. The approach includes explicit steps for selecting, tailoring, and evaluating an implementation strategy regarding the mechanisms that the strategy is initially hypothesized to activate, as well as additional mechanisms that are identified through the steps. We illustrate the approach using a case example. We then discuss the strengths and limitations of this approach, as well as when these steps might be most appropriate, and suggest work to further the contributions of systems analysis methods to implementation mechanisms research.

Conclusions

Our approach to applying systems analysis methods can encourage more mechanisms research efforts to consider these methods and in turn fuel both (i) rigorous comparisons of these methods to alternative mechanisms research approaches and (ii) an active discourse across the field to better delineate when these methods are appropriate for advancing mechanisms-related knowledge.

^{**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**}

✪ Assessing drivers of implementing “Scaling-up the Systems Analysis and Improvement Approach” for Prevention of Mother-to-Child HIV Transmission in Mozambique (SAIA-SCALE) over implementation waves

Authors:

Celso Inguane, Sarah Gimbel, Caroline Soi, Esperança Tavede, Filipe Murgorgo, Xavier Isidoro, Yaesh Sidat, Regina Nassiaca, Joana Coutinho, Maria Cruz, Mery Agostinho, Fernando Amaral, Aneth Dinis, Kristjana Ásbjörnsdóttir, Jonny Crocker, Nélia Manaca, Isaias Ramiro, James Pfeiffer, Maria de Fátima Cuembelo, & Kenneth Sherr

^{University of Washington affiliated authors are displayed in bold.}

✪ Open Access

Published: July 2023

Read the full text in the open access journal Implementation Science Communication

Abstract:

Background

The Systems Analysis and Improvement Approach (SAIA) is an evidence-based package of systems engineering tools originally designed to improve patient flow through the prevention of Mother-to-Child transmission of HIV (PMTCT) cascade. SAIA is a potentially scalable model for maximizing the benefits of universal antiretroviral therapy (ART) for mothers and their babies. SAIA-SCALE was a stepped wedge trial implemented in Manica Province, Mozambique, to evaluate SAIA’s effectiveness when led by district health managers, rather than by study nurses. We present the results of a qualitative assessment of implementation determinants of the SAIA-SCALE strategy during two intensive and one maintenance phases.

Methods

We used an extended case study design that embedded the Consolidated Framework for Implementation Research (CFIR) to guide data collection, analysis, and interpretation. From March 2019 to April 2020, we conducted in-depth individual interviews (IDIs) and focus group discussions (FGDs) with district managers, health facility maternal and child health (MCH) managers, and frontline nurses at 21 health facilities and seven districts of Manica Province (Chimoio, Báruè, Gondola, Macate, Manica, Sussundenga, and Vanduzi).

Results

We included 85 participants: 50 through IDIs and 35 from three FGDs. Most study participants were women (98%), frontline nurses (49.4%), and MCH health facility managers (32.5%). An identified facilitator of successful intervention implementation (regardless of intervention phase) was related to SAIA’s compatibility with organizational structures, processes, and priorities of Mozambique’s health system at the district and health facility levels. Identified barriers to successful implementation included (a) inadequate health facility and road infrastructure preventing mothers from accessing MCH/PMTCT services at study health facilities and preventing nurses from dedicating time to improving service provision, and (b) challenges in managing intervention funds.

Conclusions

The SAIA-SCALE qualitative evaluation suggests that the scalability of SAIA for PMTCT is enhanced by its fit within organizational structures, processes, and priorities at the primary level of healthcare delivery and health system management in Mozambique. Barriers to implementation that impact the scalability of SAIA include district-level financial management capabilities and lack of infrastructure at the health facility level. SAIA cannot be successfully scaled up to adequately address PMTCT needs without leveraging central-level resources and priorities.

Trial registration

ClinicalTrials.gov, NCT03425136. Registered on 02/06/2018.

