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首页> 外文期刊>Online Journal of Public Health Informatics >Finding Chances to Intervene Before the Fatal Overdose: Linking ED and Mortality Data
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Finding Chances to Intervene Before the Fatal Overdose: Linking ED and Mortality Data

机译:在致命用药过量之前找到干预的机会:将ED和死亡率数据联系起来

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Objective Link emergency department (ED) with death certificate mortality data in order to examine the prior medical history of opioid overdose victims leading up to their death. Introduction In 2017, 951 Missouri residents died from an opioid overdose—a record number for the state. 1 This continues the trend from 2016, which saw an increase of over 30% in opioid overdose deaths compared to 2015. The Missouri Department of Health and Senior Services (MDHSS) manages several public health surveillance data sources that can be used to inform about the opioid epidemic. Opioid overdose deaths are identified through death certificates which are collected through the vital records system. MDHSS also manages the Patient Abstract System (PAS), which contains ED and inpatient hospitalization data from approximately 132 non-federal Missouri hospitals. PAS contains about 130 variables, which include demographic data, diagnoses codes, procedures codes, and other visit information. Records can have up to 23 diagnosis fields, which are coded using ICD-10-CM (International Classification of Diseases, Clinically Modified). The first diagnosis field is the primary reason for a visit. Methods Linkage and analysis of the data was performed using SAS Enterprise Guide 6.1. Opioid overdose deaths were identified through ICD-10 analysis looking for drug poisoning underlying cause of death codes and opioid-specific codes found in the multiple cause (contributing cause) of death fields. Table 1, below, summarizes the ICD-10 codes used. Mortality data from the 951 decedents were linked to ED data from 2016 and 2017. Records were linked using multiple passes over the ED records. Records were first linked on social security number. Following this linkage, ED records with no initial match went through a second pass and linked on name and date of birth. Finally, a third pass for records still without a match was conducted using date of birth, census tract, and sex. After these passes, the linkages were reviewed to identify any false positives. The 23 diagnosis fields contained in PAS were analyzed to look for patterns in diagnosis coding. ICD-10-CM codes were too broad so CCS (Clinical Classifications Software) categories were utilized. Results In total, 3,500 ED records were linked to the 951 decedents. After removing false positives, the total number of ED records was 3,357. Approximately 70% (687) of decedents were linked to at least one ED record. One hundred and eighty-eight visits were due to drug overdose (153 opioid overdoses). The most common primary diagnosis CCS categories (category numbers in parentheses) were: substance-related disorders (661), Spondylosis; intervertebral disc disorders; other back problems (205), abdominal pain (251), and other nervous system disorders (95). Collectively, these four categories represented over 20% of all primary diagnoses. Across all 23 diagnosis fields there were similar results. The most common CCS categories were as follows: substance-related disorders (661), other aftercare (257), essential hypertension (98), and mood disorders (657). Pie charts (Fig. 1 and 2) below show proportions of CCS categories across all diagnoses fields and primary diagnosis broken into three major categories: pain/injury, substance abuse/mental health, and other. In order to reduce the impact of CCS categories with small numbers, these graphics represent only CCS categories that made up 1% or more of the total collection of diagnoses codes. Of the 687 decedents that were matched successfully to ED records, 96% had at least one pain/injury or one substance abuse/mental health ICD-CM code in at least one record, and 68% had both. Conclusions These findings suggest that many overdose decedents visited the ED in the years prior to death. Many of these visits were not due to an overdose; however, they could be indicative of a problem with opioids (i.e. pain, drug-seeking, substance use-related). ED staff and public health professionals could utilize these opportunities to refer patients to recovery services and recommend they heed caution when using opioids.
机译:目的将急诊室(ED)与死亡证明书的死亡率数据联系起来,以检查导致死亡的阿片类药物过量受害者的先前病史。引言2017年,有951名密苏里州居民因服用阿片类药物过量而死亡,这是该州创纪录的数字。 1这延续了2016年的趋势,与2015年相比,阿片类药物过量死亡人数增加了30%以上。密苏里州卫生和高级服务部(MDHSS)管理着多个公共卫生监测数据源,这些数据可用于告知鸦片类药物泛滥。阿片类药物过量死亡通过死亡记录确定,死亡记录通过生命记录系统收集。 MDHSS还管理患者摘要系统(PAS),其中包含来自大约132家密苏里州非联邦医院的ED和住院患者数据。 PAS包含约130个变量,其中包括人口统计数据,诊断代码,程序代码和其他访问信息。记录最多可包含23个诊断字段,这些字段使用ICD-10-CM(国际疾病分类,临床修改)编码。第一个诊断字段是访问的主要原因。方法使用SAS企业指南6.1进行数据的链接和分析。通过ICD-10分析确定阿片类药物过量死亡,寻找引起死亡原因代码的药物中毒以及在死亡领域的多种原因(促成原因)中发现的阿片类药物特异代码。下表1总结了所用的ICD-10代码。来自951名死者的死亡率数据与2016年和2017年的ED数据相关联。使用ED记录上的多次传递将记录链接在一起。记录首先与社会保险号关联。进行这种链接后,没有初始匹配的ED记录又经过了第二遍,并在名称和出生日期上进行了链接。最后,使用出生日期,人口普查区域和性别进行了第三次仍无匹配记录的通行证。这些通过之后,将检查链接以识别任何误报。分析了PAS中包含的23个诊断字段,以寻找诊断编码中的模式。 ICD-10-CM代码过于宽泛,因此使用了CCS(临床分类软件)类别。结果共有3500条ED记录与951名死者相关。除去误报后,ED记录的总数为3,357。大约70%(687)的死者与至少一项ED记录有关。 188次拜访是由于药物过量(153阿片类药物过量)所致。 CCS最常见的主要诊断类别(括号中的类别编号)是:与物质有关的疾病(661),脊椎病;椎间盘疾病;其他背部问题(205),腹痛(251)和其他神经系统疾病(95)。总的来说,这四个类别占所有主要诊断的20%以上。在所有23个诊断领域中,结果相似。最常见的CCS类别如下:与物质有关的疾病(661),其他后期护理(257),原发性高血压(98)和情绪障碍(657)。下面的饼图(图1和2)显示了在所有诊断领域中CCS类别的比例,主要诊断分为三个主要类别:疼痛/伤害,药物滥用/心理健康和其他。为了减少带有少量数字的CCS类别的影响,这些图形仅代表占诊断代码总数的1%或更多的CCS类别。在成功符合ED记录的687名死者中,至少有一项记录中有96%的人至少有一种疼痛/伤害或一种药物滥用/心理健康的ICD-CM密码,而68%的人都有两种。结论这些发现表明,在死亡前的几年中,有许多过量的后遗症患者去过ED。这些访问中的许多并不是由于服药过量引起的。但是,它们可能表示阿片类药物存在问题(即疼痛,寻求药物,与药物使用相关)。急诊人员和公共卫生专业人员可以利用这些机会为患者提供康复服务,并建议他们在使用阿片类药物时要格外小心。

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