Sustainability and normalization of an intervention to improve evidence-based myocardial infarction care in Tanzania

Sustainability and normalization of an intervention to improve evidence-based myocardial infarction care in Tanzania | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Sustainability and normalization of an intervention to improve evidence-based myocardial infarction care in Tanzania Claire Wang, Francis M Sakita, Spencer Sumner, Frida M Shayo, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7368551/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Jan, 2026 Read the published version in Implementation Science Communications → Version 1 posted 5 You are reading this latest preprint version Abstract Background The Multicomponent Intervention to Improve Acute Myocardial Infarction Care (MIMIC) was developed to address gaps in AMI diagnosis and treatment in northern Tanzania. Although initial implementation was promising, many quality improvement interventions are not sustained after research support ends, especially in resource-limited settings. Evaluating sustainability and normalization is essential for understanding the long-term impact of implementation research. We evaluated these outcomes for the MIMIC intervention in a Tanzanian emergency department following a pilot implementation trial. Methods We conducted a cross-sectional survey of all full-time emergency department clinicians (n = 35) at Kilimanjaro Christian Medical Centre (KCMC) using two validated implementation science tools: the Clinical Sustainability Assessment Tool (CSAT) and the Normalization MeAsure Development (NoMAD) questionnaire. The CSAT assesses seven domains, with higher scores reflecting greater perceived sustainability. The NoMAD measures four constructs, with higher scores indicating stronger normalization. For each domain, scores were summarized descriptively (means, standard deviations) and compared by provider type (doctors vs. registered nurses) using independent t-tests. Results All 35 eligible clinicians (100%) completed the survey. Mean CSAT domain scores ranged from 5.81 (SD 1.04) for Organizational Context and Capacity to 6.73 (SD 0.47) for Outcomes and Effectiveness (scale 1–7). Mean NoMAD scores were uniformly high and clustered within a narrow range from 4.26 (SD 0.51) for Collective Action to 4.69 (SD 0.42) for Cognitive Participation (scale 1–5). Nurses reported significantly greater Workflow Integration than doctors (mean 6.76 vs. 6.20, p = 0.034); no other domains differed significantly by provider type. Domains related to perceived clinical benefit, individual engagement, and feedback scored highest, whereas organizational context and financial support scored comparatively lower. Conclusions This study is among the first to apply the CSAT and NoMAD tools to evaluate a quality improvement intervention in sub-Saharan Africa. Findings indicate that MIMIC is both highly sustainable and normalized in routine care at KCMC, as reflected by consistently high mean domain scores across both instruments, although formal thresholds for these measures have not yet been established. Strengthening organizational capacity and long-term support, particularly financing and team coordination, may further enhance sustained implementation. Implementation Science Sustainability Normalization Process Theory emergency department LMICs Tanzania sub-Saharan Africa myocardial infarction Figures Figure 1 Figure 2 Background Acute myocardial infarction (AMI) is a leading cause of death globally, contributing to an estimated 3 million deaths annually.(1) While high-income countries have achieved significant reductions in AMI mortality through early diagnosis and use of evidence-based treatments,(2,3) low- and middle-income countries—which now account for over 80% of global cardiovascular disease deaths—continue to face major challenges in AMI recognition and care.(4) In Tanzania, AMI is frequently under-diagnosed and under-treated. In a northern Tanzanian emergency department (ED), we found that nearly 90% of AMI cases are missed during routine care, and fewer than 25% of patients with AMI receive recommended treatments such as aspirin.(5–7) These gaps in care likely contributed to a 30-day mortality rate of 43% among AMI patients—one of the highest AMI mortality rates ever reported worldwide.(6) To address these challenges, we developed the Multicomponent Intervention to Improve Acute Myocardial Infarction Care (MIMIC). Adapted from Brazil’s ACS-BRIDGE program and contextualized for the northern Tanzanian setting using the ADAPT-ITT framework,(7,8) MIMIC was evaluated in a one-year, single-arm pilot trial at Kilimanjaro Christian Medical Centre (KCMC) in northern Tanzania. The intervention led to substantial improvements in key care metrics, including rates of ECG and troponin testing, AMI identification, and evidence-based treatment with aspirin, clopidogrel, and heparin.(9–11) While findings were encouraging, many research-driven quality improvement interventions are not sustained after the study period ends due to challenges like limited institutional support, staff turnover, and poor integration into daily workflows.(12) Sustaining interventions is difficult even in high-resource settings; for example, one review found that a third of quality improvement projects in the UK National Health Service were not maintained in real-world clinical settings after one year.(13) Poor sustainability of quality improvement interventions can lead to diminished care quality, worse patient outcomes, and inefficient use of both financial and non-financial resources.(14,15) These concerns underscore the need to evaluate not only short-term outcomes of interventions but also whether interventions demonstrate long-term sustainability and become embedded in routine clinical practice. Indeed, a growing number of implementation scientists have emphasized the importance of assessing sustainability and normalization of interventions in real-world clinical settings, beyond short-term implementation-effectiveness trials.(16) We aimed to evaluate the longer-term sustainability and normalization of MIMIC following the conclusion of the one-year pilot trial. To do so, we conducted a follow-up survey among providers at KCMC using two validated implementation science tools: the Clinical Sustainability Assessment Tool (CSAT) and the Normalization MeAsure Development (NoMAD) questionnaire. CSAT measures an organization’s capacity to sustain interventions across seven domains, including leadership support, workflow fit, and performance monitoring.(17) NoMAD, based on Normalization Process Theory, assesses the extent to which an intervention becomes embedded in practice through constructs such as coherence, cognitive participation, collective action, and reflexive monitoring.(18) By administering CSAT and NoMAD, we sought to determine whether the intervention remained in use and to identify factors that supported or limited its continued implementation. Methods Setting This study was conducted at KCMC, a 630-bed tertiary referral hospital located in Moshi, northern Tanzania. KCMC serves a catchment area of over 15 million people and includes an ED that provides 24-hour acute care. The ED is staffed by a team of nurses and doctors in a high-volume, resource-limited environment. Local challenges such as staffing variability, high clinical workload, and infrastructural constraints may affect the long-term sustainability of quality improvement efforts. The MIMIC Intervention The MIMIC intervention was a multicomponent strategy designed to improve diagnosis and treatment of AMI in a low-resource emergency care setting. It included five core components: (1) a triage card placed on the stretchers of patients with potential AMI symptoms to prompt doctor consideration of the diagnosis; (2) a pocket reference card outlining evidence-based AMI care steps; (3) a web-based refresher training module on AMI diagnosis and treatment, required for all ED clinicians; (4) educational materials for patients, including printed pamphlets and visual messaging displayed in the ED waiting room; and (5) the appointment of doctor and nurse “champions” responsible for encouraging intervention uptake and coordinating implementation. All components were developed and refined using stakeholder input and context-specific adaptation and were delivered by KCMC ED staff during routine clinical care.(19) The MIMIC pilot trial was conducted at KCMC between September 1st, 2023, and August 31st, 2024. During the pilot trial, MIMIC was implemented by the KCMC ED staff; given the positive results of the pilot trial,(9–11) the ED staff decided to continue implementing MIMIC as part of routine ED care. Participant Selection All full-time doctors and registered nurses employed in the KCMC ED between November 2024 and May 2025 were eligible to participate. Clinicians were included regardless of prior involvement in the MIMIC pilot trial, provided they were employed full-time in the ED at the time of survey distribution. At the time of the survey, the KCMC ED employed 18 full-time nurses and 17 full-time doctors. Study Procedures Participants were approached in person at work by a member of the research team during break periods. A brief explanation of the study’s purpose and procedures was provided. Participation was voluntary, and written informed consent was obtained prior to survey administration. The survey was anonymous and self-administered on a tablet to minimize social desirability bias. All survey questions were provided in both English and Swahili. Participants received 5,000 Tanzanian shillings (approximately 2 USD) as compensation for their time. Completed surveys were stored in a secure, password-protected database accessible only to the research team. Survey The survey combined CSAT and NoMAD, two widely used implementation science tools with strong reliability and construct validity.(17,20,21) CSAT has been applied in resource-limited hospital settings,(21) while NoMAD has been used across diverse healthcare contexts to assess normalization.(20) We administered the validated 21-item short version of the CSAT to minimize respondent burden while maintaining comprehensive assessment.(22) The tool includes 21 items across seven domains: engaged staff and leadership, organizational readiness, workflow integration, implementation and training, monitoring and evaluation, outcomes and effectiveness, and infrastructure.(17,22) Items were rated on a 7-point Likert scale ranging from “not at all” (score of 1) to “to a great extent” (score of 7), with an optional “don’t know” response. These domains were used to assess the ED’s capacity to sustain MIMIC over time. NoMAD includes 20 items aligned with four constructs from Normalization Process Theory: coherence, cognitive participation, collective action, and reflexive monitoring.(18) Items were rated on a 5-point Likert scale from “strongly disagree” (score of 1) to “strongly agree” (score of 5) with optional “not relevant” and “don’t know” responses. These items were used to evaluate the extent to which MIMIC had become embedded in routine clinical practice. Six supplementary questions addressed participants’ roles, clinical experience, prior involvement in MIMIC, and perceived ability to influence ED workflows. The survey took approximately 15 minutes to complete. The full instrument is included as Additional file 1. Statistical Methods Survey responses were summarized using descriptive statistics. Total and domain-level scores for the CSAT and NoMAD were reported as means and standard deviations. Although Likert-scale data are ordinal, responses were treated as continuous to facilitate comparison across domains and constructs, consistent with prior studies using these instruments. (20,23–25) Accordingly, CSAT scores were averaged within each of the seven domains to assess organizational capacity for sustainability.(17) NoMAD responses were similarly averaged within four constructs based on Normalization Process Theory.