Healthcare

We have an extensive and broad program looking at human factors in health care

Last Updated: June, 2024

Innovation and Technology Acceptance in Community Hospitals: A Human Factors Based Investigation

Duration: Sept. 2023 - Ongoing

Health IT has been shown to positively impact patient outcomes, efficiency of care, and reduce administrative errors. However, research shows that Canada continues to have low health technology adoption rates, with the highest levels found in densely populated urban areas. Conversely, rural and community healthcare facilities face challenges due to insufficient resources, like infrastructure, funding, and specialized staff, exacerbated by their remote locations. The purpose of this study is to uncover the perceptions, expectations, cultural nuances, and barriers to innovative technology adoption at GRH (Grand River Hospital), a community-level hospital in Waterloo. The study aims to bridge the gap between the development of innovative technologies in healthcare and the acceptance, implementation, and subsequent adoption of these tools into the workflow of target users. The design requirements and guidance obtained will be valuable for informing researchers, system designers, and developers of innovative healthcare technologies. Additionally, this information will benefit hospital administrators responsible for planning subsequent implementation processes of new tools.

Sponsors and Partners:

  • Luiza Dos Santos (Co-investigator)
  • Grand River Hospital - Carla Girolametto (Local investigator)
  • Ayesha Waseem (Research assistant)

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The Role of Human Factors in the Adoption of ML-Based Technologies - A Case Study in Ambient Scribe Technology

Duration: Sep. 2023 - June 2024

This work explores the integration of ambient scribe technology into healthcare, focusing on its impact on physician workflow and physician-patient interactions. The study further investigates the role of privacy and trust in the consent/adoption of the technology. Among the key contributions of the study is the development and evaluation of the Multi-Tier Granular Informed Consent (MTGIC) framework using Value Sensitive Design (VSD) and Privacy by Design (PbD) principles.

Sponsors and Partners:

  • Dr. Puneet Seth

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Ecologically Inspired AI-Based Decision-Support: A Constraint-Based Systems Approach to Uncertainty-Aware AI Interfaces for Pediatric Sepsis

Duration: June 2023 - Ongoing

In the context of high-risk, nonspecific conditions like pediatric sepsis, using AI as a clinical decision-support tool may be challenging due to high variability and uncertainty in clinical sings and symptoms. Globally, healthcare systems lack consistent standardized rules and procedures for pediatric sepsis, hindering AI performance and introducing ethical issues if relied on uncritically. An ecological approach to system design that guides both clinicians and AI in decision-making is crucial. This approach would require an AI to learn the clinical boundaries of a child's health and predict deviations from a baseline state, and for clinicians to easily recognize the socio-technical system constraints within which AI predictions are being made, to understand how and when to appropriately rely on them. This doctoral thesis project focuses on the domain of pediatric sepsis because of its incomplete diagnostic definition which leads to inconsistency in clinical applications and treatment across institutions. These inconsistencies provide an ideal context to investigate the advantages of the proposed constraint-based approach to system design in support of human-AI teaming. The outcomes of this work will be (1) an improved understanding of how clinicians conceptualize uncertainty in pediatric sepsis decision-making and the use of AI predictions, (2) a comprehensive Cognitive Work Analysis model of the pediatric sepsis work domain and how AI uncertainty information may impact decision-making, (3) the development and evaluation of ecologically inspired human-AI interface graphics that visualize AI and work domain uncertainty information, and (4) understanding how these graphics may impact expert and non-expert healthcare professionals in a team huddle.

Related Publication:

Tennant, R., Graham, J., Mercer, K., Ansermino, J. M., & Burns, C. M. (2022). Automated digital technologies for supporting sepsis prediction in children: A scoping review protocol. BMJ Open, 12(11), e065429. https://doi.org/10.1136/bmjopen-2022-065429

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Designing a real-time medication intake and adherence dashboard: Features, functionality, and data display to meet the needs of patients, care partners and clinicians

Duration: Jan. 2023 - August 2024

The objective of this study was to determine the key features, utilities, and functionalities of an adherence dashboard to enable patients, care partners, and clinicians to effectively identify and improve medication nonadherence. To achieve this, the study aimed to identify the key features and functionalities users want and need from the dashboard, develop a framework for the essential components of an adherence dashboard, and design a prototype based on this framework. The study successfully accomplished these objectives, resulting in a well-defined prototype that addresses user requirements and supports improved medication adherence.

