Sunday, December 15, 2024

Current issues with MD residency thesis projects and potential solutions

Summary:


The MD thesis project system in tier 2 medical colleges in India is increasingly challenged, with students and faculty struggling to navigate the process. A proposed solution involves optimizing study design, prospective data capture, and thematic analysis using collective medical cognition tools and AI-driven qualitative thematic analysis.

Key words:

1. MD thesis projects
2. India
3. Study design optimization
4. Prospective data capture
5. Collective cognition tools
6. AI-driven qualitative thematic analysis
7. Medical education
8. Research methodology



Problem statement:

MD thesis projects submitted in India has become a quagmire and often hated by faculty and students both as a sore point that continues to be enforced by policy makers as a mandatory requirement to obtain the MD degree and most tier 2 medical colleges in India just pay superficial lip services to these thesis projects as also shared earlier in the UDLCO linked here: https://userdrivenhealthcare.blogspot.com/2024/02/udlco-indian-medical-faculty-and.html?m=1
One of the biggest reasons for the problem is that faculty and students are largely left to their own survival strategies to execute their thesis workflow and learn to fend for themselves, anecdotally often believed to learn to utilise short cuts that do more harm than good to their overall learning experience.

Solutions:

1) Optimizing Study Design:

Real patient centered qualitative study design with quantitative descriptions (mixed methods) that enables easier integration with existing patient care workflows.


2) Optimizing prospective data capture utilising collective cognition tools:

This tackles one of the biggest issues of the system's current inability to offer the lonely post graduate resident learner a  collective cognitive support that is also transparent and accountable.

Each patient data is begun to be captured as soon as the first encounter happens in the outpatient or inpatient setting and the patient is followed up through a system of PaJR and CBBLE where a team of patient centered advocates, faculty, students, interns and post graduate resident learners make the data grow with time through team based learning as illustrated here: 

Sample PaJR data of individual thesis patients in NMC dynamic E logged case report links:


The above single patient's data with clinical complexity and comorbidities can fit into multiple ongoing thesis projects as illustrated here:

1) Factors influencing sepsis outcomes: 

2) Trunkal obesity and biopsychosocial factors influencing outcomes:

3) Diagnostic and therapeutic factors influencing outcomes of patients with anemia in chronic renal failure

4) Spectrum of clinical presentations in diabetes with multimorbidities and factors influencing their outcomes 


The above single patient's data with clinical complexity and comorbidities can fit into multiple additional ongoing thesis projects as illustrated here:

4) Factors influencing the  development of heart failure and other outcomes in patients with suspected chronic CAD

6) Factors influencing  recovery outcomes in patients with respiratory failure 




3) Thematic analysis sample drafts of thesis projects analysed and submitted to university:





Inspite of the above simple strategy that involves regular participation through a  collectively supported ecosystem it's still cumbersome for post graduate residents to warm up to the above collectively supported transparent and accountable workflow and many of them simply resort to collecting very sketchy data alone in limited paper based 
case report forms and then retrospectively analysing those limited data where large part of the patient's could be missing. Last year we managed to upgrade this paper based limited thesis data collection by utilising EMR summaries prepared by the interns during each patient's discharge and while these were still far from the quality of data desired it was very useful in faster thematic data analysis using current AI LLM tools.


Sample final assessment and certification of the thesis:


Submitted template:
This is to certify that this dissertation titled ‘‘... outcomes in patients with ... disease in chronic ... disease" is a bonafide research work done from Mid 20xy - Mid 20xz under my guidance by Dr. ABC  ( Reg No: abcefgD )

The quality and validity of the data captured from each case, including patient outcomes in the study, may have been enhanced if it had been shared with our team regularly from the first and subsequent clinical encounters and not just before final submission deadline. This work was done in partial fulfilment of regulations laid down by xyz University of Health Sciences for MD General Medicine Degree Examination to be held in mm/DD/yy


Date:  
Place: 

                                                                                                        Professor
Department of General Medicine


Thematic Analysis of the entire above write up:

The conversation can be grouped into several themes:

1. _Problem Statement_: The MD thesis project system in India is flawed, with students and faculty struggling to navigate the process.

2. _Solutions_: Optimizing study design, prospective data capture, and thematic analysis using collective cognition tools and AI-driven qualitative thematic analysis.

3. _Collective Cognition Tools_: Utilizing tools like PaJR and CBBLE to facilitate collective cognition and support students in their thesis projects.

