Technical Report 33: Comparing the Measurement of Chronic Conditions in ICD-9-CM and ICD-10-CM in VA Patients, FY2014-FY2016
Suggested CitationYoon J, Chow A. Comparing the Measurement of Chronic Conditions in ICD-9-CM and ICD-10-CM in VA Patients, FY2014-FY2016. Technical Report 33. Health Economics Resource Center, VA Palo Alto Health Care System, U.S. Department of Veterans Affairs. July 2017.
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1. Introduction
On October 1, 2015, U.S. health care providers transitioned from using the 9th version of the International Classification of Diseases (ICD-9-CM) to version 10 (ICD-10-CM). ICD-10-CM uses more than 70,000 codes which is almost a five-fold increase in codes from ICD-9-CM. Measuring diagnoses accurately is critical to both patient and population management, so greater specificity in ICD-10-CM improves upon the ICD-9-CM system. However, this transition creates challenges to measuring chronic conditions over time within a health care system or population of interest. It is unknown how assignment of diagnoses may be affected by the transition to ICD-10-CM due to the adoption of new coding practices. Looking at how chronic condition rates changed before and after the transition to ICD-10-CM can help inform VA providers, clinical program offices, and researchers about measurement issues related to the transition to ICD-10-CM.
In this technical report, we developed ICD-9-CM and ICD-10-CM definitions for 34 different chronic conditions, and we compared the prevalence rates of these chronic conditions from federal fiscal year (FY) 2014 to FY2016 in a large sample of VA patients in order to measure the changes before and after transition to ICD-10-CM. We selected common chronic conditions that accounted for most of VA health care costs.1 We compared the prevalence rate of each condition in FY2014, FY2015 and FY2016. We also estimated how many patients with each condition had the condition diagnosed in the previous year, how many were newly diagnosed with the condition in the current year, and how many who were previously diagnosed with the condition were not diagnosed in the current year.
2. Methods
2.1. Chronic condition codes
We created definitions for 34 common chronic conditions among VA patients for both ICD-9-CM and ICD-10-CM systems. Chronic conditions and corresponding ICD-9-CM diagnoses were identified from previous work of HERC researchers.1,2 To develop ICD-9-CM definitions for the conditions, we identified ICD-10-CM codes assigned by public health resources and VA clinical care programs for conditions when available. When there were no publicly available resources, we identified all relevant ICD-10-CM codes based on mappings of ICD-9-CM codes to ICD-10-CM codes for each condition. We mainly based our list of ICD-10-CM codes on Elixhauser comorbidities, such as hypertension, renal failure, congestive heart failure, diabetes, depression, and peripheral vascular disease from the Agency for Healthcare Research and Quality. We used ICD-10-CM codes for spinal cord injury based on the definition developed by the Centers for Medicare and Medicaid Services. For arthritis, asthma, AIDS/HIV, and stroke we applied the ICD-10-CM codes as defined by the University of Manitoba developed for comorbidity indices such as the Charlson Index and Elixhauser Score.3
Several VA clinical workgroups developed comprehensive ICD-10-CM diagnosis lists for several chronic conditions, and we obtained the ICD-10-CM codes for chronic obstructive pulmonary disease, ischemic heart disease, and lung cancer from the VA Almanac Workgroup. Codes for dementia were obtained from the VHA Dementia Diagnostic Codes Workgroup (Intranet-only: http://vaww.infoshare.va.gov/sites/geriatrics/national/AH/Forms/AllItems.aspx?RootFolder=%2Fsites%2Fgeriatrics%2Fnational%2FAH%2FDEMENTIA%20MATERIALS%2FVHA%20Dementia%20Diagnostic%20Code%20List%20%2D%20CURRENT&FolderCTID=0x01200023199D6EAA75DD4088835A382085B7D2&View={5A8485CC-B221-4537-B876-B37158ED49F5}), and codes for hepatitis C virus were obtained from the VA Liver Disease Cube. ICD-10-CM codes for all mental health and substance use disorder conditions in this report were primarily based on the VA risk-adjustment system called Nosos.4
To obtain corresponding ICD-10-CM codes for the remaining conditions, we crosswalked the original ICD-9-CM codes for each condition to ICD-10-CM codes using general equivalency mapping (GEM), publicly available from the Centers for Disease Control and Prevention and CMS. We supplemented codes obtained from exact mappings by considering additional ICD-10-CM codes obtained by matching the first three bytes of the ICD-10-CM to the original ICD-9-CM codes. We also considered codes obtained from the Lussier Group’s “Transition to ICD-10-CM” tool. These maps were then reviewed by several clinicians. Table 1 contains a final list of ICD-10-CM codes for each of the conditions in this report.
