About

Drew Hamilton is a professor of Computer Science and Engineering at Texas A&M University. His research interests include computer security, simulation of computer networks, command and control interoperability, and software architectures. He has extensive experience in distributed simulation, network simulation, and software engineering.

Research topics

• Sociology
• Computer Science
• Medicine
• Medical education
• Psychology
• Nursing
• Human–computer interaction
• Simulation
• Geography

Selected publications

• Secure Aggregation Protocols in Federated AI for Anonymized Health Data

  Preprints.org · 2025-06-13

  preprintOpen accessSenior author

  In the increasingly data-driven landscape of healthcare, the application of Federated Learning (FL) has emerged as a transformative paradigm, enabling the collaborative training of machine learning models across decentralized datasets while preserving data privacy. This approach is particularly pertinent for health data, which is often sensitive and subject to stringent regulatory requirements. However, the integration of secure aggregation protocols within Federated AI systems is crucial for ensuring the confidentiality and integrity of anonymized health data during the aggregation process. This paper comprehensively reviews the state of secure aggregation protocols in the context of Federated AI, emphasizing their role in safeguarding patient privacy while allowing for the effective utilization of health data. We categorize existing secure aggregation methods based on their cryptographic techniques, including homomorphic encryption, secure multiparty computation, and differential privacy, analyzing their strengths and limitations in practical applications. Furthermore, we explore the implications of these protocols on data utility, computational efficiency, and scalability in real-world healthcare settings. By synthesizing recent advancements and ongoing challenges in the field, this study underscores the importance of designing robust aggregation protocols that not only enhance security but also facilitate the seamless integration of diverse health data sources. We propose a framework for evaluating the performance of these protocols, taking into account factors such as communication overhead, resilience against attacks, and adaptability to various federated learning architectures. Our findings indicate that while significant progress has been made, there remains a critical need for ongoing research to balance the trade-offs between security, privacy, and model performance. This paper aims to contribute to the development of more sophisticated secure aggregation protocols that can effectively support the growing demand for collaborative, AI-driven health analytics without compromising patient confidentiality. Ultimately, we advocate for a multidisciplinary approach that incorporates insights from cryptography, data science, and healthcare policy to advance the secure and ethical use of federated AI in health data research.

  PublisherOA PDFDOI

• Society of Critical Care Medicine 2024 Guidelines on Adult ICU Design: Executive Summary

