October 5, 2015

ICD-10: It’s Now the Standard

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After multiple delays, ICD-10 is now the national (and to some degree, international) standard for the definition of each patient’s health state.   

While there are many different standards in other areas, this is the only standard of its kind for the definition of patient condition that is nationally mandated and interoperable for all payers, providers, and clearinghouses. For many, this is a time of concern about the potential disruption of the current care delivery process due to such a significant change. It’s well-known, however, that all meaningful change is disruptive.

 

As we move forward, there will be an opportunity to capture more accurate, consistent, and complete information about the nature of patients’ health conditions, but ICD-10 does not in of itself result in any improvement in the data we have about the nation’s health. 

We can be just as vague, incomplete, and inconsistent in ICD-10 as we were in ICD-9. An analysis of three years of professional claim-based payer data (representing over $4 billion in charges) demonstrates that historically, 54 percent of all claims included a primary diagnosis that could be classified as an “unspecified,” “other,” or “symptom or finding” code. The same types of codes exist in ICD-10. ICD-10 provides the opportunity for greater specificity and quality of data, but only if those who capture data at the source believe that more accurate, complete, and reliable data is important and worth the additional effort.

Many electronic health record (EHR) systems, in an attempt to shield clinicians from any additional disruption, are providing a one-to-one map from the non-specific ICD-9 code to equally non-specific ICD-10 codes. They are encouraging the use of “favorite codes,” but unfortunately many patients don’t have the physicians’ “favorite” condition. Collecting data about the patient is supposed to be for the patient’s benefit, not simply the convenience of the clinician.

As I have travelled around the country talking to physicians about the importance of complete and accurate data, the common responses that I hear from clinicians include:

  • “Being more specific won’t improve my reimbursement.”
  • “Data that I submit goes into a black hole. I don’t get any information back for the data that I submit.”
  • “Getting to the right code takes too much time and is not consistent with the way I think.”

In order to improve the quality of information about the healthcare that’s being provided in this country, as well as to track diseases and injuries in a way helps protect patient safety, we need to address these concerns head-on. Otherwise it is unlikely that the effort put into transitioning to ICD-10 will reap any benefit.

Charting a Course to Better Data 

If data is going to improve, we have to address the obstacles that limit the collection of data at the source. There needs to be a different approach. As has been often quoted, “the definition of insanity is doing the same thing and expecting a different result.” 

  1. Payment models should be more aligned with the patient condition and less with services. Service-based payment just encourages more service, but does not focus on the risk, severity, and complexity of the patient heath state as related to outcomes of patient care. Why should a clinician caring for a patient with type 1 diabetes with hyperglycemia, ketoacidosis, and diabetic nephropathy be reimbursed the same as a clinician treating a type 2 diabetic who is stable, controlled, and without any complications? It doesn’t make sense that a full review of system, family history, physical exam, and other components of care should be the basis for adjusting the payment when it’s really about the risk, severity, and complexity of the patient’s health state. Other incentives also should be considered to encourage improved data quality. For most hospitals, clinical documentation improvement is a key focus for one primary reason: more specific data means greater revenue.  Payers that participate in Medicare Advantage are investing millions in improving provider coding, all driven by the impact of HCCs on the premium bottom line.
  2. All data submitted by the clinician as well as the analysis of comparisons of coding patterns related to that data should be readily available to provide feedback. If providers have this data, they become much more interested in the quality of the data. Variations in data, when presented to providers, change behavior and create incentives for better data going forward. If all of the data submitted goes into a black hole, then why would anyone care?
  3. Organizations need to make data and information governance a core competency. Each organization must have as a goal a commitment to standardized, accurate, consistent, and complete data about the delivery of healthcare. In a data-driven healthcare environment, this will be key to surviving and thriving. In this type of environment, you will want to know more about the care you deliver and the nature of the health state of the people you treat than any other entity looking at you from the outside.
  4. More robust solutions for code searches need to be developed that work based on clinical concepts consistent with the way clinicians think. Currently, clinicians find that when they enter terms into the system that they are used to, the search hits a wall and they can’t find the appropriate code. As a result, many clinicians simply select the least specific code since they can’t find the correct one.

Summary 

  • ICD-10 has finally arrived, resulting in both relief and dread by many within the healthcare industry.
  • The potential advantage of ICD-10 in improving data related to patients’ health conditions is only a potential. There is nothing about ICD-10 that will result in better data, just like there is nothing about more words in a dictionary that will make you a great author. You can be just as vague in ICD-10 as you were in ICD-9.
  • In the changing environment of healthcare that is more focused on the improvement of the patient health condition, the definition of the nature, risk, severity, and complexity of the underlying condition is critical.
  • Organizations should provide incentives for clinicians and others to collect better data at the source: the patient encounter.
  • Data should be shared with clinicians to show them their patterns and comparisons to their peers.
  • Organizations should create a governance structure focused on the quality of data and information to ensure that the organization has better information about the nature of the patients they care for and the outcomes of care they experience.
  • Organizations should have better data about their population than any other entity.
  • The migration to ICD-10 is a journey that has just started. If the goal of improving information about patient healthcare is to be realized, we all have a lot work ahead.

 

Joseph C. Nichols, MD

Dr. Nichols is a board-certified orthopedic surgeon with a long history in health information technology. He has a wide range of experiences in healthcare information technology on the provider, payer, government, and vendor side of the healthcare business. He has served in positions in executive management, system design, logical database architecture, product management, consulting, and healthcare value measurement for the last 15 of his 35 years in the healthcare industry. He has given over 100 presentations nationally related to ICD-10 over the past three years on behalf of payers, providers, integrated delivery systems, consulting groups, CMS, universities, government entities, vendors, and trade associations. He co-chairs the WEDI (Workgroup on Electronic Data Interchange) translation and coding sub-workgroup and has received WEDI merit awards three years in succession. He is also an AHIMA-approved ICD-10 coding trainer. He is currently providing consulting services as the president of Health Data Consulting Inc. Dr. Nichols is a member of the ICD10monitor editorial board.

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