Care Labor and AI
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Care Labor and AI

Design Considerations for Home Health Care.

Photo by Christina Victoria Craft on Unsplash

Home Health Care is crucial yet complex. Here are a few considerations to keep in mind while designing for this industry.

  • Accounting for all Stakeholders — We’re looking not just at the HHA’s but the agencies that they work with, doctors and nurses that they communicate with, the patient that’s under their care, and anyone else who may be present in their location of work. The needs and difficulties of each stakeholder vary greatly which makes it a challenge to design for everyone.
  • Privacy Protection — A patient's data is protected under HIPAA and additional channels of communication between various stakeholders run the risk of violating confidentiality. Any technologies designed to aid HHA’s and provide enhanced methods of communication and information sharing would have to be mindful of this.
  • Scalability — I was surprised to learn that HHA’s are one of the fastest-growing segments of the American workforce. Given their high numbers and impact it would make sense to design supportive systems that can either be suited to all requirements or easily customized to meet more specific needs.
  • Mode of delivery — The effectiveness of new technology could differ based on how it’s made available to the users. For example, would it make more sense to deploy a digital solution on an HAA’s personal device for convenience or an additional device for security? Both come with their own set of capabilities and trade-offs.
  • Levels of abstraction — How much does an HHA need to know? How detailed should their instructions be? If they are supported in their job by having access to resources to learn more about their patient's condition, would they be overwhelmed? It becomes important to determine what information should be shared with them to reach a level of practical awareness.
  • Increasing support — Most HHA’s report back to agencies that handle their payments and appointments. Naturally, there is a level of friction between both parties. Additional technologies may lead to more detailed logging of an HHA’s work and in turn greater scrutiny from the agencies. How might we design a system that supports HAAs in their role but doesn’t make them feel like they’re being constantly monitored?
  • Considerations for the larger ecosystem — HHAs fit into the overarching ecosystem of healthcare. It becomes important to be mindful of how changes that are made within their environment have an impact on the bigger picture.
  • Learning curves — It can be tempting to design and deploy a new system that addresses every pain point, but an unfamiliar system will take time to learn and could have an adverse effect on a stakeholder's overall performance. Should it be released in phases? Should it be as close as possible to existing systems?
  • Low scope for error — Design is usually best validated when tested with real users. While that should be the goal in this case too, several initial validations will have to come from different means because a flaw in design could have an effect on a patient's health. Initial versions of developed technologies would have to already to fairly robust and functional.

(This article is one in a series of more to come, consolidating research done at the Tech Solidarity and CoALA Labs)

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