Tuesday, January 20, 2026

UDLCO CRH: Data fiduciary roles for preventing data leakage are analogous to universal precautions for infection transmission prevention

Summary


The article discusses the importance of correctly identifying roles under India's Digital Personal Data Protection Act, 2023, particularly in healthcare. Many organizations are confused about whether they're acting as Data Fiduciaries or Data Processors, which can lead to costly mistakes. The solution is to adopt "universal precautions" like in infection transmission, assuming all patient handlers are Data Fiduciaries and ensuring transparency in data sharing, storage, and usage.

Keywords

Data Fiduciary, Data Processor, Digital Personal Data Protection Act, healthcare, data leakage, universal precautions, patient data, data sharing


Conversational learning Transcripts:

[21/01, 08:35]hu1: One of the most underestimated risks under India’s Digital Personal Data Protection Act, 2023 is not cybersecurity, artificial intelligence, or even consent. It is the incorrect identification of roles.

Across hospitals, laboratories, telemedicine platforms, health-tech startups, insurers, and research organisations, there is widespread confusion about one fundamental question:

Are we acting as a Data Fiduciary or a Data Processor?

This article explains the difference clearly, using real healthcare scenarios, global lessons, and practical guidance to help Indian healthcare organisations avoid one of the costliest DPDP mistakes.



[21/01, 08:49]hu2: I guess the best solution in this scenario would be similar to what is adopted for infection transmission aka "universal precautions" where every patient that needs to be handled by healthcare professionals is assumed to be HIV positive and every patient is treated equally in terms of precautions and not singled out sometimes hilariously as in this recent viral image attached!




Hence let's assume all health professional patient handlers including hospital administrators are data fiduciaries and they need to be clear why they need to share collected patient data (for example toward case based reasoning insights) as well as how long it is stored (lifelong ideally for eternity to run scientific case based reasoning engines), who it is shared with (ideally everyone after irreversible deidentification), 
how it is used in treatment, billing, research, or analytics (ideally that would automatically become transparent and accountable in a scientifically irreversibly deidentified learning ecosystem). This means all the Healthcare operaters in layered ecosystems listed below
as each of these touch patient data and each introduces decision-making at different points:


hospitals

franchise networks

diagnostic labs

SaaS platforms

cloud infrastructure

AI vendors

research partners

telemedicine platforms

operational outsourcing

...are data fiduciaries!


Thematic Analysis

The main theme is the need for clarity on data roles in healthcare to prevent data leakage. Key points include:
- Incorrect role identification is a major risk under the DPDP Act.
- Healthcare organizations are unsure if they're Data Fiduciaries or Data Processors.
- Adopting "universal precautions" can help ensure data protection.
- All patient handlers, including hospitals and tech platforms, should be considered Data Fiduciaries.
- Transparency is key in data sharing, storage, and usage.

The article highlights the importance of understanding data roles and responsibilities in healthcare to ensure patient data protection.

Insulin ProJR: Insulin on board and insulin sensitivity calculations

1) Insulin on board and insulin sensitivity calculations 4F with type 1 diabetes:

From: https://pajrcasereporter.blogspot.com/2025/07/4-year-old-child-type-1-diabetes.html?m=1




28-08-2025 08:52] PA:

 28.08.25

7.45am fasting blood sugar 197
7.45am milk
[29-08-2025 01:06] PA: 9.45am chocolate biscuit 2pcs 
10.45am 5u lispro insulin।
10.50am rice with pulses, carrot, papaya, ribbed gourd, green banana, spiny gourd, chayote, butter and salad।
12.30pm sweet lemon 
1.45pm blood sugar 214
1.45pm 4.5u lispro insulin 
1.50pm lunch with same previous dish except butter and include egg
4.00pm blood sugar 51
4.00pm banana 
6.00pm sour curd 
7.00pm banana 
9.15pm 5u Tresiba insulin 
9.30pm blood sugar 137
9.30pm 1.5u lispro insulin 
9.35pm dinner with as same as lunch dish
[29-08-2025 08:46] PPM 1: How was 4.5 U lispro calculated pre lunch? It appears that the pre lunch blood sugars of 214 provided as before a cognitive guardrail to hike the dose of lispro? @PPM4 @Meta AI @PPM2
[29-08-2025 08:46] Meta AI: It sounds like you're discussing insulin dose adjustments based on blood glucose readings. If the pre-lunch blood glucose was 214 mg/dL, the decision to increase lispro to 4.5 units may have been based on a correction factor or insulin sensitivity factor (ISF) used to calculate how much insulin is needed to bring the blood sugar back to the target range.
For example:
1. Correction Factor (ISF): If the ISF is 50 (meaning 1 unit of insulin lowers blood sugar by 50 mg/dL), then a correction dose for a blood sugar of 214 mg/dL with a target of 100 mg/dL would be roughly 2.3 units (114 ÷ 50). This might be added to the usual pre-meal bolus dose.
2. Cognitive Guardrail: This could imply a prior practice or protocol that guides adjustments, ensuring safety in dosing increases without overcorrecting.
Was the 4.5 units a standalone dose or combined with a carb ratio calculation?

