Background: Trend analyses of opioid-related inpatient stays depend on the availability of comparable data over time. In October 2015, the US transitioned diagnosis coding from International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) to ICD-10-CM, increasing from ∼14,000 to 68,000 codes. This study examines how trend analyses of inpatient stays involving opioid diagnoses were affected by the transition to ICD-10-CM.
Subjects: Data are from Healthcare Cost and Utilization Project State Inpatient Databases for 14 states in 2015−2016, representing 26% of acute care inpatient discharges in the US.
Study Design: We examined changes in the number of opioid-related stays before, during, and after the transition to ICD-10-CM using quarterly ICD-9-CM data from 2015 and quarterly ICD-10-CM data from the fourth quarter of 2015 and the first 3 quarters of 2016.
Results: Overall, stays involving any opioid-related diagnosis increased by 14.1% during the ICD transition—which was preceded by a much lower 5.0% average quarterly increase before the transition and followed by a 3.5% average increase after the transition. In stratified analysis, stays involving adverse effects of opioids in therapeutic use showed the largest increase (63.2%) during the transition, whereas stays involving abuse and poisoning diagnoses decreased by 21.1% and 12.4%, respectively.
Conclusions: The sharp increase in opioid-related stays overall during the transition to ICD-10-CM may indicate that the new classification system is capturing stays that were missed by ICD-9-CM data. Estimates of stays involving other diagnoses may also be affected, and analysts should assess potential discontinuities in trends across the ICD transition.
*Center for Delivery, Organization, and Markets, Agency for Healthcare Research and Quality, Rockville, MD
†ML Barrett Inc., Del Mar, CA
‡IBM Watson Health, Ann Arbor, MI
Support for this study was provided by the Agency for Healthcare Research and Quality (AHRQ) Center for Delivery, Organization, and Markets, Healthcare Cost and Utilization Project (HCUP).
The views expressed herein are those of the authors and do not necessarily reflect those of AHRQ or the US Department of Health and Human Services.
Reprints: Kevin C. Heslin, PhD, Agency for Healthcare Research and Quality, 5600 Fishers Lane, Rockville, MD 20857. E-mail: email@example.com.
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The authors declare no conflict of interest.
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