24 articles found

Original Research

Emergency Medicine Data Analytics

15 September 2026

The emergency department (ED) is often referred to as the heart of the hospital, but it faces significant challenges such as overcrowding, understaffing, and budget constraints. According to Hu, Chan, and Dong (2024), data analytics plays a vital role in addressing these challenges by enabling hospitals to predict patient trends and manage staffing and resources more effectively. By examining historical data, healthcare providers can anticipate surges in specific medical conditions, such as flu seasons or pandemics, leading to more efficient staffing and equipment management. This, in turn, contributes to improved patient satisfaction and outcomes.

Connor Mitchell

Original Research

Remote Speakers for Emergency Medicine Residency Education

15 September 2026

The COVID-19 pandemic has created an unanticipated and sudden change to the traditional delivery of Emergency Medicine (EM) residency conference. The use of digital platforms, like Academic Life in Emergency Medicine (ALiEM) Remote, has eased the transition to a virtual platform for medical education. ALiEM Remote supports educators by providing a curated list of speakers and their topics for virtual lectures and educational resources for launching a virtual curriculum, and by providing a calendar of residency conference dates and time so that programs can identify opportunities to combine or co-host conference sessions. In this descriptive observational study, we used the Airtable platform to create a form that collected speaker and residency conference information, and Google Analytics to collect and store data on website traffic between March 10, 2020 and April 28, 2020 which coincided with the transition from in-person to virtual educational engagement. During this period, the website received a total of 1,852 unique users, with the majority being located in the United States (79%). Ultimately, ALiEM compiled a list of 162 speakers from 54 institutions across the globe with a wide range of expertise in the areas of public policy, critical care, and pediatrics, among others. Engagement data suggest early utilization of the speaker list for conference planning. However, no learner-level or educational outcome data were collected. Our repository of virtual speakers and educational material on virtual instruction offer a descriptive, early-stage model for recruiting speakers for future virtual conferences.

Deborah Lai

Adaira Landry

Sarah Mott

+6

Application of the ARIMA Model to Forecast Future Overdose Deaths

Original Research

Application of the ARIMA Model to Forecast Future Overdose Deaths

12 February 2026

Current data for opioid policy in affected states is outdated by 1-2 years, highlighting the necessity for a predictive model to forecast fatal drug overdoses and aid in the implementation of evidence-based preventative policies. We utilized Auto-ARIMA, an automated version of the ARIMA linear regression model, to forecast overdose deaths in the U.S., each state, and Washington D.C. Our forecasts for 2021 and 2022 were based on data from 2015 to 2021, sourced from the CDC's Vital Statistics Rapid Release program. Our ARIMA model forecasts an increase in overdose deaths across the U.S. and in many states, with some states potentially seeing a doubling of deaths from 2020 to 2022. This research represents an initial step in using real-time forecasts to evaluate the effectiveness of state-level public health policies in combating the opioid crisis.

Parash Bhakta

Neha Balapal

Saadh Ahmed

+7

An Entropy-Based Approach to Decision Tree Analysis in Emergency Medicine: Optimization of Diagnostic Tool Selection to Thoracic Aortic Dissection

Original Research

An Entropy-Based Approach to Decision Tree Analysis in Emergency Medicine: Optimization of Diagnostic Tool Selection to Thoracic Aortic Dissection

22 January 2026

Introduction Shannon entropy is a key concept in both machine learning and information theory, significantly influencing decision tree modeling. In emergency medicine, the utilization of testing and imaging tools to reduce uncertainty is vital for enhancing medical decision-making, especially in time-sensitive scenarios. While sensitivity and specificity assess test accuracy, entropy provides insight into how much a test clarifies the overall clinical picture, which is crucial in time-sensitive situations like thoracic aortic dissection. The aim of this study is to evaluate and compare the effectiveness of entropy and entropy reduction against conventional metrics of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), in the diagnostic evaluation of thoracic aortic dissection. Methodology We gathered diagnostic metrics, including true positives and negatives, as well as false positives and negatives, from a well-established online diagnostic accuracy database known as "Get the Diagnosis" for thoracic aortic dissection. Data collection took place from November 17, 2022, to January 22, 2023. This dataset allowed us to compute sensitivities, specificities, negative predictive values (NPVs), and positive predictive values (PPVs). A decision tree representing the diagnostic tool was created and examined for Shannon entropy and entropy reduction across the various child nodes. The decision tree was based on 2x2 diagnostic tables, covering total cases (N), true positives (TP), false positives (FP), false negatives (FN), and true negatives (TN). Results Using a helical CT scan for thoracic aortic dissection, we observed a sensitivity of 97.64% and a specificity of 98.90%, whereas MRI exhibited a lower sensitivity (93.33%) but a higher specificity (99.30%). However, entropy removal calculations revealed that the helical CT scan removed 87.23% of entropy associated with thoracic aortic dissection, while MRI removed 81.36%. Within these populations studied, this suggests helical CT scan may provide greater reduction in diagnostic uncertainty than MRI in thoracic aortic dissection assessment and underscores the unique insights offered by entropy removal, which sensitivity and specificity fail to provide. Conclusion Unlike sensitivity and specificity, entropy captures the inherent variability and uncertainty in diagnostic data, especially in complex medical scenarios where it accommodates individual variability in patient responses and disease manifestations.

