Let me concede from the outset that, in this blog post, I lean toward the negative—dire predictions, worst-case scenarios, a bit of doom and gloom, etc.
But I ask you, oh gentle, patient reader, how could I not?
Let’s go to the satellite. You can see warm air from a low-pressure system (Meaningful Use Stage 2, not changed dramatically by the one-year extension) collide with cool, dry air from a high-pressure area (the turmoil of Obamacare) and tropical hurricane moisture (ICD-10). Tell me you don’t see the Perfect Storm yourself.
And here we sit in our little fishing boat, waiting for the mighty ocean to consume us.
Overly dramatic? Certainly, but still not wholly inappropriate, I will argue.
Consider a recent report on the HIMSS/WEDI ICD-10 National Pilot Program collaborative that was created to, “…minimize the guess work related to ICD-10 testing and to learn best practices from early adopter organizations.”
Designed to ascertain the realities of the entire healthcare system adopting and using ICD-10, this pilot included an education and adoption program for all participants, followed by a set of “waves” in which diagnoses for the 100-200 most common medical conditions were actually coded and submitted using ICD-10.
The end-to-end testing approach …
…would encompass a number of medical test cases that mirror actual processing, including situations with multiple “hops” or “steps” between providers, clearinghouses, and health plans; the identification of high-risk medical test cases to help prioritize testing; the identification of available testing partners; and key reporting and sharing of test results. The test environment must mirror production.
And how did this pilot testing go? (Cue dark, foreboding music here …)
The average accuracy was in the 60 percent range with low scores around 30 percent. Yes, some medical scenarios had nearly 100 percent accuracy, which is great. But very low accuracy accompanied a number of very common conditions. Not so great. To be more specific:
- 40%: Chest pain, unspecified
- 33%: Closed fracture of unspecified part of femur
- 45%: Coronary atherosclerosis of native coronary artery
- 40%: Congestive heart failure, unspecified
- 42%: Degeneration of the limb or lumbosacral intervertebral discs
- 46%: Acute chronic systolic heart failure
- 29%: Sebaceous cyst
- 35%: Closed fracture of the intracapsular section of femur, unspecified
Predictably, the pilot identified coding-based challenges as the primary cause of low accuracy rates. Some are easily solved. Others, not so easily. You be the judge of this coding error best-of list:
- Mixing up similar letters and numbers
- Technical glitches with uploading and transmission of documents
- Overworked coders
- Incomplete EHR documentation
- Coders forgetting key aspects of ICD-10 not present in the ICD-9 code set
Of course, all these errors require understanding the problem and tackling it within the context of process and team. If test subjects scored lower than 50 percent accuracy coding common diagnoses even after a well developed and implemented training program, what will mainstream providers achieve? How much worse might they be?
I am speaking primarily of resource constrained provider organizations that are already on the edge financially, not Partners Healthcare or Mayo Clinic. For them, I think these pilot study figures portend a financial disaster: 50 percent coding accuracy means 50 percent claims denial and a precipitous decline in revenue. How will they make the needed changes to increase accuracy when organizations in the study could not?
According to the frank assessment offered by pilot study organizers, they will just need to focus.
The “perfect storm” will be quickly descending upon the healthcare system … All ICD-10 impacted organizations should act now to allocate as much time as possible for testing and remediation to protect their corporate bottom lines and cash flow to successfully achieve compliance.
While the pilot does not actually quantify the time and resources required for organizational change and ICD-10 compliance, a comment on the pilot offered by one physician speaks of an exhausted profession that can’t see a better day on the horizon.
As a practicing physician and using EHR (sic) for last 10 years, the last 2 with Epic both in office and hospital, I cannot image (sic) what this will mean. I now spend 11 to 15 hours a day, Monday through Friday, plus many hours on the weekend working on the computer. This ICD-10 sounds ridiculous to try to implement on top of everything else.
While I’m in partial agreement with Dr. John Halamka of Beth-Israel Deaconess and Harvard on this one, I don’t think his suggestion of a 6-month ICD-10 extension is enough. What will be so significantly different in 6 months? In that timeframe, I think the challenges that exist now—Meaningful Use Stage 2, the upheaval of the Affordable Care Act–will pretty much be the same. While I don’t expect it to happen, I’d suggest we delay ICD-10 until innovation makes it less of a burden. I can’t say when that will be, but I do have faith that it will happen.
It’s not that ICD-10 is an inherently bad idea, or that hospitals and providers can’t meet the challenge with reasonable deadlines. But they have too many challenges right now, and we are forgetting that most of healthcare is small provider organizations, regional and county hospitals and critical access facilities. If Kaiser struggles with MU, the ACA and ICD-10 all at once, what is a county hospital in Kansas or Idaho, or New York or California, supposed to do? When their reimbursement rates fall, they will face bankruptcy, and vital healthcare services will disappear from the areas that can least afford to lose them.
Yes, it is a clichéd pop-culture reference, but we truly are looking at a healthcare perfect storm like no other next year. We expect that this confluence of challenges will eliminate some health IT companies, and we generally accept that the herd needs to be thinned anyway. But can we be so sanguine about the potential impact on healthcare itself when financial ruin and simple emotional overload seem highly possible, even likely?
Providers will be driven to the brink, and I cannot see how this ends well for American healthcare, which I thought was the original goal.