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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; Keywords: Systems analysis and improvement approach (SAIA), Hypertension, CFIR, ORIC, Process mapping, Cascade analysis, Continuous quality improvement, Implementation science, Systems engineering, HIV

Objective The diagnosis and treatment rates for hepatitis C virus (HCV) remain below target levels. This study aims to define and analyze the HCV care cascade for surgical patients in a high-prevalence region, evaluate the impact of a hospital-wide elimination program, and identify barriers and facilitators to completing the diagnostic pathway. Methods This retrospective cohort study analyzed de-identified electronic health records from 114,968 consecutive preoperative patients undergoing routine Hepatitis C virus (HCV) antibody screening at a tertiary academic medical center between January 2021 and December 2024. We evaluated the effectiveness of a multifaceted HCV elimination program initiated in 2022 by assessing patient management through a predefined three-step care cascade: (1) universal anti-HCV antibody screening; (2) HCV RNA testing within 72 h for antibody-positive individuals; and (3) prompt hepatology referral within the patient’s hospitalization for RNA-positive cases. Data on patient demographics, clinical department, HCV antibody results, HCV RNA testing completion status, and key clinical variables (emergency surgery, transfusion history, dialysis, length of stay, physician practice duration) were extracted from standardized electronic health records. Data accuracy was verified via a manual audit of 200 randomly selected records. Continuous variables were summarized as mean ± standard deviation (SD) and categorical variables as counts (percentages). Group comparisons were performed using Pearson’s χ2 or Fisher’s exact tests. A multivariable binary logistic regression model with backward stepwise selection was employed to identify independent predictors of HCV RNA testing completion, and the Hosmer-Lemeshow test was used to assess model goodness-of-fit. Results were reported as adjusted odds ratios (aORs) with 95% confidence intervals (CIs). A two-tailed P-value < 0.05 was considered statistically significant. A post-hoc power analysis confirmed the study was sufficiently powered (> 80%) for its primary outcomes. Results Among 114,968 patients, the overall anti-HCV positivity rate was 2.03% (95% CI: 1.95–2.11; n  = 2,334), with significant demographic disparities: males had a 1.48-fold higher positive rate than females (2.45% vs. 1.63%, P  < 0.001). The prevalence of hepatitis C antibodies exhibited a nonlinear positive correlation with age distribution, with infection rates rising significantly after the age of 30. The 70–79 age group presented an 11.74-fold greater prevalence than patients aged 40–49 years (3.64% vs. 0.31%, P  < 0.001). Significant gaps were observed in the care cascade, with only 33.6% of anti-HCV positive patients completing RNA confirmation. There were notable interdepartmental disparities: Hepatobiliary Surgery had the highest anti-HCV positivity rate (7.90%), whereas Pediatric (0.04%) and Obstetric (0.26%) departments had the lowest. Multivariate logistic regression identified key factors associated with testing completion. A hospital stay of ≤ 7 days was the strongest barrier (aOR = 0.48, 95% CI: 0.39–0.60; P  < 0.001). Conversely, receipt of dialysis was the strongest facilitator (aOR = 8.69, 95% CI: 3.83–19.76; P  < 0.001), followed by admission to an HCV-related department (aOR = 2.18, 95% CI: 1.75–2.71; P  < 0.001) and history of blood transfusion (aOR = 1.82, 95% CI: 1.20–2.76; P  = 0.005). Physicians with < 5 years (aOR = 1.60, 95% CI: 1.27–2.01; P  < 0.001) or 5–10 years of experience (aOR = 1.71, 95% CI: 1.35–2.18; P  < 0.001) were more likely to order testing than those with > 10 years of experience. The model demonstrated good discriminative ability, with an overall correct classification rate of 69.6%. Conclusion This study identifies a critical breakdown in the hepatitis C virus (HCV) care cascade at our institution, where a substantial “diagnostic gap” resulted in only 33.63% of anti-HCV positive patients receiving confirmatory RNA testing. The high seroprevalence (2.03%) in our pre-operative cohort, particularly among males and the elderly (peaking at 3.64% in the 70–79 age group), underscores the need for targeted screening. The primary barrier was identified as a fundamental incompatibility between the two-step diagnostic process and clinical workflows, with short hospital stays (≤ 7 days) being the strongest negative predictor. This systemic failure, observed across various non-hepatology departments, contrasts sharply with high performance in settings like Nephrology (87.80% testing rate) and mirrors challenges reported globally. Conversely, downstream linkage to care proved successful, with hepatology referral rates rising to 66.67% in 2024, demonstrating the effectiveness of structured, technology-driven interventions like electronic referral systems. These findings advocate for fundamental system-level reforms, including the implementation of reflex RNA testing, intelligent EMR alert systems, and performance-linked quality metrics, to bridge the diagnostic gap and advance progress towards HCV elimination goals.

