Validation of an ICD-Code-Based Case Definition for Psychotic Illness Across Three Health Systems,Schizophrenia Bulletin

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Validation of an ICD-Code-Based Case Definition for Psychotic Illness Across Three Health Systems
Schizophrenia Bulletin ( IF 5.3 ) Pub Date : 2024-05-10 , DOI: 10.1093/schbul/sbae064
Anthony J Deo _{1,

2,

3,

4} , Victor M Castro ₅ , Ashley Baker ₆ , Devon Carroll _{1,

7} , Joseph Gonzalez-Heydrich _{1,

2,

8,

9} , David C Henderson _{10,

11} , Daphne J Holt _{2,

12} , Kimberly Hook ₁₃ , Rakesh Karmacharya _{2,

14,

15,

16} , Joshua L Roffman _{2,

12} , Emily M Madsen _{17,

18} , Eugene Song ₁₇ , William G Adams ₁₀ , Luisa Camacho ₁₀ , Sarah Gasman ₁₀ , Jada S Gibbs ₁₉ , Rebecca G Fortgang _{18,

20} , Chris J Kennedy _{2,

18} , Galina Lozinski ₁₀ , Daisy C Perez _{10,

11} , Marina Wilson _{17,

18} , Ben Y Reis _{21,

22} , Jordan W Smoller _{2,

17,

18,

23}

Affiliation

Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, NJ, USA.
Psychiatric Evaluation of Adolescent and Child Experiences (P.E.A.C.E.) Program, Rutgers University Behavioral Health Care, Piscataway, NJ, USA.
Research Information Science and Computing, Mass General Brigham, Somerville, MA, USA.
Ascend Integrative Medicine LLC, MA, USA.
College of Nursing, University of Rhode Island, Providence, RI, USA.
Tommy Fuss Center for Neuropsychiatric Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
Early Psychosis Investigation Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
Boston Medical Center, Boston, MA, USA.
Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
Department of Psychiatry, Massachusetts General Hospital, Boston MA, USA.
Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
Chemical Biology and Therapeutic Science Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Schizophrenia and Bipolar Disorder Program, McLean Hospital, Belmont, MA, USA.
Psychiatric & Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
Rutgers New Jersey Medical School, Newark, NJ, USA.
Department of Psychology, Harvard University, Cambridge, MA, USA.
Predictive Medicine Group, Harvard Medical School, Boston, MA, USA.
Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA.
Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA.

Background and Hypothesis Psychosis-associated diagnostic codes are increasingly being utilized as case definitions for electronic health record (EHR)-based algorithms to predict and detect psychosis. However, data on the validity of psychosis-related diagnostic codes is limited. We evaluated the positive predictive value (PPV) of International Classification of Diseases (ICD) codes for psychosis. Study Design Using EHRs at 3 health systems, ICD codes comprising primary psychotic disorders and mood disorders with psychosis were grouped into 5 higher-order groups. 1133 records were sampled for chart review using the full EHR. PPVs (the probability of chart-confirmed psychosis given ICD psychosis codes) were calculated across multiple treatment settings. Study Results PPVs across all diagnostic groups and hospital systems exceeded 70%: Mass General Brigham 0.72 [95% CI 0.68–0.77], Boston Children’s Hospital 0.80 [0.75–0.84], and Boston Medical Center 0.83 [0.79–0.86]. Schizoaffective disorder PPVs were consistently the highest across sites (0.80–0.92) and major depressive disorder with psychosis were the most variable (0.57–0.79). To determine if the first documented code captured first-episode psychosis (FEP), we excluded cases with prior chart evidence of a diagnosis of or treatment for a psychotic illness, yielding substantially lower PPVs (0.08–0.62). Conclusions We found that the first documented psychosis diagnostic code accurately captured true episodes of psychosis but was a poor index of FEP. These data have important implications for the case definitions used in the development of risk prediction models designed to predict or detect undiagnosed psychosis.

中文翻译：

在三个卫生系统中验证基于 ICD 代码的精神病病例定义

背景和假设与精神病相关的诊断代码越来越多地被用作基于电子健康记录（EHR）的算法的病例定义，以预测和检测精神病。然而，关于精神病相关诊断代码有效性的数据是有限的。我们评估了国际疾病分类（ICD）代码对精神病的阳性预测值（PPV）。研究设计使用 3 个卫生系统的 EHR，包括原发性精神病障碍和伴有精神病的情绪障碍的 ICD 代码被分为 5 个高阶组。使用完整的 EHR 对 1133 条记录进行抽样以进行图表审查。计算多种治疗环境中的 PPV（给定 ICD 精神病代码的图表确认精神病的概率）。研究结果所有诊断组和医院系统的 PPV 超过 70%：麻省总医院布莱根 0.72 [95% CI 0.68-0.77]，波士顿儿童医院 0.80 [0.75-0.84]，波士顿医疗中心 0.83 [0.79-0.86]。分裂情感性障碍 PPV 在各个地点始终最高（0.80-0.92），而伴有精神病的重度抑郁症的可变性最大（0.57-0.79）。为了确定第一个记录的代码是否捕获了首次发作的精神病（FEP），我们排除了具有精神病诊断或治疗的先前图表证据的病例，从而产生显着降低的 PPV （0.08-0.62）。结论我们发现第一个记录的精神病诊断代码准确地捕捉了精神病的真实发作，但 FEP 指数较差。这些数据对于开发旨在预测或检测未确诊精神病的风险预测模型时使用的病例定义具有重要意义。

更新日期：2024-05-10

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