Related Publications:

This study's findings were presented by Faisal Ghaffar at the Agewell Conference 2023.

Sponsors and Partners:

  • School of Pharmacy, University of Waterloo

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Remote Medical Diagnosis in Virtual Reality: A Mixed-Methods Study of Stakeholder Perceptions Using Thematic Analysis and Regression Discontinuity Design

Duration: Sep. 2022- August 2024

Global healthcare faces challenges, including physician shortages and resource limitations. Telehealth has offered solutions through services such as text and video chats. Yet, these methods have their issues: they provide only limited opportunities for diagnoses, and they do not foster strong patient-physician relationships. Virtual reality (VR) offers a promising future alternative that could facilitate real-time patient-physician interactions that resemble real-life visits through realistic 3D avatars. However, understanding the needs, attitudes, and concerns of both patients and physicians is crucial for tailoring such VR solutions to healthcare's unique demands. Therefore, we conducted an online patient survey (n = 402) and physician interviews (n = 6) to understand these needs. Through thematic analysis, we identify common telehealth concerns, including privacy and the limited scope of diagnoses in VR, and uncover unique elevated concerns, mostly around technology reliability, required expertise, accessibility, and integration with existing workflows. Also, we quantitatively assess the influence of technology affinity on patients' acceptance of VR telehealth through a regression-discontinuity design (RDD) approach, among other techniques. Our mixed-methods approach not only explores critical concerns but also proposes evidence-based considerations for the development of VR-based telehealth solutions.

Sponsors and Partners:

  • Mitacs Accelerate Fellowship

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Understanding the impact of data modality and accuracy on Human-AI collaborative decision-making in sociotechnical systems

Duration: Jan. 2022 - August 2024

This project explores the role of data modality and accuracy in human-AI collaborative decision-making, aiming to understand how these factors influence users' trust and acceptance of AI systems. The research involves human-subject studies with participants interacting with AI systems. It investigates how different data modalities affect decision-making across varied levels of user expertise and examines the impact of AI systems, when using similar and different data modalities as humans, on trust and acceptance. The goal is to identify key variables that enhance the perception of AI systems as reliable teammates, ultimately improving their integration and effectiveness in collaborative environments

Sponsors and Partners:

  • School of Optometry and Vision Science, University of Waterloo

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Patient Registration Transformation at Grand River Hospital

Duration: Jan. 2022- June 2022

This project focused on analyzing the registration efficiency and utilization at Grand River Hospital (GRH) Kitchener-Waterloo campus. Given the significant increase in registration volume over the past decade, compounded by the COVID-19 pandemic, the hospital's registration team faces severe pressures on personnel and space capacity. The study reviewed the registration trajectory from patient arrival to waiting before treatment, aiming to identify efficiency, utilization, and potential bottlenecks. The methodology included observations, interviews, and data collection from various sources. The findings and recommendations were compiled into a report that has been submitted to Grand River Hospital.

Sponsors and Partners:

  • Fan He (partner)
  • Grand River Hospital
  • Kitchener-Waterloo region

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Supporting COVID-19 Mass Vaccination Clinics in the Region of Waterloo

Duration: May 2021-Dec. 2021

The objective of this inter-disciplinary research project was to analyze and improve the COVID-19 immunization campaign in the Region of Waterloo from a human factors perspective. We observed six mass vaccination clinics over four weeks in 2021. Contextual inquiry, contextual design, and tools from the Cognitive Work Analysis framework were applied to model information flow and decision-making processes among clinic workers, and inform the design of an information management and communication software tool. We then iteratively developed, tested, and implemented a cross-platform mobile application to support cognitive work tasks related to tracking client intake and vaccine preparation, improve situational awareness, and minimize the risk of unused doses at the end of each day. Our human factors analysis led to two significant recommendations for future mass vaccination clinics: (1) standardizing strategies and artifacts for data gathering and synthesis to reduce uncertainties for end-of-day-doses decision-making, and (2) co-locating the workstations of vaccine preparation and client intake leads or implementing collaborative digital tools for information sharing. Through the implementation of our contextually informed mobile application, clinic staff reported reduced stress and improved communication efficiency and satisfaction. The app had positive impacts on improved workflow, and future design changes could improve its usefulness. For the 22 participants, the average System Usability Score was 87. The most challenging aspect of design and implementation in this context was meeting the evolving needs of the clinics as rules and mandates quickly changed over time.