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; https://register.clinicaltrials.gov/prs/beta/studies/S000EVJR00000029/recordSummary ).

With population aging, the burden of tuberculosis (TB) among the elderly is rising. Older adults are at high risk of TB but susceptible to poor TB care. In this study, we enrolled TB patients aged over 60 years registered in Shanghai during 2019-2021. A seven-step care cascade from estimated TB burden in the community to treatment outcomes was constructed to quantify retention and attrition at each step of TB health service. Patient pathway analysis was carried out in two districts of Shanghai to describe patients' care-seeking behaviors, service coverage, and diagnosis delays. Across the care cascade, the largest gaps occurred from symptom onset to care seeking (11.3%) and from treatment initiation to completion (10.7%). Male sex, older age, and mycobacterium tuberculosis positivity were associated with treatment discontinuation and unfavorable outcomes. The patient pathway analysis revealed that first contact at lower-level or non-TB-designated hospitals was associated with more complex pathways and May contribute to diagnostic delays. These findings highlight the need to promote proactive care seeking upon symptoms, strengthen targeted adherence support for older people, and improve diagnostic capacity and referral efficiency at lower-level health facilities.

The ongoing endeavors to uncover the link between the prevalent errors in clinical endodontic training and undergraduate education are founded on tentative assumptions. This investigation was aimed at determining if cascade analysis can provide an understanding of the origins and causes of errors and if the sensitivity of student reports to the impact of errors on treatment outcomes can be established.In 2021, a group of investigators from the endodontics department concerned with clinical dental education launched the Study of Endodontic Errors (SEE). Sixty-six undergraduate dental students at one dental teaching hospital submitted anonymous narratives of problems they witnessed in their root canal treatment practices. The reports were examined to determine the sequence of events and the major errors. We kept track of the consequences of treatment outcomes, both as reported by students and as deduced by investigators.In 77% of the narratives, a chain of errors was recorded. The majority of the errors that took place were related to the working length or width of root canals. A substantial portion, 86%, of these errors could have been prevented through a deeper comprehension of the concepts that underlie working length and width. 75% of the errors that initiated cascades involved losing the correct working length. When asked whether the treatment outcome was compromised, students answered affirmatively in 16% of cases in which their narratives described compromised outcomes. Unacceptable outcomes necessitating re-treatment accounted for only 3% of student-reported consequences, but when investigator-inferred consequences were considered, the percentage more than doubled (7%).Cascade analysis of student error narratives is useful in understanding the triggering chain of events, but students provide insufficient information about how treatment outcomes are affected. Misconceptions about working length and width appear to play a significant role in the propagation of procedural errors.