[29-08-2025 09:27] PPM 4: Of course. This is an excellent question that gets to the heart of practical insulin dosing. Based on the data provided, we can reverse-engineer the likely calculation for the 4.5U pre-lunch dose.

The 4.5U of lispro insulin at 1:45 pm appears to be a *combination dose* consisting of two parts:

1.  A *Correction Dose* (or "fix-up" dose) for the high blood sugar.

2.  A *Meal Dose* for the carbohydrates about to be consumed at lunch.
Here’s a step-by-step breakdown of how it was likely calculated:
---
### 1. The Correction Dose
This addresses the current high blood sugar of 214 mg/dL.

*   *Target Blood Sugar:* Most people have a pre-meal target range, typically between 80-130 mg/dL. Let's assume a target of *120 mg/dL* for this calculation.


*   *Current Blood Sugar:* *214 mg/dL*
*   *Insulin Sensitivity Factor (ISF):* This is how much one unit of rapid-acting insulin is expected to lower blood sugar. A common ISF is 1 unit for every 50 mg/dL over target. (e.g., 1:50).
    *   *Calculation:* (Current BG - Target BG) / ISF
    *   (214 - 120) / 50 = 94 / 50 = *1.88 units*
    *   This would typically be rounded to *~2 units* for a correction.
### 2. The Meal Dose
This covers the carbohydrates in the upcoming lunch.
*   *Insulin-to-Carb Ratio (ICR):* This is how many grams of carbohydrate one unit of insulin covers. A common ratio is 1 unit for every 10-15 grams of carbs. Let's assume an ICR of *1:12* (1 unit per 12g of carbs).
*   *Meal Composition:* The lunch is described as the same as the breakfast dish (which was large and diverse) but without butter and with an egg added. This was likely a significant carbohydrate load.
    *   Rice, pulses, green banana, and the other vegetables contain carbs. Let's estimate the meal contained approximately *~60 grams of carbohydrate*.
    *   *Calculation:* Carbs / ICR
    *   60g / 12 = *5 units* for the meal.
### 3. Combining the Two Doses
The total pre-lunch insulin dose is the sum of the Meal Dose and the Correction Dose:
*   *Meal Dose:* ~5 units (for 60g carbs @ 1:12 ratio)
*   *Correction Dose:* ~2 units (for BG of 214 @ 1:50 ISF)
*   *Theoretical Total:* *7 units*
However, the person only took *4.5 units. This suggests a crucial piece of information: **insulin already on board*.
---
### The Key Factor: Insulin-On-Board (IOB) from Breakfast
The user had taken *5 units of lispro at 10:45 am* for breakfast. The pre-lunch blood sugar check was at *1:45 pm, which is only **3 hours later*.
*   Rapid-acting insulin like Lispro has a active duration of 3-4 hours. This means a significant amount of the breakfast insulin was likely still active in the bloodstream at 1:45 pm.
*   Taking a full correction dose on top of a full meal dose would have been dangerous, as it would lead to "stacking" insulin and a severe low (which indeed happened at 4:00