Daerin Hwang

Abdel Badih El Ariss

Norawit Kijpaisalratana

+4

A Qualitative Assessment of the Feasibility, Usability, and Clinical Impact of the Keva365 Remote Patient Monitoring Platform for Asthma Management

Original Research

A Qualitative Assessment of the Feasibility, Usability, and Clinical Impact of the Keva365 Remote Patient Monitoring Platform for Asthma Management

30 October 2025

Background Remote Patient Monitoring (RPM) has emerged as a promising approach to managing chronic conditions like asthma, particularly during the COVID-19 pandemic. However, limited research exists on the use of qualitative analysis to capture patient feedback and experiences in RPM programs. This study extends a quantitative observational study that explored the impact of RPM on patients with moderate-to-severe asthma. Objective The aim of this study was to evaluate the feasibility and usability of Keva365, a digital therapeutic platform designed for remote asthma management, and to explore its impact on patient-provider relationships, asthma management, patient compliance, and engagement. Methods A purposeful sample of six patients with moderate-to-severe persistent asthma participated in the study. Over a nine-month period, participants were interviewed once using an open-ended question guide to collect qualitative data. The interviews were recorded, transcribed, and analyzed thematically using NVivo software. Data were used to assess the feasibility of the RPM intervention, its usability, and its impact on patient experiences. Written consent to publish these details has been obtained from all participants that were included in this research. Results Thematic analysis identified key themes related to patients' experiences with the app, their compliance and engagement with the program, their relationships with providers, and asthma management. All participants reported positive experiences with the program, noting the app’s usability, efficiency, and impact on their relationships with healthcare providers. Participants expressed high levels of satisfaction and a willingness to recommend the program to others. Feedback from the interviews contributed to near real-time modifications of the RPM application, enhancing its usability and navigation. Conclusions The study found that integrating patient feedback is essential for improving the usability of RPM platforms. Continuous iterative refinement based on patient experiences can lead to more patient-centered digital health solutions, enhancing both patient compliance and the overall care experience. The findings suggest that RPM programs can effectively support asthma management while fostering positive patient-provider relationships. make a scope statement for Conduct Science journal that focuses on current and latest research that focuses on shaping the future of medicine.

Naomi Rajput

Jyotsna Mehta

Denzil Reid

+1

Humanizing Critical Care: Transforming ICUs Through Empathy and Innovation

Original Research

Humanizing Critical Care: Transforming ICUs Through Empathy and Innovation

2 September 2025

Background: Intensive Care Units (ICUs) in resource-limited settings face persistent challenges, including high infection rates, staffing shortages, and inconsistent patient-family engagement. Standardized ICU audits provide a structured approach to assessing and improving infection control, staff preparedness, and patient-centered care. This study evaluates CritiCore, a structured ICU audit framework innovation piloted and applied longitudinally over three sequential cycles at a single center, designed to drive iterative, evidence-based quality improvements through targeted intervention cycles. Methods: CritiCore was implemented at Evercare Hospital Lahore, Pakistan, across three cycles: baseline audit (November 2024), first re-audit (January 2025), and second re-audit (April 2025). Each cycle included structured observational assessments, infection-surveillance review, and multidisciplinary stakeholder interviews with ~20 ICU professionals (physicians, nurses, infection control specialists, and administrative staff). Findings from each audit informed targeted interventions focusing on real-time infection surveillance, simulation-based staff training, and standardized patient-family engagement strategies (Empatheon). Results: The initial audit revealed elevated hospital-acquired infection rates (≈40–50%), linked to inconsistent hand hygiene and ventilation gaps. Staffing continuity was affected by reliance on locum personnel and limited simulation-based training. Patient-family engagement was inconsistent, with unclear visitation policies and fragmented communication. By the first re-audit, adherence to infection-control protocols improved, simulation training participation increased, and structured family communication and visitation protocols were adopted. By the second re-audit, most improvements were sustained, with additional gains in simulation training coverage, consistency of family engagement, and environmental control measures. Infection control adherence remained markedly higher than baseline, and staffing continuity improvements were maintained. Conclusion: This three-cycle ICU audit from Lahore demonstrates the feasibility and sustained impact of a structured, iterative quality-improvement framework in an LMIC private hospital. The same CritiCore approach was subsequently rolled out at Evercare hospitals in Nigeria (twice) and Kenya (once), supporting adaptability across diverse settings; a formal multi-site analysis is planned. Keywords: critical care transformation; Evercare hospitals; ICU audit; infection surveillance; LMICs; patient-family engagement; quality improvement; staff training; Empatheon.