Research and development on integrated energy systems such as cogeneration and trigeneration to improve the efficiency of thermal energy as well as fuel utilisation have been a key focus of attention by researchers. Total Site Utility Integration is an established methodology for the synergy and integration of utility recovery among multiple processes. However, Total Site Cooling, Heating and Power (TSCHP) integration methods involving trigeneration systems for industrial plants have been much less emphasised. This paper proposes a novel methodology for developing an insight-based numerical Pinch Analysis technique to simultaneously target the minimum cooling, heating and power requirements for a total site energy system. It enables the design of an integrated centralised trigeneration system involving several industrial sites generating the same utilities. The new method is called the Trigeneration System Cascade Analysis (TriGenSCA). The procedure for TriGenSCA involves data extraction, constructions of a Problem Table Algorithm (PTA), Multiple Utility Problem Table Algorithm (MU PTA), Total Site Problem Table Algorithm (TS PTA) and estimation of energy sources by a trigeneration system followed by construction of TriGenSCA, Trigeneration Storage Cascade Table (TriGenSCT) and construction of a Total Site Utility Distribution (TSUD) Table. The TriGenSCA tool is vital for users to determine the optimal size of utilities for generating power, heating and cooling in a trigeneration power plant. Based on the case study, the base fuel source for power, heating and cooling is nuclear energy with a demand load of 72 GWh/d supplied by 10.8 t of Uranium-235. Comparison between conventional PWR producing power, heating and cooling seperately, and trigeneration PWR system with and without integration have been made. The results prove that PWR as a trigeneration system is the most cost-effective, enabling 28% and 17% energy savings as compared to conventional PWR producing power, heating and cooling separately.

The energy and power sectors are critical sectors, especially as energy demands rise every year. Increasing energy demand will lead to an increase in fuel consumption and CO2 emissions. Improving the thermal efficiency of conventional power systems is one way to reduce fuel consumption and carbon emissions. The previous study has developed a new methodology called Trigeneration System Cascade Analysis (TriGenSCA) to optimise the sizing of power, heating, and cooling in a trigeneration system for a Total Site system. However, the method only considered a single period on heating and cooling demands. In industrial applications, there are also batches, apart from continuous plants. The multi-period is added in the analysis to meet the time constraints in batch plants. This paper proposes the development of an optimal trigeneration system based on the Pinch Analysis (PA) methodology by minimizing cooling, heating, and power requirements, taking into account energy variations in the total site energy system. The procedure involves seven steps, which include data extraction, identification of time slices, Problem Table Algorithm, Multiple Utility Problem Table Algorithm, Total Site Problem Table Algorithm, TriGenSCA, and Trigeneration Storage Cascade Table (TriGenSCT). An illustrative case study is constructed by considering the trigeneration Pressurized Water Reactor Nuclear Power Plant (PWR NPP) and four industrial plants in a Total Site system. Based on the case study, the base fuel of the trigeneration PWR NPP requires 14 t of Uranium-235 to an average demand load of 93 GWh/d. The results of trigeneration PWR NPP with and without the integration of the Total Site system is compared and proven that trigeneration PWR NPP with integration is a suitable technology that can save up to 0.2% of the equivalent annual cost and 1.4% of energy compared to trigeneration PWR NPP without integration.

Background Healthcare systems in low-resource settings need simple, low-cost interventions to improve services and address gaps in care. Though routine data provide opportunities to guide these efforts, frontline providers are rarely engaged in analyzing them for facility-level decision making. The Systems Analysis and Improvement Approach (SAIA) is an evidence-based, multi-component implementation strategy that engages providers in use of facility-level data to promote systems-level thinking and quality improvement (QI) efforts within multi-step care cascades. SAIA was originally developed to address HIV care in resource-limited settings but has since been adapted to a variety of clinical care systems including cervical cancer screening, mental health treatment, and hypertension management, among others; and across a variety of settings in sub-Saharan Africa and the USA. We aimed to extend the growing body of SAIA research by defining the core elements of SAIA using established specification approaches and thus improve reproducibility, guide future adaptations, and lay the groundwork to define its mechanisms of action. Methods Specification of the SAIA strategy was undertaken over 12 months by an expert panel of SAIA-researchers, implementing agents and stakeholders using a three-round, modified nominal group technique approach to match core SAIA components to the Expert Recommendations for Implementing Change (ERIC) list of distinct implementation strategies. Core implementation strategies were then specified according to Proctor’s recommendations for specifying and reporting, followed by synthesis of data on related implementation outcomes linked to the SAIA strategy across projects. Results Based on this review and clarification of the operational definitions of the components of the SAIA, the four components of SAIA were mapped to 13 ERIC strategies. SAIA strategy meetings encompassed external facilitation, organization of provider implementation meetings, and provision of ongoing consultation. Cascade analysis mapped to three ERIC strategies: facilitating relay of clinical data to providers, use of audit and feedback of routine data with healthcare teams, and modeling and simulation of change. Process mapping matched to local needs assessment, local consensus discussions and assessment of readiness and identification of barriers and facilitators. Finally, continuous quality improvement encompassed tailoring strategies, developing a formal implementation blueprint, cyclical tests of change, and purposefully re-examining the implementation process. Conclusions Specifying the components of SAIA provides improved conceptual clarity to enhance reproducibility for other researchers and practitioners interested in applying the SAIA across novel settings.