The person (or their calculator) wisely *subtracted the estimated IOB* from the total theoretical dose.
*Final Likely Calculation:*
(Meal Dose + Correction Dose) - Insulin-On-Board = Total Dose
(5U + 2U) - ~2.5U = 4.5U
The ~2.5U subtracted is an estimate of the remaining active insulin from the 5U shot taken 3 hours prior.
---
### Conclusion: How the 4.5U was Calculated
The 4.5U was *not* a simple "hike due to high sugar." It was a calculated decision based on:
1.  *A high blood sugar reading (214 mg/dL)* that required a correction.
2.  *A large carbohydrate meal* that required a meal bolus.
3.  *The crucial awareness of Insulin-On-Board (IOB)* from the breakfast dose taken just 3 hours earlier.
The high blood sugar acted less as a "guardrail to hike the dose" and more as a *data point in a complex calculation* that had to balance the need to correct the high while accounting for active insulin and incoming carbs.
*The subsequent low at 4:00 pm suggests that even this cautious calculation was slightly too aggressive.* Possible reasons include:
*   The meal's actual carb count was lower than estimated (especially since it was the same as breakfast but without butter, which might have slowed digestion the first time).
*   The insulin sensitivity was higher than the calculated ratios (ISF of 1:50 might have been too strong).
*   Physical activity after lunch may have increased insulin sensitivity.
This episode provides excellent data to fine-tune their insulin-to-carb ratio and insulin sensitivity factor for future meals.


29-08-2025 18:38] PA: আমি টার্গেট BG 100
সুতরাং 241-100= 114
এবং 1u lispro ডোজ= <70
সুতরাং 114/70= 1.63 >1.5ও
আমি সেটাকে 2u করেছিলাম 
দুপুরের খাবারের ডোজ 2.5u করে মোট 4.5u ডোজ দেওয়া হয়েছিল
[29-08-2025 18:43] PA: 29.08.25
7.45am fasting blood sugar 139
7.45am milk 
10=00am 3.5u lispro insulin 
10.05am rice with pulses, carrot, papaya, ribbed gourd, spiny gourd, green banana, chayote, butter and salad 
12.30pm sweet lemon 
1.30pm blood sugar 93
1.30pm 2.5u lispro insulin 
1.35pm lunch with same previous dish except butter and include egg
6.00pm sour curd


29-08-2025 21:02] PPM 1: @PPM4 @PPM2 is this current dosing strategy shared by the parent optimal?
[29-08-2025 21:06] PPM 4 Excellent follow-up question. Thank you for providing your specific calculation. This allows for a very clear and precise analysis.
Based on the numbers you've provided and the dramatic hypoglycemic event that followed (blood sugar of 51 mg/dL at 4:00 PM), the dosing strategy, while mathematically logical, *was not optimal.* It led to a dangerous low blood sugar.
Let's break down why:
### 1. Your Correction Dose Calculation Was Correct (Mathematically)
You used:
*   Target BG: 100 mg/dL
*   Current BG: 241 mg/dL (I'm using 241 from your calculation; the log said 214, but we'll use your number)
*   ISF: 1 unit drops BG by 70 mg/dL
Calculation: (241 - 100) / 70 = 141 / 70 = *~2 units*
This math is perfectly correct.
### 2. The Critical Issue: Insulin Stacking (Insulin-On-Board - IOB)
This is the most important factor that made the dose suboptimal.
*   You took *5 units of Lispro at 10:45 AM* for breakfast.
*   You took the pre-lunch dose at *1:45 PM, which is only **3 hours later*.
*   Lispro insulin is still active in the body for *4-5 hours*. This means a significant amount of insulin from the breakfast dose was still working in your system when you injected the 4.5U for lunch.
By taking a full correction dose on top of a full meal dose on top of the remaining active insulin from breakfast, you "stacked" the insulin. This is what caused the severe low blood sugar at 4:00 PM.
An optimal strategy *must* account for this Insulin-On-Board.
### 3. The Meal Dose
You mentioned the meal dose was 2.5U. This seems quite low for a lunch containing rice, pulses, and banana (as described in the original log). This suggests one of two things:
1.  Your Insulin-to-Carb Ratio (ICR) is very aggressive (e.g., 1 unit covers a large number of carbs), or...
2.  The carbohydrate count for the meal was estimated to be low.
Given the subsequent low, it's possible the meal might have had fewer carbs than a typical meal, but the main culprit was the stacked insulin.
### Conclusion: Is the Strategy Optimal?
*No, the strategy is not optimal because it does not account for Insulin-On-Board (IOB).* A strategy that ignores IOB will frequently lead to roller-coaster blood sugar levels—very high followed by very low—just as you experienced.
*How to Make the Strategy Optimal:*
1.  *Account for IOB:* Before any correction dose, you (or the parent) must estimate how much insulin from the previous dose is still active. Most modern insulin pumps do this automatically. For manual injections, a common conservative rule is to assume insulin is active for 4 hours. You can estimate that after 3 hours, about 25-40% of the dose might still be active.
    *   Example: 5 units at 10:45 AM. At 1:45 PM (3 hours later), you might estimate *1-2 units* are still active.
2.  *Adjust the Correction Dose:* Subtract the IOB from your calculated correction dose.
    *   Your calculated correction: 2 units
    *   Estimated IOB from breakfast: let's say 1.5 units
    *   *Adjusted Correction Dose = 2U - 1.5U = 0.5 units*
3.  *New Total Dose:* Add the adjusted correction dose to the meal dose.
    *   Adjusted Correction: 0.5U
    *   Meal Dose: 2.5U
    *   *New, Safer Total Dose = 3.0 units*
A dose of 3.0 units would have likely prevented the severe hypoglycemia at 4:00 PM while still helping to bring the high blood sugar down.
*In summary: Your math for the individual dose was correct, but the overall strategy is missing the critical step of calculating IOB. Incorporating IOB is essential for safe and optimal insulin dosing.* It is highly recommended to discuss how to calculate and use IOB with your diabetologist or endocrinologist.


