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The Financial Need for Quality Improvement in Healthcare Infographic

Posted on November 3, 2014 I Written By

John Lynn is the Founder of the HealthcareScene.com 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 InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

I recently received a well done infographic on the negative financial impact of poor quality healthcare on the health system. The infographic was created by Caradigm, a population health company. I think you’ll find some interesting insights in the benefits of quality healthcare in this infographic.
Need for Quality Improvement in Healthcare

Data Sources:
GE Healthcare. “Clinical Decision Support Decision: Defining our Problem Statement. 2011.
The Advisory Board. 2008. based on Kleven, RM. “Estimating Health Care-Associated Infections and Deaths in U.S. Hospitals 2002.” 2007.
The Advisory Board. “The Tip of the Iceberg: Adverse Events are Costing You More than Ever.” 2011.
GE Reports. “The Unknown Killer: Healthcare Associated Infections.” 2011. http://www.gereports.com/the-unknown-killer-healthcare-associated-illnesses/
NEMJ “Care in US Hospitals” July 2005.
HealthAffairs. Reducing Waste in Health Care. December 2012. http://www.healthaffairs.org/healthpolicybriefs/brief.php?brief_id=82
Centers for Medicare and Medicaid Services, “National Patient Safety Initiative: Saving Lives Saving Money,”

Another Example Of EMR “Golden Age” Applications

Posted on July 30, 2013 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 FierceHealthcare.com 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.

Not long ago, John posted a piece about the “Golden Age of EMRs Being Over” and how that’s playing out from an EMR vendor perspective. Since writing that piece he’s found that while the Golden Age of EMR buyer frenzy has passed, we’re entering a new EMR Golden Age which will feature amazing applications for clinicians and public health administrators. John calls these applications Smart EMR.

Today, I came across some news which I think is a perfect example of the kind of innovative applications John is predicting will emerge as EMRs mature. At the University of Notre Dame, researchers have developed a system which uses collaborative filtering of EMR records to better guide treatment, manage disease and predict disease risks across a population.

Notre Dame computer science associate professor Nitesh Chawla and doctoral student Darcy Davis call the new system the Collaborative Assessment and Recommendation Engine (CARE). CARE uses collaborative filtering to detect similarities between patients and produce personalized disease risk profiles for individuals. It does so by looking at diseases in similar patients.

“In its most conservative use, the CARE rankings can provide reminders for conditions that busy doctors may have overlooked,” Chawla said in a prepared statement. “Utilized to its full potential, CARE can be used to explore broader disease histories, suggest previously unconsidered concerns and facilitate discussion about early testing and prevention, as well as wellness strategies that may ring a more familiar bell with an individual and are essentially doable.”

Ultimately, Chawla says, such a system can produce a host of benefits. For example, he suggests, it can reduce readmission rates, improve quality of care ratings, help demonstrate Meaningful Use and improve personal and population health. On a more micro level, it can allow patients to walk out of their doctor’s office with a list of recommendations based on predicted health risks, he notes.

This is just one example of the kind of new applications that are emerging as EMRs mature and the use of big data becomes a tool for wellness. I expect to see lots of announcements of this kind over the next year or two. It’s an exciting time.

EHR Interoperability Benefits Not Related to Physician Data Sharing

Posted on February 5, 2013 I Written By

John Lynn is the Founder of the HealthcareScene.com 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 InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

I always love when someone can take a subject and expand my thinking on that subject. Whenever I thought about EHR interoperability I always thought about it from the perspective of a physician sharing that data with another physician. In this case it would be one EHR sharing with another EHR (possibly with an HIE in the middle). In a recent post, Dr. Doug Fridsma from ONC, (I love that ONC blogs) expanded my thinking when it comes to the possible benefits associated with data standards and EHR data sharing when he shared the following list:

  • Patient safety advocates may want to use EHR systems to collect patient safety information, leveraging existing standards like the AHRQ “common format” for patient safety reporting
  • Providers and researchers may want to use the EHR systems to collect data for clinical research, including patient-centered outcomes research, and to identify patients who could benefit from participating in a research study
  • Providers may want to give referrals to their patients for community services, like smoking cessation or weight management programs, after discussing these topics with them during an office visit
  • Providers working with disease surveillance case report forms may wish to collect additional information about reportable conditions, such as infectious diseases
  • Provider’s office staff can use EHR’s to gain pre-authorization of certain kinds of medical devices where health payers may want to leverage clinical information collected in EHRs to support additional review of expensive medical equipment.