Background The introduction of option B+—rapid initiation of lifelong antiretroviral therapy regardless of disease status for HIV-infected pregnant and breastfeeding women—can dramatically reduce HIV transmission during pregnancy, birth, and breastfeeding. Despite significant investments to scale-up Option B+, results have been mixed, with high rates of loss to follow-up, sub-optimal viral suppression, continued pediatric HIV transmission, and HIV-associated maternal morbidity. The Systems Analysis and Improvement Approach (SAIA) cluster randomized trial demonstrated that a package of systems engineering tools improved flow through the prevention of mother-to-child HIV transmission (PMTCT) cascade. This five-step, facility-level intervention is designed 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). This protocol describes a novel model for SAIA delivery (SAIA-SCALE) led by district nurse supervisors (rather than research nurses), and evaluation procedures, to serve as a foundation for national scale-up. Methods The SAIA-SCALE stepped wedge trial includes three implementation waves, each 12 months in duration. Districts are the unit of assignment, with four districts randomly assigned per wave, covering all 12 districts in Manica province, Mozambique. In each district, the three highest volume health facilities will receive the SAIA-SCALE intervention (totaling 36 intervention facilities). The RE-AIM framework will guide SAIA-SCALE’s evaluation. Reach describes the proportion of clinics and population in Manica province reached, and sub-groups not reached. Effectiveness assesses impact on PMTCT process measures and patient-level outcomes. Adoption describes the proportion of districts/clinics adopting SAIA-SCALE, and determinants of adoption using the Organizational Readiness for Implementing Change (ORIC) tool. Implementation will identify SAIA-SCALE core elements and determinants of successful implementation using the Consolidated Framework for Implementation Research (CFIR). Maintenance describes the proportion of districts sustaining the intervention. We will also estimate the budget and program impact from the payer perspective for national scale-up. Discussion SAIA packages user-friendly systems engineering tools to guide decision-making by frontline health workers, and to identify low-cost, contextually appropriate PMTCT improvement strategies. By integrating SAIA delivery into routine management structures, this pragmatic trial is designed to test a model for national intervention scale-up. Trial registration ClinicalTrials.gov NCT03425136 (registered 02/06/2018).

The infrared band is one of the important communication windows. Most of the detectors and sensors working in this band are designed and manufactured based on micro- and nano-lithography technology. In this article, we cut the giant-sized thickness of the transparent substrate and the metal film was uniformly sliced. Then, we used the CST software to simulate the sliced substrate and the metal film to obtain the optical response parameters for each slice. Finally, the combination of metal film and substrate was realized by cascading calculation of the two port transmission line theory, which solves problems such as overlong simulation time and cumbersome running load caused by huge grid divisions due to the difference between the substrate thickness and the response wavelength in the process of simulating light propagation. On the other hand, the cascade analysis method was experimentally verified by constructing a surface plasmon filter in the medium infrared band, which provides an effective idea and solution for bridging the gap between simulation and engineering application.