  Critical Care Medicine · 2025-02-21 · 4 citations

  article1st authorCorresponding

  Advances in technology, challenges in infection control—such as the severe acute respiratory syndrome coronavirus 2 pandemic, and evolutions in patient- and family-centered care highlight ideal aspects of ICU design present opportunities for enhancement (1,2). For example, prior Society of Critical Care Medicine (SCCM) ICU design guidelines (1995–2012) did not envision remote manipulation of ventilator settings or infusion pumps (3,4) or the unique aspects of pandemic care. Design elements spanning square footage, air handling, airborne isolation, linkage to electronic and digital local or remote systems, as well as ICU organization and layout may be addressed during new construction, revision of existing critical care spaces, or conversion of previously noncritical care space to render ICU care. Ensuring proximity to key destinations helps enable safe, quality care for all ICU subspecialties. ICU design may influence safety and security for patients, visitors, and staff (5). Due to substantial shifts in healthcare and intervening research, SCCM sought to update the 2012 ICU design guidelines to provide expert guidance for clinicians, administrators, and healthcare architects considering constructing a new ICU or renovating one. ICU DESIGN POPULATION, INTERVENTION, COMPARISON, AND OUTCOMES QUESTIONS A summary of Good Practice Statements (GPSs) and Strong Recommendations for selected Population, Intervention, Comparison, and Outcomes (PICO) questions are presented in Table 1 along with panel generated design themes. PICO questions in “bold italics” represent the most impactful areas determined by the panel and are presented herein. Figure 1 provides a Visual Summary of the certainty of evidence and strength of recommendations for each PICO question. Evidence summaries and recommendation justifications for all 15 questions are located within the supporting materials. Overall, the panel articulated 17 recommendations (PICO questions 2.1. and 5.2. each yielded two recommendations), including five GPS. TABLE 1. - Complete Summary of ICU Design Themes and Related Population, Intervention, Comparison, and Outcomes Questionsa Theme Population, Intervention, Comparison, and Outcomes Question 1. ICU layout 1.1. Should high-visibility layouts vs. low-visibility layouts be used in ICUs? 1.2. Should centralized charting areas vs. decentralized charting areas be used in intensive care? 1.3. Should single-bed rooms vs. open bay layouts be used in ICUs? 1.4. Should designs with close proximity to key destinations vs. without close proximity to key destinations be used for ICUs? 2. Room design 2.1. Should rooms with environmental features to enhance sleep and recovery vs. standard rooms be used in ICUs 2.2. Should in-room supplies vs. centralized supply rooms be used in ICUs? 3. Infection control 3.1. Should advanced HVAC designs vs. standard HVAC designs be used in ICUs? 3.2. Should advanced infection prevention features vs. no advanced infection prevention features be used in ICUs? 4. Infrastructure 4.1. Should outside-room monitoring and control of devices vs. inside-room only monitoring and control of devices be used in ICUs? 4.2. Should advanced remote monitoring (e.g., telemedicine) vs. usual care be used in ICUs? 4.3. Should flexible surge capacity vs. no specific design for surge capacity be used in ICUs? 4.4. Should nonwall-based life support utility access vs. wall-based life support utility access be used in ICUs? 5. Staff space 5.1. Should ergonomic features vs. usual designs be used for ICUs? 5.2. Should integrated break/respite space vs. nonintegrated break/respite spaces be used in ICUs? 5.3. Should mobile workstations, or combination workstations vs. fixed workstations, be used in ICUs? HVAC = heating, ventilation, and air conditioning.aItems in “bold italics” represent the one Population, Intervention, Comparison, and Outcomes question in each theme that have been selected for presentation within the Executive Summary; all others are fully reviewed in the complete article (6). Figure 1.: Society of Critical Care Medicine (SCCM) ICU design guidelines, all Population, Intervention, Comparison, and Outcomes—visual summary. GRADE = Grading of Recommendations, Assessment, Development and Evaluation, HVAC = heating, ventilation, and air conditioning.High Level Summary of PICO Questions With Strong Recommendations and GPS Theme 1: ICU Layout 1.1. Should high-visibility vs. low-visibility layouts be used in ICUs? One primary determinant of patient visibility is ICU layout. Visibility of patients at risk of deterioration is a high priority and complements existing monitoring devices, as the sickest patients benefit from early problem detection (7–10). Caring for patients in more visible areas may allow staff to more rapidly intervene and to recognize when colleagues require assistance. The panel noted that “visibility” specifically refers to the patient including their face, monitors, and bedside alarms—as opposed to the room entryway or nonpatient-care design elements. A Strong Recommendation was made in favor of high visibility, despite a low certainty of evidence that evaluated patient safety during critical illness. Although the certainty of evidence is low, this is a fundamental aspect of ICU care. The undesirable effects of high-visibility rooms (e.g., reduced privacy) are believed to be minimal by comparison to the anticipated benefits and may be easily mitigated (11). ICU design for optimum patient visibility from staff workstations is a priority. Theme 2. Room Design 2.1. Should rooms with environmental features that enhance sleep and recovery (light and noise mitigation, natural lighting) vs. standard rooms be used in ICUs? These aspects are priorities as ICU environments commonly disrupt natural sleep cycles, promote delirium, and impede recovery. Incorporation of natural lighting, dynamic lighting, and noise mitigation could reduce sleep disruption. While early studies of windows suggested an impact upon mortality and delirium, effects remain unclear. Due to confounding risks in