(20) Responses marked as “unable to answer” or “not relevant” were excluded from analysis. A total of 9 CSAT responses (1.2%) and 1 NoMAD response (0.1%) were excluded for this reason. To ensure scoring consistency in the NoMAD tool, the item “The MIMIC intervention disrupts working relationships” (commonly listed as Item 10) was reverse coded so that higher scores indicate greater normalization, consistent with the directionality of other items. To evaluate differences by provider type (doctor vs. nurse), independent-samples t-tests were conducted for overall CSAT and NoMAD scores, as well as for each individual domain score within both tools. For the purposes of analysis, providers were categorized into two groups: “doctor” (including both general and emergency specialist doctors) and “nurse” (including all registered nurses. A p-value of less than 0.05 was considered significant statistically. Given the use of CSAT and NoMAD in a novel population from a low-resource emergency setting, we assessed the internal consistency of each instrument and its individual domains in our setting using Cronbach’s alpha. Statistical analyses were performed using R Statistical Software (version 4.5.1; R Core Team 2024). Ethics Ethical approval for this follow-up study was obtained from the Tanzania National Institute for Medical Research (NIMR/HQ/R.8a/Vol. IX/2436), Kilimanjaro Christian Medical Centre (Proposal 893), and the Duke Health Institutional Review Board (Pro00090902). All procedures adhered to the ethical principles outlined in the Declaration of Helsinki (2000 revision). Written informed consent was obtained from all participants prior to survey administration. Materials were available in both English and Swahili to ensure participant understanding, and participation was voluntary. Respondents could decline or withdraw at any time without penalty. Reporting guidelines This manuscript was prepared in accordance with the StaRI checklist for reporting implementation studies and the STROBE checklist for observational studies. The completed checklists are provided in the Supplementary Materials (Additional file 2 and Additional file 3). Results Participant Characteristics All 35 emergency department clinicians completed the survey, including 18 nurses (51%), 15 general doctors (43%), and 2 emergency specialist doctors (6%). The mean age was 32.7 years (SD 6.9), and participants reported an average of 3.4 years (SD 2.7) of clinical experience. Most participants (n = 29, 83%) reported delivering the MIMIC intervention as part of their routine clinical duties, while the remaining six (17%) served as champions or supervisors (Table 1 ). Table 1 Participant Characteristics Measure N (%) or Mean (SD) 1 Gender Female: 14 (40%) Male: 21 (60%) Age (years) 32.7 (6.9) Years of Clinical Experience 3.4 (2.7) Role in MIMIC Delivers MIMIC during routine ED work: 29 (83%) Supervises MIMIC (Champion/Supervisor): 6 (17%) Provider Type Emergency specialist physician: 2 (6%) General physician: 15 (43%) Nurse: 18 (51%) 1 Values are expressed as means (SD) for continuous variables or N (%) for categorical variables. CSAT Scores CSAT domain scores, rated on a 7-point Likert scale, indicated high perceived capacity to sustain the intervention. Scores ranged from 5.81 (SD 1.04) for Organizational Context and Capacity to 6.73 (SD 0.47) for Outcomes and Effectiveness (Table 2 ; Fig. 1). Item-level response distributions are shown in Additional file 4. Table 2 CSAT and NoMAD Cronbach's alpha by domain Domain Cronbach's alpha CSAT Engaged Staff and Leadership Engaged Stakeholders 0.67 0.61 Organizational Context and Capacity 0.54 Workflow Integration 0.83 Implementation and Training 0.75 Monitoring and Evaluation 0.68 Outcomes and Effectiveness 0.70 Overall CSAT 0.91 NoMAD Coherence 0.84 Cognitive Participation 0.83 Collective Action 0.72 Reflexive Monitoring 0.61 Overall NoMAD 0.89 NoMAD Scores NoMAD domain scores, rated on a 5-point Likert scale, reflected strong normalization of the MIMIC intervention into routine clinical practice. Scores were highest for Cognitive Participation (mean 4.69, SD 0.42) and Reflexive Monitoring (mean 4.50, SD 0.43), followed by Coherence (mean 4.46, SD 0.55) and Collective Action (mean 4.26, SD 0.51). Item-level response distributions are shown in Additional file 5. Three general normalization items, rated on a 10-point Likert scale, were analyzed separately in accordance with prior literature.(20,23) Participants reported high familiarity with the MIMIC intervention (mean 8.97, SD 1.67), perceived it to be well normalized in current practice (mean 9.31, SD 1.41), and anticipated continued normalization in the future (mean 9.11, SD 1.69) (Fig. 2, Panel B). Full distributions are presented in Additional file 6. Internal Consistency Internal consistency of domain scores was assessed using Cronbach’s. Among CSAT domains, alphas ranged from 0.54 to 0.83 (overall = 0.91). Among NoMAD domains, alphas ranged from 0.61 to 0.84 (overall = 0.89). Cronbach’s alpha values for the full instrument and each domain are presented in Table 2 . Table 2 . CSAT and NoMAD Cronbach's alpha by domain Provider Comparison Nurses rated Workflow Integration significantly higher than doctors (mean 6.76 vs. 6.20, p = 0.034). No other CSAT domains differed significantly by provider type. NoMAD domain scores and general normalization items (familiarity, current and future normalization) also showed minimal variation between doctors and nurses (Table 3 ). Table 3 CSAT and NoMAD Scores: Comparison of Nurse vs. Doctor Responses Domain 1 Doctor 2 Mean (SD) Nurse Mean (SD) p-value CSAT Engaged Staff and Leadership 6.12 (0.99) 6.13 (1.09) 0.973 6.24 (0.92) 6.44 (0.62) 0.438 Organizational Context and Capacity 5.73 (1.04) 5.9 (1.07) 0.632 Workflow Integration 6.2 (0.93) 6.76 (0.45) 0.034* Implementation and Training 5.9 (1.37) 6.33 (1.06) 0.308 Monitoring and Evaluation 6.06 (1.09) 6.55 (0.5) 0.106 Outcomes and Effectiveness 6.65 (0.61) 6.81 (0.29) 0.311 Overall CSAT Score 6.12 (0.87) 6.42 (0.47) 0.231 NoMAD Coherence 4.4 (0.56) 4.51 (0.56) 0.541 Cognitive Participation 4.59 (0.48) 4.79 (0.32) 0.157 Collective Action 4.16 (0.6) 4.35 (0.41) 0.286 Reflexive Monitoring 4.51 (0.46) 4.49 (0.41) 0.910 Overall NoMAD Score 4.38 (0.46) 4.51 (0.36) 0.369 General Normalization Familiarity with MIMIC 9.18 (1.47) 8.78 (1.86) 0.486 Current Normalization 9.24 (1.48) 9.39 (1.38) 0.753 Future Normalization 9.18 (1.51) 9.06 (1.89) 0.835 1 Values are expressed as means (SD) for continuous variables or N (%) for categorical variables. 2 Doctor group includes both general and emergency specialist physicians. * p < 0.05 Discussion Our findings suggest that MIMIC is both sustainable and normalized in routine emergency care at KCMC. High scores across CSAT and NoMAD domains reflect strong perceived organizational capacity and widespread normalization among providers. Domains related to perceived clinical benefit, compatibility with existing workflows, and individual engagement scored especially well, underscoring that MIMIC continues to be seen as valuable, aligned with clinical priorities, and well-integrated into clinical routines. Several features of the MIMIC intervention likely contributed to these high scores. Its iterative, participatory design involving frontline KCMC providers ensured alignment with local workflows and responsiveness to site-specific barriers to AMI care.(19) Low-cost, intuitive tools—such as color-coded triage cards, pocket reference guides, and discharge checklists—were supported by visible clinical reminders and weekly case-based audits, enhancing provider engagement and reinforcing practice change. The intervention also emphasized shared responsibility between nurses and doctors, with designated champions from both cadres auditing AMI care and ensuring implementation of all MIMIC components.(19) Collectively, these characteristics—workflow fit, perceived clinical value, collective ownership, and continuous feedback—align closely with CSAT and NoMAD constructs and likely underlie the strong perceptions of MIMIC as both sustainable and normalized in routine care. While most domains showed minimal variation by provider type, nurses rated workflow integration higher than doctors. This may reflect their central role in delivering key components of the intervention—triaging patients for AMI symptoms, distributing educational materials, and reinforcing clinical reminders at the bedside—as well as greater day-to-day exposure to MIMIC-related activities. Differences in responsibilities and proximity to specific implementation tasks may shape how integrated the program feels to different provider groups. Despite overall strong results, lower scores in domains tied to organizational context and team-level coordination highlight areas for improvement. Item-level responses in these domains showed greater variability and more neutral ratings, particularly regarding perceived availability of financial resources, adequacy of training, and alignment of task assignments with staff skills. Notably, the items with the fewest respondents strongly agreeing on both the CSAT and NoMAD pertained to financial resources. The relevant CSAT item encompassed time, space, and funding needed to achieve intervention goals; responses to the NoMAD item regarding the availability of “sufficient resources” were similarly mixed. These findings echo challenges observed during the pilot trial—staffing variability, resource constraints, and gaps in coordination across roles—and point to modifiable barriers.(9–11) Targeted strategies such as strengthened leadership engagement, clearer delineation of team-based roles, and enhanced interprofessional training may help bolster institutional support and promote long-term sustainability. Given that the full cost of the MIMIC intervention reported in the initial MIMIC pilot trial was 1324 USD annually, most of which was attributed to champion stipends,(26) securing additional funding or exploring non-monetary means to support the champions may further bolster long-term sustainability and normalization of the intervention. The overall domain-level patterns observed in our study are consistent with prior studies using CSAT and NoMAD.(17,21,27–29) Across contexts, CSAT domains assessing leadership support, perceived benefit, and workflow integration often score highest, while organizational infrastructure and team coordination show greater variability, particularly in resource-limited environments..(17,21,29) Similarly, NoMAD evaluations in low-resource settings mirror our findings: the PACE program in Tanzania reported strong provider engagement and feedback mechanisms but lower scores in team coordination due to staffing and supply constraints.(28) A dementia care study likewise found high provider buy-in but emphasized infrastructure and interprofessional coordination as critical to sustainability.(27) These parallels reinforce that sustained normalization depends on both integration into clinical routines and broader organizational support. We found high Cronbach’s alpha values for both CSAT and NoMAD, indicating strong reliability and internal consistency. These results closely mirror the original validation findings reported by Malone et al. (2021) and Finch et al. (2020),(17,20) which were conducted in the United States and the United Kingdom, respectively. As is typical for multidimensional implementation measures, domains with fewer or conceptually diverse items (e.g., Organizational Context and Capacity; Reflexive Monitoring) yielded lower alpha values, while the full scales demonstrated robust internal consistency.(22,23) The slightly lower CSAT alphas likely reflect the combination of short subscales with few items and the modest sample size (n = 35), both of which are known to attenuate reliability estimates.