4. _AI-Driven Qualitative Thematic Analysis_: Leveraging AI tools to support thematic analysis and improve the quality of thesis projects.

5. _Medical Education and Research Methodology_: The need for improved medical education and research methodology in India, particularly in the context of MD thesis projects.

Codes:

1. MD thesis projects
2. Study design optimization
3. Prospective data capture
4. Collective cognition tools
5. AI-driven qualitative thematic analysis
6. Medical education
7. Research methodology
8. Problem statement
9. Solutions

Insights:

1. The MD thesis project system in India is in need of reform.
2. Optimizing study design, prospective data capture, and thematic analysis can improve the quality of thesis projects.
3. Collective cognition tools and AI-driven qualitative thematic analysis can support students in their thesis projects.
4. Improved medical education and research methodology are essential for producing high-quality thesis projects.

Learning Points:

1. The importance of optimizing study design, prospective data capture, and thematic analysis in MD thesis projects.
2. The potential benefits of using collective cognition tools and AI-driven qualitative thematic analysis in supporting students in their thesis projects.
3. The need for improved medical education and research methodology in tier 2 medical colleges in India, particularly in the context of MD thesis projects.
4. The importance of addressing the problem statement and finding solutions to improve the MD thesis project system in India.

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Friday, December 6, 2024

UG final year University exams practicals video archives

 2018-2023 batch:

https://finalmbbspart2gmpracticals.blogspot.com/2023/03/2k18-batch-university-practical-exams_29.html?m=1



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PG final year University exams practicals video archives

 Links: 

2020-23: https://gmpgpracticals.blogspot.com/2023/06/gm-pg-final-year-2k20-23-batch.html?m=1



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Sunday, December 1, 2024

UDLCO: Participatory medicine ethics training and guard rails for real patients judiciously trading off their privacy in patient centered data driven precision medicine

Summary:


There are many instances of inappropriate patient data sharing in social media and this hints at a need to incorporate a special hands on training for health professional and patient users. In the conversational transcripts below an existent experiential training in the form of an elective program for both health professionals and patient advocates is highlighted with adequate links on the theory behind the endeavour as well as videos of hands on demos.
In the second set of conversational transcripts, there's a debate on how patients themselves trade off their privacy in desperation for financial or any kind of support in their health care journey and finally there's a recent experiential sharing of a workshop detailing how collective medical cognition in an integrative participatory medicine format can be foundational to medical education and practice in ensuring ethical guard rails in global healthcare workflows.

Keywords: User driven learning,  community ontology, participatory medicine, patient privacy trade offs 


Introduction:

The popularization of the World Wide Web supported growing interest in participatory medicine through providing access to information in new ways and by different people, and new forms of shared information [79]. https://www.sciencedirect.com/topics/medicine-and-dentistry/participatory-medicine



Methodology: 

This was a qualitative study design utilising an interpretative descriptive framework that has been described previously in detail here: https://pubmed.ncbi.nlm.nih.gov/32967042/

Global data around the main theme of participatory medicine and privacy was captured from multiple online spaces through online user driven learning that were made into community ontologies (UDLCO). These techniques have been previously described here by us and others as referenced below:







Other than online global data, offline local data was captured in the form of organized face to face participatory medicine meetings between multiple stakeholders in the healthcare ecosystem. Hyperlocal data captured as part of a regular workflow of our user driven healthcare project using the PaJR and CBBLE tools were captured from respective online platforms made available for the same.


RESULTS


Results in raw qualitative multimodal data in textual conversational transcripts, clinical images and videos of real patient participatory events:


online global data captured from online global discussion fora as UDLCOs 


offline local data captured in the form of organized face to face participatory medicine meetings between multiple stakeholders in the healthcare ecosystem. 

Hyperlocal data captured as part of a regular workflow of our user driven healthcare project using the PaJR and CBBLE tools



ONLINE GLOBAL discussion data:

1) Conversational UDLCO Transcripts in a medical education group around training doctors on effective and safe use of social media by spotting the guard rails:



[30/11, 18:09] Prof Meu: Digital professionalism awareness necessary...

I am not giving NMC ideas...else they will make a module and instruct teaching right from year 1
🙏🙏


[30/11, 20:27] rb : We teach this hands on both as an elective and also for any student who works with our team and our real patients toward experiential learning.

