The True Value of an Electronic Health Record

We still struggle to define the value and return-on-investment of EHRs, often times naively attempting to justify the investment based upon improvements to physician workflow and patient volume. The real value resides in the systemic value of the data that's collected, the data that's analyzed, and the data that is presented (or not) back to the physician at the point of care, that has been dynamically tailored for the context of the patient being treated, making it easy for physicians to do the right thing.


A few days ago, I was in a meeting with members of Virginia Mason Medical Center who were visiting Northwestern to discuss clinical analytics and process improvement. Northwestern's Dr. David Baker provided an overview of an AHRQ-funded project called UPQUAL (Utilizing Precision Performance Measurement to Improve Quality) which he is leading. I think UPQUAL is the most systemic example and role model of clinical quality improvement in an ambulatory setting that I've ever seen-- every step in the care delivery process is affected. You can Google "UPQUAL Baker Persell" and find references. Darren Kaiser, my Senior Technical Guru of All Kinds, has been a critical part of this project, too.


During a break in his presentation, Dr. Baker was speaking with members of VMMC. The conversation moved to the recent clinical study published in the British Medical Journal which indicates that prophylactic aspirin for diabetes patients without cardiovascular disease is not effective in reducing heart disease-- the risks of aspirin outweigh the benefits.

Later that week, I was browsing my bloated email inbox and came across a Change Control Summary from our Clinical Systems team, entitled "Turn off BPA for Aspirin in Diabetics." Hmmm.... I opened the message and read the description: "Unrelease BPA #92 "Consider Aspirin in Diabetes" per direction of Dr. Persell/Baker. Recent evidence suggests that this Best Practice Medical Guideline is no longer deemed a best practice. Hence, we don't want to trigger BPA recommendations when there is little benefit to patient care." Translated, this means that Dr. Baker contacted our EpicCare EHR team and asked them to turn off the Epic Best Practices Alert that reminded our physicians to consider aspirin therapy for our diabetic patients.

I talked to Dr. Baker later in the week and asked him for the background. As he described it, the General Internal Medicine physicians discussed the strengths and weaknesses of the BMJ article, and then voted in one of their regular Clinical Quality Committee meetings whether to accept the new evidence and adopt the changes in practice. They voted in the affirmative and closed the loop by contacting the EpicCare team who then changed the BPA.

From start to finish, this change in clinical protocol took about eight weeks. I think the BMJ article was published on Oct 3 and the EpicCare Change Control was implemented on Dec 5.

In various lectures and presentations, I frequently speak of this concept which I call "Mean Time To Improvement" (MTTI). It is the theoretical ability to measure the time it takes a company to recognize the need for improvement, and then take action to implement that improvement on a widespread basis. I give examples of process improvement in industries like the foreign automotive market, computer chip fabrication, PDA design, wireless cellular services, and leading retailers. The examples indicate that the MTTI among the leaders in those industries can be measured in terms of hours, days, and a few weeks. They have low MTTI cultures. Then I give examples of process improvement in the U.S. government, automotive, and healthcare sectors. There are individual heroic exceptions in each of these sectors, of course, but for the most part, the MTTI can be measured in months and years... maybe decades. For dramatic impact, I use the example in healthcare in which 17 years expired before the protocol for community acquired pneumonia (CAP) was commonly accepted and practiced.

You see where I'm headed here... in the specific case of removing Epic BPAs for aspirin therapy in diabetics with no existing cardiovascular disease, we have an example which momentarily drove the MTTI in healthcare down to levels of respectability amongst the best of other industries-- maybe even better than other industries. It exemplifies the true value of an EHR to healthcare-- if that EHR is configured and utilized up to its potential by quality-dogmatic physicians and a capable IT team.

Very cool.

Northwestern Enterprise Data Warehouse Milestone

In past blogs, I've alluded to the development of our Enterprise Data Warehouse at Northwestern. The "enterprise" is currently inclusive of data content from Northwestern Memorial Hospital (NMH), the Northwestern University Biomedical Informatics Center, and the Northwestern Medical Faculty Foundation (NMFF). In the future, the enterprise will hopefully include Children's Memorial Hospital, the Rehabilitation Institute of Chicago, and our affiliated private physicians.

The EDW project is complicated by the fact that all of these organizations are separate business entities, even though we serve the common mission of Northwestern University's Feinberg School of Medicine. We all report to separate governance bodies, CEOs or the Dean. The EDW project forced us to define new models for collaborating on several levels including joint financing models, human resources management, data security, project oversight and governance, identity management, etc. Data warehouse projects are inherently very political and culturally risky, no matter what the industry or organizational structure involved. I am constantly amazed and pleased at how incredibly smooth this project has progressed. It is a phenomenally positive reflection on the culture of senior leadership, myself excluded from the compliment. Since so many new models and processes were required for the project, we've had to be comfortable with route finding and learning as we progressed. This required each organization to trust one another, significantly, as each took turns leading the climb at one time or another.

The clinical research value and momentum around the EDW is growing. At last count, 36 different research projects have been served with 62 data sets, using a secure, researcher-specific work area on the EDW web portal. The majority of these requests were fulfilled in the last 12 weeks.

Today, the EDW Team released a data set which was emblematic of the "enterprise" potential and capability of the EDW. The data set combined diagnosis data from the NMH case mix system (Primes) and the NMFF EpicCare system; and free-text data from NMH and NMFF lab reports. Another noteworthy milestone in this case-- The lab reports' text data was scrubbed of patient identifiers by an open source software algorithm developed by MIT and modified by our EDW Team for use in our system.

A description of the data set is below; 18,463 patients were in the cohort. The request was prep-to-research from one of our physicians who is investigating mild versus severe cases of the flu. Our newest member of the EDW Team, Nathan Sisterson, was the analyst who programmed the query and the text processing.

"The cohort is defined as: All patients whose text reports in Epic labs match are of a type whose lab name contains “influenza”, starts with “virus” or starts with “respiratory virus”. From this subset, the cohort is narrowed to only patients whose matching lab results contained the phrases “positive for parainfluenza”, “positive for influenza”, “influenza virus isolated”, “positive influenza”, “influenza virus detected”, or “* SD” (which is always accompanied by a number indicating a positive lab result). Patients whose ICD9 codes match 488, V04.81 or 487.x in Epic or Primes are also included."

Too early to celebrate a summit, but this is very exciting stuff at this stage of the EDW project.
:-)
Dale