(30,31) Overall, these results support the reliability of both instruments for assessing sustainability and normalization in the Tanzanian healthcare context. To our knowledge, this study represents one of the earliest applications of the CSAT and NoMAD instruments in emergency medicine and among the first efforts to apply them in implementation research in sub-Saharan Africa. Use of these instruments proved feasible, relevant, and informative in our setting, as demonstrated by complete participation from eligible clinicians and consistent, interpretable responses across both tools. Researchers conducting implementation work elsewhere in the region should consider these tools to assess long-term sustainability and normalization—two often-overlooked outcomes, particularly in resource-limited acute care settings where such data remain scarce. This study had several strengths. First, it assessed sustainability after active implementation support ended, offering rare insight into post-trial intervention persistence. Second, the combined use of CSAT and NoMAD provided a complementary evaluation of current integration and future sustainability capacity. Third, inclusion of both nurses and doctors allows for comparison across provider groups, and the 100% response rate (35 of 35) enhances internal validity and minimizes response bias. Several limitations should also be noted. First, while CSAT and NoMAD capture key dimensions of implementation processes, they are best interpreted alongside complementary data sources. Prior work highlights the value of mixed-methods approaches—such as qualitative interviews or direct observation—to capture contextual nuances.(23,32) A qualitative study exploring provider perspectives on long-term MIMIC sustainability is ongoing and will be published separately. Second, the cross-sectional design limits our ability to assess temporal trends or infer causality; longitudinal data may better characterize how normalization evolves in response to staffing changes or workflow adaptations. Third, the study was conducted at a single emergency department with a modest sample size, limiting generalizability. Fourth, social desirability bias may have skewed responses toward favorable answers. However, independent, tablet-based survey administration likely reduced this bias and facilitated candid responses. Finally, neither the CSAT nor NoMAD has been evaluated to determine whether higher scores predict future sustainability or normalization;(16,24) this lack of established predictive validity is a limitation of both the instruments and our study. Despite this, the high response rate and consistent domain-level patterns in our study suggest that these instruments captured meaningful provider perceptions, which are important precursors to sustained adoption.(29) Ongoing analyses of MIMIC’s long-term impact on AMI care delivery will help confirm their predictive validity, addressing a key evidence gap in implementation science.(16,24) Future research should evaluate the long-term clinical impact of MIMIC, its potential for national scale-up, and system-level strategies to support long-term adoption. Repeat assessments of sustainability and normalization—ideally at multiple time points—may help identify key inflection points and guide adaptive implementation support. Incorporating sustainability planning into routine operational processes may further support long-term integration. Conclusion The MIMIC intervention remained in active use and was perceived by clinicians as both sustainable and normalized within emergency care workflows at KCMC following the conclusion of the pilot trial. These findings demonstrated the feasibility of sustaining a multicomponent intervention in a resource-limited setting when it aligned with clinical priorities and was reinforced by ongoing engagement. This study highlighted the utility of structured tools like CSAT and NoMAD for assessing early sustainment and normalization, particularly in low-resource acute care environments. Insights from this evaluation may inform efforts to strengthen the durability of similar interventions across LMIC health systems. Abbreviations AMI Acute Myocardial Infarction CSAT Clinical Sustainability Assessment Tool ED Emergency Department KCMC Kilimanjaro Christian Medical Centre LMICs Low–and Middle–Income Countries MIMIC Multicomponent Intervention to Improve Acute Myocardial Infarction Care NoMAD Normalization MeAsure Development questionnaire NPT Normalization Process Theory USD United States Dollar Declarations Ethics approval and consent to participate Ethical approval for this follow-up study was obtained from the Tanzania National Institute for Medical Research (NIMR/HQ/R.8a/Vol. IX/2436), Kilimanjaro Christian Medical Centre (Proposal 893), and the Duke Health Institutional Review Board (Pro00090902). All procedures adhered to the ethical principles outlined in the Declaration of Helsinki (2000 revision). Written informed consent was obtained from all participants prior to survey administration. Materials were available in both English and Swahili to ensure participant understanding, and participation was voluntary. Respondents could decline or withdraw at any time without penalty. Consent for publication Not applicable Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding The study was funded by the US National Heart, Lung, and Blood Institute (Grant #K23-HL155500). The funder had no role in the design, collection, analysis, or interpretation of data; in the writing of the manuscript; or in the decision to submit the manuscript for publication. Author’s Contributions FMSakita, JPB, and JTH conceived the study; JPB and JTH obtained funding for the study; FMShayo, WM, HBB, and JTH designed the study; EM, AMA, and JTH created the surveys; FMSakita, JJM, JPB, ZM, and JTH supervised the study; SS, ZM and JTH curated the data; CW, SS, and JTH conducted the data analysis; CW and JTH drafted the manuscript; all authors reviewed the manuscript for critical scientific content; all authors approved of the final submitted manuscript. Acknowledgements Not applicable References GBD 2017 Causes of Death Collaborators. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet Lond Engl. 2018 Nov 10;392(10159):1736–88. Landon BE, Hatfield LA, Bakx P, Banerjee A, Chen YC, Fu C, et al. Differences in Treatment Patterns and Outcomes of Acute Myocardial Infarction for Low- and High-Income Patients in 6 Countries. JAMA. 2023 Apr 4;329(13):1088–97. Levi F, Lucchini F, Negri E, La Vecchia C. Trends in mortality from cardiovascular and cerebrovascular diseases in Europe and other areas of the world. Heart Br Card Soc. 2002 Aug;88(2):119–24. World Heart Report 2023: Confronting the World’s Number One Killer. [Internet]. World Heart Federation; 2023 [cited 2025 July 24]. Available from: https://world-heart-federation.org/wp-content/uploads/World-Heart-Report-2023.pdf Goli S, Sakita FM, Kweka GL, Tarimo TG, Temu G, Thielman NM, et al. Thirty-day outcomes and predictors of mortality following acute myocardial infarction in northern Tanzania: A prospective observational cohort study. Int J Cardiol. 2021 Nov 1;342:23–8. Hertz JT, Sakita FM, Kweka GL, Limkakeng AT, Galson SW, Ye JJ, et al. Acute myocardial infarction under-diagnosis and mortality in a Tanzanian emergency department: A prospective observational study. Am Heart J. 2020 Aug;226:214–21. Berwanger O, Guimarães HP, Laranjeira LN, Cavalcanti AB, Kodama AA, Zazula AD, et al. Effect of a multifaceted intervention on use of evidence-based therapies in patients with acute coronary syndromes in Brazil: the BRIDGE-ACS randomized trial. JAMA. 2012 May 16;307(19):2041–9. Berwanger O, Guimarães HP, Laranjeira LN, Cavalcanti AB, Kodama A, Zazula AD, et al. A multifaceted intervention to narrow the evidence-based gap in the treatment of acute coronary syndromes: rationale and design of the Brazilian Intervention to Increase Evidence Usage in Acute Coronary Syndromes (BRIDGE-ACS) cluster-randomized trial. Am Heart J. 2012 Mar;163(3):323–9, 329.e1. Hertz JT, Sakita FM, Haukila KF, Shayo PS, Shayo FM, Willy J, et al. Acceptability and Feasibility of a Multicomponent Intervention to Improve Acute Myocardial Infarction Care in Northern Tanzania: the MIMIC Pilot Trial. MedRxiv Prepr Serv Health Sci. 2024 Dec 16;2024.12.13.24319026. Hertz JT, Sakita FM, Rahim FO, Mmbaga BT, Shayo F, Kaboigora V, et al. Multicomponent Intervention to Improve Acute Myocardial Infarction Care in Tanzania: Protocol for a Pilot Implementation Trial. JMIR Res Protoc. 2024 Sept 24;13:e59917. Hertz JT, Nworie JE, Shayo FM, Galson SW, Coaxum L, Daniel I, et al. Effect of a Multicomponent Intervention on Acute Myocardial Infarction Diagnosis and Treatment in Tanzania: The MIMIC Implementation Trial. Res Sq. 2024 Dec 12;rs.3.rs-5599267. Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci IS. 2009 Aug 7;4:50. Mahler L, Gustafson D, Evans A. Sustainability model and guide. National Health Service; 2010. Schell SF, Luke DA, Schooley MW, Elliott MB, Herbers SH, Mueller NB, et al. Public health program capacity for sustainability: a new framework. Implement Sci IS. 2013 Feb 1;8:15. Goodman RM, Steckler A. A model for the institutionalization of health promotion programs. Fam Community Health. 1989;11(4):63–78. Shelton RC, Chambers DA, Glasgow RE. An Extension of RE-AIM to Enhance Sustainability: Addressing Dynamic Context and Promoting Health Equity Over Time. Front Public Health. 2020;8:134. Malone S, Prewitt K, Hackett R, Lin JC, McKay V, Walsh-Bailey C, et al. The Clinical Sustainability Assessment Tool: measuring organizational capacity to promote sustainability in healthcare. Implement Sci Commun. 2021 July 17;2(1):77. Batterham P, Allenhof C, Cerga Pashoja A, Etzelmueller A, Fanaj N, Finch T, et al. Psychometric properties of two implementation measures: Normalization MeAsure Development questionnaire (NoMAD) and organizational readiness for implementing change (ORIC). Implement Res Pract. 2024;5:26334895241245448. Hertz JT, Stark K, Sakita FM, Mlangi JJ, Kweka GL, Prattipati S, et al. Adapting an Intervention to Improve Acute Myocardial Infarction Care in Tanzania: Co-Design of the MIMIC Intervention. Ann Glob Health. 2024;90(1):21. Finch TL, Girling M, May CR, Mair FS, Murray E, Treweek S, et al. Improving the normalization of complex interventions: part 2 - validation of the NoMAD instrument for assessing implementation work based on normalization process theory (NPT). BMC Med Res Methodol. 2018 Nov 15;18(1):135. Agulnik A, Malone S, Puerto-Torres M, Gonzalez-Ruiz A, Vedaraju Y, Wang H, et al. Reliability and validity of a Spanish-language measure assessing clinical capacity to sustain Paediatric Early Warning Systems (PEWS) in resource-limited hospitals. BMJ Open. 2021 Oct 20;11(10):e053116. Malone S, Prewitt K, McKay V, Zabotka L, Bacon C, Luke DA. Lowering the burden: Shorter versions of the Program Sustainability Assessment Tool (PSAT) and Clinical Sustainability Assessment Tool (CSAT). Implement Sci Commun. 2024 Oct 10;5(1):113. May CR, Cummings A, Girling M, Bracher M, Mair FS, May CM, et al. Using Normalization Process Theory in feasibility studies and process evaluations of complex healthcare interventions: a systematic review. Implement Sci IS. 2018 June 7;13(1):80. Moullin JC, Sklar M, Green A, Dickson KS, Stadnick NA, Reeder K, et al. Advancing the pragmatic measurement of sustainment: a narrative review of measures. Implement Sci Commun. 2020;1:76. Lamarche L, Clark RE, Parascandalo F, Mangin D. The implementation and validation of the NoMAD during a complex primary care intervention. BMC Med Res Methodol. 2022 June 19;22(1):175. Hertz JT, Sakita FM, Munshi ZR, Rahim FO, Mganga D, Kachenje A, et al. Implementation Outcomes of an Intervention to Improve Myocardial Infarction Care in Tanzania. Ann Glob Health. 2025;91(1):43. Novotni G, Taneska M, Novotni A, Fischer J, Iloski S, Ivanovska A, et al. North Macedonia interprofessional dementia care (NOMAD) - personalized care plans for people with dementia and caregiver psychoeducation delivered at home by interprofessional teams. Front Dement. 