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Related Publications:

Tennant, R., Tetui, M., Grindrod, K., & Burns, C. M. (2022). Understanding Human Factors Challenges on the Front Lines of Mass COVID-19 Vaccination Clinics: Human Systems Modeling Study. JMIR Human Factors, 9(4), e39670. https://doi.org/10.2196/39670

Tennant, R., Tetui, M., Grindrod, K., & Burns, C. M. (2023). Multi-Disciplinary Design and Implementation of a Mass Vaccination Clinic Mobile Application to Support Decision-Making. IEEE Journal of Translational Engineering in Health and Medicine, 11, 60–69. https://doi.org/10.1109/JTEHM.2022.3224740

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Sponsors and Partners:

  • Dr. Kelly Grindrod, School of Pharmacy (Partners)
  • Dr. Moses Tetui, School of Pharmacy (Partners)
  • Region of Waterloo (Sponsor)

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Human Interaction with Artificial Intelligence in Healthcare

Duration: May 2020 – April 2021

Artificial Intelligence (AI) systems have been continuously developed with time for various applications in the healthcare domain. Despite having made promising contributions like disease diagnosis, patient risk stratification, drug discovery, treatment selection e.t.c., research has shown that clinicians find it difficult to interact with these AI systems making adoption and implementation very slow. The concern of the clinicians is usually regarding the black box models and how they do not find them understandable, reliable, trustworthy, ethical or fair. We are working on research into providing interpretable and explainable AI systems in healthcare. We are also investigating the interaction of both clinicians and patients with these AI systems.

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Understanding Decision-Making and Support in (Neuro-) Critical Care

Duration: 2019 – 2023

Physiological monitoring in critical care is of utmost importance when examining critically ill patients’ health. Multiple interfaces exist in the ICU and often cause higher cognitive workload as data trending and retrieval can be challenging. Within this project, we use Cognitive Work Analysis models to understand clinicians and aim to support diagnosis and thus better outcomes of patient care.

Related Publications:

  1. Üreten, E., McCredie, V., Burns, C. (2020). Cognitive Work Analysis Models of Neuro-Critical Care. Poster presentation at Human Factors and Ergonomics Society 2020, Toronto, Canada.
  2. Üreten, S., Spallek, J., Krause, D., Üreten, E. (2020). Validation of the Design for Mass Adaptation Method - A Case for Higher Medical Treatment Quality. Presentation at Human Factors and Ergonomics Society 2020, Toronto, Canada.

Sponsors and Partners:

  • Toronto Western Hospital
  • Dr. Victoria McCredie

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Evaluation of a Smart Multidose Blister Packaging System: Integration and Impact on Medication Intake Behaviour

Duration: September 2019 - December 2020

This research project is lead by the University of Waterloo School of Pharmacy, Dr. Tejal Patel and her research team, in collaboration with the AIDL. It is estimated by the World Health Organization that only 50% of people who live with a chronic illness in developed countries adhere to their medication regimen. Non-adherence can result in poor disease outcomes, increased re-hospitalization, and significant costs to our health care system. The objectives of this research are to examine the acceptance of a smart blister packaging system by patients, understand the impact of the system on patient behaviour, as well as the impact of adherence data visualizations on health care providers.

Sponsors and Partners:

Related Publications:

  1. Faisal* S, Ivo* J, Tennant* R, Prior* KA, Grindrod K, McMillan C, Patel T. Implementation of a real-time medication intake monitoring technology intervention in community pharmacy settings: A mixed-method pilot study. Pharmacy.2021;9(2):105

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Stellar Care: A Mobile Application to Support Caregiver Communication in Home Care

Duration: September 2019 - December 2020

Children with medical complexities require 24-hour care and often receive home care nursing to temporarily relieve family caregivers of their responsibilities. However, there is no standard for the handoff of care between these individuals. When a breakdown in communication occurs between caregivers, these children are put at risk for the incorrect administration of a medication and errors in care performance that often involve the use of medical technology. A lack of understanding the best practices for a specific child’s medical condition can result in further variability of the child’s treatment and comfort in their home. Stellar Care is a mobile application that was developed by 4th year Biomedical Engineering students (University of Waterloo, Class of 2019) to facilitate effective communication between family caregivers and home care nurses for continuity of care.This project is currently exploring the design of a conversational agent to support families and nurses in their respective caregiver roles in the home.