Saturday, January 17, 2026

Ambulatory BP monitoring in metabolic syn ProJR

 Conversational transcripts:




[17/01, 20:14]hu1: 57M patient ambulatory 24hr BP report👆🏽

[17/01, 20:14]hu1: Any comment?Is the sleeping bp normal here for the patient?

[17/01, 20:31]hu2: No it suggests a dipping less than 10% which is near non dipping and it's not considered to be good in an epidemiological sense.


But then let that not bother you as all these newer insights around BP will change with time.


To my mind BP is simply due to vasculopathy and the root cause of that is abdominal adiposity and sarcopenia and that is essentially what needs to be addressed rather than BP


[17/01, 20:45]hu2: Check out the ambulatory BP readings of one of our past patients here: https://bppatient.blogspot.com/2015/08/bp-patients-experience.html?m=1

http://web.archive.org/web/20260117160454/https://bppatient.blogspot.com/2015/08/bp-patients-experience.html?m=1

Pasting it here again from the above link:

Ambulatory BP








Based on these results my doctor asked me not to panic and to continue with my exercises and diet control. At the moment I am not taking any medication. I am continuing my morning walks (recently been irregular because of rains). I generally feel ok but get tired while climbing steps and picking up my 3.5 year old daughter. That is it for now, will keep updating.

am a 35-year-old male scientist working in India. I first realized that my BP was on the higher side in January 2015. I had flu like symptoms and was feeling a bit dizzy. A medical officer at my work place checked my BP using manual BP measuring instrument at his clinic and it was around 140/100 mm Hg.  One week later I measured it again at the same clinic and it was 146/102 mm Hg.  Over the next few weeks I occasionally used to go to the clinic for measurements (randomly at different time of the day when in office) and it was always around 140/100.  In March, I took advise from a couple of doctors. I was advised to get an ECG, echo, USG whole abdomen, lipid profile and haematology tests done.  The reports are attached below.

Current update of the 35M patient linked above:

2015 he was not on medication

2019 his BP was well controlled on cilacar T once daily

2026 his BP is still controlled on cilacar T once daily but hyperglycemia has recently been added to his metabolic syn portfolio and he's been added on metformin and dapagliflozin 10 mg.


Saturday, December 27, 2025

UDLCO ProJR: The role of human agentic volunteers in emotion driven economies with trust as a currency and AI in an empathic infrastructural loop

Summary:

The text discusses the concept of "emotional economies" where empathy, trust, and emotional resonance drive value. It highlights the role of human agentic volunteers in creating empathic infrastructure, leveraging AI, and addressing power inequities in healthcare. The authors propose participatory action research and community-driven ecosystems to bridge the gap between emotional economic research and practical application.