2024;3:1391471. Mwanga JR, Hokororo A, Ndosi H, Masenge T, Kalabamu FS, Tawfik D, et al. Evaluating the Implementation of the Pediatric Acute Care Education (PACE) Program in Northwestern Tanzania: A Mixed-Methods Study Guided by Normalization Process Theory. Res Sq. 2024 May 31;rs.3.rs-4432440. Al Fannah J, Al Naabi H, Al Harthi T, Al Habsi S, Al Fahdi F, Al Awaidy S. Clinical sustainability assessment of sepsis care bundle: a cross-sectional study. IJQHC Commun [Internet]. 2025 Apr 11 [cited 2025 July 21];5(1). Available from: https://academic.oup.com/ijcoms/article/doi/10.1093/ijcoms/lyaf003/8110084 Tavakol M, Dennick R. Making sense of Cronbach’s alpha. Int J Med Educ. 2011 June 27;2:53–5. Bujang MA, Omar ED, Baharum NA. A Review on Sample Size Determination for Cronbach’s Alpha Test: A Simple Guide for Researchers. Malays J Med Sci MJMS. 2018 Nov;25(6):85–99. Moore GF, Audrey S, Barker M, Bond L, Bonell C, Hardeman W, et al. Process evaluation of complex interventions: Medical Research Council guidance. BMJ. 2015 Mar 19;350:h1258. Supplementary Files Additionalfiles.docx Additionalfile1.xlsx Additionalfile2.docx Additionalfile3.docx Additionalfile4.png Additionalfile5.png Additionalfile6.png Cite Share Download PDF Status: Published Journal Publication published 15 Jan, 2026 Read the published version in Implementation Science Communications → Version 1 posted Editorial decision: Minor revision 31 Oct, 2025 Reviewers agreed at journal 21 Aug, 2025 Reviewers invited by journal 21 Aug, 2025 Editor assigned by journal 15 Aug, 2025 First submitted to journal 14 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7368551","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":503665945,"identity":"cf9c64c9-e0c7-450a-890f-90313eaca903","order_by":0,"name":"Claire Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDklEQVRIiWNgGAWjYDACdgaGA1Am44OEChvGBh4Qmw2PFmaEFmaDD2fSiNMCA2yCM9sOE9bC38z88HBFBUNi/+z2a8y8bedlN5w5fIDhQ9lhnFokDrMZHDxzhiFxxp0zZY95zt023nC2LYFxxjncWgyYGQwONrYx5DbcyEk35im7nbjhPI8B0Dp8Wtg/HGz8x5A7/0ZOmjQP2zmgFv4PzH/xauEB2tLAkLvhRvoxyRltBxI3nO1hYGbEo0XiME/BwYZjEvUbb+SAAjnZeOaZYwYHe86l49TC396++WNDjY2x3I30h8CotJPtO5P88MGPMmucWmCWATGPAZx7gJB6KGB/QKTCUTAKRsEoGGkAAEmGYhXQGC22AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0000-6543-9768","institution":"Duke University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Claire","middleName":"","lastName":"Wang","suffix":""},{"id":503665946,"identity":"54247d67-95c3-442c-b297-0aa1b18f015c","order_by":1,"name":"Francis M Sakita","email":"","orcid":"","institution":"Kilimanjaro Christian Medical Centre","correspondingAuthor":false,"prefix":"","firstName":"Francis","middleName":"M","lastName":"Sakita","suffix":""},{"id":503665947,"identity":"7bcb7c48-86ca-4341-a25a-4b1d2373272e","order_by":2,"name":"Spencer Sumner","email":"","orcid":"","institution":"Duke University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Spencer","middleName":"","lastName":"Sumner","suffix":""},{"id":503665948,"identity":"2d05730e-357c-4da5-95ba-7204b76d305f","order_by":3,"name":"Frida M Shayo","email":"","orcid":"","institution":"Kilimanjaro Christian Medical Centre","correspondingAuthor":false,"prefix":"","firstName":"Frida","middleName":"M","lastName":"Shayo","suffix":""},{"id":503665949,"identity":"343b9103-e3fe-4042-81b8-1d3b7a5ba46e","order_by":4,"name":"Zebadia Martin","email":"","orcid":"","institution":"Muhimbili University College of Health Sciences: Muhimbili University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Zebadia","middleName":"","lastName":"Martin","suffix":""},{"id":503665950,"identity":"e220382f-3130-4f34-bffa-5d1e59352ce3","order_by":5,"name":"Winnie Msangi","email":"","orcid":"","institution":"Muhimbili University College of Health Sciences: Muhimbili University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Winnie","middleName":"","lastName":"Msangi","suffix":""},{"id":503665951,"identity":"222048ad-6419-453f-bdce-83d975bddcad","order_by":6,"name":"James J Munisi","email":"","orcid":"","institution":"Tanga Regional Hospital","correspondingAuthor":false,"prefix":"","firstName":"James","middleName":"J","lastName":"Munisi","suffix":""},{"id":503665952,"identity":"c4af8d1d-0de1-4017-91db-cce600da13e6","order_by":7,"name":"Elly Mulesi","email":"","orcid":"","institution":"Muhimbili University College of Health Sciences: Muhimbili University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Elly","middleName":"","lastName":"Mulesi","suffix":""},{"id":503665953,"identity":"f8a7a79a-6130-41a2-8987-3ec12706fd9d","order_by":8,"name":"Ayshat M Aboud","email":"","orcid":"","institution":"Mnazi Mmoja Referral Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ayshat","middleName":"M","lastName":"Aboud","suffix":""},{"id":503665954,"identity":"d8d5d771-6b0f-41e8-83d2-be5750a1445f","order_by":9,"name":"Janet P Bettger","email":"","orcid":"","institution":"Duke Global Health Institute","correspondingAuthor":false,"prefix":"","firstName":"Janet","middleName":"P","lastName":"Bettger","suffix":""},{"id":503665955,"identity":"998411ab-a83b-4f7a-b782-bf0cfacc0806","order_by":10,"name":"Hayden B Bosworth","email":"","orcid":"","institution":"Duke University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hayden","middleName":"B","lastName":"Bosworth","suffix":""},{"id":503665956,"identity":"0f4755fd-6d08-4c58-9104-87772bb2e849","order_by":11,"name":"Julian T Hertz","email":"","orcid":"https://orcid.org/0000-0002-7396-4789","institution":"Duke Global Health Institute","correspondingAuthor":false,"prefix":"","firstName":"Julian","middleName":"T","lastName":"Hertz","suffix":""}],"badges":[],"createdAt":"2025-08-14 00:25:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7368551/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7368551/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s43058-026-00860-y","type":"published","date":"2026-01-15T16:28:39+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90193915,"identity":"69a58473-6c88-404b-bca7-fba3fe2de3c8","added_by":"auto","created_at":"2025-08-29 16:31:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":187014,"visible":true,"origin":"","legend":"\u003cp\u003eCSAT Domain Scores\u003c/p\u003e\n\u003cp\u003eAll items are scored 1 to 7; higher values represent stronger sustainability capacity in that\u003c/p\u003e\n\u003cp\u003edomain.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7368551/v1/2e246412cbac2f135c83b006.png"},{"id":90193911,"identity":"59283afe-5223-4a05-914f-60c5e5ee5e3a","added_by":"auto","created_at":"2025-08-29 16:31:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":153102,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of NoMAD Scores.\u003c/p\u003e\n\u003cp\u003ePanel A. NoMAD Domain Scores\u003c/p\u003e\n\u003cp\u003eAll items are scored from 1 to 5; higher values represent greater normalization for that subscale. The item “disrupts working relationships” (Collective Action domain) was reverse coded so that higher scores reflect greater normalization.\u003c/p\u003e\n\u003cp\u003ePanel B. General Normalization Item Scores\u003c/p\u003e\n\u003cp\u003eAll items are scored from 1 to 10.\u003c/p\u003e\n\u003cp\u003eFor “familiarity,” higher scores indicate the intervention feels more familiar.\u003c/p\u003e\n\u003cp\u003eFor “current” and “future” normalization, higher scores indicate greater perceived normalization.\u003c/p\u003e","description":"","filename":"Figure2panelA.png","url":"https://assets-eu.researchsquare.com/files/rs-7368551/v1/c1a1fc8130c28b985da7cca6.png"},{"id":100615856,"identity":"94858525-9363-4bf4-81b7-e6b2d039936d","added_by":"auto","created_at":"2026-01-19 17:37:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1012147,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7368551/v1/52e0335f-c058-4acc-a18d-76067558e981.pdf"},{"id":90193908,"identity":"aedbb168-2084-46ed-9a6f-621a6e4bc8ee","added_by":"auto","created_at":"2025-08-29 16:31:49","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":17013,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfiles.docx","url":"https://assets-eu.researchsquare.com/files/rs-7368551/v1/63433a142c26c96e3029eacd.docx"},{"id":90194517,"identity":"1440e27d-bd00-4fe1-91f9-96fe6b60d6b0","added_by":"auto","created_at":"2025-08-29 16:39:49","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":28885,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7368551/v1/828319ee2ef2946fd2e54fd5.xlsx"},{"id":90194523,"identity":"771aa61e-8c28-444d-8827-95964308e8aa","added_by":"auto","created_at":"2025-08-29 16:39:49","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":81610,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7368551/v1/e1833d67b7663e3fbac1374e.docx"},{"id":90194792,"identity":"4fde9b3c-057d-4e93-83b3-8de2f049a12a","added_by":"auto","created_at":"2025-08-29 16:47:49","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":33627,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile3.docx","url":"https://assets-eu.researchsquare.com/files/rs-7368551/v1/e06f09b7da1dc91e2dc04551.docx"},{"id":90194795,"identity":"47c975c0-aca8-4ac8-96df-7eb1334f9570","added_by":"auto","created_at":"2025-08-29 16:47:49","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":678202,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile4.png","url":"https://assets-eu.researchsquare.com/files/rs-7368551/v1/45be3c8ecf9d12e934b12fac.png"},{"id":90194793,"identity":"f6cf5864-7808-4d7f-b678-f5f3320cd520","added_by":"auto","created_at":"2025-08-29 16:47:49","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":574621,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile5.png","url":"https://assets-eu.researchsquare.com/files/rs-7368551/v1/5aa76c3c0016c07b88f179a7.png"},{"id":90194528,"identity":"c6fde6b4-c480-484c-b373-1378ac881a38","added_by":"auto","created_at":"2025-08-29 16:39:49","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":103205,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile6.png","url":"https://assets-eu.researchsquare.com/files/rs-7368551/v1/6f804b3787dfbf3af2648ad1.png"}],"financialInterests":"","formattedTitle":"Sustainability and normalization of an intervention to improve evidence-based myocardial infarction care in Tanzania","fulltext":[{"header":"Background","content":"\u003cp\u003eAcute myocardial infarction (AMI) is a leading cause of death globally, contributing to an estimated 3\u0026nbsp;million deaths annually.(1) While high-income countries have achieved significant reductions in AMI mortality through early diagnosis and use of evidence-based treatments,(2,3) low- and middle-income countries\u0026mdash;which now account for over 80% of global cardiovascular disease deaths\u0026mdash;continue to face major challenges in AMI recognition and care.(4)\u003c/p\u003e\u003cp\u003eIn Tanzania, AMI is frequently under-diagnosed and under-treated. In a northern Tanzanian emergency department (ED), we found that nearly 90% of AMI cases are missed during routine care, and fewer than 25% of patients with AMI receive recommended treatments such as aspirin.(5\u0026ndash;7) These gaps in care likely contributed to a 30-day mortality rate of 43% among AMI patients\u0026mdash;one of the highest AMI mortality rates ever reported worldwide.(6)\u003c/p\u003e\u003cp\u003eTo address these challenges, we developed the Multicomponent Intervention to Improve Acute Myocardial Infarction Care (MIMIC). Adapted from Brazil\u0026rsquo;s ACS-BRIDGE program and contextualized for the northern Tanzanian setting using the ADAPT-ITT framework,(7,8) MIMIC was evaluated in a one-year, single-arm pilot trial at Kilimanjaro Christian Medical Centre (KCMC) in northern Tanzania. The intervention led to substantial improvements in key care metrics, including rates of ECG and troponin testing, AMI identification, and evidence-based treatment with aspirin, clopidogrel, and heparin.(9\u0026ndash;11)\u003c/p\u003e\u003cp\u003eWhile findings were encouraging, many research-driven quality improvement interventions are not sustained after the study period ends due to challenges like limited institutional support, staff turnover, and poor integration into daily workflows.