Iterative Implementation Research Articles

Twelve tips for teaching culturally and socially responsive care to medical students

In recent years, discourse on topics like cultural humility, social determinants of health (SDOH), and health disparities and inequities has greatly increased in medical education as attention to their impact on health has magnified. Unfortunately, traditional medical education models may fail to optimize learning in this area. To address these complex social health issues, we must find innovative ways to engage students in an educational partnership in which they are challenged to critically think and reflect on their attitudes, role, and actions in health equity and culturally responsive care. Through reviews of existing literature coupled with our own experience with iterative implementation of a model that includes interpersonal engagement paired with individual self-directed learning, we assembled 12 tips on how to prepare diverse students to practice lifelong cultural humility and provide culturally and socially responsive care in an ever-changing social landscape.

Revolutionizing cancer treatment in India: Evaluating the unmet need, economics, and a roadmap for project implementation of particle therapy.

This study aims to quantitatively assess eligible patients and project the demand for particle therapy facilities in India from 2020 to 2040. In addition, an economic analysis evaluates the financial feasibility of implementing this technology. The study also examines the prospective benefits and challenges of adopting this technology in India. Cancer incidence and projected trends were analyzed for pediatric patients using the Global Childhood Cancer microsimulation model and adult patients using the Globocan data. Economic cost evaluation is performed for large-scale combined particle (carbon and proton-three room fixed-beam), large-scale proton (one gantry and two fixed-beam), and small-scale proton (one gantry) facility. By 2040, the estimated number of eligible patients for particle therapy is projected to reach 161,000, including approximately 14,000 pediatric cases. The demand for particle therapy facilities is projected to rise from 81 to 97 in 2020 to 121 to 146 by 2040. The capital expenditure is estimated to be only 3.7 times that of a standard photon linear accelerator over a 30-year period. Notably, the treatment cost can be reduced to USD 400 to 800 per fraction, substantially lower than that in high-income countries (USD 1000 to 3000 per fraction). This study indicates that, in the Indian scenario, all particle therapy models are cost-beneficial and feasible, with large-scale proton therapy being the most suitable. Despite challenges such as limited resources, space, a skilled workforce, referral systems, and patient affordability, it offers substantial benefits. These include the potential to treat many patients and convenient construction and operational costs. An iterative phased implementation strategy can effectively overcome these challenges, paving the way for the successful adoption of particle therapy in India. In India, eligible patients benefiting from high-precision particle therapy technology projected to rise till 2040. Despite high upfront costs, our study finds the long-term feasibility of all particle therapy models, potentially offering a substantial reduction in treatment cost compared to high-income countries. Despite challenges, India can succeed with an iterative phased approach.

Use of implementation mapping in the planning of a hybrid type 1 pragmatic clinical trial: the BeatPain Utah study

BackgroundConsiderable disparities in chronic pain management have been identified. Persons in rural, lower income, and minoritized communities are less likely to receive evidence-based, nonpharmacologic care. Telehealth delivery of nonpharmacologic, evidence-based interventions for persons with chronic pain is a promising strategy to lessen disparities, but implementation comes with many challenges. The BeatPain Utah study is a hybrid type 1 effectiveness-implementation pragmatic clinical trial investigating telehealth strategies to provide nonpharmacologic care from physical therapists to persons with chronic back pain receiving care in ommunity health centers (CHCs). CHCs provide primary care to all persons regardless of ability to pay. This paper outlines the use of implementation mapping to develop a multifaceted implementation plan for the BeatPain study.MethodsDuring a planning year for the BeatPain trial, we developed a comprehensive logic model including the five-step implementation mapping process informed by additional frameworks and theories. The five iterative implementation mapping steps were addressed in the planning year: (1) conduct needs assessments for involved groups; (2) identify implementation outcomes, performance objectives, and determinants; (3) select implementation strategies; (4) produce implementation protocols and materials; and (5) evaluate implementation outcomes.ResultsCHC leadership/providers, patients, and physical therapists were identified as involved groups. Barriers and assets were identified across groups which informed identification of performance objectives necessary to implement two key processes: (1) electronic referral of patients with back pain in CHC clinics to the BeatPain team and (2) connecting patients with physical therapists providing telehealth. Determinants of the performance objectives for each group informed our choice of implementation strategies which focused on training, education, clinician support, and tailoring physical therapy interventions for telehealth delivery and cultural competency. We selected implementation outcomes for the BeatPain trial to evaluate the success of our implementation strategies.ConclusionsImplementation mapping provided a comprehensive and systematic approach to develop an implementation plan during the planning phase for our ongoing hybrid effectiveness-implementation trial. We will be able to evaluate the implementation strategies used in the BeatPain Utah study to inform future efforts to implement telehealth delivery of evidence-based pain care in CHCs and other settings.Trial registrationClinicalTrials.gov Identifier: NCT04923334. Registered June 11, 2021.

