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Open research questions in Emergency and Acute Care Studies

55 unresolved questions extracted from the limitations and future-work sections of 989 Emergency and Acute Care Studies papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • OBJECTIVESPopulation aging is a major contributor to increasing demand for emergency medical services (EMS), yet EMS workforce projections based on population data remain limited.

    Projecting EMS Workforce Demand in an Aging State: A Florida Forecast Through 2035 · 2026 · DOI

  • Future multicenter randomized or stepped-wedge cluster trials with concurrent controls, subtype documentation, reperfusion modality capture, door-to-balloon and door-to-needle metrics, infarct territory data, blinded endpoint adjudication, and longer follow-up are warranted to confirm and extend these preliminary findings.

    Emergency procedural pathway combined with graded zoning management is associated with improved in-hospital survival and quality of life in patients with acute myocardial infarction · 2026 · DOI

  • In contrast, few studies have examined near-term psychiatric ED presentation in an outpatient 352 psychiatry population, and fewer still have shown potential for utility at a single practice level.

    A Local Outpatient Practice-Level Prediction Model for Short-Term Psychiatric Emergency Presentation · 2026 · DOI

  • II. LITERATURE REVIEW The efficiency and readiness of emergency departments (EDs) play a vital role in determining the quality and timeliness of healthcare services, especially during emergencies and trauma incidents. Numerous studies across Saudi Arabia and the broader Gulf region have explored factors such as triage systems, patientcentered care, overcrowding, trauma management. This section reviews eight key pieces of literature that collectively inform the current research on ―Readiness of Emergency Departments in Saudi General Hospitals: Evaluating Triage Efficiency and Trauma Response.‖ training, staff and 1.

    READINESS OF EMERGENCY DEPARTMENTS IN SAUDI GENERAL HOSPITALS: EVALUATING TRIAGE EFFICIENCY AND TRAUMA · 2026 · DOI

  • deficiencies of internal and surgical specialists about the emergency department should be determined, and branch-oriented trainings should be planned. the to CONCLUSION In conclusion, the effective functioning of emergency departments is directly related to a multidisciplinary team approach and a common training ground for all stakeholders. The knowledge of physicians from all branches interacting with the emergency department about emergency care principles, triage systems, and emergency department functioning protocols will both improve the quality of patient care and reduce the burden of this vital part of the health system by improving the emergency department workflow.

    Evaluation of Knowledge Levels of Non-Emergency Medicine Specialists about Emergency Service Functioning and Intensity · 2026 · DOI

  • While a full exploration of clinical integration is beyond the scope of this work, we hope our study serves as a foundational step, by addressing two critical pil- lars of clinical AI, predictive accuracy and bias, and provides a springboard for future research that brings these systems closer to safe, real-world deployment.

    From Promising Capabilities to Pervasive Bias: Assessing Large Language Models for Emergency Department Triage · 2026 · DOI

  • simple selection sampling, the examination of demographic This study can be evaluated in light of its strengths and limitations. Among its key strengths is the use of a validated VARK questionnaire (Version 8.01) to reliably assess learning preferences. Another significant strength is the inclusion of emergency medicine residents from eight major tertiary care centers across Riyadh, which enhances the generalizability of findings within the Saudi context. In addition, the standardized data collection through electronic surveys during academic days, strengthened combined with random bias. methodological rigor while minimizing Furthermore, influences, particularly gender and residency year, provided valuable insights into how training progression and sociocultural factors may shape educational experiences. However, several limitations warrant consideration. The final sample size of 121 residents fell short of the calculated target of 197 due to recruitment challenges and response availability during the study period. This reduction may have lowered the statistical power of the study and limited the ability to detect smaller associations between learning preferences and curriculum satisfaction. Additionally, the reduced sample size may affect the precision of estimates for less dominant learning preferences. The exclusive focus on Riyadh-based centers may not fully capture regional variations in training approaches, while the cross-sectional design precludes assessment of how learning preferences evolve over time. Moreover, self-reporting biases and potential non- response patterns may have influenced results, as well as the study’s quantitative nature did not explore the underlying reasons behind residents’ preferences and satisfaction levels. Furthermore, the curriculum satisfaction survey used in this study was developed by the research team and reviewed by faculty for content relevance, but it was not formally validated. No psychometric properties (e.g., Cronbach’s alpha, construct validity) were assessed prior to implementation. Also, the survey was designed to assess overall satisfaction rather than modality- specific satisfaction; it did not include items targeting each VARK domain separately (e.g., no specific item on adequacy of lecture sessions for aural learners). This may have limited the ability to fully capture the correlation between individual learning preferences and satisfaction with corresponding teaching methods. These limitations highlight opportunities for future multi-center longitudinal studies incorporating qualitative methods to provide deeper understanding of curriculum optimization in emergency medicine education.

