Pei-Yao Hung
HCI Researcher

Researcher and Builder

Empower People with Information and Smart Environment

peiyaoh@umich.edu
        
Resume, C.V., Google Scholar


Supporting Informal Healthcare Teams at Home using Sensor Data


Background: This project is a major part of my dissertation research. Through this project I have gained a deeper understanding of how neurological impairements affect people and their families' life and I have found opportunities to use my skills to support them.

I joined the project initially to assist a senior Ph.D. student, Ayşe Büyüktür, with a qualitative study and data analysis, under the mentorship of two faculty advisors. Since then, I have taken the lead to focus particularly with respect to using my background in computer science to explore interactive system design.


My role(s): Project Leader, Researcher, Designer, Developer

Collaborator(s): Dr. Mark S. Ackerman, Dr. Ayşe Büyüktür, Dr. Michelle Meade, Dr. Mark W. Newman


Method(s):
Contextual InquiryCo-designFocus GroupPrototypingUsability TestingQuestionnairePersonaScenarioWithin-Subject ExperimentThematic AnalysisAffinity WallCard Sorting
Skill(s):
JavascriptCSSHTMLReactNode.jsNoSQLRQualtrics

Motivation: Teenagers with a chronic health conditions, such as spinal cord injuries deal with enormous challenges, including managing ever-changing health status, working with their care-teams in their everyday lives, maintaining their self-image, and coping with social expectation for them to be independent in the process of transitioning to adulthood.

"When you are teenage, you start becoming self-conscious about everything."

~ Patient/Co-design Partner

Problem Solving: To provide important observations of the care experience, my team and I conducted interviews with 27 stakeholders to understand how sensor-based technology can support care-team collaboration. As stakeholders might be new to sensors and data, I further conducted co-design activities with 1 patient so that insights could be drawn from sharing our knowledge and experience in continuous engagement.

I developed a system, Data Checkers, that enables users to visually compose sharing settings for fine-grained control and have evaluated it with 15 patients and caregivers through a comparison study.

  • Interview & Focus Group

    27 stakeholders

  • Co-design

    1 patient

  • Protootype & Evaluations

    15 participants

  • Card Sorting

    24 participants

  • Interviews

    30 participants


Outcomes:

Findings:

  • Independence is achieved collaboratively: a patient's independence is achieved through collaboration since the distribution of responsibilities directly affects the quality of independence.
  • Responsibility is continuously redistributed: the distribution of responsibilities changes based on the patient's health and the stability of different care routines.

Major design suggestions:

  • Support fine-grained control to enable a sense of independence: sensor-based technology should allow data sharing to be continuously negotiated with fine-grained control among a patient, family, paid caregivers, and clinicians to accommodate the patient's desired level of independence.
  • Tailor system proactiveness to provide an appropriate level of engagemnet: sensor-based technology should tailor user engagement with different levels of proactiveness to align with the stability of care routines.

I am still continuing the design and evaluation of Data Checkers. Initial analysis shows that participants can use the visual composition environment provided by Data Checkers to create and adjust sharing settings efficiently and flexibly. I have recently conducted two additional studies, and I am currently writing reports to summarize my findings on how to further simplify the process of creating sharing settings and using additional support to manage sharing through team collaboration.

"[Sharing data that is] sensitive enough but not so sensitive!"

~ Patient/Co-design Partner

The outcomes of this project include several scholarly publications (link) and a web-based prototype that allows patients to create sharing settings through a grid-based user interface.


Summary:


Date: 2017 ~ Present.

Poster for Privacy@Michigan 2019 - Celebrating International Data Privacy Day

Research & Design Strategy


Understand Care Team Members' Lived Experience using Interview and Focus Group

The goal of the research project is to understand the lived experience of patients with neurological impairments such as spinal cord injuries and that of their family members, and clinicians, as such chronic care often time requires assistance from them. I am particularly interested in how members of such care team collaborate and coordinate with each other with the goal of informing the design of sensor-based technology that can collect data to support such collaboration.

The overall approach for this project is to ground our design based on a solid understanding of care teams' experiences. I employed multiple methods to understand the care team members' perspectives and invited a patient to co-design with the research team.

My team and I started by using semi-structured interviews and a focus group to obtain team members' experiences of managing or helping to manage the illness and care activity.

The care team of a patient: the patient, family caregivers, paid caregivers, and clinicians

Engage Stakeholders with the Concepts of Sensors and Data through Sketches to Facilitate Brainstorming

With a solid understanding of the way care team members are collaborating and the challenges they faced currently, I then invoked sketches and other visual materials to introduce the concept of sensor and data. I employed visual materials as tools because our participants might not be familiar with the concept of sensors and data. Therefore, it might be hard for them to provide feedback simply through methods such as interviews that are heavily based on experience. The use of such visual materials helped our participants to reflect on how sensor technology could create a positive impact on their work and the unintended consequence that designers of such technology should be aware of.

Four charts showing different visualization (left to right) highlighting 1) amount, 2) goal and progress, 3) ratings, and 4) a check mark (done it). The charts were used to prompt particiapnts to think about how different data categories and granularity might be useful for monitoring care activities and a patient's health.

The Lo-Fi prototype was used to gauge users' reaction to systems that would engage after certain care activity had been carried out. The system would (A) report current progress toward goal or (B) recommand a specific plan.