Asad I Mian

Muhammad Taha Anver

Mahreen Sulaiman

+4

Empathy-Driven Innovation: Human-Centered Design Thinking for Transforming Healthcare Delivery

Original Research

Empathy-Driven Innovation: Human-Centered Design Thinking for Transforming Healthcare Delivery

23 August 2025

Background: Healthcare systems in low- and middle-income countries [LMICs] face systemic challenges in high-stakes environments such as emergency medicine and intensive care. Limited resources, fragmented workflows, and communication gaps often compromise patient care. Human-Centered Design Thinking [HCDT] provides an empathy-driven, iterative framework for problem-solving tailored to these settings. Methods: Two HCDT workshops were conducted in 2024 at Evercare hospitals in Lekki [Nigeria] and Lahore [Pakistan]. Using the Stanford d.school’s five-step framework—Empathy, Problem Definition, Ideation, Prototyping, and Testing—participants applied tools including empathy mapping, PICO problem dissection, brainstorming, and rapid prototyping. Teams included physicians, nurses, paramedics, and administrators. Results: Eighty-six participants engaged, with 23 structured evaluations per site. In Lekki, solutions addressed referral delays and communication gaps through referral coordinators, checklists, and digital tools. In Lahore, ICU-focused teams developed interventions for staff turnover, communication inefficiencies, and humanization of care—culminating in the Empatheon program, which applied PDSA cycles to strengthen staff well-being and patient-family engagement. Both sites reported high satisfaction, with >65% rating inspiration, knowledge, and practicality as very high. Conclusion: HCDT shows strong potential to address healthcare challenges in LMICs through low-cost, scalable, and context-sensitive innovations. Embedding empathy, co-creation, and iteration into care processes enhances outcomes and fosters sustainable, patient-centered innovation. Further validation through real-world implementation is warranted.

Mahreen Sulaiman

Hira Amran Chowdhry

Kazim Ali Tarar

+5

From Boarding to Breakthrough: Tailored Interventions for Vulnerable Patients

Original Research

From Boarding to Breakthrough: Tailored Interventions for Vulnerable Patients

22 August 2025

Emergency Department (ED) boarding–prolonged stays in the ED while awaiting inpatient placement–is a crisis exacerbating crowding, increasing costs, and negatively impacting health outcomes. Vulnerable populations, including individuals with low socioeconomic status (SES), medically-complex older adults, and psychiatric patients are disproportionately affected. Yet, solutions tailored to their needs remain underexplored. This discussion examines root causes of boarding and proposes innovative, scalable interventions to mitigate its harms, specifically for marginalized groups. We highlight three strategies: (1) Patient Navigators, who assist low-SES patients navigating healthcare systems, (2) Community Paramedicine, which delivers in-home care to complex patients, and (3) Emergency Psychiatric Assessment, Treatment and Healing (EmPATH) Units, which provide targeted care for psychiatric patients. All three are associated with reduced ED visits. Traditional approaches to boarding have fallen short, particularly for vulnerable populations. Patient navigation, Community Paramedicine, and EmPATH units represent feasible, evidence-based solutions that health systems can implement. Broader adoption of these models can alleviate crowding, enhance care quality, and promote health equity. Future efforts must align these innovations with policy and funding mechanisms to ensure sustainable, system-wide improvements.