(12) Sustaining interventions is difficult even in high-resource settings; for example, one review found that a third of quality improvement projects in the UK National Health Service were not maintained in real-world clinical settings after one year.(13) Poor sustainability of quality improvement interventions can lead to diminished care quality, worse patient outcomes, and inefficient use of both financial and non-financial resources.(14,15) These concerns underscore the need to evaluate not only short-term outcomes of interventions but also whether interventions demonstrate long-term sustainability and become embedded in routine clinical practice. Indeed, a growing number of implementation scientists have emphasized the importance of assessing sustainability and normalization of interventions in real-world clinical settings, beyond short-term implementation-effectiveness trials.(16)\u003c/p\u003e\u003cp\u003eWe aimed to evaluate the longer-term sustainability and normalization of MIMIC following the conclusion of the one-year pilot trial. To do so, we conducted a follow-up survey among providers at KCMC using two validated implementation science tools: the Clinical Sustainability Assessment Tool (CSAT) and the Normalization MeAsure Development (NoMAD) questionnaire. CSAT measures an organization\u0026rsquo;s capacity to sustain interventions across seven domains, including leadership support, workflow fit, and performance monitoring.(17) NoMAD, based on Normalization Process Theory, assesses the extent to which an intervention becomes embedded in practice through constructs such as coherence, cognitive participation, collective action, and reflexive monitoring.(18) By administering CSAT and NoMAD, we sought to determine whether the intervention remained in use and to identify factors that supported or limited its continued implementation.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eSetting\u003c/h2\u003e\u003cp\u003eThis study was conducted at KCMC, a 630-bed tertiary referral hospital located in Moshi, northern Tanzania. KCMC serves a catchment area of over 15\u0026nbsp;million people and includes an ED that provides 24-hour acute care. The ED is staffed by a team of nurses and doctors in a high-volume, resource-limited environment. Local challenges such as staffing variability, high clinical workload, and infrastructural constraints may affect the long-term sustainability of quality improvement efforts.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eThe MIMIC Intervention\u003c/h3\u003e\n\u003cp\u003eThe MIMIC intervention was a multicomponent strategy designed to improve diagnosis and treatment of AMI in a low-resource emergency care setting. It included five core components: (1) a triage card placed on the stretchers of patients with potential AMI symptoms to prompt doctor consideration of the diagnosis; (2) a pocket reference card outlining evidence-based AMI care steps; (3) a web-based refresher training module on AMI diagnosis and treatment, required for all ED clinicians; (4) educational materials for patients, including printed pamphlets and visual messaging displayed in the ED waiting room; and (5) the appointment of doctor and nurse \u0026ldquo;champions\u0026rdquo; responsible for encouraging intervention uptake and coordinating implementation. All components were developed and refined using stakeholder input and context-specific adaptation and were delivered by KCMC ED staff during routine clinical care.(19)\u003c/p\u003e\u003cp\u003eThe MIMIC pilot trial was conducted at KCMC between September 1st, 2023, and August 31st, 2024. During the pilot trial, MIMIC was implemented by the KCMC ED staff; given the positive results of the pilot trial,(9\u0026ndash;11) the ED staff decided to continue implementing MIMIC as part of routine ED care.\u003c/p\u003e\n\u003ch3\u003eParticipant Selection\u003c/h3\u003e\n\u003cp\u003eAll full-time doctors and registered nurses employed in the KCMC ED between November 2024 and May 2025 were eligible to participate. Clinicians were included regardless of prior involvement in the MIMIC pilot trial, provided they were employed full-time in the ED at the time of survey distribution. At the time of the survey, the KCMC ED employed 18 full-time nurses and 17 full-time doctors.\u003c/p\u003e\n\u003ch3\u003eStudy Procedures\u003c/h3\u003e\n\u003cp\u003eParticipants were approached in person at work by a member of the research team during break periods. A brief explanation of the study\u0026rsquo;s purpose and procedures was provided. Participation was voluntary, and written informed consent was obtained prior to survey administration. The survey was anonymous and self-administered on a tablet to minimize social desirability bias. All survey questions were provided in both English and Swahili. Participants received 5,000 Tanzanian shillings (approximately 2 USD) as compensation for their time. Completed surveys were stored in a secure, password-protected database accessible only to the research team.\u003c/p\u003e\n\u003ch3\u003eSurvey\u003c/h3\u003e\n\u003cp\u003eThe survey combined CSAT and NoMAD, two widely used implementation science tools with strong reliability and construct validity.(17,20,21) CSAT has been applied in resource-limited hospital settings,(21) while NoMAD has been used across diverse healthcare contexts to assess normalization.(20)\u003c/p\u003e\u003cp\u003eWe administered the validated 21-item short version of the CSAT to minimize respondent burden while maintaining comprehensive assessment.(22) The tool includes 21 items across seven domains: engaged staff and leadership, organizational readiness, workflow integration, implementation and training, monitoring and evaluation, outcomes and effectiveness, and infrastructure.(17,22) Items were rated on a 7-point Likert scale ranging from \u0026ldquo;not at all\u0026rdquo; (score of 1) to \u0026ldquo;to a great extent\u0026rdquo; (score of 7), with an optional \u0026ldquo;don\u0026rsquo;t know\u0026rdquo; response. These domains were used to assess the ED\u0026rsquo;s capacity to sustain MIMIC over time.\u003c/p\u003e\u003cp\u003eNoMAD includes 20 items aligned with four constructs from Normalization Process Theory: coherence, cognitive participation, collective action, and reflexive monitoring.(18) Items were rated on a 5-point Likert scale from \u0026ldquo;strongly disagree\u0026rdquo; (score of 1) to \u0026ldquo;strongly agree\u0026rdquo; (score of 5) with optional \u0026ldquo;not relevant\u0026rdquo; and \u0026ldquo;don\u0026rsquo;t know\u0026rdquo; responses. These items were used to evaluate the extent to which MIMIC had become embedded in routine clinical practice.\u003c/p\u003e\u003cp\u003eSix supplementary questions addressed participants\u0026rsquo; roles, clinical experience, prior involvement in MIMIC, and perceived ability to influence ED workflows. The survey took approximately 15 minutes to complete. The full instrument is included as Additional file 1.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Methods\u003c/h2\u003e\u003cp\u003eSurvey responses were summarized using descriptive statistics. Total and domain-level scores for the CSAT and NoMAD were reported as means and standard deviations. Although Likert-scale data are ordinal, responses were treated as continuous to facilitate comparison across domains and constructs, consistent with prior studies using these instruments. (20,23\u0026ndash;25) Accordingly, CSAT scores were averaged within each of the seven domains to assess organizational capacity for sustainability.(17) NoMAD responses were similarly averaged within four constructs based on Normalization Process Theory.(20) Responses marked as \u0026ldquo;unable to answer\u0026rdquo; or \u0026ldquo;not relevant\u0026rdquo; were excluded from analysis. A total of 9 CSAT responses (1.2%) and 1 NoMAD response (0.1%) were excluded for this reason.\u003c/p\u003e\u003cp\u003eTo ensure scoring consistency in the NoMAD tool, the item \u003cem\u003e\u0026ldquo;The MIMIC intervention disrupts working relationships\u0026rdquo;\u003c/em\u003e (commonly listed as Item 10) was reverse coded so that higher scores indicate greater normalization, consistent with the directionality of other items.\u003c/p\u003e\u003cp\u003eTo evaluate differences by provider type (doctor vs. nurse), independent-samples t-tests were conducted for overall CSAT and NoMAD scores, as well as for each individual domain score within both tools. For the purposes of analysis, providers were categorized into two groups: \u0026ldquo;doctor\u0026rdquo; (including both general and emergency specialist doctors) and \u0026ldquo;nurse\u0026rdquo; (including all registered nurses. A p-value of less than 0.05 was considered significant statistically. Given the use of CSAT and NoMAD in a novel population from a low-resource emergency setting, we assessed the internal consistency of each instrument and its individual domains in our setting using Cronbach\u0026rsquo;s alpha.\u003c/p\u003e\u003cp\u003eStatistical analyses were performed using R Statistical Software (version 4.5.1; R Core Team 2024).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eEthics\u003c/h3\u003e\n\u003cp\u003eEthical approval for this follow-up study was obtained from the Tanzania National Institute for Medical Research (NIMR/HQ/R.8a/Vol. IX/2436), Kilimanjaro Christian Medical Centre (Proposal 893), and the Duke Health Institutional Review Board (Pro00090902). All procedures adhered to the ethical principles outlined in the Declaration of Helsinki (2000 revision). Written informed consent was obtained from all participants prior to survey administration. Materials were available in both English and Swahili to ensure participant understanding, and participation was voluntary. Respondents could decline or withdraw at any time without penalty.\u003c/p\u003e\u003c/p\u003e\n\u003ch3\u003eReporting guidelines\u003c/h3\u003e\n\u003cp\u003eThis manuscript was prepared in accordance with the StaRI checklist for reporting implementation studies and the STROBE checklist for observational studies. The completed checklists are provided in the Supplementary Materials (Additional file 2 and Additional file 3).\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eParticipant Characteristics\u003c/h2\u003e\u003cp\u003eAll 35 emergency department clinicians completed the survey, including 18 nurses (51%), 15 general doctors (43%), and 2 emergency specialist doctors (6%). The mean age was 32.7 years (SD 6.9), and participants reported an average of 3.4 years (SD 2.7) of clinical experience. Most participants (n\u0026thinsp;=\u0026thinsp;29, 83%) reported delivering the MIMIC intervention as part of their routine clinical duties, while the remaining six (17%) served as champions or supervisors (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParticipant Characteristics\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeasure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eN (%) or Mean (SD)\u003c/em\u003e\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale: 14 (40%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale: 21 (60%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32.7 (6.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYears of Clinical Experience\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.4 (2.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRole in MIMIC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDelivers MIMIC during routine ED work: 29 (83%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSupervises MIMIC (Champion/Supervisor): 6 (17%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProvider Type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmergency specialist physician: 2 (6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGeneral physician: 15 (43%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNurse: 18 (51%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Values are expressed as means (SD) for continuous variables or N (%) for categorical variables.