After just publishing my recent post about The Coming Physician EHR Revolt, I can’t help but ask what any of the above items do to help a doctor. The last one could help a physician’s workflow, but the rest of them have limited specific value to a physician. This is one of the challenges with EHR data sharing. Doctors don’t buy and implement an EHR because they want to give better referrals to their patients for community services. There’s a mismatch between providers’ needs and healthcare data exchange desires.

ICD-10 Benefits for Population Health

Posted on November 13, 2012 I Written By

John Lynn is the Founder of the HealthcareScene.com 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 InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

I’ve asked many people why we haven’t had more stories on the benefits of ICD-10 since so many other countries have been using ICD-10 for many years.

In the following video I asked Doris Gemmell, BSc, MBA, CHIM, Director of Coding Services at Accentus Inc. about the benefits of ICD-10 to population health and she provided an answer from her ICD-10 experience in Canada.

You should also check out this video where Doris Gemmell talks about the patient benefits of ICD-10. Plus, Doris also has a blog.

EMR Interfaces Gone Wrong, Or The Tale Of The Albanian Patient

Posted on October 16, 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 FierceHealthcare.com 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.

Today, for your consideration, we have the tale of the Albanian patient who wasn’t Albanian.  More broadly, I’m here to discuss the perils of adding an extra interface consideration to the workflow of busy EMR users, and the impact that has on data quality.

Scope, a blog published by the Stanford School of Medicine, shares the case of the Merced County, California physician who, exasperated with the requirement that he identify the ethnicity of each patient, chooses “Albanian” for all of them. Why? Simply because “Albanian” is the first item of the rather long list in the pulldown menu.

As a result of this interface issue, any attempt to mine this veteran doctor’s data for population health analysis is weakened, writes Anna Lembke, MD, asssistant professor of psychiatry and behavioral sciences at Stanford.  And this physician’s choices should give the “big data” users pause, she suggests:

Misinformation in electronic medical records, whether accidental or otherwise, has far-reaching consequences for patients and health care policy, because electronic medical records are being actively ‘data-mined’ by large health care conglomerates and the government as a basis for improving care. This is an important downside to consider as we move forward.

Dr. Lembke’s observations are important ones. If government entities and health organizations would like to mine the increasingly large pools of data EMRs are collecting, it’s important to look at whether the data collected actually reflects the care being given and the patients being seen.

I’m not suggesting that we audit clinicians’ efforts wholesale — they’d rightfully find it offensively intrusive — but I am suggesting that we audit the interfaces themselves from time to time.  Even a quarterly review of the interfaces and workflow an EMR demands, and results it produces, might help make sure that the data actually reflects reality.

EMR Data Often “Inaccurate” Or “Missing”, Study Says

Posted on September 17, 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 FierceHealthcare.com 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.

EMR adoption continues to march forward, spurred not only by Meaningful Use requirements but also the need for doctors to access data remotely and the rise of cloud infrastructure to support such initiatives.  According to research firm IDC, 80 percent of healthcare organizations should adopt EMRs by 2016.  Pretty much what you might expect.

Hopefully, this will have a positive impact on clinical care. However, EMRs may be less useful than they should be for population health research, as data is often inaccurate or missing, according to a new report published in the Journal of  The Medical Informatics Association.

Researchers behind the report said that while data from EMRs can be useful, it’s prone to certain types of errors which undermine its value.  For example, EMR data accuracy varies depending on whether the patient was treated during the day or during the night, in part because patients at night are often sicker, according to Dr. George Hripcsak, a professor of biomedical informatics at Columbia, who recently spoke with eWeek magazine.

Another issue of concern is that patient symptoms are often poorly documented in EMRs before death. For example, patients with community-acquired pneumonia who enter the ED and die quickly don’t have symptoms entered into the EMR before they die. Later on, their medical records make it look as though a healthy patient died, the researchers note.

Dr. Hripcsak told the magazine that researchers in informatics, computer science, statistics, physics, mathematics, epidemiology and philosophy will need to work together to get an accurate read on EMR data and avoid biases. (Whew!)

Clearly, the kind of teamwork Dr. Hripcsak has in mind will take a great deal of resources. They’re on their way, it seems. For example, I’m betting that the new Johns Hopkins center for population health IT will serve as a model for the kind of interdisciplinary efforts he’s describing. But that’s just one effort. It will be interesting to see whether other universities follow in Johns Hopkins’ footsteps.