Alister Martin

Timothy Scheinert

Amelia Papadimitriou

+1

Innovation Skills Assessment in Healthcare: Benchmarking Capacities in Low-Resource Settings

Original Research

Innovation Skills Assessment in Healthcare: Benchmarking Capacities in Low-Resource Settings

17 August 2025

ABSTRACT Background: Innovation is a key driver of healthcare transformation, particularly in low-resource settings where systemic constraints often hinder service delivery. Assessing innovation capacities among healthcare employees can inform workforce development strategies. This study applies the previously validated Innovation Skills Assessment (ISA) tool to examine workforce innovation potential at a tertiary care hospital in Pakistan, offering insights for targeted capacity-building interventions. Methods: A cross-sectional survey was conducted at Mukhtar A. Sheikh Hospital in Multan, Pakistan, using the ISA tool adapted from the General Innovation Skills Aptitude Test. The survey captured demographic data and assessed innovation skills across four pillars: idea generation, risk-taking, interpersonal relationships, and idea implementation. A total of 250 electronic surveys were distributed via hospital communication channels, with 161 responses (64% response rate). Responses were rated on a 5-point Likert scale, and mean scores with standard deviations were calculated for each pillar. Descriptive statistics were used to explore observable trends across age, gender, education level, and job designation, without formal hypothesis testing. Results: Participants aged 36–45 years had the highest overall mean scores (4.48 ± 0.31), with notable strengths in idea generation (4.48 ± 0.31) and implementation (4.53 ± 0.33). Males showed higher average scores across all pillars, with interpersonal relationships as the strongest domain (4.49 ± 0.42). Participants with intermediate education reported higher mean scores in creativity and risk-taking (4.36 ± 0.45 and 4.20 ± 0.57, respectively). These patterns suggest potential demographic influences on innovation capacities. Conclusion: The ISA tool can be feasibly applied to map innovation skills within healthcare workforces in low-resource contexts. The identified trends may help guide workforce development through tailored training and institutional policies that promote a culture of innovation. Keywords: Innovation Skills Assessment, Healthcare Workforce, Low-Resource Settings, Human-Centered Design, Capacity-Building, Pakistan, Benchmarking, Workforce Innovation

Ahmed Raheem

Hasan N Tahir

Zeeshan Ahsan Allana

+5

Human Drugs & Veterinary Drugs - A Cost Comparison

Original Research

Human Drugs & Veterinary Drugs - A Cost Comparison

16 August 2025

Objective: The aim of this study was to provide an updated comparison of veterinary drug costs with human pharmacy equivalents. Design: A cross-sectional study was conducted by identifying the 50 most common drugs from Medicare Part D spending data, and obtaining the costs of these drugs, in addition to select antidepressants and ophthalmic medications, from human retail (GoodRx, DiRx, and Cost Plus Drugs) and veterinary pharmacy websites (Chewy and Pet Meds). Main outcome measures: Drug costs per tablet were calculated using 30-, 60-, and 90-count quantities. Drug cost data was normalized, and costs were compared via Student’s T-test. Results: 41 drugs were analyzed between human and veterinary pharmacy alternatives. For 90-day supply costs, Cost Plus Drugs provided the cheapest price for 30/41 cases. The lowest normalized drug cost per unit 90-day supply was 0.4406 for Cost Plus Drugs, with DiRx second at 0.5789 (p < .05). For 30-day supply costs, Chewy provided the cheapest price for 30/41 cases. The lowest normalized drug cost per unit for a 30-day supply was 0.4665 for Chewy, with no significant difference to Cost Plus Drugs at 0.5270 (p > .05). Conclusion: These results demonstrate that home-delivery pharmaceutical services offer more affordable options and address the high cost of human medications compared to equivalent veterinary medications. This represents a step forward in identifying solutions to reduce healthcare expenditures and pharmaceutical costs.

Paul Chong

Kevin Shannon

Julian Fine

+2

Leveraging Text-Based Outreach to Improve Enrollment in Federal Benefit Programs and Address Broadband Internet Access

Original Research

Leveraging Text-Based Outreach to Improve Enrollment in Federal Benefit Programs and Address Broadband Internet Access

