Monday, October 24, 2022

Departmental Senior Resident online learning portfolios

2018 MD entry :


Aditya Samitinjay :


Junior residency archives :


Arvind Reddy : 

Senior residency portfolio: 

Nil entries as of 24/10/22 

Junior residency archives :

CASES

https://2018-21batchpgy3gmpracticals.blogspot.com/2021/08/18100006001-case-presentations.html

THESIS

https://2018-21batchpgy3gmpracticals.blogspot.com/2021/08/18100006001-thesis.html

ACADEMIC PRESENTATIONS

https://2018-21batchpgy3gmpracticals.blogspot.com/2021/08/18100006001-academic-presentations.html

2019 MD Entry :

Sushmita :

Senior Residency portfolio :

Nil entries as of 24/10/2022


Junior residency archives 

https://dailyelog.blogspot.com/?m=1

Zain Alam:

Senior Residency Portfolio  :

Nil entries as of 24/10/2022

Junior residency archives :

https://zainalammohammed59.blogspot.com/?m=1

Nikita Shirine :

Senior Residency portfolio :

Nil entries as of 24/10/2022

Junior residency archives :

https://nikithashirineoneliner.blogspot.com/?m=1(Non existent on clicking) 




Thursday, October 13, 2022

Medical Cognition tools to resolve clinical complexity: System 1 (heuristics,eyeballing) and system 2 (evidence based reflective sharing) toward a dynamic ontology in healthcare

Abstract :


The entire write up below is a preliminary draft with extensive quotes borrowed from various resources to provide the audience here with a fair idea of Medical cognition, which is a broad area consisting of various system 1 and system 2 human cognitive tools to resolve clinical complexity (diagnostic and therapeutic uncertainty). These tools are often used through various medical cognitive platforms such as synchronous face to face interactions (often system 1) and asynchronous communication and learning between multiple stakeholders in connected web space (user driven healthcare UDHC, patient journey records PaJR) and blended to form "case based blended learning ecosystems CBBLE (often a blend of system 1 and 2). 

Introduction :

"Medical cognition research looks at the psychological processes underlying healthcare performance, focusing on in-depth analysis of the perceptual and cognitive processes that lead to observable behavior in all healthcare stakeholders. The focus is on understanding the knowledge structures and mental processes in healthcare brought to bear during cognitive activity (e.g., problem solving and decision making)."(Patel 2001). More about our past work around it here: http://medicinedepartment.blogspot.com/2021/06/evolution-of-model-forpatient-centered.html?m=1



Clinical complexity consists of a few defining characteristics such as uncertainty, non linearity, unpredictability and yet an overall pattern leading to resolution through attractor states over time. (Greenhalgh 2001) As physician attractors we are uniquely privileged to "be" with our patients regardless of the diagnosis and that is the only way we may know our patient's outcomes where our "being" with them is the most significant (and often overlooked) intervention. 


"Decision-making is complex. It is partly based on the dual-process theory of Epstein and Hammond, recently popularized in Daniel Kahneman’s book “Thinking Fast and Slow.” Two families of cognitive operations, called System 1 (intuitive) and System 2 (analytical) thinking, are used in decision-making. System 1 thinking is often described as a reflex system, which is “intuitive” and “experiential” or “pattern recognition”, which triggers an automated mode of thinking. 

System 2 is the more “analytical,” “deliberate” and “rational” side to the thinking process. It is pieced together by logical judgment and a mental search for additional information acquired through past learning and experience. The data are then processed carefully, through a conscious application of rules, making it a much slower and cognitively demanding process but more likely to lead to better decisions. The analytical system is engaged usually when there is uncertainty, complexity, or the outcomes give little room for error but there is time to think."




We regularly use "medical cognition" system 1 and system 2 tools to tackle clinical complexity and some of these are are often used through various medical cognitive platforms such as synchronous face to face interactions (often system 1) and asynchronous communication and learning between multiple stakeholders in connected web space (user driven healthcare UDHC, patient journey records PaJR) and blended offline and online to form "case based blended learning ecosystems CBBLE (often a blend of system 1 and 2).

Glossary of terms :

user driven healthcare UDHC : Subset of "Medical Cognition' globally where multiple users, all healthcare stakeholders including patients, interact online to understand and take decisions on meeting patient requirements. 



Here's about how it transformed into the current CBBLE since 2017 at Narketpally : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6163835/

CBBLE (pronounced cable) : Case based blended learning ecosystem that is available locally in many institutions and some are connected globally to each other. CBBLE is different from UDHC in that it is not purely online but blended offline and online. 