An ensemble multi-scale framework for long-term forecasting of air quality.

The significance of accurate long-term forecasting of air quality for a long-term policy decision for controlling air pollution and for evaluating its impacts on human health has attracted greater attention recently. This paper proposes an ensemble multi-scale framework to refine the previous version with ensemble empirical mode decomposition (EMD) and nonstationary oscillation resampling (NSOR) for long-term forecasting. Within the proposed ensemble multi-scale framework, we on one hand apply modified EMD to produce more regular and stable EMD components, allowing the long-range oscillation characteristics of the original time series to be better captured. On the other hand, we provide an ensemble mechanism to alleviate the error propagation problem in forecasts caused by iterative implementation of NSOR at all lead times and name it improved NSOR. Application of the proposed multi-scale framework to long-term forecasting of the daily PM2.5 at 14 monitoring stations in Hong Kong demonstrates that it can effectively capture the long-term variation in air pollution processes and significantly increase the forecasting performance. Specifically, the framework can, respectively, reduce the average root-mean-square error and the mean absolute error over all 14 stations by 8.4% and 9.2% for a lead time of 100 days, compared to previous studies. Additionally, better robustness can be obtained by the proposed ensemble framework for 180-day and 365-day long-term forecasting scenarios. It should be emphasized that the proposed ensemble multi-scale framework is a feasible framework, which is applicable for long-term time series forecasting in general.

Solutions of random ordinary differential equations with laplace transform - Adomian decomposition method

Combine the Laplace Adomian Decomposition method (LTADM) for non-linear random ordinary differential equations is utilised in a novel way to obtain accurate solutions.The iterative implementation of the Laplace transform decomposition is employed to approximate the solutions of ordinary differential equations with random components. We use a Normal distribution to analyse the parameters and initial conditions of ordinary differential equations with random components. Using the Mathematica 13.3 programme, the graphs of the approximate solutions and absolute error are presented. An investigation is conducted into the effects of the normal distribution on the results of random component differential equations. According to the results of the numerical investigations, this method is extremely effective. Two applications are presented as examples of how the proposed technique can be utilised to obtain analytical or numerical solutions for certain kinds of random differential equations in order to demonstrate its efficacy and potential.

Transition of care: lessons from the Standardizing Care to Improve Outcomes in Pediatric End Stage Renal Disease (SCOPE) dialysis collaborative.

Acknowledging the importance of preparing the pediatric dialysis patient for successful transfer to adult providers, centers from the Standardizing Care to Improve Outcomes in Pediatric End Stage Renal Disease (SCOPE) Dialysis Collaborative developed transition tools and performed iterative implementation of a transition of care (TOC) program to gain real-life insight into drivers and barriers towards implementation of a transition program for patients receiving dialysis. A TOC innovation workgroup was developed in 2019 from within SCOPE Collaborative that developed nine educational modules, along with introductory letter and assessment tool to be utilized by SCOPE centers. A 4-month pilot implementation study among six centers of varying patient population (age ≥ 11years) was performed. TOC tools were further refined, and broader implementation within the collaborative was performed. Interim assessment of TOC tool utilization and implementation success was performed among 11 centers, as a foundation towards broader discussion regarding process, barriers, and success towards TOC implementation among 26 centers. Transition champion was a key driver of successful implementation, and lack of institutional support and collaboration with adult dialysis centers were important barriers towards sustainability. COVID pandemic and increased staff turnover affected longer term implementation of TOC program. Successful transition and transfer of adolescents/young adults with kidney failure on dialysis remains a challenge. This study represents the experience of the largest cohort of pediatric dialysis centers, with diversity in population size and geography, towards development and implementation of a TOC program. This adds to the resources available to assist centers towards transition and transfer, with particular focus on transitioning patients on dialysis.