observational studies, as well as effect estimate imprecision, the panel assigned a low certainty of evidence for window and natural lighting effects on mortality, delirium, as well as ventilator or ICU length of stay. Windows are inherently desirable as they humanize the critical care setting, reflect current patient, family, and staff expectations and are encoded in existing ICU standards. A strong recommendation was made supporting windows in patient rooms. Studies of specific design-related features to address ICU noise mitigation were not identified. Noise canceling ceiling tiles may enhance patient rest and staff communication (12). Common ICU noise sources include staff activity and conversation, furniture movement, other patients, visitors, and device alarms. Because alarms often exceed the World Health Organization decibel standards, they are associated with impaired sleep hygiene (13–16). The panel agreed that the effect of ICU design noise mitigation strategies warranted a very low certainty of evidence assessment due to limited study data. Theme 3. Infection Control 3.2. Should advanced infection prevention features vs. no advanced infection prevention features be used in ICUs? Nosocomial infection is a challenging source of morbidity and mortality in the ICUs and localized outbreaks are well described (17). There is no strong evidence supporting the efficacy of any single infection prevention/control measure to address nosocomial infection. Many measures may reduce microbe prevalence on surfaces, in air, and in water. It is less clear that these measures result in reduced colonization and subsequent infection, but they offer interventions designed to reduce the likelihood of nosocomial pathogen acquisition and subsequent infection, especially in those with immune compromise. Studied interventions included: 1) reducing or clearing pathogen bioburden (18–20); 2) improving hand hygiene compliance (21–25); 3) concerns regarding sink location, splash guard use, and water filter emplacement (26–33); 4) appropriate space for personal protective equipment storage and use (34); 5) pathogen-reducing or surface-cleaning enabling surface materials (35–46); and 6) the impact of push-plate door handles (47). Most interventions demonstrate face validity and appear to reduce microbe counts on surfaces as well as patient colonization by antimicrobial-resistant or multidrug-resistant organism pathogens. While it is unclear which single advanced infection prevention and control feature is most effective, the cumulative effect of multiple simultaneous interventions to mitigate nosocomial colonization, infection, and localized outbreaks is anticipated to be large. A GPS recommendation to incorporate design features to prevent airborne, water-borne, and surface transmission. Theme 4. Infrastructure 4.3. Should flexible surge capacity vs. no specific design for surge capacity be used in ICUs? The COVID-19 pandemic highlighted the unpredictability of critical care needs and the importance of being able to rapidly augment bed capacity to address patient volume surges. Surge capacity includes equipment, staff, and the ICU physical infrastructure (i.e., beds or care locations). While comparison studies of surge capacity were not identified, strategies to rapidly increase capacity included: 1) cohorting multiple patients within a single room (48,49); 2) using novel spaces for patient care (50,51); 3) leveraging resources across health systems such as load balancing across sites (52); 4) deploying infant monitors to increase observation capability (50,53); and 5) emplacing portable high-efficiency particulate air filters to improve airborne isolation room complement (50). Designs that accommodate large patient volume surges may support continued access to routine as well as emergency care despite system stress. Additionally, staff augmentation may occur using a tiered-staffing structure where ICU clinicians guide teams of non-ICU clinicians to provide critical care during surges (54). Theme 5. Staff Space 5.2. Should integrated break/respite space vs. nonintegrated break/respite spaces be used in ICUs? Staff satisfaction, burnout, and clinical performance may be influenced by the design, usability, and impact provided by nonworkspaces such as break rooms and respite areas. Break rooms are often multifunctional, providing space for nourishment, team education, as well as team bonding and mentoring. Such spaces may promote staff well-being. Since critical care environments are often high-stress environments, individual spaces devoted to recovery and well-being complement breakroom functionality. The panel made two recommendations. First, including dedicated staff break rooms that provided storage lockers, washrooms with showers, and nutrition areas was embraced as a GPS. An additional consideration is to locate the break room within the ICU, in a space with windows for natural light. Second, a conditional recommendation was crafted for less essential “wellness rooms” or “respite spaces” as promising complements to break rooms, noting that there is limited evidence to support this as a routine practice (55,56). CONCLUSIONS This executive summary and associated article are SCCM evidence-based guidelines, including 15 PICO questions that update SCCMs 2012 guidelines. The guidelines panel considered five themes—layout of ICU rooms, room design, infrastructure, infection control and prevention, and space for staff—as domains related to ICU design. This summary presents five of the 17 recommendations that if implemented will result in ICU designs that are patient, family, and clinician centered. Strong Recommendations were made for: 1) high patient visibility and 2) room environmental features that enhance sleep and recovery. Other recommendations were conditional along with GPSs including: 1) integrated staff break/respite spaces, 2) advanced infection prevention features, and 3) flexible surge capacity design. While the underpinning evidence was of low certainty, these guidelines provides a unique and comprehensive summary of evidence-based design data informed by practice-based expertise.

