Telehealth and Digital Health Innovations

Telehealth and digital health innovations: A mixed landscape of access Phuong J, Ordóñez P, Cao J, Moukheiber M, Moukheiber L, et al. (2023) Telehealth and digital health innovations: A mixed landscape of access. PLOS Digital Health 2(12): e0000401. https://doi.org/10.1371/journal.pdig.0000401

In the wake of emergent natural and anthropogenic disasters, telehealth presents opportunities to improve access to healthcare when physical access is not possible. Yet, since the beginning of the COVID pandemic, lessons learned reveal that various populations in the United States do not or cannot adopt telehealth due to inequitable access. We explored the Digital Determinants of Health (DDoHs) for telehealth, characterizing the role of accessibility, broadband connectivity and electrical grids, and patient intersectionality. In addition to its role as an existing Social Determinant of Health, Policies and Laws directly and indirectly affect these DDoHs, making access more complex for marginalized populations. Digital systems lack the flexibility, accessibility, and usability to inclusively provide the essential services patients need in telehealth. We propose the following recommendations: (1) design technology and systems using accessibility and value sensitive design principles; (2) support a range of technologies and settings; (3) support multiple and diverse users; and (4) support clear paths for repair when technical systems fail to meet users’ needs. Addressing these requires change not only from providers but also from the institutions providing these systems.

“A Tool for Freedom”

Jerry Cao, Krish Jain, Julie Zhang, Yuecheng Peng, Shwetak Patel, and Jennifer Mankof. 2025. “A Tool for Freedom”: Co-Designing Mobility Aid Improvements Using Personal Fabrication and Physical Interface Modules with Primarily Young Adults. In CHI Conference on Human Factors in Computing Systems (CHI ’25), April 26–May 01, 2025, Yokohama, Japan. ACM, New York, NY, USA, 16 pages. https://doi.org/10.1145/3706598.3713366

Mobility aids (e.g., canes, crutches, and wheelchairs) are crucial for people with mobility disabilities; however, pervasive dissatisfaction with these aids keeps usage rates low. Through semi-structured interviews with 17 mobility aid users, mostly under the age of 30, we identified specific sources of dissatisfaction among younger users of mobility aids, uncovered community-based solutions for these dissatisfactions, and explored ways these younger users wanted to improve mobility aids. We found that users sought customizable, reconfigurable, multifunctional, and more aesthetically pleasing mobility aids. Participants’ feedback guided our prototyping of tools/accessories, such as laser cut decorative sleeves, hot-swappable physical interface modules, and modular canes with custom 3D-printed handles. These prototypes were then the focus of additional co-design sessions where six returning participants offered suggestions for improvements and provided feedback on their usefulness and usability. Our findings highlight that many mobility aid users have the desire, ability, and need to customize and improve their aids in different ways compared to older adults. We propose various solutions and design guidelines to facilitate the modifications of mobility aids.

Domain Specific Metaheuristic Optimization

For non-technical domain experts and designers it can be a substantial challenge to create designs that meet domain specific goals. This presents an opportunity to create specialized tools that produce optimized designs in the domain. However, implementing domain specific optimization methods requires a rare combination of programming and domain expertise. Creating flexible design tools with re-configurable optimizers that can tackle a variety of problems in a domain requires even more domain and programming expertise. We present OPTIMISM, a toolkit which enables programmers and domain experts to collaboratively implement an optimization component of design tools. OPTIMISM supports the implementation of metaheuristic optimization methods by factoring them into easy to implement and reuse components: objectives that measure desirable qualities in the domain, modifiers which make useful changes to designs, design and modifier selectors which determine how the optimizer steps through the search space, and stopping criteria that determine when to return results. Implementing optimizers with OPTIMISM shifts the burden of domain expertise from programmers to domain experts.

Megan Hofmann, Nayha Auradkar, Jessica Birchfield, Jerry Cao, Autumn G. Hughes, Gene S.-H. Kim, Shriya Kurpad, Kathryn J. Lum, Kelly Mack, Anisha Nilakantan, Margaret Ellen Seehorn, Emily Warnock, Jennifer Mankoff, Scott E. Hudson: OPTIMISM: Enabling Collaborative Implementation of Domain Specific Metaheuristic Optimization. CHI 2023: 709:1-709:19

https://youtube.com/watch?v=wjQrFeLbOiw%3Fsi%3DkMTxEkEBjoUrQDJ3

Rapid Convergence: The Outcomes of Making PPE during a Healthcare Crisis

Kelly Avery MackMegan HofmannUdaya LakshmiJerry CaoNayha AuradkarRosa I. ArriagaScott E. HudsonJennifer Mankoff. Rapid Convergence: The Outcomes of Making PPE During a Healthcare Crisis. [Link to the paper]

The U.S. National Institute of Health (NIH) 3D Print Exchange is a public, open-source repository for 3D printable medical device designs with contributions from clinicians, expert-amateur makers, and people from industry and academia. In response to the COVID-19 pandemic, the NIH formed a collection to foster submissions of low-cost, locally-manufacturable personal protective equipment (PPE). We evaluated the 623 submissions in this collection to understand: what makers contributed, how they were made, who made them, and key characteristics of their designs. We found an immediate design convergence to manufacturing-focused remixes of a few initial designs affiliated with NIH partners and major for-profit groups. The NIH worked to review safe, effective designs but was overloaded by manufacturing-focused design adaptations. Our work contributes insights into: the outcomes of distributed, community-based medical making; the features that the community accepted as “safe” making; and how platforms can support regulated maker activities in high-risk domains.

Maptimizer

Megan HofmannKelly MackJessica BirchfieldJerry CaoAutumn G. HughesShriya KurpadKathryn J. LumEmily WarnockAnat CaspiScott E. Hudson, Jennifer Mankoff:
Maptimizer: Using Optimization to Tailor Tactile Maps to Users Needs. CHI 2022: 592:1-592:15 [pdf]

Tactile maps can help people who are blind or have low vision navigate and familiarize themselves with unfamiliar locations. Ideally, tactile maps are created by considering an individual’s unique needs and abilities because of their limited space for representation. However, significant customization is not supported by existing tools for generating tactile maps. We present the Maptimizer system which generates tactile maps that are customized to a user’s preferences and requirements, while making simplified and easy to read tactile maps. Maptimizer uses a two stage optimization process to pair representations with geographic information and tune those representations to present that information more clearly. In a user study with six blind/low-vision participants, Maptimizer helped participants more successfully and efficiently identify locations of interest in unknown areas. These results demonstrate the utility of optimization techniques and generative design in complex accessibility domains that require significant customization by the end user.

A system diagram showing the maptimizer data flow setup. The inputs are geography sets, representations options, and user preferences. Geography types and representation options are paired and tuned using an optimizer. The output is a tactile map.