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eCSAT Scores\u003c/h2\u003e\u003cp\u003eCSAT domain scores, rated on a 7-point Likert scale, indicated high perceived capacity to sustain the intervention. Scores ranged from 5.81 (SD 1.04) for \u003cem\u003eOrganizational Context and Capacity\u003c/em\u003e to 6.73 (SD 0.47) for \u003cem\u003eOutcomes and Effectiveness\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e; Fig.\u0026nbsp;1). Item-level response distributions are shown in Additional file 4.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCSAT and NoMAD Cronbach's alpha by domain\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDomain\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCronbach's alpha\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCSAT\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEngaged Staff and Leadership\u003c/p\u003e\u003cp\u003eEngaged Stakeholders\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003cp\u003e0.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrganizational Context and Capacity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWorkflow Integration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.83\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImplementation and Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonitoring and Evaluation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcomes and Effectiveness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.70\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverall CSAT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNoMAD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoherence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCognitive Participation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.83\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollective Action\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReflexive Monitoring\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverall NoMAD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eNoMAD Scores\u003c/p\u003e\u003cp\u003eNoMAD domain scores, rated on a 5-point Likert scale, reflected strong normalization of the MIMIC intervention into routine clinical practice. Scores were highest for Cognitive Participation (mean 4.69, SD 0.42) and Reflexive Monitoring (mean 4.50, SD 0.43), followed by Coherence (mean 4.46, SD 0.55) and Collective Action (mean 4.26, SD 0.51). Item-level response distributions are shown in Additional file 5.\u003c/p\u003e\u003cp\u003eThree general normalization items, rated on a 10-point Likert scale, were analyzed separately in accordance with prior literature.(20,23) Participants reported high familiarity with the MIMIC intervention (mean 8.97, SD 1.67), perceived it to be well normalized in current practice (mean 9.31, SD 1.41), and anticipated continued normalization in the future (mean 9.11, SD 1.69) (Fig.\u0026nbsp;2, Panel B). Full distributions are presented in Additional file 6.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eInternal Consistency\u003c/h2\u003e\u003cp\u003eInternal consistency of domain scores was assessed using Cronbach\u0026rsquo;s. Among CSAT domains, alphas ranged from 0.54 to 0.83 (overall\u0026thinsp;=\u0026thinsp;0.91). Among NoMAD domains, alphas ranged from 0.61 to 0.84 (overall\u0026thinsp;=\u0026thinsp;0.89). Cronbach\u0026rsquo;s alpha values for the full instrument and each domain are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. CSAT and NoMAD Cronbach's alpha by domain\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eProvider Comparison\u003c/h2\u003e\u003cp\u003eNurses rated Workflow Integration significantly higher than doctors (mean 6.76 vs. 6.20, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.034). No other CSAT domains differed significantly by provider type. NoMAD domain scores and general normalization items (familiarity, current and future normalization) also showed minimal variation between doctors and nurses (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCSAT and NoMAD Scores: Comparison of Nurse vs. Doctor Responses\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDomain\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDoctor\u003csup\u003e2\u003c/sup\u003e Mean (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNurse Mean (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCSAT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEngaged Staff and Leadership\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.12 (0.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.13 (1.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.973\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.24 (0.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.44 (0.62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.438\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrganizational Context and Capacity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.73 (1.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.9 (1.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.632\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWorkflow Integration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.2 (0.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.76 (0.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.034*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImplementation and Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.9 (1.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.33 (1.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.308\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonitoring and Evaluation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.06 (1.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.55 (0.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.106\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcomes and Effectiveness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.65 (0.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.81 (0.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.311\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverall CSAT Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.12 (0.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.42 (0.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.231\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNoMAD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoherence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.4 (0.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.51 (0.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.541\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCognitive Participation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.59 (0.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.79 (0.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.157\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollective Action\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.16 (0.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.35 (0.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.286\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReflexive Monitoring\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.51 (0.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.49 (0.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.910\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverall NoMAD Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.38 (0.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.51 (0.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.369\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGeneral Normalization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFamiliarity with MIMIC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.18 (1.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.78 (1.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.486\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCurrent Normalization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.24 (1.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.39 (1.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.753\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFuture Normalization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.18 (1.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.06 (1.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.835\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e1\u003c/sup\u003e Values are expressed as means (SD) for continuous variables or N (%) for categorical variables.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e2\u003c/sup\u003e Doctor group includes both general and emergency specialist physicians.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e* \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur findings suggest that MIMIC is both sustainable and normalized in routine emergency care at KCMC. High scores across CSAT and NoMAD domains reflect strong perceived organizational capacity and widespread normalization among providers. Domains related to perceived clinical benefit, compatibility with existing workflows, and individual engagement scored especially well, underscoring that MIMIC continues to be seen as valuable, aligned with clinical priorities, and well-integrated into clinical routines.\u003c/p\u003e\u003cp\u003eSeveral features of the MIMIC intervention likely contributed to these high scores. Its iterative, participatory design involving frontline KCMC providers ensured alignment with local workflows and responsiveness to site-specific barriers to AMI care.(19) Low-cost, intuitive tools\u0026mdash;such as color-coded triage cards, pocket reference guides, and discharge checklists\u0026mdash;were supported by visible clinical reminders and weekly case-based audits, enhancing provider engagement and reinforcing practice change. The intervention also emphasized shared responsibility between nurses and doctors, with designated champions from both cadres auditing AMI care and ensuring implementation of all MIMIC components.(19) Collectively, these characteristics\u0026mdash;workflow fit, perceived clinical value, collective ownership, and continuous feedback\u0026mdash;align closely with CSAT and NoMAD constructs and likely underlie the strong perceptions of MIMIC as both sustainable and normalized in routine care.\u003c/p\u003e\u003cp\u003eWhile most domains showed minimal variation by provider type, nurses rated workflow integration higher than doctors. This may reflect their central role in delivering key components of the intervention\u0026mdash;triaging patients for AMI symptoms, distributing educational materials, and reinforcing clinical reminders at the bedside\u0026mdash;as well as greater day-to-day exposure to MIMIC-related activities. Differences in responsibilities and proximity to specific implementation tasks may shape how integrated the program feels to different provider groups.\u003c/p\u003e\u003cp\u003eDespite overall strong results, lower scores in domains tied to organizational context and team-level coordination highlight areas for improvement. Item-level responses in these domains showed greater variability and more neutral ratings, particularly regarding perceived availability of financial resources, adequacy of training, and alignment of task assignments with staff skills. Notably, the items with the fewest respondents strongly agreeing on both the CSAT and NoMAD pertained to financial resources. The relevant CSAT item encompassed time, space, and funding needed to achieve intervention goals; responses to the NoMAD item regarding the availability of \u0026ldquo;sufficient resources\u0026rdquo; were similarly mixed. These findings echo challenges observed during the pilot trial\u0026mdash;staffing variability, resource constraints, and gaps in coordination across roles\u0026mdash;and point to modifiable barriers.