  PublisherDOI

• Design and the PICO Question

  HERD Health Environments Research & Design Journal · 2025-02-13 · 4 citations

  editorial1st authorCorresponding
  PublisherDOI

• A Tale of Two Guidelines: ICU Design and SCCM

  HERD Health Environments Research & Design Journal · 2025-08-11

  editorialOpen access1st authorCorresponding
  PublisherOA PDFDOI

• Patient experience and information systems research

  Edward Elgar Publishing eBooks · 2025-02-10

  book-chapter1st authorCorresponding

  In recent years as patient-centric care has grown in influence, the state of patient experience has become increasingly important. Patient experience may be the effect of multiple elements, such as the individual's exposure to pain or fear, access to the system, clinical condition, episode outcome, interaction with staff, religious or spiritual situation, or family support, among others. The patient experience is inextricably linked to the provider experience. Patient and provider are bound together by their common digital experiences, including the electronic health information system (HIS). Provider experience may also be the effect of multiple elements, including the physical environment, communication, team resourcing, interoperability, productivity, training and education, among others. Patient experience research has the potential to provide valued feedback, design insight, and a basis for important new interventions and initiatives. In spite of patient-centered care setbacks resulting from COVID, the rich potential for experience-related research studies in healthcare is promising.

  PublisherDOI

• Society of Critical Care Medicine 2024 Guidelines on Adult ICU Design

  Critical Care Medicine · 2025-02-21 · 18 citations

  article1st authorCorresponding

  RATIONALE: Advances in technology, infection control challenges-as with the COVID-19 pandemic-and evolutions in patient- and family-centered care highlight ideal aspects of ICU design and opportunities for enhancement. OBJECTIVES: To provide evidence-based recommendations for clinicians, administrators, and healthcare architects to optimize design strategies in new or renovation projects. PANEL DESIGN: A guidelines panel of 27 members with experience in ICU design met virtually from the panel's inception in 2019 to 2024. The panel represented clinical professionals, architects, engineers, and clinician methodologists with expertise in developing evidence-based clinical practice guidelines. A formal conflict of interest policy was followed throughout the guidelines-development process. METHODS: Embase, Medline, CINAHL, Central, and Proquest were searched from database inception to September 2023. The Grading of Recommendations Assessment, Development, and Evaluation approach was used to determine certainty in the evidence and to formulate recommendations, suggestions, and practice statements for each Population, Intervention, Control, and Outcomes (PICO) question based on quality of evidence and panel consensus. Recommendations were provided when evidence was actionable; suggestions, when evidence was equivocal; and practice statements when the benefits of the intervention appeared to outweigh the risks, but direct evidence to support the intervention did not exist. RESULTS: The ICU Guidelines panel issued 17 recommendations based on 15 PICO questions relating to ICU architecture and design. The panel strongly recommends high-visibility ICU layouts, windows and natural lighting in all patient rooms to enhance sleep and recovery. The panel suggests integrated staff break/respite spaces, advanced infection prevention features, and flexible surge capacity. Because of insufficient evidence, the panel could not make a recommendation around in-room supplies, decentralized charting, and advanced heating, ventilation, and air conditioning systems. CONCLUSIONS: This ICU design guidelines is intended to provide expert guidance for clinicians, administrators, and healthcare architects considering erecting a new ICU or revising an existing structure.

  PublisherDOI

• Researching Building Materials for Passive Pollution Remediation: The 2025 Latrobe Prize