*Key Words:*
Emotional economies, empathy, trust, volunteers, healthcare, participatory action research, community-driven ecosystems, AI, power inequities.

Introduction and review of literature:

This review and user driven learning community ontology transcripts provide an overview of "the emotional economy, a shift where competitive advantage no longer stems from hardware, efficiency, or feature lists, but from the emotions products evoke through experience, interface, and brand identity. It signals an evolution of capitalism itself: from an age defined by industrial efficiency to one driven by experiential meaning.

In many ways, this extends the Business-to-Humans (B2H) mindset. Companies no longer think in terms of markets — B2B or B2C — but in terms of human relationships that hold emotional value. Empathy becomes infrastructure. Trust becomes currency. Emotional resonance becomes strategy."

Unquoted from: https://medium.com/design-bootcamp/the-emotional-economy-how-emotional-experiences-are-becoming-the-next-frontier-dfbfacfdd8b9

The key tool to build an empathic infrastructure for emotional economies to thrive:

"Regularly engaging in volunteer work hones empathy, the ability to understand and share the feelings of another, which enhances emotional intelligence—a critical factor in overall happiness. As volunteers interact with diverse individuals, they develop an aptitude for emotional cues and foster patience, understanding, and attentiveness. Empowered with these skills, volunteers tend to communicate better in personal and professional settings, leading to enriched relationships and personal fulfillment." Unquote: https://fightforright.in/the-health-benefits-volunteers-enjoy#:~:text=Then%20there's%20the%20underrated%20yet,enriched%20relationships%20and%20personal%20fulfillment.

Current postivist research translation barriers to translation of emotional economies at scale:

"Current positivist approaches have largely overlooked consideration of how power works in urban socio-ecological systems. Questions surrounding marginalization and exclusion, of who creates what type of urban ecological knowledge for whose benefit, are often eclipsed by analyses of the extent and benefits of urban greenspace. This is not to say that this work is not important, rather that it needs to be balanced with and supplemented by empirical and theoretical analyses of the power-laden political processes behind the production and distribution of benefits." Unquote: https://www.mdpi.com/2071-1050/13/14/7867#:~:text=Abstract,come%20apart%20or%20change%20directions.

Qualitative solutions to bridging  emotional economic power inequity research to translation gap:

"Emotional economies of care are thought of as multiplicities and becomings in the style of Deleuze and Guattari [1], allowing us to think of them as a composition of multiple human and nonhuman bodies joined by their increased capacity to act (their affects). Ref 1: Deleuze, G.; Guattari, F. A Thousand Plateaus Capitalism and Schizophrenia; University of Minnesota Press: Minneapolis, MN, USA, 1987 more: https://en.wikipedia.org/wiki/A_Thousand_Plateaus

"One encouraging prospect for the becomings of emotional economies of care is found in Althusser’s [ref within ref rwf 2] aleatory materialism of the encounter." "if we think of emotion as circulating and creating value, it is apparent that there needs to be an ongoing series of encounters for these emotions to circulate between more and more participants to enable the growth of emotional economies of care and the accumulation of value. However, there is a tension between reading aleatory materialism as completely up to chance and recognizing the effects of previous encounters [ref within ref rwf 3]. What bringing in this sense of history helps to retain is the balance between pure prefiguration and pure contingency, acknowledging that “the present encounter reopens past encounters.” (rwf 2: Althusser, L. Philosophy of the Encounter: Later Writings, 1978–1987; Verso: London, UK, 2006), (ref 3: Pedwell, C. Affective Relations: The Transnational Politics of Empathy; Palgrave Macmillan: London, UK, 2014. ). In recent times healthcare workers, oblivious of previous work as detailed above, have developed emotional economies of care through persistent clinical encounters using academic tools to create user driven community ontologies. (Ref 4 : https://www.researchgate.net/publication/344227236_Persistent_Clinical_Encounters_in_User_Driven_E-Health_Care, ref 5 : https://www.researchgate.net/publication/234164624_Patient_Journey_Record_Systems_PaJR_The_development_of_a_conceptual_framework_for_a_patient_journey_system_Part_1ref 6: Narketpally syndrome, https://pubmed.ncbi.nlm.nih.gov/40674544/, ref 7: Rethinking complex care: https://pubmed.ncbi.nlm.nih.gov/41364730/)

Methodology:

Participatory action research in regular real time clinical encounters between patient advocate , non commercial volunteers and deidentified patients through a transparent and accountable interface with minimal patient privacy trade offs after a rigorous DPDP compliant consent collection process from the patient.