13 August 2025

Background: Federal benefit programs form the backbone of a social safety-net that provides access to essential services for millions of Americans. However, access to these programs is hampered by complex application processes and administrative barriers. Link Health is a Boston-based nonprofit organization that, through strategic community partnerships, has developed a framework to streamline benefit program enrollment, resulting in the disbursal of over $4 million in benefits. We evaluate the effectiveness of embedding benefits access within existing private messaging frameworks as a strategy for reducing systemic barriers to federal program utilization and improve broadband internet access. Methods: In this prospective observational study of data from June 2024 through December 2024, Link Health conducted a targeted Massachusetts-based text-messaging campaign aimed at enrolling patients from partner community health centers in the Lifeline program, a broadband phone and internet access discount. DaisyChain, a web-based communication platform, enabled Link Health’s multilingual digital navigator team to collect patient responses and conduct follow-ups. Results: The campaign reached 68,529 patients, with 2.15% (n=1,470) engaging with the initial message. Among those who engaged, 41.84% identified as Hispanic, 35.58% as White, 10.61% as Black or African American, and 2.79% as Asian. 62.59% of participants preferred English, 32.31% preferred Spanish, and 5.10% preferred another language. 68.91% of sign-ups were female. Applicants were predominantly working and middle-age adults, with 24.15% of applicants between the ages of 35-44 years and 24.15% between 45-54 years. Patients primarily qualified for Lifeline through SNAP (64.97%), Medicare (37.21%), or Medicaid (41.16%). Conclusion: This study describes the effectiveness and feasibility of text-based initiatives in connecting patients from racially and linguistically diverse communities with the Lifeline benefit program. The campaign successfully and predominantly engaged Hispanic, publicly-insured groups, with an especially high enrollment rate among working and middle-age adults. By integrating digital technology with public health, Link Health’s text-messaging campaign provides a scalable and replicable framework to improve access to federal benefits.

Abhi Jain

Timothy Scheinert

Sammer Marzouk

+3

A Three-Pillar Approach to Benefit Enrollment Reaches Underserved Communities

Original Research

A Three-Pillar Approach to Benefit Enrollment Reaches Underserved Communities

31 July 2025

Background. The Affordable Connectivity Program (ACP), established in 2021, provided eligible low-income households a monthly $30 internet subsidy. Despite its role in reducing digital disparities, only 40% of eligible households enrolled nationally. Link Health (LH), a Boston-based grassroots initiative, implemented a three-pillar (active, passive, and digital) outreach model to increase ACP uptake in Massachusetts and Texas. Methods. From November 2022 to May 2024, LH partnered with community health centers in Boston and Houston to deliver on-site sign-up clinics (active approach), distribute multilingual printed materials (passive approach), and provide personalized text-message support (digital approach). Multilingual volunteers led screening and application filing, with follow-up via a dedicated helpline. Enrollment data were collected across 17 clinics and analyzed descriptively. Results. Of approximately 9,774 individuals screened, 1,086 (11.1%) enrolled in the ACP. Enrollees were predominantly racial/ethnic minorities (78.9%), with 55.4% Hispanic/Latinx and 23.5% Black/African American. 68.4% of enrollees qualified for the ACP through current Medicaid enrollment, and 29.2% qualified through current SNAP enrollment. Digital sign-ups constituted 33.8% of enrollments. LH’s efforts distributed an estimated $390,960 in annual subsidies. Conclusion. LH’s community-driven, three-pillar strategy bridged barriers to ACP enrollment. This model may inform future initiatives aimed at closing the digital divide and advancing health equity through targeted benefit enrollment.

Nicholos P Joseph

Timothy Scheinert

Ashley K Roth

+4

Leveraging Network Analysis for Global Connectivity in Emergency Medicine

Original Research

Leveraging Network Analysis for Global Connectivity in Emergency Medicine

29 July 2025

Introduction: In the field of international emergency medicine (IEM), navigating the vast and often fragmented online resources can be a challenge. This abstract explores how network analysis, a method examining connections within a system, can be applied to improve online accessibility and navigability of these resources. By focusing on the International Federation for Emergency Medicine (IFEM), the study aims to utilize network analysis to understand the current digital landscape of IEM stakeholders and their connections. This will ultimately lead to recommendations for improved information sharing within the IEM community. Methods: We focused our data collection on the IFEM website (www.ifem.cc), a central node connected to global emergency medicine organizations. Using an automated network analysis pipeline, we crawled the IFEM website to three levels deep with the Screaming Frog SEO Spider tool, mapping its structure and extracting pertinent data. The BeautifulSoup library was then used to parse the HTML content, while the Gemini 1.0 Pro language model helped filter and identify relevant information about global emergency medicine organizations. This results were then compared with the official IFEM member list for validation. Finally, Geographical details were pinpointed using the Geopy library and Nominatim tool to convert names and countries into exact coordinates. An interactive global map of these organizations was created with the Folium library, enhancing our understanding of the global emergency medicine network and its interconnections. Results: We identified 4,775 external links, narrowing down to 156 unique base URLs for further content analysis. On the IFEM website, of 55 countries listed, only 41 had accessible links; 10 were non-functional, and 3 were missing. Our automated pipeline pinpointed 41 pertinent multilingual URLs from the available ones, achieving 100% accuracy rate. Our analysis also revealed 28 additional URLs, potentially linked to EM organizations not listed on their member page. Conclusion: By leveraging an automated network analysis pipeline, we gained valuable insights into the digital connections between emergency medicine organizations. This approach not only identified key organizations and their connections but also potentially improved the accessibility and navigation of online information in emergency medicine