Velocity 5k Pitch Video: https://www.youtube.com/watch?v=o3uPSR0nkOc

Related Publications:

  1. Tennant*, R., Leggett*, A., Smith*, C., Tan*, L., Mercer, K., & Burns, C. M. (2020). Addressing Human Factor Challenges in Paediatric Home Care: Development and Evaluation of a Mobile Home Care Communication App. Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care, 9(1), 37–39. https://doi.org/10.1177/2327857920091051

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Stress and Performance in the Workplace

Duration: Sept 2019 – Present

The objective of this research is to investigate how stress management training affects performance in the workplace. To do this, participants experienced a stress-inducing virtual reality simulation made to emulate an industrial setting.  Measurements of heart rate variability were collected during the simulation to be used as an indicator of stress. With the use of HRV and other qualitative measurements, we hope to identify the effect stress management training has on an individual’s overall performance and stress levels.

Sponsors and Partners:

  • NSERC
  • EXO Insights

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The Impact of Ventilator Usability on Patient Safety

Duration: 2018

The high number of ventilated patients in the ICU are often a significant group affected by the outcome of human errors. This pilot study aimed to detect usability errors with different ventilator interfaces, i.e. transitioning from a familiar to an unfamiliar ventilator as well as their equivalent interfaces when standardized nomenclature is incorporated as proposed in the ISO 19223.

Related Publications:

  1. Casares Li, R., Üreten, E., Dain, S., Weiss, K., Burns, C. (2019). A Pilot Study to Assess Ventilators’ Terminology as Proposed in ISO 19223. Poster presentation at Human Factors and Ergonomics Society 2019, Chicago, Illinois.

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Understanding the Effect of Information Exposure on Behaviour Intention

Duration: 2017

The purpose of this study was to investigate how people interact with external information environments for health information gathering and how the exposure to health information actually impacts their behaviour.

Related Publications:

  1. Chin, J., Üreten, E., Burns, C. (2019). Health Behavior Nudging Through Health Information Exposure and Information Search. Poster presentation at Human Factors and Ergonomics Society 2019, Chicago, Illinois.
  2. Chin, J., Üreten, E., Burns, C. (2018). Search for health information across the lifespan: Validation, confirmation or learning. Poster presented at the Cognitive Aging Conference 2018, Atlanta, GA.

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Human factors of improving health care data quality

Duration: January 2014-December 2020

This multiyear project has had several stages.  First we looked at the data quality tradeoffs that primary care physicians make.  Then we implemented a persuasive solution to improve their data entry experience.  Now we are looking at data quality in other contexts.

  1. St. Maurice*, J. and Burns, C.M. (2017). Using cognitive work analysis to compare complex system domains.  Theoretical Issues in Ergonomics Science. Available online at https://doi.org/10.1080/1463922X.2017.1406556
  2. St. Maurice*, J. and Burns, C.M. (2017). Modeling patient treatment with medical records: An abstraction hierarchy to understand competencies and needs. JMIR Human Factors 4(3):e16. 10.2196/humanfactors.6857
  3. St. Maurice*, J. and Burns, C.M. (2017). An exploratory case study to understand primary care users and their data quality tradeoffs. Journal of Data and Information Quality 8, 3-4, 24 pages. 10.1145/3058750
  4. St. Maurice*, J and Burns, C.M. (2016). A method for developing data quality metrics for primary care data. HFES 2016 International Symposium on Human Factors and Ergonomics: Shaping the Future. San Diego, CA. April 13-16. 2016.
  5. St. Maurice*, J., Burns, C.M. (2015). Using comparative cognitive work analysis to identify design priorities in complex socio-technical systems. 2015 International Symposium on Human Factors and Ergonomics in Health Care: Improving the Outcomes, vol 4 no 1, 118-123. doi: 10.1177/2327857915041019.

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Human factors in medication management

Duration: January 2015-December 2020.