PaJR : The key concept lies in the use of regular patient reported outcomes to locate the phase of illness in 

System 1 thinking and human visual pattern recognition through approximations rather than accurate measures :

Humans may, to quote, "share a commitment that there is one true value for any experienced visual magnitude in the world – even if our analog magnitude systems are incredibly limited in their ability to discern what value this is. Visual analog magnitudes do not represent "fuzzy" or "noisy" estimates – rather they represent precise estimates that are subject to epistemic limitations."



Although a large part of human activity and system 1 decision making happens through heuristics and visual pattern recognition (often called eyeballing), this area of human endeavor is relatively less well studied.

Here's a link to some articles and review quotes on system 1  heuristics and  medical eyeballing that we have compiled : https://userdrivenhealthcare.blogspot.com/2022/10/eyeballing-as-system-1-intuitive.html?m=1

Our current projects in Medical cognition and decision making attempt to address this. 

Projects on visual approximation and shared pattern recognition to :

Document and validate medical outcomes of reduced muscle mass and increased visceral fat in various manifestations of the metabolic syndrome in the form of non communicable diseases NCDs such as 

Diabetes 

Hypertension 

CAD, CVD, CKD etc 

Alcoholic liver disease and chronic vascular complications of alcoholism overlapping with usual vasculopathy of metabolic syndrome 

Current project plans around the above are linked here below :


System 1 visual pattern recognition of muscle mass and trunkal fat needs a database of patients with varying degrees of muscle mass and fat correlated with metabolic syndrome outcomes. Our project objective is to create that database but meanwhile here's https://www.ruled.me/visually-estimate-body-fat-percentage/,
what others have shared around normal muscle mass and visceral fat and at what level that may be assessed visually where it may begin to look abnormal hinting at disease. According to the images shared by the authors who created the link above, all current sedentary humans appear likely to develop metabolic syndrome soon if they haven't already. The images that the authors have shared appear self explanatory (system 1?) although there is no scientific system 2 validation. 

System 2 validation : Rationale for various interventions to build muscle mass and prevent metabolic syndrome :

Scientific article : πŸ‘‡




Document and validate medical outcomes of certain types of fever patterns :

Current planπŸ‘‡


Past system 2 work πŸ‘‡


System 1 attempts in this area in the past :


Creating a dynamic ontology toward faster (system 1) and safer (system 2) medical cognition in healthcare :

Here is a link : https://medicinedepartment.blogspot.com/2022/02/?m=0, to 5000 case reports (and growing daily) from our case based reasoning database dashboard that represent single thematic analysis projects to identify the system 1 and system 2  issues in each and review/audit their challenges toward developing better solutions. 


Will be looking forward to your help in classifying these individual patient case reports into topical areas that represent 
knowledge, which can be used to integrate and analyze large amounts of heterogeneous data, allowing precise classification of any subsequent patient toward better diagnosis, care management, and translational research. This will help to create a dynamic medical ontology that may have a profound impact on how healthcare is practiced today. 

More here : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6503847/ on medical ontology and one of the challenges that you may notice in our dashboard link above also mentioned here in the medical ontology article and that is, "phenotypic information about individual patients is often insufficiently detailed or inaccessible, thus obstructing the detection of similarities and the classification of patients into clinically useful groups." This is a major area that we are currently grappling with that is primarily to do with how we capture and frame the patient data and is primarily because of social political factors governing medical education today. 


References:

1) Plsek PE, Greenhalgh T. Complexity science: the challenge of complexity in health care. BMJ. 2001 Sep 15;323(7313):625–8. doi: 10.1136/bmj.323.7313.625.

2) Patel VL, Kaufman DR. Medical informatics and the science of cognition. J Am Med Inform Assoc. 1998 Nov-Dec;5(6):493-502. doi: 10.1136/jamia.1998.0050493. PMID: 9824797; PMCID: PMC61330.



Eyeballing as a system 1 (intuitive medical cognition), heuristic tool


A few compilations on system 1 experiential learning and eyeballing as a system 1 (intuitive medical cognition) tool below :


1) Eyeballing: the use of visual appearance to diagnose ‘sick.

To quote, 

"Experienced emergency physicians are able to visually assess patients rapidly and predict disposition in a very short time, albeit with fair reliability and lower accuracy than reported previously. Subjectively, they reported that the majority of decisions were on the side of ‘knew immediately’, consistent with the application of System 1 processing."

Sibbald  M, Sherbino  J, Preyra  I, Coffin-Simpson  T, Norman  G, Monteiro  S.  Eyeballing: the use of visual appearance to diagnose ‘sick.’  Med Educ. 2017;51(11):1138-1145. doi:10.1111/medu.13396

2)

A perspective on judgment and choice: mapping bounded rationality

Daniel Kahneman. Am Psychol. 2003 Sep.