Norawit Kijpaisalratana

Abdel badih El Ariss

Jeffrey Yuan

+6

LipidLlama: A Multilingual AI Chatbot for Personalized Cardiovascular Risk Assessment

Original Research

LipidLlama: A Multilingual AI Chatbot for Personalized Cardiovascular Risk Assessment

23 July 2025

Background Cardiovascular disease is the leading cause of death worldwide. Many patients with cardiovascular disease struggle to understand their risk factors and medical test results due to health literacy limitations and/or inadequate resources for personalized education. Existing digital solutions often provide generic, one-size-fits-all information with varying degrees of medical accuracy. Methods LipidLlama addresses this gap by integrating a rule-based AI system—adapted from a validated cardiovascular risk assessment tool—and a chatbot powered by a Large Language Model (LLM) enhanced with retrieval augmented generation (RAG). To improve document retrieval, a custom query-only adapter was trained on synthetic query corpus document pairs. Response quality was independently evaluated by three board-certified physicians (two cardiologists and one internist) who rated 30 responses to synthetically generated, realistic patient queries using a 5-point Likert scale across four dimensions: correctness, conciseness, comprehensiveness, and comprehensibility. Rater reliability was assessed using generalizability theory. Results The trained adapter improved top-k document retrieval accuracy from 67% to 80%. Responses received consistently high clinical ratings across all dimensions (mean composite score = 18.21, 95% CI: 17.80-18.62) and demonstrated strong reliability metrics across raters (generalizability coefficient E⍴² = 0.88; dependability coefficient Φ = 0.84). Conclusion LipidLlama provides clinically grounded, personalized explanations in response to cardiovascular health questions. With further clinical validation, this mobile health application has the potential to enhance health literacy and minimize provider burden, significantly improving access to preventive cardiovascular care, particularly in underserved communities.

Tyler J Smith

Amogh Karnik

Jonathan Hourmozdi

+2

Transforming Emergency Care: Scalable Clinical Audit Innovations for Emerging Markets

Original Research

Transforming Emergency Care: Scalable Clinical Audit Innovations for Emerging Markets

22 July 2025

Resource constraints, staff brain drain, operational inefficiencies, and incidents of workplace violence undermine emergency care outcomes in emerging markets. The Emergency and Trauma Excellence (EmTEx) framework, a structured and human-centered approach, was implemented at Evercare Hospital Lahore to address these systemic challenges. A two-day clinical audit, led by a senior emergency physician, pediatrician, and innovation consultant, evaluated resuscitation readiness, triage efficiency, infection control, staffing adequacy, and staff safety using JCIA-inspired checklists, staff interviews, and facility walkthroughs. Findings revealed insufficient resuscitation spaces, poor separation of pediatric and adult patients, inconsistent triage protocols during peak hours, staffing shortages, and reports of aggression toward healthcare staff during high patient volumes of up to 190 daily. Additional gaps in infection control practices and variability in triage accuracy highlighted operational inefficiencies. Recommendations included tablet-based triage systems for real-time data capture, enhanced isolation zones for infection control, structured staff training programs, and robust safety measures such as de-escalation training and security protocols. Projected outcomes include a 20–30% reduction in patient wait times, improved workflows, and enhanced staff safety and engagement. These findings underscore the scalability of the EmTEx framework, demonstrating its ability to deliver empathy-driven solutions for transforming emergency care in resource-limited settings.

Asad I Mian

Muhammad Taha Anver

Mahreen Sulaiman

+5

Evaluating Pediatric Healthcare Spaces: Evidence-Based Recommendations for Design and Engagement

Original Research

Evaluating Pediatric Healthcare Spaces: Evidence-Based Recommendations for Design and Engagement