    Exploring VARK learning preferences, curriculum satisfaction, and the impact of demographic factors among emergency medicine residents at multiple training centers in Riyadh · 2026 · DOI

  • The interrupted time series analysis identified that ambulance offload delays are declining and ED LOS is stabilising post-COVID, but the underlying mechanisms driving these temporal trends remain unexplained; prospective multi-centre studies with qualitative investigations into ED operational dynamics are needed to understand what specific operational changes or interventions contributed to these improvements.

    Declining Ambulance Offload Delays and Stabilised Emergency Department Length of Stay Post-COVID: An Interrupted Time Series Analysis · 2026 · DOI

  • The study integrated SERP-30d with PACS triage across four acuity levels but did not evaluate whether the 16.1% of patients identified as high-risk (SERP-30d ≥26) differ meaningfully in clinical characteristics from low-risk patients within the same PACS category, limiting understanding of the interpretable machine learning features driving risk stratification in borderline triage cases.

    Integrating the interpretable machine learning Score For Emergency Risk Prediction (SERP) with emergency department triage to better predict 30-Day mortality · 2026 · DOI

  • While PACS+ model 1 achieved higher sensitivity (0.835) and PPV (0.084) for 30-day mortality compared to PACS alone (0.979 sensitivity, 0.034 PPV), the clinical impact on reducing under-triage and over-triage rates in the context of ED crowding and admission delays has not been measured, particularly whether SERP-30d integration affects patient disposition decisions and subsequent outcomes.

    Integrating the interpretable machine learning Score For Emergency Risk Prediction (SERP) with emergency department triage to better predict 30-Day mortality · 2026 · DOI

  • The development and test cohorts (n=97,188 and n=97,212 respectively) were drawn from a single ED with specific demographic composition (70.5% Chinese, 13.1% Malay, 12.1% Indian); validation in multi-ethnic and multi-center ED settings with different baseline mortality rates and patient acuity distributions is needed to establish generalizability of the PACS+ models.

    Integrating the interpretable machine learning Score For Emergency Risk Prediction (SERP) with emergency department triage to better predict 30-Day mortality · 2026 · DOI

  • The PACS+ models show differential performance across timeframes (2-day AUC 0.870, 7-day AUC 0.859, 30-day AUC 0.828 for model 1), but the mechanisms underlying this performance degradation at longer prediction horizons have not been analyzed, nor has the optimal SERP-30d threshold of ≥26 been validated across age-stratified cohorts despite evidence that age incorporation affects triage accuracy.

