White Jessica R, Berisha Vjollca, Lane Kathryn, Ménager Henri, Gettel Aaron, Braun Carol R
1 Office of Epidemiology, Maricopa County Department of Public Health, Phoenix, AZ, USA.
2 Bureau of Environmental Surveillance and Policy, New York City Department of Health and Mental Hygiene, Long Island City, NY, USA.
Public Health Rep. 2017 Jul/Aug;132(1_suppl):31S-39S. doi: 10.1177/0033354917706517.
We evaluated a novel syndromic surveillance query, developed by the Council of State and Territorial Epidemiologists (CSTE) Heat Syndrome Workgroup, for identifying heat-related illness cases in near real time, using emergency department and inpatient hospital data from Maricopa County, Arizona, in 2015.
The Maricopa County Department of Public Health applied 2 queries for heat-related illness to area hospital data transmitted to the National Syndromic Surveillance Program BioSense Platform: the BioSense "heat, excessive" query and the novel CSTE query. We reviewed the line lists generated by each query and used the diagnosis code and chief complaint text fields to find probable cases of heat-related illness. For each query, we calculated positive predictive values (PPVs) for heat-related illness.
The CSTE query identified 674 records, of which 591 were categorized as probable heat-related illness, demonstrating a PPV of 88% for heat-related illness. The BioSense query identified 791 patient records, of which 589 were probable heat-related illness, demonstrating a PPV of 74% for heat-related illness. The PPV was substantially higher for the CSTE novel and BioSense queries during the heat season (May 1 to September 30; 92% and 85%, respectively) than during the cooler seasons (55% and 29%, respectively).
A novel query for heat-related illness that combined diagnosis codes, chief complaint text terms, and exclusion criteria had a high PPV for heat-related illness, particularly during the heat season. Public health departments can use this query to meet local needs; however, use of this novel query to substantially improve public health heat-related illness prevention remains to be seen.
我们评估了由州和领地流行病学家理事会（CSTE）热综合征工作组开发的一种新型综合征监测查询方法，该方法利用2015年亚利桑那州马里科帕县急诊科和住院医院的数据，近乎实时地识别与热相关的疾病病例。
马里科帕县公共卫生部将2种与热相关疾病的查询方法应用于传输至国家综合征监测计划生物传感平台的地区医院数据：生物传感“热，过度”查询方法和新型CSTE查询方法。我们审查了每个查询方法生成的病例清单，并使用诊断代码和主诉文本字段来查找可能的热相关疾病病例。对于每个查询方法，我们计算了热相关疾病的阳性预测值（PPV）。
CSTE查询方法识别出674条记录，其中591条被归类为可能的热相关疾病，热相关疾病的PPV为88%。生物传感查询方法识别出791条患者记录，其中589条为可能的热相关疾病，热相关疾病的PPV为74%。在炎热季节（5月1日至9月30日；PPV分别为92%和85%），CSTE新型查询方法和生物传感查询方法的PPV显著高于凉爽季节（分别为55%和29%）。
一种结合诊断代码、主诉文本术语和排除标准的新型热相关疾病查询方法对热相关疾病具有较高的PPV，尤其是在炎热季节。公共卫生部门可以使用此查询方法来满足当地需求；然而，使用这种新型查询方法能否大幅改善公共卫生领域对热相关疾病的预防还有待观察。
