- Consumers don't know their best course of action because they lack accurate medical and care information at the times when they need to make decisions.
- Physicians are often uninterested in providing this information.
- Perhaps consumers don't care about controlling their healthcare, as evidenced by the failure of personal health records like Google Health and Microsoft HealthVault.
- Shouldn't we make it easy for consumers to access their health records?
- Do we need national standards for healthcare records?
Big picture issue:
PERSONAL HEALTH RECORDS: ARE THEY READY FOR PRIME TIME? IF NOT, WHY? WHAT CAN WE DO ABOUT IT?
In December of last year I changed my diet and exercise habits with the goal of losing weight, improving my wellness, and reducing my longer-term risk of acquiring cardiovascular disease and diabetes. I have reached my weight and blood-chemistry goals simply by cutting refined sugar, bread and starches (potatoes, rice and pasta) from my diet, and walking a few minutes every day.
Along the way, I started playing with several personal health records systems. I tried Google Health (soon to be discontinued), Microsoft HealthVault, and WebMD Health Record. In one word, these systems are terrible, as we discussed at the meeting.
But how poorly designed these systems are isn't the worst part.
My WebMD health record is automatically updated by Anthem Blue Cross, my health insurance carrier. Anthem BX gets billing claims from my medical providers (doctors, labs, imaging centers, etc.), and Anthem BX automatically posts data from the claims into my WebMD record.
Using screenshots, I used my personal data exactly as it appears in my WebMD records -- an exact replica of Anthem's database -- to demonstrate how useless are the clinical data in the systems because they are wrong. In my case, almost 100% wrong.
The reason is well known in the healthcare industry: medical providers submit billing claims to payors (insurance companies, Medicare, Medicaid) with the sole purpose of getting paid as much and as quickly as possible. This strategy is completely dominated by payors' policies. Among these, we have what might be the biggest cause of distortion: "normal" diagnoses don't get reimbursed.
Let me explain with one example I used at the meeting:
- June 21, 2010: I visited an orthopedist for a dull pain I had been experiencing on my right knee. He determined that it could be either nothing or a meniscus tear. He prescribed an MRI scan as the best and fastest modality to obtain an accurate diagnosis.
- June 29, 2010: I got an MRI scan. Results: no meniscus tear. (For another day: the nightmare I had to suffer to find how much I would have to pay for the MRI at various imaging centers I called.)
- July 6, 2010: The orthopedist prescribed physical therapy to "balance" my gait. My knee discomfort was caused by walking a little "crooked", which put more pressure on the outside edge of the meniscus.
- July 7-August 11, 2010: I visited a physical therapist. Result: fixed the problem.
This is what my clinical records show based on the claims data submitted by the three providers I visited:
- Current tear of the lateral cartilage and/or meniscus of knee. Submitted by the orthopedist for the June 21 visit, probably because it pays better than "knee pain" and certainly pays more than "I don't know yet".
- Knee meniscus tear. Submitted by the imaging center for the MRI scan of June 29. Since the resulting diagnosis of "normal" and the admitting diagnosis of "rule out tear" don't get paid, they submitted "meniscus tear" as if I actually had a tear.
- Degenerative arthritis. Submitted by the physical therapist. I don't have a lick of arthritis on my knee (or anywhere else, for that matter). I can only explain this absurd diagnosis as being produced by a random generator of codes guaranteed to get reimbursed.
A quick show-of-hands poll of the room showed that two thirds did not know this is how these things work.
Comments posted on the LAVA Healthcare LinkedIn page:
"Regarding your fascinating WebMD PHR example, I could not attend the meeting, but I wanted to share some of what I have seen in the areas of the industry I have worked. There are even consulting companies that specialize in this gray area/black box 'payment optimization'! While payors have claimed that they have all this great data, at least today, this is not really true - often, the payors have a data disaster. In fact, a significant portion of auditing work that goes on inside of insurance companies is due to the need to verify that the billed claim matches and is validated by the actual medical record - something that is often done manually, is very difficult, expensive, and quite error prone in most health plans. One example of this is verifying 'medical necessity' - which is also often defeated by medical record systems that optimize the wording of the text in the documented medical record in such a way as to ensure payment by an insurance company (walking a fine line). This is the same text that may provide little use as PHR later." Jon Saltzman
"I concur. I work at Children's Hospital LA in a research group whose aim is to apply machine learning and other computational methods to digital health data from the pediatric intensive care unit. In much of our current work, we are largely disregarding both coded diagnoses and even provider notes because the clinicians I work with assure me that these have much more to do with billing and liability than with the care delivered. Sad but true, but this is why my colleagues and peers are pretty skeptical of the irrational exuberance surrounding electronic/personal health records. The devil is in the details, and most {E,P,D}HR systems suffer from poor implementation and improper use, not to mention the fact that they are horribly overpriced. These systems need to adopt the design principles (ubiquitous, automatic data capture, beautiful UIs) of the most successful web properties." David Kale