22 July 2025

Background Hospital environments significantly impact pediatric patients’ physical and emotional well-being. However, conventional hospital designs often fail to integrate child-friendly engagement strategies, leading to increased anxiety, reduced caregiver satisfaction, and operational inefficiencies. The HackPeds clinical audit, grounded in a continuous quality improvement framework, evaluated pediatric healthcare spaces at Evercare Hospital Lahore to identify systemic gaps and implement targeted interventions over a structured audit cycle. Methods A two-phase clinical audit was conducted at Evercare Hospital Lahore, with an initial assessment in November 2024, followed by a structured re-audit in January 2025, allowing for approximately three months of intervention implementation. The assessment was inspired by Joint Commission International and similar global pediatric care standards while also incorporating human-centered design principles. A checklist-based facility evaluation, structured staff interviews, and real-time benchmarking against best practices were used. The auditor, a pediatrician, emergency medicine consultant, and health innovation expert, assessed spatial utilization, caregiver engagement, and pediatric emergency preparedness, among other factors. Results The initial audit identified underutilized pediatric spaces, lack of interactive play zones, inconsistent emergency preparedness, and inadequate staff training in play therapy. Over the three-month intervention period, structured play areas were introduced, pediatric emergency response protocols were strengthened, and caregiver education initiatives were expanded. The January 2025 re-audit showed improvements in the use of engagement spaces, staff preparedness, and caregiver participation in pediatric care activities, although gaps remained in optimizing space utilization and embedding structured storytelling interventions. Conclusion By embedding continuous quality improvement strategies and structured re-audit cycles, HackPeds provides a scalable framework for pediatric healthcare transformation. The model is positioned for multi-site validation across Evercare Group hospitals in Nigeria and Kenya, with potential for broader adaptation in global pediatric healthcare settings. Future audits will assess longitudinal impact and sustainability to optimize pediatric patient experience, caregiver engagement, and emergency preparedness. Keywords: Pediatric hospital design, clinical audit, quality improvement, human-centered design, play therapy, storytelling in healthcare, pediatric emergency care, caregiver engagement, healthcare innovation, global health scalability.

Asad I Mian

Muhammad Taha Anver

Mahreen Sulaiman

+4

Zalsa: A Contextualized Low-cost and Low-tech Wellness and Well-being Innovation for University Students

Original Research

Zalsa: A Contextualized Low-cost and Low-tech Wellness and Well-being Innovation for University Students

13 June 2025

Introduction: Zalsa, an amalgamation of Zumba and Salsa, represents a dynamic and culturally rich form of physical and psychological activity that has shown promise in building wellness and well-being at the community level. This study explored the effects of Zalsa participation on physical fitness, mental health, and social integration at a comprehensive university in a Low-Middle Income Country (LMIC) setting. Method: Through a mixed-methods, quasi-experimental approach, the Zalsa intervention was performed through open houses at the Aga Khan University Hospital (AKUH) in Karachi, Pakistan. The intervention was open to all AKUH students, spanning July to Sept 2023. Immediately following the intervention, an online Google survey was conducted based on 20 questions in subcategories self-assessing physical/mental health, stress, social interaction, concentration, and work-life balance. Results: Of the 107 participants, the vast majority (80%) were women in their 20s and 30s; 41% were medical students. Likert scores were high across the board, with up to 90% of respondents falling within the moderate to significant satisfaction range. The intervention was associated with high mean aggregate scores for psychological well-being (72%), work-life balance (73%), overall quality of life (80%), and future intention (75%), but lower for physical well-being (67%). The mean % score tended to be significantly higher in the over 35 years age group for all categories tested. Conclusion: Data supports positive influence on burnout mitigation potential, physical, mental, and social wellness and well-being, and personal/professional growth through community building, amongst university students. These findings have implications for incorporating Zalsa-like wellness and well-being programs to build novel core competencies for 21st-century learners in their higher education pursuit.

Syed Waqas

Zeeshan Ahsan

Aisha Pervaiz

+4

HackAway! Innovating Mental Wellness for Students of Higher Education through a Comprehensive Brain-Mind Hackathon

Original Research

HackAway! Innovating Mental Wellness for Students of Higher Education through a Comprehensive Brain-Mind Hackathon