It begins with their understanding the informed consent form which sometimes needs supplementation with a video consent 👇


We shouldn't forget that whatever we study today as medical science has been extracted as data from real individual patients who traded off bits and pieces of themselves (their individual information and not just their physical bodies for transplant or the dissection table) as their valuable contribution to science and not training our students in how to do this properly is itself a crime.



Past UDLCOs around this topic: 



Conversational UDLCO Transcripts from another group highlighting patient trade offs and the differences between desperation and compulsion as well as vulnerability:

The conversations begin after one of the users shares an image revealing a patient's picture apparently shared by the family to get financial support toward their further care.

Similar public links that often are displayed as social media ads that users may have often encountered:


One can also go to Facebook and type ketto to find 1000 such posts driven by patients and their family users of this social media driven fund sourcing platform where sharing personal details appear to be mandatory and you can find thousands of such patient trade offs to gather financial support and it may be actually quite difficult to trace the real outcomes of such trade offs in terms of the same patient's illness recovery outcomes although not impossible if one has the resources to take up such a project.

Here's the bottom-line stance hosted in the ketto site itself and to quote:

"Crowdfunding helps researchers focus their efforts on specific diseases and gives patients hope that they will one day be free from their illness. Once people get behind a cause and make it their own, they are much more likely to donate money now rather than later when it matters most."


UDLCO begins with:

IMAGE OF PATIENT with an appeal to donate:

[13/11, 17:25] OP user: Forwarding message for spouse of ... colleague - MR ... I did my bit of donation. Request all to support 🙏 Attached 


[13/11, 17:27] BR: THIS IS NOT RIGHT PLATFORM FOR THOSE ACTIVITIES

[13/11, 17:27] BR: PLEASE DELETE IT WITH IMMEDIATE  EFFECT

[13/11, 17:58] OP user: Dear sir, It is a genuine case and trying assist a colleague in severe distress. 

Kindly ignore the message if you are not connecting to it.

This is large group of gentleman and ladies who are doing wonderful  work for our country. 

A little help to an individual will go long way.  

Hence pardon my position for once , I won’t be deleting the post . 🙏

[13/11, 18:44] BR: No issue at all, I am just directing you to the rule book

[13/11, 18:45] BR: this group will then be flooded by all those donation requests, as this group representing at least 250 Organisation with average 50 K employees and millions ex employees

[13/11, 20:08]: Trying to leverage this post to make a health IT relevant point about patient confidentiality and privacy:

Notice how patient privacy gets traded off in the hope of better interventions and outcome.

Similarly patients are regularly trading off their privacy with their doctors to develop a better relationship with them only in the hope of better outcomes for themselves. 

This subtle undercurrent needs to be weighed into consideration while framing privacy laws?


[13/11, 20:13] +91A: Well said....
Patients and there relatives can go to any extend for a better outcome..
We still use open post cards...


[13/11, 20:53] AN : I do respect and advocate privacy but it is always a trade off. My personal opinion is that the data privacy was never a concern of a  common man. His   worry is accessibility of Care at an affordable price. If that is not met he doesn't care about the privacy as evident from the above outcry for help in the public domain.  Privacy is a concern for a common man in India only when there is a social stigma associated with the condition. ( HIV, infertility etc )

Celebrities and VIPs  on the other hand want everything about them to be super private.  Why do we generalise this and impose on everyone? Let there be only a few hospitals that are ultra sensitive to privacy, where celebrities will get treated  at a price only they can afford.  Trust hospitals may not spend exorbitantly on those processes and will offer Care where availability and affordability is placed above privacy. 

Like in the case of banking very few have peculiar preference for the privacy and then they go to Switzerland. But not everyone needs to follow Swiss banking practices!


[13/11, 21:11] rb: Recall having had this conversation with you and KS in a restaurant near Mumbai way back in 2008 when we were on our way to a conference from Mumbai to Baramati!


[13/11, 21:18] AN: Intel India sponsored event if I remember correctly.

[13/11, 21:23] AN: Thanks to @⁨~AB

[13/11, 21:54] A: Where is AB..?

[14/11, 00:54] AC: Nice points. 

Desperation vs compulsion - which is the greater evil, maybe that's what one needs to ask. 

Most of our arguments against privacy are those arising out of desperate situations. If a dear one can be saved at the cost of loss of privacy - so be it.