Conceptualization, development, and early dissemination of eMPACTTM: A competency-based career navigation system for translational research professionals.

Purposeful training and ongoing career support are necessary to meet the evolving and expanding roles of clinical research professionals (CRP). To address the training and employment needs of clinical research coordinators (CRCs), one of the largest sectors of the CRP workforce, we designed, developed, and implemented an online career navigation system, eMPACTTM (eMpowering Purposeful Advancement of Careers and Training). A design-based research method was employed as an overarching approach that frames iterative design, development, and implementation of educational interventions. The five major phases of this project - conceptualization, task analysis for measurement development, algorithms development, algorithms validation, and system evaluation - presented specific goals and relevant methods. The results reported how the eMPACTTM system was conceptualized, developed, and validated. The system allowed CRCs to navigate tailored training and job opportunities by completing their task competencies and career goals. The data sets could, in turn, support employees' and training coordinators' informed decisions about organizational training needs and recruitment. The early dissemination results showed steady growth in registered CRCs and diversity in users' ethnicity and job levels. The eMPACTTM service showed the possibility of supporting CRCs' individual career advancement and organizational workforce enhancement and diversity. Long-term research is needed to evaluate its impact on CRC workforce development, explore key factors influencing workforce sustainability, and expand eMPACTTM service to other CRP sectors.

Revision of Malawi’s Health Benefits Package: A Critical Analysis of Policy Formulation and Implementation

ObjectivesHealth benefits packages (HBPs), which define specific health services that can be offered for free or at a reduced cost to fit within public revenues, have been recommended for over 30 years to maximize population health in resource-limited settings. However, there remain gaps in defining and operationalizing HBPs. We propose a combination of design and prioritization methods along with practical strategies to improve the implementation of future iterations of the HBP in Malawi. MethodsFor HBP development for Malawi’s Third Health Sector Strategic Plan, we combined cost-effectiveness analysis with a quantitative, consultative multicriteria decision analysis. Throughout the process of development, we documented challenges and opportunities to improve HBP design and application. ResultsThe primary and secondary HBP included 115 interventions. However, the definition of an HBP is just one step toward focusing limited resources, with functional operationalization as the most critical component. Full implementation of previous HBPs has been limited by challenges in aid coordination with the misalignment of nonfungible vertical donor funding for the HBP without accounting for the complexity and interconnectedness of the health system. Opportunities for improved application include creation of a complementary minimum health service package to guide overall resource inputs through an integrative approach. ConclusionsWe believe that expanded participatory HBP methods that consider value, equity, and social considerations, along with a shift to providing integrated health service packages at all levels of care, will improve the efficiency of using scarce resources along the journey to universal health coverage.

The iterative implementation of a comprehensive enhanced recovery after surgery protocol in all spinal surgery in Korea: a comparative analysis of clinical outcomes and medical costs between primary spinal tumors and degenerative spinal diseases.