15 May 2025

Background: With the growing recognition of mental health challenges, particularly among students, innovative and sustainable solutions are crucial. Traditional methods have their limitations, and new approaches are needed to foster collaborative problem-solving. The "Brain and Mind Institute: Student Mental Health Hackathon," held at Aga Khan University in October 2021, was conceived as an innovative platform to engage participants from diverse backgrounds in brainstorming solutions for student mental health challenges. This Hackathon, rather than focusing solely on the mental health issue itself, aimed to leverage interdisciplinary collaboration to generate practical, scalable solutions for student well-being. Methods: A descriptive analysis was conducted to assess the outcomes of the Hackathon, focusing on its effectiveness as a collaborative platform. The study involved 74 participants, predominantly students, who were randomly assigned to teams based on shared problem-solving approaches. Descriptive statistics were used to analyze data collected on participants’ experiences, specifically assessing how well the Hackathon fostered teamwork and the development of viable solutions to the challenges presented. Results: Among the 74 participants, 62% were female, with 65% aged between 21 and 30 years. Over 70% of participants were students, with 59% from healthcare backgrounds. The Hackathon received overwhelmingly positive feedback, with a mean score of 4.41 out of 5 on a Likert scale. Participants reported that the event effectively fostered empathy towards mental health issues and helped generate actionable ideas for addressing student mental health. Time constraints were identified as a significant challenge, limiting the depth of some proposed solutions. Conclusion: The Hackathon organized by the Brain and Mind Institute demonstrated the power of interdisciplinary collaboration in addressing complex student mental health challenges. Despite time constraints, it proved to be an effective platform for generating practical solutions and fostering empathy. These findings highlight the potential of Hackathons as a model for future initiatives focused on student well-being, with further research needed to explore the long-term impact and scalability of such solutions.

Ume-e-Aiman Chhipa

Ayesha Memon

Zeeshan Ahsan Allana

+6

Innovating Emergency Medicine: Generative AI, Narrative Medicine, and Human-Centered Design

Original Research

Innovating Emergency Medicine: Generative AI, Narrative Medicine, and Human-Centered Design

26 April 2025

Introduction: Emergency medicine in less resourceful areas struggles with the rising burden of disease and disability. Recognizing the limitations of conventional problem-solving has prompted reevaluating our approach to leverage AI capabilities. This article presents the introduction of a masterclass called ‘Create to Innovate’ (C2i) built using Human Centered Design Thinking. We explore narrative medicine through storytelling as an innovative method of promoting emotional engagement and clinical decision making in emergency medicine. Methods: The 'C2i' masterclasses were held at Aga Khan University Hospital in Karachi, Pakistan in December 2023 and at Evercare Hospital in Lagos, Nigeria in March 2024. This study used an explanatory mixed methods approach, collecting quantitative data from a post-intervention 'MoodBoard' survey and qualitative data from the AI-generated children's stories, with a total sample size of 60 participants. Results: The pilot study included 22 participants from the Karachi cohort and 38 from the Lagos cohort. A five-point validated visual analog scale, the MoodBoard, assessed the impact of the masterclasses. A significant difference was observed in the overall mean score between the two cohorts (Karachi 3.74 vs. Lagos 3.96; p < 0.05, C.I: -0.42 to -0.01). Qualitative analysis revealed three specific themes within the generated stories: prosocial behavior, resourcefulness and health awareness. Conclusion: The masterclass achieved its goal of fostering innovative solutions through storytelling. The MoodBoard survey highlighted its effectiveness and enjoyment. The imaginative stories offered educational insights into healthcare challenges, highlighting their potential for broader applications in healthcare education and professional training, while enhancing problem-solving and emotional engagement.

Syed Waqas

Zunaira Namal

Ahmed Raheem

+1

Removing Barriers to Government Benefits: Link Health’s Role in Advancing Health Equity Through Expanded Enrollment

Original Research

Removing Barriers to Government Benefits: Link Health’s Role in Advancing Health Equity Through Expanded Enrollment

27 March 2025

Objectives. To evaluate Link Health’s role in improving federal benefit program enrollment by analyzing application trends and impact from 2022-2024. Methods. Link Health connects eligible populations to federal benefits through in-person and digital ethods. Using data from clinics in Massachusetts and Texas and digital sign-ups, we analyze enrollment trends, funding disbursed, and demographics. Results. From 2022-2024, Link Health supported 2,362 applicants, disbursing over $2.8 million to eligible families. Application methods differed significantly by language (𝛸2=97.4, P<0.001, v=0.4), age (W=589819, P=0.03, r=0.05), state (𝛸2=11.5, P<0.001, v=0.1), and race (𝛸2=138.1, P<0.001). Conclusions. Link Health’s hybrid approach and community partnerships may reduce barriers and optimize benefit enrollment, supporting marginalized communities across several health determinants. In the context of diminishing federal support and the postpandemic benefits cliff era, organizations like Link Health are critical to help individuals access resources. Policy Implications. Targeted, community-based digital enrollment models like Link Health’s could be applied to enhance access to vital resources across the country.

Reese Joy Fields Green

Timothy Scheinert

Sudarshan Krishnamurthy

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