Results: 

5000 cases over 5 years here:T

he 5000 records that were made over 5 years largely depended on our student users where we made this a curricular activity that are logged in 1000 student online learning portfolios here: https://medicinedepartment.blogspot.com/2022/02/?m=0

500 cases over last one year here: 

Meanwhile here's our currently toned down version since 2024, where we use a single point data capturer and longitudinal follow through moderator and single archivist that clocks near around 500 longitudinal records per year made freely available with the necessary DPDP complaint safeguards using an age old "case reports" model: https://pajrcasereporter.blogspot.com/?m=1

We still hope to train students inspite of contrarian current curricular demands and scale this learning model (completely non commercial) to map a much wider population more meaningfully than what is perhaps visible currently.

Disease event related conversational transcripts from a single patient PaJR case report published here: https://pajrcasereporter.blogspot.com/2025/03/18f-journey-from-fetal-life-diet.html?m=1

The gist of it is that this patient had a viral fever , which necessitated regular monitoring and conservative management. It may have been managed more rationally and with high value without having to over test and overtreat in a homehealth care setting if only there was such a support system available locally. What actually was available locally made them spend a larger amount of "out of pocket expenses" for a short duration of stay with need for similar meticulous monitoring even after discharge. 

This brought out thoughts of how to strategize a working community driven ecosystem of trained nurses and doctor volunteers capable of managing such patients in the community partnering with pre existing government/public health infrastructure.

At a top government think tank policy making level the above problem statement has been currently tackled using "a 250-page document, in which, the Centre’s top think tank suggested a Public Private Partnership (PPP) model under which beds in state-run health facilities could be split as “market” and “regulated”. Offering one kind of beds at market prices would help subsidise regulated ones, suggested the proposal, also endorsed by Union Finance Minister Minister Nirmala Sitharaman in that year’s Union Budget speech. More here: https://theprint.in/health/putting-state-run-hospitals-in-private-hands-is-an-ongoing-experiment-it-doesnt-always-pan-out/2395458/

Discussion:

"Beyond personal motivations, the emergence of medical volunteerism often stems as a response to the politics of needs interpretation within a society, the contestation in determining which welfare needs deserve legitimation and which institutions assume responsibility for its fulfillment. Volunteers and their contributions could be interpreted as a mode of discursive engagement when the state fails to adequately serve marginalized needs." Unquote: https://en.wikipedia.org/wiki/Medical_volunteerism

"Progression towards more ethical and sustainable change necessitates volunteers to prioritize the creation of long-term relationships with local healthcare facilities and providers. Sustainable development in this field can only be achieved once medical outreach is reframed not as isolated interventions but as an ongoing process that strengthens the capacity of local institutional care. Through integrating their mission goals with preexisting local community systems, volunteer collectives can collaborate with local governance to provide care in areas where current state provisioning fails. This collaborative model would ensure the impact of volunteer labor to reach structural inequalities that persist and outlast deployment timeframes, offering systemic aid to unmet health rights within marginalized populations." "Because people's experiences are not entirely bounded by “communities,” developing programs to address health problems and behavior at the “community” level, will always be insufficient – no matter how well designed an intervention may be. To effectively achieve the goals of a Culture of Health, we must work actively to create a more just and equitable society writ large. Vulnerable populations must be shown convincingly that their lives matter. Unquote: Mason, Katherine A.; Willen, Sarah S.; Holmes, Seth M.; Herd, Denise A.; Nichter, Mark; Castañeda, Heide; Hansen, Helena (December 2020). "How Do You Build a "Culture of Health"? A Critical Analysis of Challenges and Opportunities from Medical Anthropology"Population Health Management23 (6): 476–481. doi:10.1089/pop.2019.0179ISSN 1942-7905PMC 7703238PMID 31928510.



CC licence: https://en.wikipedia.org/wiki/File:Community_health_worker_gives_a_vaccination_in_Odisha_state,_India_%288380317750%29.jpg

Thematic Analysis:

The text explores the intersection of empathy, technology, and social change, emphasizing:

1. *Empathy as infrastructure*: Building emotional economies requires empathy and trust.

