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EHR Code of Conduct – Siemens Healthcare

Posted on June 25, 2013 I Written By

John Lynn is the Founder of the blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of and John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

Here at EMR Thoughts we’re going to do our best to keep track of which EHR vendors and other healthcare IT companies choose to adopt the EHR Code of Conduct. Hopefully by doing so we can offer at least one small part in helping to hold EHR vendors accountable for the code.

Today, Siemens Healthcare Adopted the EHR Developer Code of Conduct. Siemens was a major part of the effort to create the EHR code of conduct, so this doesn’t come as a surprise. Unfortunately, the press release didn’t have any details or a link to a website or anything to show how they’ve actually implemented the EHR code of conduct.

If you’re someone who uses a Siemens Healthcare product, I’d love to see if you think that they’re following the EHR Code of Conduct or if they still have room to improve. Hopefully we can get more exposure for those EHR vendors that really implement the spirit of the EHR Code of Conduct and expose those who do so only with their lips.

Creating The Intelligence-Based EMR

Posted on August 21, 2012 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Given today’s trends, I’m betting most of us would agree that EMRs need to evolve from transaction-based to intelligence based systems. They need to do better leveraging “big data,” make context-based care recommendations and support smart processes.  John likes to call them “Smart EMR,” but what would such an EMR look like?

In a recent issue of Hospitals & Health Networks, Dr. John Glaser, Ph.D.,  lays out a long– but useful– explanation as to why EMRs are stiffly focused on transactions such as documenting a visit or writing a prescription. (Very short summary: That’s just where they are coming from historically.)  Then he offers a take on the “intelligence-based EMR” and what it will take to get there.

Glaser, CEO of the Health Services Business for Siemens Healthcare, was formerly VP and CIO for Partners HealthCare, so he’s got both the vendor and the care provider view, which I think proves very useful for this discussion.

In his article, he argues that the next-gen EMR needs to offer the following:

  • foundational sets of templates, guidelines and order sets that reflect the best evidence or established best practice;
  • a process-management infrastructure that supports basic transaction checking such as drug-drug interactions, as well as asynchronous alerting like panic lab reporting and process monitoring and guidance;
  • team-based care support such as shared work lists, as well as tools for patient engagement and health information exchange;
  • novel decision aids like predictive models that can tell us if a particular patient is likely to be readmitted because he or she is fragile or has a substandard social situation at home that may negatively impact healing;
  • context-aware order sets and documentation templates that guide the physician and help infer what types of orders should be placed and what types of documentation should be done
  • intelligent displays of data, intelligent correction and identification of data, and extraction of structure by going through free text and pulling out quality measures or problems that were not previously in a patient’s problem list, for example.

The question is, are these functions science fiction (i.e. many years away from being standard) or just an evolutionary leap from today’s systems?  What are you seeing out there?