Early studies of intuitive judgment and decision making conducted with the late Amos Tversky are reviewed in the context of two related concepts: an analysis of accessibility, the ease with which thoughts come to mind; a distinction between effortless intuition and deliberate reasoning. Intuitive thoughts, like percepts, are highly accessible. Determinants and consequences of accessibility help explain the central results of prospect theory, framing effects, the heuristic process of attribute substitution, and the characteristic biases that result from the substitution of nonextensional for extensional attributes. Variations in the accessibility of rules explain the occasional corrections of intuitive judgments. The study of biases is compatible with a view of intuitive thinking and decision making as generally skilled and successful.

Citation : Kahneman D. A perspective on judgment and choice: mapping bounded rationality. Am Psychol. 2003 Sep;58(9):697-720. doi: 10.1037/0003-066X.58.9.697. PMID: 14584987.

3)

Is the “beach position” of value during the “eyeball” assessment of patients?


To quote, "The rapid identification at low cost of patients at risk is particularly important in emergency departments in low- and middle-income countries, which may lack experienced emergency healthcare providers and cannot afford to waste scarce resources [ 
[1] 
]. Within seconds some clinicians use fast System 1 thinking to determine if a patient is sick or not [ 
[2] 
], a judgement often based on the patient's facial expression and their behaviour [ 
[3] 
]. Supine emergency room patients with crossed ankles, crossed hands behind the neck, or folded hands over the upper abdomen, as if they were relaxing on a beach, have been reported to be highly unlikely to have any acute critical condition"

Alfred Lumala, John Kellett, Jelmer Alsma, Christian H Nickel, Is the “beach position” of value during the “eyeball” assessment of patients?, European Journal of Internal Medicine, 10.1016/j.ejim.2021.02.01488, (139-140), (2021).

4) Experiential knowledge in clinical medicine: use and justification

To quote, 

"Clinicians' primary experience tends to be dismissed by EBM as unsystematic or anecdotal, a source of bias rather than knowledge, never serving as the "best" evidence to support a clinical decision. The position that clinical expertise is necessary but that primary experience is untrustworthy in clinical decision-making is epistemically incoherent. Here we argue for the value and utility of knowledge gained from primary experience for the practice of medicine. Primary experience provides knowledge necessary to diagnose, treat, and assess response in individual patients. Hierarchies of evidence, when advanced as guides for clinical decisions, mistake the relationship between propositional and experiential knowledge. We argue that primary experience represents a kind of medical knowledge distinct from the propositional knowledge produced by clinical research, both of which are crucial to determining the best diagnosis and course of action for particular patients."

Mark R. Tonelli, Devora Shapiro, Experiential knowledge in clinical medicine: use and justification, Theoretical Medicine and Bioethics, 10.1007/s11017-020-09521-041, 2-3, (67-82), (2020).
Wikipedia : heuristic (/hjʊˈrΙͺstΙͺk/; from Ancient Greek Ξ΅α½‘ρίσκω (heurΓ­skō) 'I find, discover'), or heuristic technique, is any approach to problem solving or self-discovery that employs a practical method that is not guaranteed to be optimal, perfect, or rational, but is nevertheless sufficient for reaching an immediate, short-term goal or approximation. Where finding an optimal solution is impossible or impractical, heuristic methods can be used to speed up the process of finding a satisfactory solution. Heuristics can be mental shortcuts that ease the cognitive load of making a decision.[1][2]

Examples that employ heuristics include using trial and error, a rule of thumb or an educated guess.

Heuristics are the strategies derived from previous experiences with similar problems. These strategies depend on using readily accessible, though loosely applicable, information to control problem solving in human beings, machines and abstract issues.[3][4] When an individual applies a heuristic in practice, it generally performs as expected. However it can alternatively create systematic errors.

Another wiki on heuristic psychology below :

https://en.m.wikipedia.org/wiki/Heuristic_(psychology)

Heuristics is the process by which humans use mental short cuts to arrive at decisions. Heuristics are simple strategies that humans, animals,[1][2][3] organizations,[4] and even machines[5] use to quickly form judgmentsmake decisions, and find solutions to complex problems. Often this involves focusing on the most relevant aspects of a problem or situation to formulate a solution.[6][7][8][9] While heuristic processes are used to find the answers and solutions that are most likely to work or be correct, they are not always right or the most accurate.[10] Judgments and decisions based on heuristics are simply good enough to satisfy a pressing need in situations of uncertainty, where information is incomplete.[11] In that sense they can differ from answers given by logic and probability.

The economist and cognitive psychologist Herbert A. Simon introduced the concept of heuristics in the 1950s, suggesting there were limitations to rational decision making. In the 1970s, psychologists Amos Tversky and Daniel Kahneman added to the field with their research on cognitive bias. It was their work that introduced specific heuristic models, a field which has only expanded since