Sunday, February 2, 2025

Bloom's Taxonomy level 6 toward integrating real patient centred Medical education and practice, delivered in real time with parallel transformation to medical education simulations

 Introduction:


In clickable PPT slides one after the other back and forth:

 

 

Current Demo:


Here's one patient centred level 6 , team based learning exercise archived on a daily basis : https://pajrcasereporter.blogspot.com/2024/10/80m-diabetes-hypertension-30yrs-ckd.html?m=1

where the diet plates have been analysed by AI and team members have had to creatively rack their minds on how to balance the patient's far from ideal diet due to poverty, frailty and lack of exercise due to aging and insulin requirements further complicated by the fact that the free government supply that he survives on is a mixtard insulin that cannot be taken more than twice and increasing the doses can produce hypoglycemia while keeping it less produces hyperglycemia giving a very narrow therapeutic window to work on unless one is allowed to add plain soluble insulin (which is unfortunately not in government supply). He also survives on a meager pension of 2000 RS per month!

 

We took the patient on stage to the university of Hyderabad for a gathering of AI  engineers from India and Australia working on elderly care and in slide 8 here: https://medicinedepartment.blogspot.com/2024/11/technology-end-user-driven-ecosystem.html?m=1, you can find his videos where he and his wife have taken center stage and are answering questions from our students and the gathered audience.


Some more links around our work that can answer:

1) How should we teach medical students in the digital era, based on our observations around harnessing Blooms level 6 in real time real patient centered care as well as transform them into medical education simulations?

Here's more as to how the digital era of medical education challenges the traditional era of dyadic doctor patient relationships and calls for team based learning across multiple stakeholders including across a web based interface aka user driven healthcare (which in general has spontaneously evolved over the last few decades globally and currently happens in multiple patient and professional user groups) centred around individual patients: https://pmc.ncbi.nlm.nih.gov/articles/PMC4587042/

Here's the conceptual model of PaJR which is currently our most used and apparently effective tool to interact around individual patient centered issues of clinical complexity in their own separate groups: https://userdrivenhealthcare.blogspot.com/2022/09/current-pajr-workflow-and-how-to-make.html?m=1


The individual patient PaJRs are fed also by a CBBLE (pronounced cable) that is essentially humanly analogous to the hidden layer of an artificial neural network model where team based learning discussion happens around individual patients, particularly where the technical details may not be palatable for the individual patient and their advocates who are included and limited to the PaJR but not in CBBLE and the eventual broader aim of a CBBLE is to achieve individual patient centred age old precision medicine as highlighted in it's flagship article here: https://pmc.ncbi.nlm.nih.gov/articles/PMC6163835/

2) What recommendations should we make to develop such training programs,  which includes collaborations among health practitioners/biomedical engineers/ Social scientists/Patients/ Script writers to create a set of visual of  reality-based simulations?

Background to evolution of reality based simulations in medical education as an offshoot of trying to integrate medical practice with education in real time:

Here's a simulation derived from a real PaJR patient reported by PaJR Jarvis: https://userdrivenhealthcare.blogspot.com/2023/11/pajr-jarvis-reports-final-entry-for.html?m=1

Here's a real PaJR patient, e-met and worked up online from USA by one of our students who has made it a simulation driver here: https://classworkdecjan.blogspot.com/2019/05/?m=0, and this was subsequently analysed by a batch of 200 of our MBBS students as a clinical data analysis project available in their individual online learning portfolios (pre LLM era, with 5000 cases in 1000 online learning portfolios available here in our dashboard: https://medicinedepartment.blogspot.com/2022/02/dashboard-for-our-current-cbble-case.html?m=0), also subsequently recently analysed using an LLM here: https://classworkdecjan.blogspot.com/2024/09/just-another-llm-analytics-but-for-our.html?m=0

Here's a AR VR simulation created by one of our students around a patient which one can even use a 3D goggles to view:


Here are our online patient records encased in a virtual ward http://myvirtualward.blogspot.in/2016/01/blog-post.html

where one can get inside by clicking below the ward image and then further access each patient record  by clicking on the bed numbers.

Recommendations:

The first step to creating a patient simulation is to deidentify the patient as per HIPAA guidelines, again a regular feature in all the case reports in our PaJR CBBLE as an important part of our training program: 


Past recommendations to global learning toward hyperlocal caring: 



Building dynamic ontologies that can continue to optimize themselves to adapt to change over that of static ontologies that can't be optimised and are copyrighted:


[01/12, 17:45] Meta AI: Dynamic ontologies offer several advantages over static ontologies:

*Advantages of Dynamic Ontologies*

1. *Adaptability*: Dynamic ontologies can adapt to changing knowledge, new discoveries, or updates in a domain, ensuring the ontology remains relevant and accurate.
2. *Improved accuracy*: By continuously optimizing themselves, dynamic ontologies can reduce errors, inconsistencies, and ambiguities, leading to more reliable and trustworthy knowledge representations.
3. *Enhanced scalability*: Dynamic ontologies can handle increasing amounts of data and complexity, making them more suitable for large-scale applications and big data integration.
4. *Collaboration and community engagement


The above theme of "Bloom's Taxonomy level 6 toward integrating real patient centred Medical education and practice" also 

builds on many decades long medical education journey right from our first reading of this article :

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC65539/


We have learned after countless editing journeys of long case reports that real OSCEs bloom in the "discussion" section of the long case report and that discussion is Blooms level 4-6 that analyzes (level 4) the applied (level 3) case data and provides an evaluation (level 5) of the overall patient's predicament synthesizing (level 6) data collected from collective memory (level 1) of the patient's life events and outcomes comparing it with a conceptual understanding (level 2) of collective memories of other similar and dissimilar patients that insinuate our collective consciousness.  


If one can get the osce right in each and every real patient participant, one can easily attain the Bloom's level 6 goal of utilising medical education learning outcomes to positively drive real patient participant outcomes!


The apparently new OSCE we are trying to promote is hands on professional skill development in objectively structuring (OS) real patient centered subjectivity toward optimal clinical evaluation (CE) in improving real patient outcomes in real time!

There's nothing new to it as it's an age old routine real clinical workflow for every physician that often goes unsung and we are probably trying to add a song here! 



 Above is an image of our online patient records encased in a virtual ward that you can actually see by clicking in the link here: http://myvirtualward.blogspot.in/2016/01/blog-post.html


After getting inside the ward one can further access each patient record  by clicking on the bed numbers.

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