Conduct Thematic Analysis to Identify Key Insights for Sensor System Design

By performing thematic analysis on the transcripts and memos, my team and I identified design implications for systems and applications that use sensor data to support care team collaboration. The two major themes were supporting routinization of care activity and allowing fine-grained control over data to share. For more details, please see the Outcomes section, including publications.

Co-Design with a Young Adult as Design Partner to Identify Key Attributes and Develop a Web System

To investigate how fine-grained control can be realistically implemented for regular users without technical training, I employed a co-design process with an undergrad student with a neurological condition for two semesters to design a mobile app for managing the sharing of sensor data. To truly engage the participant as a co-design partner, I designed a short version of the Human-Centered Design curriculum for the participant to get familiar with concepts such as persona and scenario. I invited the participant to be the designer who could bring in his own experience interacting with care team members to guide the design. Through weekly co-design sessions, I worked with the participant to design a mobile app that allowed a patient to control sensor data collected for and about the patient by regulating data sharing with care team members.

A whiteboard snapshot of our co-design session where my co-design partner and I were discussing, for the same data category, he (partner) might want to have the capability to present data at different levels of details for paid caregivers and the primary caregiver.

As the participant was very passionate about video games, I also explored the possibility of incorporating certain game design elements (e.g., visual) to enrich the experience for patients to understand how to control the sharing of their data, in addition to the mobile app. I have implemented a system, Data Checkers, and conducted a comparison study to evaluate the effectiveness of the design to support data sharing in chronic care.


Outcomes

Findings & Implications

Designing Technological Intervention and Support to Facilitate Routine Development

By engaging with participants through various approaches, my team and I have identified two key aspects that designers should consider. First, care activities (e.g., drinking waters and doing bowel program) are being routinized continuously for patients and care team members to provide stability of care. Sensor-based technology should tailor user engagement with different levels of proactiveness based on the stage of routinization to provide the necessary support to care teams.

Sensor-based technology to support chronic care should tailor automatic and manual tracking based on difference phases of routinization of care activities to properly support the patient and the care team as a whole.

Support Fine-Grained Control over Data Sharing to Balance Sharing and Privacy (Sharing Just Enough)

Second, patients desire to gain independence progressively within a complex and ever-changing care team. Patients want to control their lives but are not familiar with the nature of sensor data. Sensor-based technology should allow fine-grained control over data being shared to different care team members and provide support for patients to jump-start and understand the data sharing process. At the same time. as health, care team, and hence the care evolve, care team members will need a certain level of autonomy to access data so as to support their work effectively. Sensor-based technology should allow data sharing to be continuously negotiated among care team members.

Sensor-based technology to support chronic care should support continuous negotiation of fine-grained data sharing to appropriately support the development of independence within an ever-changing care team, whose members have different experience and expertise.

Systems & Applications

An interactive system, Data Checkers, using a board-game metaphor such as Checkers was developed to support fine-grained control. Data Checkers' system consists of a front-end user interface and a backend server. The backend server was developed to support the interpretation and enforcement of sharing decisions. I conducted a within-subject study to compare our design with another state-of-the-art design proposed by fellow researchers. My evaluation demonstrated that Data Checkers allowed participants to effectively think and control data sharing of multiple sensor data sources with care team members and has the potential to support the long-term management of sensor data.

Publications

Hung, Pei-Yao, Mark S. Ackerman (2022). Helping People to Control Their Everyday Data for Care: A Scenario-Based Study. Lewy, H., Barkan, R. (eds) Pervasive Computing Technologies for Healthcare. PH 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 431. Springer, Cham[Online][BibTex]

Hung, Pei-Yao, Drew Canada, Michelle A. Meade, Mark S. Ackerman (2022). Data Checkers: A Grid-Based UI for Managing Patient-Generated Data Sharing to Support Collaborative Self-Care. Frontiers in Computer Science, Volume 3, January 2022[Online][BibTex]

Hung, Pei-Yao (2022). Designing System Support for Sharing Everyday Data for Chronic Care. UMich PhD Dissertation, Ann Arbor, Michigan, USA[Online][BibTex]

Hung, Pei-Yao, Mark S. Ackerman (2019). Supporting Care Teams with Participatory Governance over Data Sharing. Who Cares? Exploring the Concept of Care Networks for Designing Healthcare Technologies Workshop in the The 17th European Conference on Computer-Supported Cooperative Work (ECSCW), June 8, Salzburg, Austria[BibTex]

Büyüktür, Ayse G., Pei-Yao Hung, Mark S. Ackerman, Mark W. Newman (2018). Supporting Collaboratively Constructed Independence: A Study of Spinal Cord Injury. Journal Proceedings of the ACM on Human-Computer Interaction - CSCW, Volume 2 Issue CSCW, November 2018, Article No. 26[Online][BibTex]

Büyüktür, Ayse G., Mark S. Ackerman, Mark W. Newman, Pei-Yao Hung (2017). Design Considerations for Semi-Automated Tracking: Self-Care Plans in Spinal Cord Injury. 11th EAI International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), Barcelona, Spain, May 23-26. pp 183-192[Online][BibTex]

Ackerman, Mark S., Ayse G. Büyüktür, Pei-Yao Hung, Michelle Meade, Mark W. Newman (2017). Sociotechnical Design for the Care of People with Spinal Cord Injuries, in Designing Healthcare That Works: A Sociotechnical Approach, Ackerman, Mark, A., Michael Prilla, Christian Stary, Thomas Herrmann, Sean Goggins (eds.), Academic Press, 2017[Online][BibTex]




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