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Optimizing clinical complexity in neurodegenerative disorders using medical cognition tools

Abstract:

We illustrate conversational learning through our udhc global and local CBBLE groups around neurodegenerative disorder patients and topics as well as insights from their informational continuity through PaJR groups. We demonstrated almost 6 patients who approached us through our PaJR groups and finally travelled from distant places to meet us in our hospital. We further share our workflow around these neurodegenerative disorder patients to demonstrate how PaJR driven informational continuity has the potential to not just improve health professionals learning outcomes but also real patient outcomes

Keywords: neurodegenerative disorder, case-based blended learning ecosystem, Huntington disease.


 Introduction:

Neurodegenerative disorders are a major public health and medical problem that impose substantial damage on people all over the world. The rate and frequency of these diseases increase significantly with age; consequently, the prevalence is anticipated to rise in the near future as life expectancies in many countries keep increasing.(Checkoway et al., 2011). Apart from the selective static neuronal loss seen in metabolic or toxic illnesses, the gradual loss of selectively susceptible neuronal populations characterises neurodegenerative disorders.(Dugger & Dickson, 2017) Pyramidal and extrapyramidal movement disorders, as well as cognitive or behavioural disorders, are the most prevalent clinical manifestations of neurodegenerative diseases. Few patients exhibit clear syndromes, while the majority have complex clinical characteristics.


 Medical cognition tools, such as Patients Journey Recording System(PaJR), User Driven Health Care(UDHC), and Case Based Blended Learning Ecosystems (CBBLE) are playing a predominant role in resolving the clinical complexity(diagnostic and therapeutic uncertainty) of different neurodegenerative diseases.

The aforementioned cognitive tools contribute not only to resolving clinical complexity, but also to enhancing the clinical knowledge of health professionals through collective conversational learning on these platforms. Here, we present several of our neurodegenerative cases and illustrate how the these medical cognition tools are greatly influencing the optimisation of clinical complexity and uncertainty.


 Aim and Objective:

1) Provide an illustration of certain medical cognition tools such as user-driven health care (UDHC), where a network of providers, patients, students, and researchers collaborate to improve neurodegenerative patient care.

2) Describe UDHC as well as its

Subsets such as CBBLE, PaJR and their

opportunities and challenges in care coordination to reduce costs, bring equity, and enhance care quality.

3) Share relevant evidence in the field of neurodegenerative disease.

4) Share the impacts of these cognition tools for resolving complexity of the patients illness as well as to broaden the clinical knowledge of health professionals through collective conversational learning on these platforms.


 Study Design: Prospective, observational qualitative study.

Methodology: Illustration of our regular UDHC and CBBLE workflow with particular emphasis on PaJR created for every single patient, the entire workflow of which is depicted in open access case report forms again prepared solely for every individual patient with suspected neurodegenerative disorder patients among others.

Cases: We have listed 6cases of different neurodegenerative diseases including huntington disease, ALS, snake bite related neural symptoms etc.

Inclusion criteria: Patients above 18 years, Patients with neurodegenerative diseases.

Exclusion criteria: Patients below 18 years, Patients with no obvious neurodegenerative disease, Patients who does not want to be a part of study.


 Reference:

1) Checkoway, H., Lundin, J. I., & Kelada, S. N. (2011). Neurodegenerative diseases. IARC Scientific Publications,

163, 407–419.

2) Dugger, B. N., & Dickson, D. W. (2017). Pathology of Neurodegenerative Diseases. Cold Spring Harbor Perspectives in Biology, 9(7), a028035. https://doi.org/10.1101/cshperspect.a028035

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