This multiyear project has been looking at the human side of medication management.  What decision support do pharmacists need? How do patients manage their medications?  How do we improve adherence to medication based treatment?  This project is funded by TELUS Health and through NSERC and CIHR grants.

  1. Mercer, K., Carter, C., Burns, C., Tennant*, R., Guirguis, L., & Grindrod, K. (2021). Including the Reason for Use on Prescriptions Sent to Pharmacists: Scoping Review. JMIR Human Factors, 8(4), e22325. https://doi.org/10.2196/22325
  2. Mercer, K., Burns, C., Guirguis, L., Abidi, S., Borsema, J., Chabot, C., Chin*, J., Dogba, J., Dolovich, L., Guenette, L., Legare, F., McKinnon, A., Waked, K., Grindrod, K. (2017). What patients want: Understanding how patients view decision making about treatment. CAHSPR: Canadian Association for Health Services and Policy Research. May 24-26, 2017. Toronto, ON.
  3. Grindrod, K., Burns, C., Guirguis, L., Abidi, S., Borsema, J., Chabot, C., Chin*, J., Dogba, J., Guenette, L., Legare, F., Mercer, K., McKinnon, A., Waked, K. (2017). Playing telephone: Understanding the state of medication decision making in growing healthcare teams in the time of electronic health records. CAHSPR: Canadian Association for Health Services and Policy Research. May 24-26, 2017. Toronto, ON.
  4. McMurray, J., Grindrod, K.A., and Burns, C.M. (2017). How appropriate is all this data sharing? Building consensus around what we need to know about shared electronic health records in extended circles of care. Healthcare quarterly 4: 28-36.

  5. Chin*, J., Üreten*, E., Burns, C. (2018). Search for health information across the lifespan: Validation, confirmation or learning. Poster presented at the Cognitive Aging Conference 2018,  Atlanta, GA.

  6. Keresteglioclu*, D., Burns, C.M., Grindrod, K. (2016). Building Bridges Between Physicians And Pharmacists: An Interprofessional Approach to Electronic Health Record Requirements. HFES 2016 International Symposium on Human Factors and Ergonomics: Shaping the Future. San Diego, CA. April 13-16, 2016.
  7. Grindrod, K., Tran*, P., Burns, C.M. (2015). Medication reconciliation: More than just a check. 2015 International Symposium on Human Factors and Ergonomics in Health Care: Improving the Outcomes,vol 4 no 1, 206-212. doi: 10.1177/2327857915041014

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The Monitoring Messenger: Mobile Patient Monitoring for the Intensive Care Unit

Duration: January 2011 - March 2014

Critically ill patients in the intensive care unit (ICU) require constant specialized observation by a number of clinicians (nurses, respiratory therapists, doctors) at a given time. To make decisions and plan treatments, these clinicians need to observe, combine and understand a wide range of information from various devices located at the bedsides of multiple patients. The problems with existing technology are: a) fixed location of monitoring devices at the bedside; b) information overload from too many devices, each with its own display; c) no integration and interaction between devices; d) displays which do not show information in a way that is easy to understand; and e) lack of historical information to support understanding of data and clinical decision making.

To develop the Monitoring Messenger device we have completed a detailed analysis of the work-flow in a pediatric ICU. Based on the results of this analysis we have developed mock-ups of the device. Now we will improve and finalize the device with the direct involvement of healthcare providers. 

The novelty of our project is in its use of a formal design approach and transferring technology developed for the OR into the ICU.

Related Publications:

  1. Görges, M., Morita, P.P., Burns, C.M., Ansermino, J.M. (2013). Mobile Patient Monitoring for the Pediatric Intensive Care Unit – Work Domain Analysis and Rapid Prototyping Results*. IEEE International Conference on Systems, Man, and Cybernetics, 3765-3770.

Sponsors and Partners:

  1. CIHR
  2. NSERC

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Ecological Interface Design for an Automated Rehabilitation Supporting System

Duration: November 2012 - 2014

With the rising number of hip and knee replacement surgeries, more patients are requiring rehabilitation to accelerate the healing process. Rehabilitation clinics are led by physiotherapists who prescribe and customize workout programs based on a clinical assessment of the patient’s progress. These assessments are performed by visual observation, patient questionnaires and goniometry, which can measure range of motion of only a single joint while the patient is at rest. However, even when carefully performed, human errors and biases are likely to occur due to the inherent element of subjectivity in these methods.