    Integrating the interpretable machine learning Score For Emergency Risk Prediction (SERP) with emergency department triage to better predict 30-Day mortality · 2026 · DOI

  • Our study has several strengths and limitations. One of the key strengths of this study is its rigorous methodol- ogy, adhering to PRISMA guidelines for transparency and reproducibility and employing the PROBAST framework to assess the quality and risk of bias in included studies [7]. Furthermore, this is the first systematic review and meta- analysis to evaluate the diagnostic accuracy of ML mod- els in predicting hospital admission in the paediatric ED from data obtained at triage, providing a comprehensive synthesis of available evidence. A sensitivity analysis was conducted to assess the robustness of the findings, ensuring the reliability of the results. Despite the promising findings, limitations must be acknowledged. The small number of included studies and the high degree of heterogeneity—stemming from vari- ations in data preprocessing, variable selection, outcome definitions, and unspecified hospitalization timing—limit generalizability. Future meta-analyses should address these European Journal of Pediatrics (2026) 185:229 Page 11 of 12 229 issues through study stratification or meta-regression. In addition, the absence of a standardized definition of hospi- tal admission, often influenced by subjective clinical judg- ment, affects model reproducibility and warrants further investigation using more objective criteria. Furthermore, hospitalization timings were unspecified across studies and therefore will likely be a source of heterogeneity. Most models were developed using retrospective data with lim- ited external validation, highlighting the need for prospec- tive studies to confirm clinical utility. Incomplete reporting in some studies also impacted quality assessment. Finally, although restricting inclusion to studies using data avail- able at triage facilitated comparability, it excluded models incorporating additional diagnostic data, potentially limit- ing variable identification. This was done to avoid the intro- duction of important disparities in training data that could lead to biased or overly optimistic estimates of diagnostic performance. Future research should incorporate a broader range of studies while accounting for differences in model development and training to support the advancement of ML implementation in paediatric emergency department triage.

    Machine learning to predict hospital admission at triage in paediatric emergency care: A meta-analysis · 2026 · DOI

  • Although the period of data researched and presented was only over 4 months (01 January 2019 to 30 April 2019), the study highlights gaps in EMS data related to patients with NCDs who may require palliative care, noting that symptoms and keywords merely estimate potential need rather than accurately identifying current demand. Structural deficiencies in PRFs, such as the omission of risk factors like smoking, likely lead to underdiagnoses of conditions such as chronic obstructive pulmonary disease and emphasise the need for repeat call-out data for better insight; this is also a limitation of the retrospective research design. The timing and restrictions on data collection presented by COVID-19 influenced the timing and consistency of data collection, which could have resulted in inaccurate and missing data.

    Reframing Emergency Medical Service in the context of chronic non-communicable disease and palliative care · 2026 · DOI

  • A key strength of this study is its multi-site, qualitative design, which enabled rich, contextualized insights into the implementation of virtual urgent care across diverse rural settings, including multiple professional roles also ensured a range of perspectives from frontline staff. Limitations include participant demographics were not collected to preserve anonymity in small settings, limiting the ability to assess how experiences varied by role or tenure, because data relied on self-report and group discussion. There is also a risk of recall bias and social desirability bias.

    Implementing virtual urgent care services in emergency departments: a multi-site focus group study of adaptation and sustainability · 2026 · DOI

  • Despite the promising results, this study has several limitations. First, our evaluation was conducted in a simulated environment, which cannot fully replicate the high-stress, unpredictable nature of real-world 911 calls, Li et al. BMC Emergency Medicine (2026) 26:78 Page 17 of 20 including background noise and extreme caller emotional states, as well as low-affect/stoic presentations where urgency may be less overtly displayed in talk [60, 61]. While our main evaluation uses English dialogues, we additionally conducted an English-only stress test in which the caller agent’s functional English communication was constrained (fluent English vs LEP-English prompt setting). This supplementary analysis found no statistically significant between-condition differences across rubric dimensions, although guidance delivery showed the largest non-significant trends (Supplementary Methods S7). In this supplementary experiment, “limited proficiency” was operationalized as an Englishonly prompt constraint rather than true multilingual or interpreter-mediated communication. Specifically, the caller agent was instructed to remain English-speaking but use short phrases, simple vocabulary, grammatical errors, occasional misunderstanding, and greater difficulty responding to long or bundled questions. This manipulation was intended to approximate reduced functional English communication under stress, allowing a controlled test of how constrained comprehension and expression may affect dispatch interaction quality. However, this design does not capture true multilingual interactions (e.g., mixed-language or code-switched calls), nor does it evaluate how language identification, translation, or culturally specific phrasing might affect comprehension and repair; extending the framework to non-English and mixed-language dispatch scenarios remains an important direction for future work. Second, to simplify scenario generation and enable controlled comparisons, we fixed the caller location to a single placeholder address (“123 Main Street”) across cases. This choice reduces diversity in address formats and removes realistic complexities that often drive dispatch delays and miscommunication in practice (e.g., incomplete addresses, landmarks, apartment/building identifiers, rural locations, caller uncertainty, or mobile callers in transit). Future studies should introduce location variability and structured address perturbations to more faithfully test location elicitation, confirmation strategies, and error recovery under realistic conditions.