Most studies on the enhanced recovery after surgery (ERAS) protocol in spine surgery have focused on patients with degenerative spinal diseases (DSDs), resulting in a lack of evidence for a comprehensive ERAS protocol applicable to patients with primary spine tumors (PSTs) and other spinal diseases. The authors had developed and gradually adopted components of the comprehensive ERAS protocol for all spine surgical procedures from 2003 to 2011, and then the current ERAS protocol was fully implemented in 2012. This study aimed to evaluate the impact and the applicability of the comprehensive ERAS protocol across all spine surgical procedures and to compare outcomes between the PST and DSD groups. Adult spine surgical procedures were conducted from 2003 to 2021 at the Seoul National University Hospital Spine Center and data were retrospectively reviewed. The author divided the study periods into the developing ERAS (2003-2011) and post-current ERAS (2012-2021) periods, and outcomes were compared between the two periods. Surgical procedures for metastatic cancer, infection, and trauma were excluded. Interrupted time series analysis (ITSA) was used to assess the impact of the ERAS protocol on medical costs and clinical outcomes, including length of stay (LOS) and rates of 30-day readmission, reoperation, and surgical site infection (SSI). Subgroup analyses were conducted on the PST and DSD groups in terms of LOS and medical costs. The study included 7143 surgical procedures, comprising 1494 for PSTs, 5340 for DSDs, and 309 for other spinal diseases. After ERAS protocol implementation, spine surgical procedures showed significant reductions in LOS and medical costs by 22% (p = 0.008) and 22% (p < 0.001), respectively. The DSD group demonstrated a 16% (p < 0.001) reduction in LOS, whereas the PST group achieved a 28% (p < 0.001) reduction, noting a more pronounced LOS reduction in PST surgical procedures (p = 0.003). Medical costs decreased by 23% (p < 0.001) in the DSD group and 12% (p = 0.054) in the PST group, with a larger cost reduction for DSD surgical procedures (p = 0.021). No statistically significant differences were found in the rates of 30-day readmission, reoperation, and SSI between the developing and post-current ERAS implementation periods (p = 0.65, p = 0.59, and p = 0.52, respectively). Comprehensive ERAS protocol implementation significantly reduced LOS and medical costs in all spine surgical procedures, while maintaining comparable 30-day readmission, reoperation, and SSI rates. These findings suggest that the ERAS protocol is equally applicable to all spine surgical procedures, with a more pronounced effect on reducing LOS in the PST group and on reducing medical costs in the DSD group.

Model resolution-based deconvolution for improved quantitative susceptibility mapping.

Quantitative susceptibility mapping (QSM) utilizes the relationship between the measured local field and the unknown susceptibility map to perform dipole deconvolution. The aim of this work is to introduce and systematically evaluate the model resolution-based deconvolution for improved estimation of the susceptibility map obtained using the thresholded k-space division (TKD). A two-step approach has been proposed, wherein the first step involves the TKD susceptibility map computation and the second step involves the correction of this susceptibility map using the model-resolution matrix. The TKD-estimated susceptibility map can be expressed as the weighted average of the true susceptibility map, where the weights are determined by the rows of the model-resolution matrix, and hence a deconvolution of the TKD susceptibility map using the model-resolution matrix yields a better approximation to the true susceptibility map. The model resolution-based deconvolution is realized using closed-form, iterative, and sparsity-regularized implementations. The proposed approach was compared with L2 regularization, TKD, rescaled TKD in superfast dipole inversion, the modulated closed-form method, and iterative dipole inversion, as well as sparsity-regularized dipole inversion. It was observed that the proposed approach showed a substantial reduction in the streaking artifacts across 94 test volumes considered in this study. The proposed approach also showed better error reduction and edge preservation compared with other approaches. The proposed model resolution-based deconvolution compensates for the truncation of zero coefficients in the dipole kernel at the magic angle and hence provides a closer approximation to the true susceptibility map compared with other direct methods.

A multi-step relay implementation of the successive iteration of analysis and design method for large-scale natural frequency-related topology optimization

A multi-step relay implementation of the successive iteration of analysis and design method for large-scale natural frequency-related topology optimization

A First Exploration on the Use of Head-Mounted Augmented Reality in the Context of the Portuguese Military

In this paper, we present the design and implementation of a first iteration of an augmented reality (AR) system for dismounted soldiers in the Portuguese military. We started the work via a survey of 86 members of the military to better understand their experience, needs, and preferences with current Command &amp; Control (C2) systems. We then assessed the effects of our prototype on the performance, situational awareness, and perceived usability and workload of 13 participants from a local Commando Regiment. We compared our results to a representative baseline using a paper map and radio in a hostage extraction simulation and found that our first AR iteration, despite a short practice session, increased the quality of the information available and decreased the complexity, temporal demands, and effort required to complete the study tasks; leading to an overall decrease in perceived workload. Overall, participants described the AR experience as more user-friendly. We conclude our case study with research ideas for further iterations of our prototype.

