验证一种用于严重阿片类药物过量的行政索赔编码算法：病历回顾。
Validation of an administrative claims coding algorithm for serious opioid overdose: A medical chart review.
机构信息
Venebio Group, LLC, Richmond, Virginia.
Indegene, Inc, Kennesaw, Georgia.
出版信息
Pharmacoepidemiol Drug Saf. 2019 Oct;28(10):1422-1428. doi: 10.1002/pds.4886. Epub 2019 Sep 4.
PURPOSE
A standardized definition for serious opioid overdose has not been clearly established for disease surveillance or assessing the impact of risk mitigation strategies. The purpose of this study was to use medical chart review to clinically validate a claims-based algorithm to identify serious opioid overdose events.
METHODS
The algorithm for serious opioid overdose required an opioid poisoning or external cause ICD-9-CM code occurring within 1 day of (a) an adverse effect code for serious central nervous system or respiratory depression or (b) a mechanical ventilation or critical care CPT code. The claims coding algorithm identified a sample of 145 individuals 18 years or older among patients that presented to the emergency department of two large hospitals in metropolitan Atlanta, Georgia from January 2014 to August 2015. Claims-defined cases were evaluated against rigorous clinical definitions for serious opioid overdose using (a) literature-based criteria for typical clinical manifestations of opioid overdose and/or (b) clinical response to the opioid-specific reversal agent naloxone. The positive predictive value (PPV) for a serious opioid overdose was calculated as the percentage of clinically confirmed cases (definite or probable).
RESULTS
Among 140 evaluable claims-defined cases, 107 fulfilled clinical criteria for a serious opioid overdose [95 definite and 12 probable; PPV of 76.4% (95% CI 69.4%, 83.5%)]. Among 30 nonconfirmed cases, 20 were polyintoxications involving one or more nonopioid psychoactive agents.
CONCLUSIONS
An administrative claims coding algorithm for serious opioid overdose had high clinical predictive performance in a medical chart review.
目的
由于缺乏用于疾病监测或评估风险缓解策略影响的明确严重阿片类药物过量定义，因此本研究旨在使用医疗记录审查对基于索赔的算法进行临床验证，以识别严重阿片类药物过量事件。
方法
严重阿片类药物过量的算法要求阿片类中毒或外部原因 ICD-9-CM 代码在（a）严重中枢神经系统或呼吸抑制的不良反应代码或（b）机械通气或重症监护 CPT 代码发生的 1 天内出现。索赔编码算法从佐治亚州亚特兰大市两家大医院的急诊部门 2014 年 1 月至 2015 年 8 月就诊的 18 岁及以上患者中确定了 145 名患者。使用（a）阿片类药物过量的典型临床表现的文献标准或（b）阿片类特异性逆转剂纳洛酮的临床反应，根据严格的临床严重阿片类药物过量定义对索赔定义的病例进行评估。严重阿片类药物过量的阳性预测值（PPV）计算为经临床确认的病例（确定或可能）的百分比。
结果
在 140 例可评估的索赔定义病例中，有 107 例符合严重阿片类药物过量的临床标准[95 例为确定，12 例为可能；PPV 为 76.4％（95％CI 69.4％，83.5％）]。在 30 例未确认的病例中，有 20 例为涉及一种或多种非阿片类精神活性药物的多毒物中毒。
结论
在医疗记录审查中，用于严重阿片类药物过量的行政索赔编码算法具有较高的临床预测性能。
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