2.2. Analysis
Once we developed a list of diagnosis codes for each condition, we identified a 20% sample of all VA patients for a total of 1.0 million VA patients who used any VA inpatient or outpatient care in each year from FY2014-FY2016 and did not die during that time. We coded all their chronic conditions based on the presence of at least one diagnosis in each year from all VA inpatient and outpatient utilization records from the VA Medical SAS files. For FY2014 we summarized the percent of patients who were identified with each condition using ICD-9-CM codes. For FY2015 we summarized the percent of patients who were identified with each condition, including (1) patients that had the condition recorded in FY2014 and (2) patients that did not have the condition recorded in FY2015. For FY2016 we summarized the percent of patients who were identified with each condition using ICD-10-CM codes, including (1) patients that had the condition recorded in FY2015 as identified by ICD-9-CM codes, (2) patients that did not have the condition using ICD-9-CM codes, and (3) patients that had a diagnosis in FY2015 but not in FY2016.
3. Results
Overall, condition prevalence estimates were similar before and after the transition to ICD-10-CM for most of the conditions we examined, although there were some differences across conditions (Table 2). We did not find any consistent decrease or increase in the prevalence rates after the transition. Some notable differences in total condition prevalence from FY2015 to FY2016 were: an increase in Alzheimer’s disease from 0.4% in to 0.6%, an increase in heart failure from 4.6% to 5.2%, an increase in spinal cord injury from 0.4% to 0.5% and a decrease in arthritis from 20.0% to 14.8%. There were also large changes in several mental health and substance use conditions from FY2015 to FY2016, including: a decrease in alcohol dependence from 4.0% to 3.0%, a decrease in drug dependence from 4.7% to 3.6%, and a decrease in depression from 21.6% to 16.9%. All of the changes noted were associated with a greater than 20% change in the overall rate between FY2015 and FY2016.
For stroke and alcohol dependence there was a large decrease in FY2016 in the number of patients who had the diagnosis in the current year and were also diagnosed in the previous year. There was also a large increase in patients who were not diagnosed with these conditions in the current year but were in the year prior, compared to the same statistics from the previous year. For depression in FY2016, there was a large increase in the percent of patients who did not have a diagnosis in the current year although they did have a depression diagnosis in the previous year, and this pattern deviated from the year before.
We were unable to determine the reasons for changes in prevalence rates over time although the transition to ICD-10-CM may account for some of these differences. It is unknown why there were large decreases in rates of some mental health and substance use disorder conditions after ICD-10-CM, but it raises questions about potential undercoding of these conditions that should be looked into greater detail in the future. For all of the conditions, some year-to-year variation may be due to treatment patterns such as patients not having the condition treated during that year or not being recorded in utilization data. A portion of patients who are newly diagnosed in each year may not have developed the condition until the current year, or else the condition was not previously recorded.
Since we did not find any consistent decrease in chronic condition prevalence in FY2016, there does not appear to be widespread undercoding of diagnosis codes after the transition to ICD-10-CM. While prevalence of common chronic conditions was generally stable over time, there may be difference in how individual patients were identified with conditions such as mental health and substance use and several other conditions under ICD-10-CM, so analysts should take these differences into account in the measurement of chronic conditions in patient populations over time.
4. References
1. Yu W, Ravelo A, Wagner TH, et al. Prevalence and costs of chronic conditions in the VA health care system. Med Care Res Rev 2003;60:14S-67S.
2. Yoon J, Scott JY, Phibbs CS, Wagner TH. Recent Trends in Veterans Affairs Chronic Condition Spending. Popul Health Manag 2011;14:293-8.
3. Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005;43:1130-9.
4. Wagner T, Stefos T, Moran E, et al. Risk Adjustment: Guide to the V21 and Nosos Risk Score Programs. Technical Report 30. Menlo Park, CA. VA Palo Alto, Health Economics Resource Center; February 2016.
AcknowledgementsWe wish to thank the following individuals for reviewing diagnosis codes to develop definitions for the chronic conditions listed in the report: Evelyn T. Chang, Donna M. Zulman, Manjula K. Tamura, John Leppert, Stephens Burns, and Todd H. Wagner. Denise Hynes, Elizabeth Gehlert, Charlesnika Evans, and Adam J. Batten also provided valuable assistance.
Last Updated Date: 2017-07-14