Systematic User-centered Design of a Prototype Clinical Decision Support System for Glaucoma.

To rigorously develop a prototype clinical decision support (CDS) system to help clinicians determine the appropriate timing for follow-up visual field testing for patients with glaucoma and to identify themes regarding the context of use for glaucoma CDS systems, design requirements, and design solutions to meet these requirements. Semistructured qualitative interviews and iterative design cycles. Clinicians who care for patients with glaucoma, purposefully sampled to ensure a representation of a range of clinical specialties (glaucoma specialist, general ophthalmologist, optometrist) and years in clinical practice. Using the established User-Centered Design Process framework, we conducted semistructured interviews with 5 clinicians that addressed the context of use and design requirements for a glaucoma CDS system. We analyzed the interviews using inductive thematic analysis and grounded theory to generate themes regarding the context of use and design requirements. We created design solutions to address these requirements and used iterative design cycles with the clinicians to refine the CDS prototype. Themes regarding decision support for determining the timing of visual field testing for patients with glaucoma, CDS design requirements, and CDS design features. We identified 9 themes that addressed the context of use for the CDS system, 9 design requirements for the prototype CDS system, and 9 design features intended to address these design requirements. Key design requirements included the preservation of clinician autonomy, incorporation of currently used heuristics, compilation of data, and increasing and communicating the level of certainty regarding the decision. After completing 3 iterative design cycles using this preliminary CDS system design solution, the design was satisfactory to the clinicians and was accepted as our prototype glaucoma CDS system. We used a systematic design process based on the established User-Centered Design Process to rigorously develop a prototype glaucoma CDS system, which will be used as a starting point for a future, large-scale iterative refinement and implementation process. Clinicians who care for patients with glaucoma need CDS systems that preserve clinician autonomy, compile and present data, incorporate currently used heuristics, and increase and communicate the level of certainty regarding the decision. Proprietary or commercial disclosure may be found after the references.

Enterprise Transformation Projects

This article presents the ETP-HSC and a corresponding enterprise transformation framework, where the focus is on the application of Enterprise Architecture (EA) to support Security (EA4S) and it is the central topic. The EA4S is a Polymathic-holistic approach, which adopts a clear EA as the main ETP constraint for the implementation of a secured Information and Communications System’s (ICS). EA and all other ICS related architecture disciplines, are inspired from the term Architecture that comes from civil engineering, and in this domain, secured building objects are achieved by implementing robust building and urbanistic architectures, like the famous case of Hausmann’s Architecture and Urbanistic plan for the (re)Architecture of Paris in France, in which its primary objective was to assert Paris’ security. Therefore, the author considers that EAS’ first step is to build an enterprise security concept. But for enterprises that have been archaically built and do not have the needed resources to implement a Haussmannian security concept, therefore an iterative ETP-HSC implementation process can transform the enterprise’s security. ETP-HSC’s feasibility and integrity can be supported by an integrated Applied Holistic Mathematical Model (AHMM) for EAS (AHMM4EAS), and the author’s various research works on the applications of holistic security concepts, ETPs, Artificial Intelligence (AI), Cloud Services (CS), and AHMM. The ETP-SRC is based on a multi-disciplinary proprietary-mixed research method.