(9\u0026ndash;11) Targeted strategies such as strengthened leadership engagement, clearer delineation of team-based roles, and enhanced interprofessional training may help bolster institutional support and promote long-term sustainability. Given that the full cost of the MIMIC intervention reported in the initial MIMIC pilot trial was 1324 USD annually, most of which was attributed to champion stipends,(26) securing additional funding or exploring non-monetary means to support the champions may further bolster long-term sustainability and normalization of the intervention.\u003c/p\u003e\u003cp\u003eThe overall domain-level patterns observed in our study are consistent with prior studies using CSAT and NoMAD.(17,21,27\u0026ndash;29) Across contexts, CSAT domains assessing leadership support, perceived benefit, and workflow integration often score highest, while organizational infrastructure and team coordination show greater variability, particularly in resource-limited environments..(17,21,29) Similarly, NoMAD evaluations in low-resource settings mirror our findings: the PACE program in Tanzania reported strong provider engagement and feedback mechanisms but lower scores in team coordination due to staffing and supply constraints.(28) A dementia care study likewise found high provider buy-in but emphasized infrastructure and interprofessional coordination as critical to sustainability.(27) These parallels reinforce that sustained normalization depends on both integration into clinical routines and broader organizational support.\u003c/p\u003e\u003cp\u003eWe found high Cronbach\u0026rsquo;s alpha values for both CSAT and NoMAD, indicating strong reliability and internal consistency. These results closely mirror the original validation findings reported by Malone et al. (2021) and Finch et al. (2020),(17,20) which were conducted in the United States and the United Kingdom, respectively. As is typical for multidimensional implementation measures, domains with fewer or conceptually diverse items (e.g., Organizational Context and Capacity; Reflexive Monitoring) yielded lower alpha values, while the full scales demonstrated robust internal consistency.(22,23) The slightly lower CSAT alphas likely reflect the combination of short subscales with few items and the modest sample size (n\u0026thinsp;=\u0026thinsp;35), both of which are known to attenuate reliability estimates.(30,31) Overall, these results support the reliability of both instruments for assessing sustainability and normalization in the Tanzanian healthcare context.\u003c/p\u003e\u003cp\u003eTo our knowledge, this study represents one of the earliest applications of the CSAT and NoMAD instruments in emergency medicine and among the first efforts to apply them in implementation research in sub-Saharan Africa. Use of these instruments proved feasible, relevant, and informative in our setting, as demonstrated by complete participation from eligible clinicians and consistent, interpretable responses across both tools. Researchers conducting implementation work elsewhere in the region should consider these tools to assess long-term sustainability and normalization\u0026mdash;two often-overlooked outcomes, particularly in resource-limited acute care settings where such data remain scarce.\u003c/p\u003e\u003cp\u003eThis study had several strengths. First, it assessed sustainability after active implementation support ended, offering rare insight into post-trial intervention persistence. Second, the combined use of CSAT and NoMAD provided a complementary evaluation of current integration and future sustainability capacity. Third, inclusion of both nurses and doctors allows for comparison across provider groups, and the 100% response rate (35 of 35) enhances internal validity and minimizes response bias.\u003c/p\u003e\u003cp\u003eSeveral limitations should also be noted. First, while CSAT and NoMAD capture key dimensions of implementation processes, they are best interpreted alongside complementary data sources. Prior work highlights the value of mixed-methods approaches\u0026mdash;such as qualitative interviews or direct observation\u0026mdash;to capture contextual nuances.(23,32) A qualitative study exploring provider perspectives on long-term MIMIC sustainability is ongoing and will be published separately. Second, the cross-sectional design limits our ability to assess temporal trends or infer causality; longitudinal data may better characterize how normalization evolves in response to staffing changes or workflow adaptations. Third, the study was conducted at a single emergency department with a modest sample size, limiting generalizability. Fourth, social desirability bias may have skewed responses toward favorable answers. However, independent, tablet-based survey administration likely reduced this bias and facilitated candid responses. Finally, neither the CSAT nor NoMAD has been evaluated to determine whether higher scores predict future sustainability or normalization;(16,24) this lack of established predictive validity is a limitation of both the instruments and our study. Despite this, the high response rate and consistent domain-level patterns in our study suggest that these instruments captured meaningful provider perceptions, which are important precursors to sustained adoption.(29) Ongoing analyses of MIMIC\u0026rsquo;s long-term impact on AMI care delivery will help confirm their predictive validity, addressing a key evidence gap in implementation science.(16,24)\u003c/p\u003e\u003cp\u003eFuture research should evaluate the long-term clinical impact of MIMIC, its potential for national scale-up, and system-level strategies to support long-term adoption. Repeat assessments of sustainability and normalization\u0026mdash;ideally at multiple time points\u0026mdash;may help identify key inflection points and guide adaptive implementation support. Incorporating sustainability planning into routine operational processes may further support long-term integration.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe MIMIC intervention remained in active use and was perceived by clinicians as both sustainable and normalized within emergency care workflows at KCMC following the conclusion of the pilot trial. These findings demonstrated the feasibility of sustaining a multicomponent intervention in a resource-limited setting when it aligned with clinical priorities and was reinforced by ongoing engagement. This study highlighted the utility of structured tools like CSAT and NoMAD for assessing early sustainment and normalization, particularly in low-resource acute care environments. Insights from this evaluation may inform efforts to strengthen the durability of similar interventions across LMIC health systems.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eAMI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAcute Myocardial Infarction\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eCSAT\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eClinical Sustainability Assessment Tool\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eED\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEmergency Department\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eKCMC\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eKilimanjaro Christian Medical Centre\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eLMICs\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLow\u0026ndash;and Middle\u0026ndash;Income Countries\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eMIMIC\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMulticomponent Intervention to Improve Acute Myocardial Infarction Care\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eNoMAD\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNormalization MeAsure Development questionnaire\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eNPT\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNormalization Process Theory\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eUSD\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eUnited States Dollar\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for this follow-up study was obtained from the Tanzania National Institute for Medical Research (NIMR/HQ/R.8a/Vol. IX/2436), Kilimanjaro Christian Medical Centre (Proposal 893), and the Duke Health Institutional Review Board (Pro00090902). All procedures adhered to the ethical principles outlined in the Declaration of Helsinki (2000 revision). Written informed consent was obtained from all participants prior to survey administration. Materials were available in both English and Swahili to ensure participant understanding, and participation was voluntary. Respondents could decline or withdraw at any time without penalty.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was funded by the US National Heart, Lung, and Blood Institute (Grant #K23-HL155500). The funder had no role in the design, collection, analysis, or interpretation of data; in the writing of the manuscript; or in the decision to submit the manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFMSakita, JPB, and JTH conceived the study; JPB and JTH obtained funding for the study; FMShayo, WM, HBB, and JTH designed the study; EM, AMA, and JTH created the surveys; FMSakita, JJM, JPB, ZM, and JTH supervised the study; SS, ZM and JTH curated the data; CW, SS, and JTH conducted the data analysis; CW and JTH drafted the manuscript; all authors reviewed the manuscript for critical scientific content; all authors approved of the final submitted manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGBD 2017 Causes of Death Collaborators. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980\u0026ndash;2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet Lond Engl. 2018 Nov 10;392(10159):1736\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLandon BE, Hatfield LA, Bakx P, Banerjee A, Chen YC, Fu C, et al. Differences in Treatment Patterns and Outcomes of Acute Myocardial Infarction for Low- and High-Income Patients in 6 Countries. JAMA. 2023 Apr 4;329(13):1088\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLevi F, Lucchini F, Negri E, La Vecchia C. Trends in mortality from cardiovascular and cerebrovascular diseases in Europe and other areas of the world. Heart Br Card Soc. 2002 Aug;88(2):119\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWorld Heart Report 2023: Confronting the World\u0026rsquo;s Number One Killer. [Internet]. World Heart Federation; 2023 [cited 2025 July 24]. Available from: https://world-heart-federation.org/wp-content/uploads/World-Heart-Report-2023.pdf\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoli S, Sakita FM, Kweka GL, Tarimo TG, Temu G, Thielman NM, et al. Thirty-day outcomes and predictors of mortality following acute myocardial infarction in northern Tanzania: A prospective observational cohort study. Int J Cardiol. 2021 Nov 1;342:23\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHertz JT, Sakita FM, Kweka GL, Limkakeng AT, Galson SW, Ye JJ, et al. Acute myocardial infarction under-diagnosis and mortality in a Tanzanian emergency department: A prospective observational study. Am Heart J. 2020 Aug;226:214\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBerwanger O, Guimar\u0026atilde;es HP, Laranjeira LN, Cavalcanti AB, Kodama AA, Zazula AD, et al. Effect of a multifaceted intervention on use of evidence-based therapies in patients with acute coronary syndromes in Brazil: the BRIDGE-ACS randomized trial. JAMA. 2012 May 16;307(19):2041\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBerwanger O, Guimar\u0026atilde;es HP, Laranjeira LN, Cavalcanti AB, Kodama A, Zazula AD, et al. A multifaceted intervention to narrow the evidence-based gap in the treatment of acute coronary syndromes: rationale and design of the Brazilian Intervention to Increase Evidence Usage in Acute Coronary Syndromes (BRIDGE-ACS) cluster-randomized trial. Am Heart J. 2012 Mar;163(3):323\u0026ndash;9, 329.e1.