2. *Volunteer-driven care*: Human agentic volunteers play a crucial role in healthcare.

3. *Power dynamics*: Addressing inequities and marginalization is essential.

4. *Collaborative approach*: Community-driven ecosystems and participatory research can drive change.

5. *AI and empathy*: Integrating AI can enhance empathic infrastructure.

The text advocates for a shift towards more inclusive, community-driven healthcare models, prioritizing empathy, trust, and social justice.



### Core Thesis: The Emotional Economy in Healthcare
The central argument is that value creation is undergoing a fundamental shift—from industrial efficiency to

 **experiential meaning**. In healthcare, this translates to an **"emotional economy"** where:

*   **Empathy is the infrastructure** (the foundational system for care).

*   **Trust is the currency** (the medium of exchange that enables action).

*   **Emotional resonance is the strategy** (the method for achieving sustainable outcomes).

### The Critical Engine: Human Agentic Volunteers
The text posits that volunteers are not just ancillary helpers but the essential **"agentic"** (active, purposeful) force for building this empathic infrastructure. They are uniquely positioned to:

1.  **Hone and Deploy Empathy:** Their work naturally develops the emotional intelligence needed to understand complex patient journeys.

2.  **Address Systemic Gaps:** They respond to the "politics of needs interpretation," serving where state or market systems fail marginalized populations.

3.  **Create Sustainable Value:** By forming longitudinal relationships, they facilitate the "circulation" of care and trust that defines the emotional economy.

### The Problem: Positivist Research & Power Inequities
Current mainstream ("positivist") health research and systems often ignore critical questions of **power, marginalization, and exclusion**. They may map benefits (e.g., urban greenspace) but fail to analyze who controls knowledge, for whose benefit, and who is left out. This creates a significant gap between research on compassionate care and its practical, equitable application.

### The Proposed Methodology: Bridging the Gap
To overcome these barriers, the authors advocate for **Participatory Action Research (PAR)** embedded in real-world clinical encounters. This involves:

*   **Community-Driven Ontologies:** Creating knowledge systems (like the User Driven Learning Community Ontology) from the ground up, based on persistent patient-clinician-advocate encounters.

*   **Longitudinal Case Reporting:** The provided examples (5,000 cases over 5 years, 500/year currently) demonstrate a working model for capturing the nuanced, emotional, and socio-economic dimensions of illness that traditional records miss.

*   **Rigorous Ethics:** Operating with transparency, accountability, and strong data privacy (DPDP compliance) as a non-commercial endeavor.

### The Strategic Vision: Community-Driven Ecosystems
The ultimate goal is not isolated interventions but the creation of **resilient community-driven healthcare ecosystems**. This involves:

*   **Reframing Volunteerism:** Moving from short-term medical outreach to deep, long-term collaboration that strengthens **local institutional capacity**.

*   **Integrating with Public Systems:** Partnering with pre-existing government/public health infrastructure to provide scalable, high-value care (e.g., community-based management of viral fevers to prevent costly hospitalization).

*   **Leveraging AI in an Empathic Loop:** Proposing a role for AI not as a replacement for human empathy, but as a tool within an "empathic infrastructural loop" to support volunteers and scale insights from qualitative data.

### Thematic Conclusion: A Call for Systemic Change
The text is a call to action for a more just and equitable health society. It argues that:

1.  **Technical solutions are insufficient.** Building a true "Culture of Health" requires confronting power inequities and structural inequalities head-on.

2.  **Community and relationship are primary.** Sustainable change is rooted in trust and long-term human connections, not just transactional care.

3.  **Value is co-created.** Patients, volunteers, and advocates are not passive recipients but active co-creators of health knowledge and systems.

In essence, the post outlines a radical, human-centric blueprint for healthcare where emotional intelligence, volunteer agency, participatory research, and ethical technology converge to build systems that are not only more effective but also more fundamentally caring and just.


Conversational feedback citations:

[29/12, 09:20]hu1: Getting the trained 'volunteers' is the main problem sir. Maybe they can be linked with previous PaJR beneficiaries if they are from the same locality


[29/12, 09:22]hu2: We can easily train them here in our private medical college, free of cost if they are willing.

