Where it in my humble opinion (as a non-medical outsider) boils down to as far as I can follow your explanations from this paper is that exchangebility or better interoperability between both the OpenEHR and FHIR standards in stead of having one standard is what you discussed earlier with Ewout Kramer (Founding Father of FHIR) in one of your previous videos is about 'the role of human behavior in data modeling' for their specific use cases.Even in the financial industry, where my own expertise lies as an integration developer, there is one universal standard called SWIFT that has so many optional fields in their datamodel-entities that one uses its own mostly country specific "standards" derived from these yearly globally evaluated SWIFT standards. But from the dynamic data exposure needs in the health industry it becomes a huge challenge to even see how from these different perspectives/paradigms (OpenEHR archetypes -and templates / FHIR profiles) work to extract and maintain relevant patient data for a life long purpose. Perhaps you could evaluate or elaborate more on that specific patient centric need and topic in one of your future videos.
Hey Adam! This is an excellent reply. Thanks for adding to the argument. In my opinion, the data models "patient centric need" is very dynamic and has insane amount of variability. Unlike banking and the SWIFT data model, which can be decided upon by committees and can stay stationary for a long period of time, the healthcare requirements of a population is always in flux. A rural doctor in India does NOT care about how many steps the patient has taken on their wearables, whereas urban doctors in first world countries really don't care about the source of water for the patient - because they know it's mostly always clean. And then a sudden outbreak happens, and you want to collect completely new sets of data points yet again. Tbh, I don't have all the answers. I'm trying to figure out what works best and how we can progress this space together. And this is definitely the kind of discussion that's needed!
Thank you, Dr. Sidharth. I appreciate your explanation of the OpenEHR, FHIR, and OMOP standards, their use cases, and their interrelation. Your clarification of the term 'lossy' and its acceptance in longitudinal analysis is also valuable. No matter the strategy taken for the various domains (Clinical Care and Administration, Data Exchange, and Longitudinal Analysis), the issues with both intra-operability and inter-operability, data collection, and exchange solutions will persist. Personally, I believe we should identify and eliminate the root cause of complexity that has the least impact on patient care/health. So far, all the solutions have been equally frustrating.
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Where it in my humble opinion (as a non-medical outsider) boils down to as far as I can follow your explanations from this paper is that exchangebility or better interoperability between both the OpenEHR and FHIR standards in stead of having one standard is what you discussed earlier with Ewout Kramer (Founding Father of FHIR) in one of your previous videos is about 'the role of human behavior in data modeling' for their specific use cases.Even in the financial industry, where my own expertise lies as an integration developer, there is one universal standard called SWIFT that has so many optional fields in their datamodel-entities that one uses its own mostly country specific "standards" derived from these yearly globally evaluated SWIFT standards.
But from the dynamic data exposure needs in the health industry it becomes a huge challenge to even see how from these different perspectives/paradigms (OpenEHR archetypes -and templates / FHIR profiles) work to extract and maintain relevant patient data for a life long purpose. Perhaps you could evaluate or elaborate more on that specific patient centric need and topic in one of your future videos.
Hey Adam! This is an excellent reply. Thanks for adding to the argument. In my opinion, the data models "patient centric need" is very dynamic and has insane amount of variability. Unlike banking and the SWIFT data model, which can be decided upon by committees and can stay stationary for a long period of time, the healthcare requirements of a population is always in flux. A rural doctor in India does NOT care about how many steps the patient has taken on their wearables, whereas urban doctors in first world countries really don't care about the source of water for the patient - because they know it's mostly always clean. And then a sudden outbreak happens, and you want to collect completely new sets of data points yet again. Tbh, I don't have all the answers. I'm trying to figure out what works best and how we can progress this space together. And this is definitely the kind of discussion that's needed!
Thank you, Dr. Sidharth. I appreciate your explanation of the OpenEHR, FHIR, and OMOP standards, their use cases, and their interrelation. Your clarification of the term 'lossy' and its acceptance in longitudinal analysis is also valuable.
No matter the strategy taken for the various domains (Clinical Care and Administration, Data Exchange, and Longitudinal Analysis), the issues with both intra-operability and inter-operability, data collection, and exchange solutions will persist. Personally, I believe we should identify and eliminate the root cause of complexity that has the least impact on patient care/health. So far, all the solutions have been equally frustrating.
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hey hi there can you make a video on current scenario of ABDM as i have seen your old one comparing with US , currently working on ABDM
Just thinking about ABDM gives me nightmares. Even the current scenario.
Your English is so good! Thanks for this.