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHertz JT, Sakita FM, Haukila KF, Shayo PS, Shayo FM, Willy J, et al. Acceptability and Feasibility of a Multicomponent Intervention to Improve Acute Myocardial Infarction Care in Northern Tanzania: the MIMIC Pilot Trial. MedRxiv Prepr Serv Health Sci. 2024 Dec 16;2024.12.13.24319026.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHertz JT, Sakita FM, Rahim FO, Mmbaga BT, Shayo F, Kaboigora V, et al. Multicomponent Intervention to Improve Acute Myocardial Infarction Care in Tanzania: Protocol for a Pilot Implementation Trial. JMIR Res Protoc. 2024 Sept 24;13:e59917.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHertz JT, Nworie JE, Shayo FM, Galson SW, Coaxum L, Daniel I, et al. Effect of a Multicomponent Intervention on Acute Myocardial Infarction Diagnosis and Treatment in Tanzania: The MIMIC Implementation Trial. Res Sq. 2024 Dec 12;rs.3.rs-5599267.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDamschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci IS. 2009 Aug 7;4:50.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMahler L, Gustafson D, Evans A. Sustainability model and guide. National Health Service; 2010.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchell SF, Luke DA, Schooley MW, Elliott MB, Herbers SH, Mueller NB, et al. Public health program capacity for sustainability: a new framework. Implement Sci IS. 2013 Feb 1;8:15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoodman RM, Steckler A. A model for the institutionalization of health promotion programs. Fam Community Health. 1989;11(4):63\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShelton RC, Chambers DA, Glasgow RE. An Extension of RE-AIM to Enhance Sustainability: Addressing Dynamic Context and Promoting Health Equity Over Time. Front Public Health. 2020;8:134.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMalone S, Prewitt K, Hackett R, Lin JC, McKay V, Walsh-Bailey C, et al. The Clinical Sustainability Assessment Tool: measuring organizational capacity to promote sustainability in healthcare. Implement Sci Commun. 2021 July 17;2(1):77.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBatterham P, Allenhof C, Cerga Pashoja A, Etzelmueller A, Fanaj N, Finch T, et al. Psychometric properties of two implementation measures: Normalization MeAsure Development questionnaire (NoMAD) and organizational readiness for implementing change (ORIC). Implement Res Pract. 2024;5:26334895241245448.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHertz JT, Stark K, Sakita FM, Mlangi JJ, Kweka GL, Prattipati S, et al. Adapting an Intervention to Improve Acute Myocardial Infarction Care in Tanzania: Co-Design of the MIMIC Intervention. Ann Glob Health. 2024;90(1):21.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFinch TL, Girling M, May CR, Mair FS, Murray E, Treweek S, et al. Improving the normalization of complex interventions: part 2 - validation of the NoMAD instrument for assessing implementation work based on normalization process theory (NPT). BMC Med Res Methodol. 2018 Nov 15;18(1):135.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAgulnik A, Malone S, Puerto-Torres M, Gonzalez-Ruiz A, Vedaraju Y, Wang H, et al. Reliability and validity of a Spanish-language measure assessing clinical capacity to sustain Paediatric Early Warning Systems (PEWS) in resource-limited hospitals. BMJ Open. 2021 Oct 20;11(10):e053116.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMalone S, Prewitt K, McKay V, Zabotka L, Bacon C, Luke DA. Lowering the burden: Shorter versions of the Program Sustainability Assessment Tool (PSAT) and Clinical Sustainability Assessment Tool (CSAT). Implement Sci Commun. 2024 Oct 10;5(1):113.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMay CR, Cummings A, Girling M, Bracher M, Mair FS, May CM, et al. Using Normalization Process Theory in feasibility studies and process evaluations of complex healthcare interventions: a systematic review. Implement Sci IS. 2018 June 7;13(1):80.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoullin JC, Sklar M, Green A, Dickson KS, Stadnick NA, Reeder K, et al. Advancing the pragmatic measurement of sustainment: a narrative review of measures. Implement Sci Commun. 2020;1:76.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLamarche L, Clark RE, Parascandalo F, Mangin D. The implementation and validation of the NoMAD during a complex primary care intervention. BMC Med Res Methodol. 2022 June 19;22(1):175.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHertz JT, Sakita FM, Munshi ZR, Rahim FO, Mganga D, Kachenje A, et al. Implementation Outcomes of an Intervention to Improve Myocardial Infarction Care in Tanzania. Ann Glob Health. 2025;91(1):43.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNovotni G, Taneska M, Novotni A, Fischer J, Iloski S, Ivanovska A, et al. North Macedonia interprofessional dementia care (NOMAD) - personalized care plans for people with dementia and caregiver psychoeducation delivered at home by interprofessional teams. Front Dement. 2024;3:1391471.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMwanga JR, Hokororo A, Ndosi H, Masenge T, Kalabamu FS, Tawfik D, et al. Evaluating the Implementation of the Pediatric Acute Care Education (PACE) Program in Northwestern Tanzania: A Mixed-Methods Study Guided by Normalization Process Theory. Res Sq. 2024 May 31;rs.3.rs-4432440.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAl Fannah J, Al Naabi H, Al Harthi T, Al Habsi S, Al Fahdi F, Al Awaidy S. Clinical sustainability assessment of sepsis care bundle: a cross-sectional study. IJQHC Commun [Internet]. 2025 Apr 11 [cited 2025 July 21];5(1). Available from: https://academic.oup.com/ijcoms/article/doi/10.1093/ijcoms/lyaf003/8110084\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTavakol M, Dennick R. Making sense of Cronbach\u0026rsquo;s alpha. Int J Med Educ. 2011 June 27;2:53\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBujang MA, Omar ED, Baharum NA. A Review on Sample Size Determination for Cronbach\u0026rsquo;s Alpha Test: A Simple Guide for Researchers. Malays J Med Sci MJMS. 2018 Nov;25(6):85\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoore GF, Audrey S, Barker M, Bond L, Bonell C, Hardeman W, et al. Process evaluation of complex interventions: Medical Research Council guidance. BMJ. 2015 Mar 19;350:h1258.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"implementation-science-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iscm","sideBox":"Learn more about [Implementation Science Communications](https://implementationsciencecomms.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ISCM/default.aspx","title":"Implementation Science Communications","twitterHandle":"@ImplementSci","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Implementation Science, Sustainability, Normalization Process Theory, emergency department, LMICs, Tanzania, sub-Saharan Africa, myocardial infarction","lastPublishedDoi":"10.21203/rs.3.rs-7368551/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7368551/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThe Multicomponent Intervention to Improve Acute Myocardial Infarction Care (MIMIC) was developed to address gaps in AMI diagnosis and treatment in northern Tanzania. Although initial implementation was promising, many quality improvement interventions are not sustained after research support ends, especially in resource-limited settings. Evaluating sustainability and normalization is essential for understanding the long-term impact of implementation research. We evaluated these outcomes for the MIMIC intervention in a Tanzanian emergency department following a pilot implementation trial.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe conducted a cross-sectional survey of all full-time emergency department clinicians (n\u0026thinsp;=\u0026thinsp;35) at Kilimanjaro Christian Medical Centre (KCMC) using two validated implementation science tools: the Clinical Sustainability Assessment Tool (CSAT) and the Normalization MeAsure Development (NoMAD) questionnaire. The CSAT assesses seven domains, with higher scores reflecting greater perceived sustainability. The NoMAD measures four constructs, with higher scores indicating stronger normalization. For each domain, scores were summarized descriptively (means, standard deviations) and compared by provider type (doctors vs. registered nurses) using independent t-tests.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAll 35 eligible clinicians (100%) completed the survey. Mean CSAT domain scores ranged from 5.81 (SD 1.04) for \u003cem\u003eOrganizational Context and Capacity\u003c/em\u003e to 6.73 (SD 0.47) for \u003cem\u003eOutcomes and Effectiveness\u003c/em\u003e (scale 1\u0026ndash;7). Mean NoMAD scores were uniformly high and clustered within a narrow range from 4.26 (SD 0.51) for \u003cem\u003eCollective Action\u003c/em\u003e to 4.69 (SD 0.42) for \u003cem\u003eCognitive Participation\u003c/em\u003e (scale 1\u0026ndash;5). Nurses reported significantly greater \u003cem\u003eWorkflow Integration\u003c/em\u003e than doctors (mean 6.76 vs. 6.20, p\u0026thinsp;=\u0026thinsp;0.034); no other domains differed significantly by provider type. Domains related to perceived clinical benefit, individual engagement, and feedback scored highest, whereas organizational context and financial support scored comparatively lower.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThis study is among the first to apply the CSAT and NoMAD tools to evaluate a quality improvement intervention in sub-Saharan Africa. Findings indicate that MIMIC is both highly sustainable and normalized in routine care at KCMC, as reflected by consistently high mean domain scores across both instruments, although formal thresholds for these measures have not yet been established. Strengthening organizational capacity and long-term support, particularly financing and team coordination, may further enhance sustained implementation.\u003c/p\u003e","manuscriptTitle":"Sustainability and normalization of an intervention to improve evidence-based myocardial infarction care in Tanzania","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-29 16:31:44","doi":"10.21203/rs.3.rs-7368551/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revision","date":"2025-10-31T15:54:15+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-08-21T14:59:00+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-21T12:24:33+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-15T07:54:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Implementation Science Communications","date":"2025-08-14T10:11:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"implementation-science-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iscm","sideBox":"Learn more about [Implementation Science Communications](https://implementationsciencecomms.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ISCM/default.aspx","title":"Implementation Science Communications","twitterHandle":"@ImplementSci","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e1537cce-ed59-4dca-9a3f-4aeedecd9c41","owner":[],"postedDate":"August 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-19T17:03:05+00:00","versionOfRecord":{"articleIdentity":"rs-7368551","link":"https://doi.org/10.1186/s43058-026-00860-y","journal":{"identity":"implementation-science-communications","isVorOnly":false,"title":"Implementation Science Communications"},"publishedOn":"2026-01-15 16:28:39","publishedOnDateReadable":"January 15th, 2026"},"versionCreatedAt":"2025-08-29 16:31:44","video":"","vorDoi":"10.1186/s43058-026-00860-y","vorDoiUrl":"https://doi.org/10.1186/s43058-026-00860-y","workflowStages":[]},"version":"v1","identity":"rs-7368551","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7368551","identity":"rs-7368551","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}