  HERD Health Environments Research & Design Journal · 2025-11-06

  editorial1st authorCorresponding
  PublisherDOI

• Privacy-Preserving Machine Learning for Electronic Health Records

  Preprints.org · 2025-06-13

  preprintOpen accessSenior author

  The integration of machine learning (ML) in healthcare has the potential to revolutionize patient care, optimize clinical workflows, and facilitate personalized medicine. However, the utilization of electronic health records (EHRs) for training ML models raises significant privacy concerns due to the sensitive nature of health data. This paper explores the emerging field of privacy-preserving machine learning (PPML) as a critical approach to safeguarding patient confidentiality while enabling the effective analysis of EHRs. We systematically review various PPML techniques, including differential privacy, homomorphic encryption, and federated learning, assessing their applicability in the context of healthcare data. Differential privacy is examined as a method for adding controlled noise to data outputs, ensuring that the contributions of individual patients cannot be easily inferred. We discuss its implementation challenges, particularly in maintaining the trade-off between data utility and privacy guarantees. Homomorphic encryption, which allows computations to be performed on ciphertexts, is analyzed for its capacity to secure sensitive health information during model training and inference. However, we highlight the computational complexity and resource demands associated with this technique, which may limit its practical application in real-world healthcare settings. Federated learning emerges as a promising paradigm that enables decentralized model training across multiple institutions, allowing EHRs to remain localized and secure. This section delves into the benefits of federated learning in facilitating collaborative research while addressing the challenges of communication overhead and model performance. We also consider hybrid approaches that combine multiple privacy-preserving techniques to enhance security without significantly compromising model accuracy. Furthermore, we investigate the ethical and regulatory implications of implementing PPML in healthcare, particularly in light of stringent data protection regulations such as HIPAA and GDPR. The role of patient consent, data governance, and the need for transparent AI systems are discussed to ensure that privacy-preserving measures align with ethical standards and foster patient trust. In conclusion, while privacy-preserving machine learning presents a viable pathway for leveraging EHRs in healthcare analytics, ongoing research is essential to refine these techniques and address their limitations. This paper contributes to the discourse on balancing the benefits of advanced ML methodologies with the imperative of protecting patient privacy, ultimately advocating for a multidisciplinary approach that integrates insights from computer science, healthcare, and ethical governance. As the healthcare landscape evolves, the adoption of robust privacy-preserving frameworks will be pivotal in harnessing the power of machine learning while safeguarding the confidentiality of sensitive health data.

  PublisherOA PDFDOI

• Survey of Instrumentation Use in Industry: What Does Industry Want New Chemists to Know?

  Journal of Chemical Education · 2024-04-23 · 15 citations

  articleOpen access1st author

  Instrumentation plays a vital role in almost every area of chemistry. As such, it is imperative that the undergraduate curriculum is designed to allow students to have opportunities to use a variety of instruments to best prepare them for careers in chemistry. Previous work has provided evidence of the types of instruments students use in undergraduate chemistry laboratories. However, little is known about employers’ expectations for specific instrument knowledge as chemistry students enter industry. With most chemistry undergraduate students entering careers in chemical industry upon graduation, the aim of this research was to determine the frequency of occurrence and value of specific instruments used in industry to help better align undergraduate chemistry laboratory curricula with the needs of industry. Additional data was also collected on the most important skills needed to succeed in industry, as well as the perceptions of the undergraduate courses where these skills are most effectively acquired. Results emphasize the need to improve how undergraduate students are taught instrumentation-specific skills and provide evidence on the best avenues in which to begin curricular improvement.

  PublisherOA PDFDOI

• An Important Resolution for Design and Health

  HERD Health Environments Research & Design Journal · 2024-08-28

  editorialOpen access1st authorCorresponding
  PublisherOA PDFDOI

Frequent coauthors

• Diana C. Anderson

  Boston University

  26 shared

• Sandra M. Swoboda

  Johns Hopkins University

  20 shared

• Jin-Ting Lee

  National Yunlin University of Science and Technology

  17 shared

• S. W. French

  Google (United States)

  7 shared

• Mardelle McCuskey Shepley

  7 shared

• Debajyoti Pati

  Texas Tech University

  7 shared

• Arsalan Gharaveis

  Arcadis (United States)

  6 shared

• Jaynelle F. Stichler

  5 shared

Labs

• Drew Hamilton LabPI

Education

• B.A., Journalism/Public Relations

  Texas Tech University

  1979

• Other

  New Mexico Military Institute

  1977

• M.S., Systems Management

  University of Southern California

  1987

• M.S., Computer Science

  Vanderbilt University

  1990

• Ph.D., Computer Science

  Texas A&M University

  1996

Awards & honors

• ACM Special Interest Group Ada Distinguished Service Award (…
• Fellow of the Society for Modeling and Simulation Internatio…
• Alumni Professorship, Endowed by the Auburn University Alumn…
• Society for Modeling and Simulation Presidential Service Awa…
• Joint Appointment, Idaho National Laboratory (2020 to presen…