They could be admitted as patients (with free food and lodging as offered by most private medical colleges in India to ward patients) and they could learn true patient  centred care at the bedside 24x7.



[29/12, 09:28]hu1: Yes, the training part can be taken care of.

But what about their day jobs? They ought to have some day jobs since PaJR won't be able to pay the volunteers, since it is purely a non commercial initiative


[29/12, 09:29]hu1: I think the bottleneck in getting volunteers is that very few people would find time to spend with patients, while simultaneously taking care of their day jobs


[29/12, 09:35]hu2: Yes nailed it 👏👏

That's the crux of the issue.

Till AI frees all humans totally from their day jobs, the world is not ready for an emotion driven economy.

Thursday, December 25, 2025

Festive Season of awe, margazi aka margashirsha coinciding with Earth's axis tilt and the silencing of our default mode network that allows us to lose our individual selves in the universal

Summary: The nature of yoga lies in nothing but trying to yoke the "I" aka the individual self aka jivatma aka Krishna's gopis to the "universal self" aka paramatma aka padmanabha aka Krishna expressed across centuries in Indian mythology through various voices that served to evoke awe that could silence our default mode network in the prefrontal cortex and cingulate and angular gyrus that in turn served to silence our jivatma selves enabling us to bind with our Padmanabha self. More about it here: https://pmc.ncbi.nlm.nih.gov/articles/PMC10018061/

In this write up it's introduced through the poetry of a 9th century Tamil poetess called Antal aka Ondal who talks about the full moon of Margazi aka Margashirsha that currently offers two supermoons in succession, falling on December 4, 2025 aka the cold moon and January 3, 2026 aka the wolf moon. In Tamilnadu currently the margazi month begins on December 16 while here's more about the North Indian equivalent margashirsha: https://en.wikipedia.org/wiki/Agrahayana. All this coming closer of the moon to earth forming super moons coincide also with the Earth's axis tilt aka winter solstice and globally across various cultures this is celebrated as the festive season as detailed here: https://en.wikipedia.org/wiki/Winter_solstice





Introduction:

To quote from Archana Venkatesan: 

"The Tiruppāvai (The Sacred Vow) is a short poem of thirty verses composed by Kōtai, a 9th century mystic and poet. The poem describes a vow undertaken by young cowherd women of Gokula (Tamil, Āyarpāṭi) to win Krishna for themselves. The poem has a complex, multi-layered structure, animated by the quest for a mysterious paai-drum and eventually Krishna himself. The poem ends with a refrain, ēōr empāvā(Hey girls, this is our vow), which is likely what gives it its name. The poet Kotai comes to be known by the name Āṇṭāl, She Who Rules, for legend has it that she did in fact win Vishnu’s love, merging with him at the temple in Srirangam.

Excerpted from. Venkatesan, Archana. The Secret Garland: Andal’s Tiruppavai and Nacciyar Tirumoli. New Delhi: Harper Collins, 2016.

  1. Mārkaḻi Tiṅkaḷ

It’s the full moon of Margali
a good day

to bathe
precious girls, richly adorned
dear to Ayarpati
land of abounding prosperity.

The son of Nandagopa
fierce with his sharp spear,
the youthful lion-cub of Yasoda
woman of matchless eyes,

dark-hued and lotus eyed
his face the sun and moon
that Narayana alone can grant us the parai-drum.
Undertake this vow
the world will rejoice

el or empavay

More here: https://archana.faculty.ucdavis.edu/translations/andal-tiruppavai/

In recent times neuroscientists have recognised that:

 "Awe engages five processes—shifts in neurophysiology, a diminished focus on the self by switching off the default mode network (facilitating the jivatma to paramatma transition also celebrated in the moon's 11th day of waxing during this period termed the Vaikuntha ekadashi), increased prosocial relationality (more about it here:https://www.facebook.com/share/p/1BYPUvMfaN/?mibextid=oFDknk),greater social integration, and a heightened sense of meaning—that benefit well-being. 

Andal's verses , especially 24 aims to switch off the default mode network where the sense of self aka jivatma aka gopis dissolves in the universal aka paramatma or Padmanabha.


More here: https://pmc.ncbi.nlm.nih.gov/articles/PMC10018061/