ICD-10 for Busy Physicians – Asthma and COPD

Asthma and COPD are two chronic conditions common enough in the general population that most physicians will want to know the documentation needs for coding in ICD-10. I’ll compare them to documentation for ICD-9.

Asthma

Asthma coding has changed. Two axes of classification that physicians rarely documented in ICD-9 have been eliminated, and two axes of classification (that hopefully physicians will find useful) have been added in ICD-10. As a result, the total number of asthma and COPD codes is roughly the same in ICD-9 and ICD-10—17 ICD-9 codes and 20 ICD-10 codes.

Here are the two hair-splitting ICD-9 axes of classification that have been eliminated in ICD-10:

• ICD-10 does not force physicians to categorize asthma as intrinsic or extrinsic. Asthma is just asthma.
• ICD-10 does not have separate codes for chronic obstructive asthma, as opposed to chronic obstructive bronchitis or plain old chronic obstructive pulmonary disease. COPD is just COPD in ICD-10. More about COPD when we finish with asthma.

Read my latest blog at PhysBizTech.

‘Big Data’ Initiative and Healthcare

On March 29, 2012, President Obama’s administrators announced the $200 million dollar R&D investment in the ‘big data’ project.  According to the press release, the “Big Data Research and Development Initiative” will “improve our ability to extract knowledge and insights from large and complex collections of digital data”. It further suggests that this project will “help solve some of the Nation’s most pressing challenges.”  The project is a joint collaboration with the Office of Science and Technology and other agencies and is supported by the National Science Foundation (NSF) and the National Institute of Health. NIH is “particularly interested in imaging, molecular, cellular, electrophysiological, chemical, behavioral, epidemiological, clinical, and other data sets related to health and disease.” Read the press release here.

3M and CodeRyte

Today, 3M HIS announced it has acquired CodeRyte. As division scientist, this is exciting news from a technology perspective. Here’s my take on what it means for NLP:

The distinctive feature of CodeRyte’s technology is its strong statistical NLP capability. As I discussed in the 3M white paper, Auto-coding and Natural Language Processing, statistical machine learning systems offer the possibility of significant accuracy improvements in data-rich environments, compared to traditional rules-based approaches. A good example is in the outpatient coding environment, where data volumes are large, and CodeRyte has a history of performing very well compared to other systems.

There are multiple ways to boost the accuracy of statistical NLP, and the combination of 3M and CodeRyte will allow us to pursue several paths to the direct benefit of end users. 

ICD-10 Benefits: Research

ICD-10’s finer detail, and the fact that the cleaner logic of the codes may lead to fewer coding errors in the long term, cannot help but improve research.

If you look at the overall cost of medical care, a lot of the arguments are not that we’re spending too much, but that we’re spending it in a blind fashion. We’re spending money inappropriately. The ability to target our spending money and to try to get the money that we do spend to the places that it’s needed requires a higher level of that spending analysis than we can currently do with ICD-9.

Talking to Caregivers Instead of Computers

Human language developed at least 100,000 years ago, and has evolved into an amazingly complex and subtle mechanism for communicating ideas.

Computers emerged on the scene a mere half-century ago. And yet, we often find ourselves trying to structure our clinical communications around “talking” to computers, rather than talking to other caregivers. The impact to quality of care is potentially large, and often ignored.

Diving into the Details of Your Next Health Care IT Project

It would be great if you could get your staff to buy-in to your next technology project by telling them, “This change will save the organization thousands of dollars by increasing productivity and reducing administrative overhead.”  However, they would probably much rather hear, “This change is going to eliminate that one extra step that really gets on  your nerves and will give you access to additional bells and whistles that are really cool.”

HIM workers by nature pay close attention to detail, and in my experience, they really appreciate when attention is given to eliminating their pain points.  Personally, I gravitate toward details and process mapping because I know that day-to-day workflow is where the rubber meets the road.

How Do You Measure Accountable Care?

There is a transformation occurring in health care. What traditionally had been the responsibility of payers is now shifting to providers. Providers and health systems haven’t been responsible for comparing the total cost of care against total health outcomes. As  part of this transformation, health systems will increasingly be held accountable for total costs of care.

My concern about putting the “accountable” in “accountable care” is measurement. What will be measured? How does a provider or health system that traditionally has billed for services now assume responsibility for the total cost of care?

ICD-10 for Busy Physicians — Diabetes and CHF

As promised, I am going to talk about chronic conditions that are common enough that most physicians see patients who have them. And that means dealing with the documentation needs for coding the patient encounter in ICD-9 now and ICD-10 in the future. In this blog I am going to highlight the similarities and differences between ICD-9 and ICD-10 documentation and coding needs for diabetes and congestive heart failure (CHF).

Diabetes
Diabetes coding will actually be easier and more efficient in ICD-10, which should translate into fewer queries from coders. There are two basic changes in ICD-10 diabetes classification:

• No more coding and documentation hassles with uncontrolled diabetes.
• Complex diabetes cases that required multiple ICD-9 codes can be coded with one ICD-10 code.

Read my latest blog at PhysBizTech.

Why We Can’t Skip ICD-10 and Go Straight to ICD-11

Since the recent announcement by CMS that ICD-10 implementation will be delayed for certain healthcare entities, some industry pundits have argued, “Let’s just skip ICD-10 and go straight to ICD-11.”

Skipping ICD-10 assumes that we haven’t started implementing ICD-10. Well, the U.S. did start—19 years ago.

What have we been doing for the last 19 years?

Federal agencies kicked off ICD-10 implementation in 1993 by preparing to develop a clinical modification of ICD-10 (a U.S. version), then getting a grant and assigning a contractor to develop a clinical modification. Ditto for a procedure coding system.

New Metrics for Health Care Reform

By: Sandeep Wadhwa

There is a big shift occurring in the way we measure the efficiency and effectiveness of health care. The shift is moving beyond process measures toward patient-satisfaction measures, such as CAHPS surveys and outcomes measures, including hospital-acquired conditions and hospital readmissions. These new measures are quickly becoming the foundation of new payment systems.

For example, the CMS hospital readmissions reduction program will penalize excessive hospital readmissions. This provides a huge incentive for hospitals to improve protocols and procedures to lower readmission rates. However, it isn’t just a clinical care issue. It’s a measurement issue, too, as pointed out by the Healthcare Financial Management Association (HFMA) in their letter to CMS. HFMA argues for CMS to provide data on readmissions and to change how they are defined and calculated. (They also made an unsolicited endorsement of 3M classification methodologies. Thanks, HFMA!)

Traditionally our industry has focused on quality process measures such as whether a medicine was delivered or not on time. Process measures are important.  That’s a critical step in an equality hierarchy, but they’re not a measurement of the outcome of interest. If you’re trying to measure infection rates after surgery or a lung puncture or aspiration pneumonia, that’s the outcome.