To address this concern, an Automatic Rehabilitation System (ARS) is being developed to provide the physiotherapist with quantitative patient data using human motion tracking technologies. Our lab tackles the issue of how to display this information effectively while minimizing the added complexity so that physiotherapists can better assess patient recovery. To this end, evaluations of early prototypes have been conducted with patients and physiotherapists at St. Joseph’s Health Centre (Guelph, ON). This project is in conjunction with the Adaptive Systems Laboratory (Department of Electrical and Computer Engineering) and Cardon Rehabilitation & Medical Equipment Ltd.

Related Publications:

  1. Li*, Y, Kulic, D., and Burns, C.M. (in press). Ecological Interface Design for Knee and Hip Automatic Physiotherapy Assistant and Rehabilitation System. HFES 2014 International Symposium on Human Factors and Ergonomics in Health Care.  Chicago, March 16-19 2014.

Sponsors and Partners:

  1. Adaptive Systems Laboratory (Department of Electrical and Computer Engineering, University of Waterloo)
  2. Cardon Rehabilitation & Medical Equipment Ltd.
  3. NSERC
  4. Ontario Centres of Excellence

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Mobile UI and Persuasive Design for Supporting Patient Adherence and Home Health

Duration: Completed February 2014

Research indicates that behavior change interventions can assist a patient's performance with respect to their health, and empower them to take a proactive role in their well-being. The objective of this research was to identify features that make remote health-monitoring systems more effective. To that end, a persuasive design approach was used to design a prototype application that encourages patients to consult their home monitoring devices appropriately. An exploratory user study was conducted to evaluate the participants’ opinions about the developed prototype, their preferences, as well as their concerns regarding the different components of the mockup.

Related Publications:

  1. Sadat Rezai*, L., Torenvliet, G. and Burns, C.M. (in press). Increasing patient adherence to remote health monitoring systems. HFES 2014 International Symposium on Human Factors and Ergonomics in Health Care.  Chicago, March 16-19 2014.
  2. Sadat Rezai*, L. and Burns, C.M. (in press). Using Work Domain Analysis and Persuasive Design approach for design effective remote health-monitoring systems.  HFES 2014 International Symposium on Human Factors and Ergonomics in Health Care.  Chicago, March 16-19 2014.

Sponsors and Partners:

  • Medtronic
  • NSERC

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Mobile Decision Support for Facilitating Patients in Medical Emergencies 

Duration: Completed September 2013

This research was about developing an effective user interface for a decision support tool for mobile devices, aimed at presenting emergency department waiting-time information to the patient population. The prototype received very positive feedback from a variety of stakeholders, the head of the Emergency Department, and the trained nurses. A user study was also conducted to evaluate the usability of the system. 

Sponsors and Partners:

  • Oculys Health Informatics
  • FedDev Ontario

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Improving Labelling of Pharmaceutical Containers for Injection

Duration: 2006 - 2008

The project provided guidance to improve the labelling of injectable pharmaceutical containers. Existing labels for injectable pharmaceutical containers, specifically ampoules and vials, were evaluated against the Health Canada regulations and the standard developed by the CSA International. A FMEA was performed on the label reading process to identify potential human errors in the process and prioritise their criticality. Based on the results of FMEA, improved label designs will be developed and evaluated via user testing.

Related Publications: 

  1. Jeon*, J. and Burns, C.M. (2009). Standardization and use of colour for labelling of injectable drugs. Proceedings of the International Ergonomics Association World Congress. Beijing, China, August 9-14, 2009.
  2. Jeon*, J., Hyland, S., Burns, CM., Momtahan, K. (2007). Applying FMEA on the process for reading the labels on ampoules and vials for injectable drugs. The 12th World Congress on Health (Medical) Informatics, MEDINFO 2007, 23.
  3. Jeon*, J. Hyland, S. Burns, CM, Momtahan, K. (2007). Applying FMEA on the process for reading the labels on ampoules and vials for injectable drugs. National Healthcare Leadership Conference. Toronto.June 11-12, 2007.
  4. Jeon*, J., Hyland, S., Momtahan, K., and Burns, C.M. (2007). Challenges with applying FMEA to the process for reading the labels on the containers for injectable drugs.  Proceedings of the 51st Annual Meeting of the Human Factors and Ergonomics Society, 735-739.