    DispatchMAS: fusing taxonomy and artificial intelligence agents for emergency medical services · 2026 · DOI

  • Social emergency medicine education and infrastructure requirements are identified as necessary but currently non-existent in many emergency departments, yet the paper does not specify what competencies, curriculum components, or resource allocations emergency physicians need to function as social welfare navigators.

    Principles of Social Emergency Medicine · 2019 · DOI

  • The authors emphasize that emergency medicine researchers must collaborate with departments of public health, law enforcement, and case managers, but provide no concrete framework for integrating data collection, outcome tracking, or intervention evaluation across these traditionally siloed systems.

    Principles of Social Emergency Medicine · 2019 · DOI

  • The paper notes that firearm-related violence and injury prevention research was unstudied for 2 decades due to the Dickey Amendment, but does not identify current gaps in understanding how emergency physicians should systematically screen for, document, or intervene on firearm-related social risk factors within ED protocols.

    Principles of Social Emergency Medicine · 2019 · DOI

  • Research on how social factors intersect with emergency care remains fundamentally uncertain, but the paper does not delineate which specific social factors (housing, food insecurity, violence exposure, legal status) have the strongest causal impact on emergency department utilization, severity of presentation, or clinical outcomes.

    Principles of Social Emergency Medicine · 2019 · DOI

  • The authors call for prospective interventional trials in social emergency medicine but do not specify what types of social interventions should be prioritized for clinical trials, what outcome measures should be standardized across studies, or how to design rigorous controls when studying social determinants of health in emergency care settings.

    Principles of Social Emergency Medicine · 2019 · DOI

  • The paper identifies that social emergency medicine research networks need to be established to enable multicenter studies, but provides no specific framework for how these networks should be structured, what data standardization protocols should be implemented, or how to coordinate between emergency departments and external partners in public health and law enforcement.

    Principles of Social Emergency Medicine · 2019 · DOI

  • But the role of the non-ICU staff nurse during a MET call remains unclear; nurses were neutral about their level of understanding of and comfort with their roles as members of the MET.

    Original Research: The Role of the Non-ICU Staff Nurse on a Medical Emergency Team: Perceptions and Understanding · 2011 · DOI

  • The paper argues that acute physicians working 24/7 in acute medical units produce better patient outcomes than 'part-time' traditional arrangements but does not specify what comparative studies are needed to isolate whether improvements derive from specialist generalist expertise, continuous unit-based assessment, or the structural reorganization of bed allocation and care pathways.

    Acute hospital medicine — A new sub-speciality or internal medicine re-born? · 2011 · DOI

  • The paper notes physician burnout is recognized in acute medical specialties but proposes only general structural solutions (reduced emergency duty, increased management roles). There is no specific research design outlined to quantify burnout rates in acute hospital physicians versus other specialties or to test interventions for physician fatigue and retention in 24/7 acute medical units.

    Acute hospital medicine — A new sub-speciality or internal medicine re-born? · 2011 · DOI

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55 open questions have been extracted from the limitations and future-work passages of 989 Emergency and Acute Care Studies papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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