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Using AI to Address Medical Record Dirty Data with Dr. Jay Anders Medicomp

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Manage episode 490808224 series 99915
Content provided by Karen Jagoda. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Karen Jagoda or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Dr. Jay Anders, Chief Medical Officer at Medicomp Systems, discusses the issue of dirty data — inaccurate and inconsistent medical data — and its origins, as well as how technology can be used to maintain correct health records. These kinds of errors can lead to incorrect diagnoses, inappropriate treatment, and negative consequences for patients, providers, and payers. AI and other technologies are being leveraged to help identify and flag inconsistencies, providing stakeholders with the tools to prioritize accuracy over efficiency.

Jay explains, "What we do at Medicomp is a clinical knowledge engine with a knowledge graph that's built in that helps clinicians document, sort data, and clean up data. That engine was developed 46 years ago, and it's been done over again in different iterations for those 46 years. We're now incorporating new technologies inside of it to make it more efficient. But we handle medical data in documentation, presentation, and cleanup."

"Well, dirty data has been around since physicians got a chisel and a hammer and etched it in a rock. Because if you think about the old days of dictation, when physicians didn't follow what they dictated or read it very carefully, things got into that medical record that may or may not be correct. What I mean by dirty data is, does the documentation of that patient's data actually represent what's going on with the patient?"

"The other thing that happens, and it's happening more now with ambient listing technologies and other things, is that a family history of a terminal disease will all of a sudden be applied to the patient that's in front of you. So my father had Alzheimer's, now I have Alzheimer's, and it gets into the medical record that way. Gender changes. I have seen this back in the days of dictation, where he turns to her and back and forth again in the same note, which is obviously not correct. So when I say dirty data, that's the kind of thing I'm talking about. Basically, it's incorrect or misconstrued, and it gets propagated through the medical record, and with interoperability, that medical record tends to follow you everywhere you go now, and getting rid of some of that is a daunting task at best."

#Medicomp #MedAI #MedicalRecords #PatientInformation #EHR

medicomp.com

Download the transcript here

  continue reading

2247 episodes

Artwork
iconShare
 
Manage episode 490808224 series 99915
Content provided by Karen Jagoda. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Karen Jagoda or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Dr. Jay Anders, Chief Medical Officer at Medicomp Systems, discusses the issue of dirty data — inaccurate and inconsistent medical data — and its origins, as well as how technology can be used to maintain correct health records. These kinds of errors can lead to incorrect diagnoses, inappropriate treatment, and negative consequences for patients, providers, and payers. AI and other technologies are being leveraged to help identify and flag inconsistencies, providing stakeholders with the tools to prioritize accuracy over efficiency.

Jay explains, "What we do at Medicomp is a clinical knowledge engine with a knowledge graph that's built in that helps clinicians document, sort data, and clean up data. That engine was developed 46 years ago, and it's been done over again in different iterations for those 46 years. We're now incorporating new technologies inside of it to make it more efficient. But we handle medical data in documentation, presentation, and cleanup."

"Well, dirty data has been around since physicians got a chisel and a hammer and etched it in a rock. Because if you think about the old days of dictation, when physicians didn't follow what they dictated or read it very carefully, things got into that medical record that may or may not be correct. What I mean by dirty data is, does the documentation of that patient's data actually represent what's going on with the patient?"

"The other thing that happens, and it's happening more now with ambient listing technologies and other things, is that a family history of a terminal disease will all of a sudden be applied to the patient that's in front of you. So my father had Alzheimer's, now I have Alzheimer's, and it gets into the medical record that way. Gender changes. I have seen this back in the days of dictation, where he turns to her and back and forth again in the same note, which is obviously not correct. So when I say dirty data, that's the kind of thing I'm talking about. Basically, it's incorrect or misconstrued, and it gets propagated through the medical record, and with interoperability, that medical record tends to follow you everywhere you go now, and getting rid of some of that is a daunting task at best."

#Medicomp #MedAI #MedicalRecords #PatientInformation #EHR

medicomp.com

Download the transcript here

  continue reading

2247 episodes

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