Sponsors and Partners: 

  1. Institute for Safe Medication Practices Canada (ISMP Canada) 
  2. University of Ottawa Heart Institute (UOHI) 
  3. Canadian Patient Safety Institute (CPSI) 

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CARDIO Project 

Duration: 2004 - 2006

This project developed a mobile decision support tool for cardiac care nursing coordinators doing telephone triage. The support included patient care algorithms, research evidence, electronic record keeping, advanced display ideas, and a mobile drug database. A two month field trial of the support tool showed it was readily adopted, gave useful advice, and supported the triage task well.

Related Publications: 

  1. Burns, C.M., Enomoto*, Y., and Momtahan, K. (2007). The Cognitive Work of Nursing.  The 12th World Congress on Health (Medical) Informatics, MEDINFO 2007, 108.
  2. Momtahan, K.L, Burns, C.M, Labinaz, M, Mesana, T, Sherrard, H.(2007). Using Personal Digital Assistants and Patient Care Algorithms to Improve Access to Cardiac Care Best Practices. The 12th World Congress on Health (Medical) Informatics, MEDINFO 2007, 117-121.
  3. Momtahan, K., Burns, CM.  (2007). Decision Support Tools on Personal Digital Assistants to Promote Knowledge Transfer and Interdisciplinary Communication, and Improve the Quality of Patient Care. National Healthcare Leadership Conference. Toronto.June 11-12, 2007.
  4. Burns, C.M., Momtahan, K., and Enomoto*, Y.  (2006). Supporting the Strategies of Cardiac Nurse Coordinators Using Cognitive Work Analysis. Proceedings of the 50th Annual Meeting of the Human Factors and Ergonomics Society.  San Francisco, CA.  October 16-20, 442-446.
  5. Enomoto*, Y., Burns, C. M., Momtahan, K., and Caves, W. (2006).  Effects of Visualization Tools on Cardiac Telephone Consultation Processes.  50th Annual Meeting of the Human Factors and Ergonomics Society, San Francisco, CA, 1044-1048.
  6. Burns, C.M., Enomoto*, Y., and Momtahan,K. (2008). A cognitive work analysis of cardiac care nurses performing teletriage. Applications of Cognitive Work Analysis.  Bisantz, A. and Burns, C.M. (Eds.). Lawrence Erlbaum and Associates, Mahwah, NJ, p. 149-174.
  7. Momtahan, K., Burns, C.M., Sherrard, H., Labinaz, M., Mesana, T., Caves, W., Enomoto*, Y., Giang*, W., Ho*, V., Pajek*, D., Saunders*, C (2006).. Personal Digital Assistants and Decision Support Software:  New Mechanisms to Improve Access to Cardiac Care Best Practices.  e-HEALTH 2006, Victoria, Canada, May 1-4, 2006.

Sponsors and Partners: 

  1. University of Ottawa Heart Institute (UOHI) 
  2. Ontario Ministry of Health and Long-Term Care 

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Mobile Ecological Interface Design for Diabetes Management 

Duration: 2002 - 2005

The mobile EID (mEID) diabetes management project involved the design and development of a mobile application to help diabetics better visualize elements of their condition, thus improving understanding and management. Variables such as blood glucose and plasma were identified at each level of the Abstraction Hierarchy in the Work Domain Analysis (WDA). The information requirements extracted from the WDA were subsequently used to design the mobile information displays for the application. A usability evaluation of the application revealed that users performed more efficiently with modified task-based mEID displays vs. mEID displays alone.

Related Publications: 

  1. Kwok, J. & Burns, C. M. (2005). Usability Evaluation of a Mobile Ecological Interface Design Application for Diabetes Management. Proceedings of the Human Factors and Ergonomics Society 49th Annual Meeting, 1042-1047.
  2. Thompson, L.K., Hickson, J.C.L., & Burns, C.M. (2003). A Work Domain Analysis for Diabetes Management. Proceedings of the Human Factors and Ergonomics Society 47th Annual Meeting, 1516-1520.

Sponsors and Partners: 

  1. Bell University Labs 
  2. Research In Motion

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