Development of a goal-directed movement intervention (GOAL) using a movement sensor for hospitalized patients: An intervention mapping approach

Objective To describe the development of a goal-directed movement intervention in two medical wards, including recommendations for implementation and evaluation. Design Implementation Research. Setting Pulmonology and nephrology/gastroenterology wards of the University Medical Centre Utrecht, The Netherlands. Participants Seven focus groups were executed including 28 nurses, 7 physical therapists and 15 medical specialists. Patients’ perceptions were repeatedly assessed during the iterative steps of the intervention development. Intervention Interventions were targeted to each ward's specific character, following an Intervention Mapping approach using literature and research meetings. Main measures: Intervention components were linked to Behavior Change Techniques and implementation strategies will be selected using the Expert Recommendation Implementing Change tool. Evaluation outcomes like number of patients using the movement intervention will be measured, based on the taxonomy of Proctor. Results The developed intervention consists of: insight in patients movement behavior (monitoring & feedback), goal setting (goals & planning) and adjustments to the environment (associations & antecedents). The following implementation strategies are recommended: to conduct educational meetings, prepare & identify champions and audit & provide feedback. To measure service and client outcomes, the mean level of physical activity per ward can be evaluated and the Net Promoter Score can be used. Conclusion(s) This study shows the development of a goal-directed movement intervention aligned with the needs of healthcare professionals. This resulted in an intervention consisting of feedback & monitoring of movement behavior, goal setting and adjustments in the environment. Using a step-by-step iterative implementation model to guide development and implementation is recommended.

Engineering of Substrate Tunnel of P450 CYP116B3 though Machine Learning

The combinatorial complexity of the protein sequence space presents a significant challenge for recombination experiments targeting beneficial positions. To overcome these difficulties, a machine learning (ML) approach was employed, which was trained on a limited literature dataset and combined with iterative generation and experimental data implementation. The PyPEF method was utilized to identify existing variants and predict recombinant variants targeting the substrate channel of P450 CYP116B3. Through molecular dynamics simulations, eight multiple-substituted improved variants were successfully validated. Specifically, the RMSF of variant A86T/T91H/M108S/A109M/T111P was decreased from 3.06 Å (wild type) to 1.07 Å. Additionally, the average RMSF of the variant A86T/T91P/M108V/A109M/T111P decreased to 1.41 Å, compared to the wild type’s 1.53 Å. Of particular significance was the prediction that the variant A86T/T91H/M108G/A109M/T111P exhibited an activity approximately 15 times higher than that of the wild type. Furthermore, during the selection of the regression model, PLS and MLP regressions were compared. The effect of data size and data relevance on the two regression approaches has been summarized. The aforementioned conclusions provide evidence for the feasibility of the strategy that combines ML with experimental approaches. This integrated strategy proves effective in exploring potential variations within the protein sequence space. Furthermore, this method facilitates a deeper understanding of the substrate channel in P450 CYP116B3.

Time to re-envisage culturally responsive care: Intersection of participatory health research and implementation science.

In the context of widening societal diversity, culturally and linguistically diverse patients continue to experience inequities in healthcare access and deficiencies in standards of nursing care. Re-framing culturally responsive care as a complex intervention spanning multiple interacting factors at micro, meso and macro levels is an essential prerequisite for addressing knowledge translation gaps into everyday nursing practice. To this end, this paper proposes and explicates the potential of applying synergistic participatory implementation methodologies for developing effective implementation strategies with impact at individual and wider structural levels. Discussion Paper. A co-design case study is presented as an example of combining normalization process theory and participatory learning and action to investigate and support the implementation of culturally responsive care in general practice nursing. Enacting culturally responsive health care is inherently complex in that it is influenced by multiple interacting factors. Viewing culturally responsive care as a complex intervention and incorporating a synergistic participatory implementation science approach offers possibilities for addressing the documented shortcomings in the implementation of culturally responsive nursing care. There is a need to move away from conventional approaches to conceptualizing and generating evidence on culturally responsive care. Incorporating participatory implementation methodologies can provide a new lens to investigate and support whole system implementation strategies. The combination of participatory and implementation methodologies is both theoretically and empirically informed. Engaging stakeholders in the co-design and co-production of evidence and solutions to long standing problems has the potential to increase the likelihood of influencing iterative and sustainable implementation and changes to clinical practice and systems. This work is part of a wider programme of participatory health research on migrant health, partnering with a non-governmental organization that supports migrants.

