administrators

Here is a bill of rights developed by a patient and healthcare person:

https://www.linkedin.com/pulse/developing-patients-ai-bill-rights-hospitals-medical-dan-noyes-rs9ae/

I came across this article by Ranvir Rai on LinkedIn about the role of caregivers in the Hospital @ Home programs. It is worth the read.

Take a look at the diagram that says it all:

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Here is how Lewis Eisen describes his book and how it relates to signs used in healthcare and how it sets up the relationship with the patient:

I specialize in policy writing, with a specific focus on how institutional policies communicate with the people expected to follow them. My work helps organizations write policies that are clear, effective, and respectful.

I recently published a book titled WHY ARE YOUR RULES YELLING AT ME? When rules treat adults like children. It applies this perspective to a problem faced by patients and caregivers in healthcare settings. Chapter 1 examines the confrontational wording frequently seen on signs stating, in one form or another, that “abuse from patients will not be tolerated. ”More broadly, the book draws attention to a longstanding but often overlooked problem: the effect institutional language can have on trust, dignity, and the relationships on which effective service depends.

Staff safety is, of course, a legitimate and important concern, and there’s no excuse for abusing service staff in any context.

The problem is that these signs start the relationship between patients, caregivers, and providers off on the wrong foot. Before anyone has even exchanged a greeting, every patient is confronted with a harsh warning that presumes they may be a potential troublemaker. The vast majority arrive in good faith, many of them anxious, in pain, or frightened, and this wording does nothing to put them at ease. Moreover, the people who actually abuse staff are generally either unaware of their behaviour or indifferent to such warnings. Essentially, the signs are ineffective on troublemakers and off-putting for everyone else.

More appropriate wording for these signs would be along the lines of “Your patience is appreciated” or “We treat everyone with respect and ask the same in return.”

I have attached a complimentary copy for your interest. There is certainly no need to read the entire book; Chapter 1 contains the discussion I am referring to.

The book was not written as a profit generator, so prices have been kept to a bare minimum. Amazon sells the paperback version for CAD $12.50, and the Kindle —and Apple —versions are both priced at $0.99. The PDF version (linked above) is available at no cost. Check out the site to https://lewiseisen.com/yelling/ to pick up their own copy.

I would be interested in learning what you think. I believe the CPCRC is an important vehicle for connecting primary care data in Canada. I will be on holidays so am counting on all of you who finally have the links. If there are still link issues, we can raise it with Onil et al.

SCPOR’s Patient Partner Mentorship Program

Interested in learning more about patient-oriented research and how to contribute as a patient partner on a research team? SCPOR’s Patient Partner Mentorship Program connects mentees with experienced mentors who can provide guidance and support in navigating patient-oriented research partnerships.

https://www.scpor.ca/mentorship

@Jayden-Tang You might want to also enter it as an Opportunity. There is a form on the Opportunities tab where you can do this.

Interesting tool developed by the Vector Institute, Canada. Take a read: UnBias-Plus AI tool detects and rewrites bias in text

David Gilbert, a leading UK patient partner has a newsletter that is worth subscribing to. He has this in his recent edition:

Dear ImPatient subscriber,

I hope you are enjoying the summer, but I know many are struggling.

AI mental health self-help tools are growing fast - I’ve used AI myself for support with my own mental health problems. But protection for the people using them isn't keeping pace.

This growing gap is precisely why I’ve worked with the Centre for Mental Health to produce Unequal benefits, unequal harms, a discussion paper on AI mental health chatbots, inequality and the risks of self-guided care. READ HERE

The paper finds people’s use of AI to support mental health has outpaced the development of robust mechanisms to mitigate problems. Oversight is uncoordinated, and there are significant gaps in evidence, accountability and patient safety.

While these tools may improve access and affordability for some, the paper warns that the benefits won't be distributed evenly - and that the risks of generative AI mental health systems are likely to fall disproportionately on people who are already vulnerable. Large language models can also absorb and repeat patterns of structural discrimination, reinforcing stereotypes or invalidating certain identities.

There's also a data gap: we don't know enough about who is using these tools across different demographic and socioeconomic groups, including in relation to deprivation, ethnicity, disability, neurodiversity, severe mental illness and experiences of trauma.

Take a look at his website InHealth Associates UK and sign up to his newsletter.