Is honour worth it when survival is at stake - what is one willing to sell? 

Then what is compulsion. Maybe when the law mandates something! It could also be a compulsion of basic necessities. 

Without offence to anyone, "loss of privacy is capitalistically lucrative"! (For want of decorum I will not share what this implies) 

No, I am not trying to make a larger demon of capitalism than we ought to. But we do need to have open public debates on where the ethical lines must be drawn.

[14/11, 01:05] AC: Continuing from above... 

Maybe a simple rule of thumb could be the delineation between desperation vs compulsion in such scenarios. 

An act of desperation, such as causing harm in self defence is usually condoned both socially and legally. 

If it's a compulsion, such as being compelled to bring down curtains of privacy that definitely is unethical. 

The challenge lies in documenting compulsion, hence even desperation is denied.

[14/11, 08:13] rb : Well elucidated 👏👏

Much needed counter to triangulate this amazing and long overdue discussion.


[14/11, 08:14]: 👆The examples from Ketto cited above is desperation

Let's look for examples of compulsion

[14/11, 08:15] AC: Did some literature survey on this yesterday. Looks like the keyword "vulnerability" is where desperation and compulsion have been explored

[14/11, 08:16]rb: Can't ask meta AI to share that literature as it would just make up it's own but if you could share some links we could ask meta to thematically analyse it with it's coding as that is something meta does well enough

[14/11, 09:03] AC: 👆 for instance. The above 2019 paper talks about the two inherent components of vulnerability. My current hypothesis - compulsion can be extraneous and intraneous, while desperation is a unipolar response to external compulsion often cited in jurisprudence as "excruciating circumstances beyond control".

(Will explore this after completing whatever I plan for https://pat.al - essentially Patal is an embodiment of vulnerability but so are the upward lokas. Kaumodini is expected to rule in the ruler, and should address extraneous compulsions. One is left to wonder why such layers of cryptic iconography are needed! )

LOCAL offline event data: 

November 28th workshop integrating healthcare professionals and patients (aka technology end users) perspectives with computer science students and faculty from the university of Hyderabad (UoH) to spread awareness around our individual patient precision medicine awareness, education and practice program:

Highlights:

Patient centered demonstration video link shared in social media with a foreword:

In the lecture organized by UoH we also took our 82 year old rural patient of Diabetes who survives on a government pension of 2000/- per month along with his wife. 

The UoH authorities had provided a 7 seater car for carrying them along with our PGs all the way from Narketpally around 80 kms to their venue and the audience there gave the patients and our PGs a standing ovation!

However the best part was seeing the patients so happy with the food there at breakfast and lunch which was never anything like what they got to taste before and the organizers ensured they also packed some for them in their return journey!

Wish we can do these patient centered participatory medicine workshops more often!

Participatory medicine session real time video capture link: 




Links to the lecture preceding the demo:

Post lecture demo discussion video:


The last demo discussion is particularly relevant as it also discusses a SWOT analysis of our participatory medicine workflow and patient privacy and security threats are likened to the omnipresent thorns in our workflow intertwined with clinical complexity.




The above as well as more notes around the face to face lecture demo is available in the link here: https://medicinedepartment.blogspot.com/2024/11/technology-end-user-driven-ecosystem.html?m=1, and this link includes further linked data to our online global, local offline and hyperlocal online workflows, all of which is thematically analysed around the chief theme of participatory medicine and privacy.

Hyperlocal data:

Other than our archived data of thousands of local patients followed up hyperlocally in our dashboard here: https://medicinedepartment.blogspot.com/2022/02/?m=1, in recent times we had the opportunity to perform a pathological autopsy of a patient we were following hyperlocally till death as archived here: https://pajrcasereporter.blogspot.com/2024/10/60f-with-cachexia-diseminated-tb-oro.html?m=1
through our regular participatory medicine PaJR workflow as the family was kind enough to consent for her pathological autopsy and this was a rare first event in the history of our two decades old institution.

The autopsy findings were shared in a clinical meeting with our formal learning ecosystem comprising of students and faculty members and as expected adequate care was taken by all participants not to divulge the patient's identity and maintain her privacy and confidentiality during the autopsy as well the clinical meeting which was part of an "NCD intertwined with CD" project published here: https://medicinedepartment.blogspot.com/2022/02/?m=1


Thematic analysis of global, local and hyperlocal data:

Discussion:

Conclusion:

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