206-478-8227 www.healthdataconsulting.com. Getting Specific. New ICD-10 codes. Will they make a difference?

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206-478-8227 www.healthdataconsulting.com Getting Specific New ICD-10 codes. Will they make a difference? [First in a series on getting to specific documentation and coding] Joseph C Nichols MD Principal A Health Data Consulting White Paper Feb 5, 2016

TABLE OF CONTENTS OPPORTUNITY VS REALIZATION... 3 HISTORICAL CODE USAGE... 4 THE CHALLENGE TO SPECIFICITY... 5 FINDING A PATH TO IMPROVING DOCUMENTATION AND CODING... 5 SUMMARY... 6 2016

Opportunity vs Realization A recent online special edition of ICD-10 Monitor reviewed the latest NCVHS ICD-10 steering committee meeting 1 about proposed additions, and changes to the current ICD-10-CM code set. There was considerable discussion about the ability of these new codes to provide much needed detail about certain conditions. These details provide the opportunity to clarify the nature of the condition and identify potential differences in risk, severity and complexity for different patients with similar types of conditions. A few of the areas addressed included: Standard categorization for reporting the level of blindness and low vision Detailed anatomical localization of breast lumps Classification of myocardial infarctions by type Additional clarification of the severity of non-pressure ulcers Addition of a specific code for the Zika virus The above were just a few of the new codes and changes reviewed. These and many other ICD-10 codes provide the opportunity for a much richer data environment to understand the key parameters of the patient condition that make dramatic differences in assessment of: Risk Severity Cost Injury causes and patterns Patient safety Disease trends Quality and outcomes Policy impacts and any other use of population data Opportunity does not however imply implementation. The advantage of this increased level of detail is not realized if we don t see this detail reflected in clinical documentation and the codes that capture these important clinical concepts. Unfortunately, our track record for capturing and coding key clinical concepts is not good. Unlike many other industries that put a premium on the quality, completeness and accuracy of transactional data, healthcare has often considered this data merely an administrative burden required to get paid. 1 ICD-10 Coordination and Maintenance Committee Meeting, March 9-10, 2016 Diagnosis agenda 2016 Page 3

2016 Historical code usage In a recent article about the ICD-10 transition, the issue of leveraging ICD-10 rather than simply mirroring ICD-9 was introduced 2. This discussion noted the fact that unless there was a significant change from old data capture habits, the additional opportunity for better data would never be realized. The ability to capture detail about the anatomical location or severity of the patient condition is meaningless if the data isn t documented and coded. Health Data Consulting has done an analysis of 3 years of payer data across all lines of business. Based on this data 5% of all ICD-9 codes were used for nearly 75% of all claim charges. Codes that would be considered unspecified, other or symptom and findings codes were used as the primary code for 54% of all outpatient (professional) claims. While there has been significant improvement in the ability of ICD-10 codes to capture more specific information about breast cancer for example, historically we have coded breast neoplasms as unspecified type or unspecified site over 80% of the time. More detailed codes have always been available, but they are rarely used. There is little reason to believe that without some change in documentation and coding habits, that data will be any better in ICD-10. So what s going wrong? 2 http://www.icd10monitor.com/enews/item/1585-data-is-what-you-make-it

2016 The challenge to specificity There are a number of factors that play into this less than optimal use of diagnostic codes. Clinicians believe that these codes are simply for payment purposes and have no other value. Most clinicians don t see any incentive to code more specifically. In some instances, there is a disincentive because vague codes may actually be more likely to pass edits than detailed codes. Transactional data goes into a black box from the provider perspective since very few providers have a robust ability to analyze their own claim data and compare their coding patterns for the same conditions to their colleagues. There is often a lack of clinical consistency in the application of key parameters across similar clinical domains within the ICD-10 code set. Some code search tools in EHRs and billing systems change descriptions so they don t represent what the code really means to the clinician entering the code. The use of code description terminology may not be consistent with terminology familiar to the clinician. Combination codes are used with widely varying levels of granularity so the clinician may be uncertain about the number of codes to use to represent various aspects of the patient condition. Coding tools frequently search for terms or words rather than medical concepts. When searching for key terms, the clinician may run into a wall and settle for a non-specific code. The changes occurring in a data driven, value-based purchasing environment are creating new incentives for providers to take the accuracy of data more seriously. If we assume however that there are strong incentives in place for more detailed data there is still the challenge of finding the right code in the nearly 70,000 codes currently in play. Finding a path to improving documentation and coding There are a number of considerations for improving the ability for the right documentation and the right code to connect in a clinically meaningful way. 1. Since the structure and terminology of codes varies greatly across different clinical domains, a specialty focused approach is critical. 2. Clinicians should be educated in:

2016 a. The variation in use of codes that combine a number of parameters into a single code (combination codes) b. Where terminology may be inconsistent with common use, or even inconsistent within the ICD-10 language. c. How to drill down on code sets without hitting a blank wall d. What additional parameters are available and need to be documented to further define a condition e. What s missing in certain clinical areas from the current code set 3. Concept based tools to assist the clinician in finding the right codes based on an ontology of clinical concepts are evolving. These tools build clinical knowledge into the code mapping so they are intelligent enough to include codes like Colle s fracture and Smith s fracture into the results of a code search that s looking for codes related to extra-articular fractures of the distal radius. 4. Clinicians should have access to meaningful analysis of their claim coding patterns and how their patterns compare to some expected benchmark. 5. A thorough analysis of the work flow of clinical data capture and system input should be done to identify process improvement opportunities. 6. Clinician incentives should be created to reward accurate, complete and specific definition of the patient health conditions they are managing. Summary A robust set of codes that define the key parameters of the patient health state provides the opportunity for valuable information to improve the health of the population and improve outcomes of care. This opportunity will not be realized however if these codes are not used. The critical path to data specificity does not lie in the number of codes, but rather in the consistent and appropriate use of those codes by providers as part of the delivery and documentation of the care they provide. A vision for understanding current incentives and challenges for provider documentation and coding must be a primary focus. Based on this understanding there must be a commitment to actively and openly identify opportunities for improvement that do not increase the administrative burden on the clinician. There must also be a commitment to act on those opportunities. As I have gone around the country, I repeatedly hear great ideas for improving both care delivery and data capture processes from many sources within the same organization. I also repeatedly hear from both the clinical and administrative side the frustration that no one is listening.

In subsequent papers in this series we will focus on some of the specialty specific challenges and potential solutions toward heading down the path to better data through better documentation and coding. 2016