^{**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**}

✪ A Conceptual Framework for Group Well-Child Care: A Tool to Guide Implementation, Evaluation, and Research

Abstract:

Objective

To use scoping review methods to construct a conceptual framework based on current evidence of group well-child care to guide future practice and research.

Methods

We conducted a scoping review using Arksey and O’Malley’s (2005) six stages. We used constructs from the Consolidated Framework for Implementation Research and the quadruple aim of health care improvement to guide the construction of the conceptual framework.

Results

The resulting conceptual framework is a synthesis of the key concepts of group well-child care, beginning with a call for a system redesign of well-child care to improve outcomes while acknowledging the theoretical antecedents structuring the rationale that supports the model. Inputs of group well-child care include health systems contexts; administration/logistics; clinical setting; group care clinic team; community/patient population; and curriculum development and training. The core components of group well-child care included structure (e.g., group size, facilitators), content (e.g., health assessments, service linkages). and process (e.g., interactive learning and community building). We found clinical outcomes in all four dimensions of the quadruple aim of healthcare.

Conclusion

Our conceptual framework can guide model implementation and identifies several outcomes that can be used to harmonize model evaluation and research. Future research and practice can use the conceptual framework as a tool to standardize model implementation and evaluation and generate evidence to inform future healthcare policy and practice.

Significance

What is already known on this subject? Group well-child care (GWCC) is associated with improved healthcare utilization (e.g., attendance, immunization rates), parent outcomes (e.g., psychological well-being, satisfaction), and clinician outcomes (e.g., self-efficacy).

What this study adds? Scoping review methodology was used to generate a conceptual framework of GWCC which can be used as a guide to standardize practices for implementation, evaluation, and research in GWCC.

^{**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**}

✪ 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

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 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.

^{**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**}

Optimizing treatment cascades for mental healthcare in Mozambique: Preliminary effectiveness of the Systems Analysis and Improvement Approach for Mental Health (SAIA-MH)

Cascade Analysis: An Adaptable Implementation Strategy Across HIV and Non-HIV Delivery Platforms

Anjuli D. Wagner, Sarah Gimbel, Kristjana H. Ásbjörnsdóttir, Peter Cherutich, Joana Coutinho, Jonny Crocker, Emiliae Cruz, Fatima Cuembelo, Vasco Cumbe, McKenna Eastment, Jennifer Einberg, Florencia Floriano, Douglas Gaitho, Brandon L. Guthrie, Grace John-Stewart, Alex H. Kral, Barrot H. Lambdin, Shan Liu, Martin Bcom Maina, Nelia Manaca, Mika Matsuzaki, Loris Mattox, Nancy Mburu, R. Scott McClelland, Mark A. Micek, Ana Olga Mocumbi, Albertoe Muanido, Ruth Nduati, Irene N. Njuguna, Geoffrey Oluoch, Laura B. Oyiengo, Keshet Ronen, Caroline Soi, Bradley H. Wagenaar, George Wanje, Lynn D. Wenger, and Kenneth Sherr

^{University of Washington affiliated authors are displayed in bold.}

Published: December 2019

Authors:

✪ Open Access

Read the full text in the open access journal Implementation Science

Abstract:

Background

Methods

Discussion

Trial registration

Contributions to the literature

Authors:

✪ Open Access

Read the full text in the open access journal Implementation Science Communication

Abstract:

Background

Methods

Discussion

Trial registration

Authors:

✪ Open Access

Read the full text in the open access journal Implementation Science Communication

Abstract:

Background

Methods

Results

Conclusions

Authors:

✪ Open Access

Read the full text in the open access journal Implementation Science Communication

Abstract:

Background

Methods

Results

Conclusions

Trial registration

Authors:

✪ Open Access

Read the full text in the open access Maternal and Child Health Journal

Abstract:

Objective

Methods

Results

Conclusion

Significance

Authors:

✪ Open Access

Read the full text in the open access journal Implementation Science

Abstract:

Background

Methods

Results

Conclusions

Trial registration

Authors:

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Read the full text in the subscription access journal Current HIV/AIDS Reports