Developing Teacher Competencies for Teaching Evolution across the Primary School Curriculum: A Design Study of a Pre-Service Teacher Education Module

Numerous studies indicate that evolutionary concepts can and should be taught at the primary school level. However, teaching evolution in primary school is presumably not yet the norm globally. At the same time, the educational potential of evolutionary concepts lies in their applicability to many curriculum topics in the natural and social sciences. Capitalizing on this potential requires broad teacher content knowledge (CK) and pedagogical content knowledge (PCK) about the teaching of evolutionary concepts. However, not much is known regarding ways to develop primary teacher CK and PCK during pre-service training. In this article, we present the iterative design, implementation, and mixed methods formative evaluation (based on a design-based research framework) of a pre-service teacher education module. Its aim was to promote the development of pre-service primary school teacher CK, PCK, as well as motivation and confidence for teaching evolution across the primary school curriculum. Results indicate that pre-service teachers can be supported and motivated to teach evolutionary concepts across various themes in the primary school curriculum through a semester long course. Participants were able to develop core aspects of CK and PCK regarding the teaching of evolutionary concepts in primary school. The resulting module design integrates existing collective PCK on teaching evolution at the primary level as well as novel design considerations and teaching approaches that can be integrated into pre-service teacher education programs. However, challenges remain, particularly regarding the integration of evolutionary concepts in mandated curriculum standards such that the educational potential of evolution can be fully capitalized on by teachers.

Digitalizing Clinical Guidelines: Experiences in the Development of Clinical Decision Support Algorithms for Management of Childhood Illness in Resource-Constrained Settings.

Clinical decision support systems (CDSSs) can strengthen the quality of integrated management of childhood illness (IMCI) in resource-constrained settings. Several IMCI-related CDSSs have been developed and implemented in recent years. Yet, despite having a shared starting point, the IMCI-related CDSSs are markedly varied due to the need for interpretation when translating narrative guidelines into decision logic combined with considerations of context and design choices. Between October 2019 and April 2021, we conducted a comparative analysis of 4 IMCI-related CDSSs. The extent of adaptations to IMCI varied, but common themes emerged. Scope was extended to cover a broader range of conditions. Content was added or modified to enhance precision, align with new evidence, and support rational resource use. Structure was modified to increase efficiency, improve usability, and prioritize care for severely ill children. The multistakeholder development processes involved syntheses of recommendations from existing guidelines and literature; creation and validation of clinical algorithms; and iterative development, implementation, and evaluation. The common themes surrounding adaptations of IMCI guidance highlight the complexities of digitalizing evidence-based recommendations and reinforce the rationale for leveraging standards for CDSS development, such as the World Health Organization's SMART Guidelines. Implementation through multistakeholder dialogue is critical to ensure CDSSs can effectively and equitably improve quality of care for children in resource-constrained settings.

An Iterative Implementation of the Signal Space Separation Method for Magnetoencephalography Systems with Low Channel Counts.

The signal space separation (SSS) method is routinely employed in the analysis of multichannel magnetic field recordings (such as magnetoencephalography (MEG) data). In the SSS method, signal vectors are posed as a multipole expansion of the magnetic field, allowing contributions from sources internal and external to a sensor array to be separated via computation of the pseudo-inverse of a matrix of the basis vectors. Although powerful, the standard implementation of the SSS method on MEG systems based on optically pumped magnetometers (OPMs) is unstable due to the approximate parity of the required number of dimensions of the SSS basis and the number of channels in the data. Here we exploit the hierarchical nature of the multipole expansion to perform a stable, iterative implementation of the SSS method. We describe the method and investigate its performance via a simulation study on a 192-channel OPM-MEG helmet. We assess performance for different levels of truncation of the SSS basis and a varying number of iterations. Results show that the iterative method provides stable performance, with a clear separation of internal and external sources.