The Dartmouth Institute for Health Policy & Clinical Practice, Lebanon, NH.
Med Care. 2019 Jul;57(7):e42-e46. doi: 10.1097/MLR.0000000000001010.
The October 1, 2015 US health care diagnosis and procedure codes update, from the 9th to 10th version of the International Classification of Diseases (ICD), abruptly changed the structure, number, and diversity of codes in health care administrative data. Translation from ICD-9 to ICD-10 risks introducing artificial changes in claims-based measures of health and health services.
Using published ICD-9 and ICD-10 definitions and translation software, we explored discontinuity in common diagnoses to quantify measurement changes introduced by the upgrade.
Using 100% Medicare inpatient data, 2012-2015, we calculated the quarterly frequency of condition-specific diagnoses on hospital discharge records. Years 2012-2014 provided baseline frequencies and historic, annual fourth-quarter changes. We compared these to fourth quarter of 2015, the first months after ICD-10 adoption, using Centers for Medicare and Medicaid Services Chronic Conditions Data Warehouse (CCW) ICD-9 and ICD-10 definitions and other commonly used definitions sets.
Discontinuities of recorded CCW-defined conditions in fourth quarter of 2015 varied widely. For example, compared with diagnosis appearance in 2014 fourth quarter, in 2015 we saw a sudden 3.2% increase in chronic lung disease and a 1.8% decrease in depression; frequency of acute myocardial infarction was stable. Using published software to translate Charlson-Deyo and Elixhauser conditions yielded discontinuities ranging from -8.9% to +10.9%.
ICD-9 to ICD-10 translations do not always align, producing discontinuity over time. This may compromise ICD-based measurements and risk-adjustment. To address the challenge, we propose a public resource for researchers to share discovered discontinuities introduced by ICD-10 adoption and the solutions they develop.
2015 年 10 月 1 日，美国医疗保健诊断和程序代码更新，从第 9 版国际疾病分类（ICD）到第 10 版，突然改变了医疗保健管理数据中的代码结构、数量和多样性。从 ICD-9 到 ICD-10 的翻译存在风险，会导致基于索赔的健康和卫生服务衡量标准出现人为变化。
使用已发布的 ICD-9 和 ICD-10 定义和翻译软件，我们探索了常见诊断中的不连续性，以量化升级引入的测量变化。
使用 100%的医疗保险住院数据，2012-2015 年，我们计算了出院记录中特定疾病的季度频率。2012-2014 年提供了基础频率和历史年度第四季度变化。我们将这些与 2015 年第四季度进行了比较，即 ICD-10 采用后的第一个月，使用医疗保险和医疗补助服务中心慢性疾病数据仓库（CCW）ICD-9 和 ICD-10 定义和其他常用的定义集。
2015 年第四季度记录的 CCW 定义的疾病的不连续性差异很大。例如，与 2014 年第四季度的诊断出现情况相比，2015 年我们看到慢性肺病突然增加了 3.2%，抑郁症减少了 1.8%；急性心肌梗死的频率保持稳定。使用已发布的软件翻译 Charlson-Deyo 和 Elixhauser 条件会导致不连续性在-8.9%到+10.9%之间变化。
ICD-9 到 ICD-10 的翻译并不总是一致的，随着时间的推移会产生不连续性。这可能会影响基于 ICD 的测量和风险调整。为了解决这一挑战，我们提出了一个公共资源，供研究人员共享由于采用 ICD-10 而引入的不连续性，以及他们开发的解决方案。
