Peoples Nicholas, Jones Jennifer L, Camp Elizabeth A, Levine Ned Norman, Shenoi Rohit P
Baylor College of Medicine, Houston, Texas, USA.
Ned Levine and Associates, Houston, Texas, USA.
Inj Prev. 2025 Mar 20;31(2):151-157. doi: 10.1136/ip-2024-045301.
Syndromic surveillance, which provides real-time data, may provide timely drowning surveillance compared with hospital discharge data where the release of data may be delayed. We compared data on hospital visits for unintentional drowning identified in hospital discharge and syndromic surveillance data sets for accuracy and completeness.
We compared data for hospital visits for unintentional drowning identified in the Texas Health Care Information Collection hospital discharge and syndromic surveillance data sets for metropolitan Houston, Texas, USA from 2019 to 2021. Hospital visits included emergency department-only visits and hospital admissions. We compared time-series visualisation of hospital visits between data sets. Injury burden, demographics and intercounty distribution of drowning patients were compared using the Pearson correlation coefficient for continuous data and the Pearson χ goodness-of-fit test for categorical data.
We identified 860 hospital discharge visits and 929 syndromic surveillance visits (quarterly median (IQR): 64.0 (26.8-117.5); 54.5 (28.0-132.3), respectively) for unintentional drowning. Time-series visualisation showed a high correlation between syndromic surveillance and hospital discharge visits (correlation coefficient: 0.93 (95% CI: 0.77 to 0.98)). There were small differences by race, ethnicity and county for all ages and for paediatrics and large differences by sex for all ages in the number of unintentional drowning hospital visits identified within the data sets.
Regional unintentional drowning burden and trends are highly correlated between syndromic surveillance and hospital discharge data. Small differences by race, ethnicity and county and large differences by sex in the number of unintentional drowning hospital visits were identified between data sets. Syndromic surveillance is useful for real-time surveillance of unintentional drowning.
症状监测可提供实时数据，与可能存在数据发布延迟的医院出院数据相比，或许能实现溺水情况的及时监测。我们比较了医院出院数据和症状监测数据集中识别出的非故意伤害性溺水的就诊数据，以评估其准确性和完整性。
我们比较了2019年至2021年美国得克萨斯州休斯敦市大都会区得克萨斯医疗信息收集医院出院数据集和症状监测数据集中识别出的非故意伤害性溺水的就诊数据。就诊包括仅在急诊科就诊和住院治疗。我们比较了数据集之间就诊情况的时间序列可视化结果。对于连续数据，使用Pearson相关系数比较溺水患者的伤害负担、人口统计学特征和跨县分布情况；对于分类数据，使用Pearson拟合优度检验进行比较。
我们识别出860例医院出院就诊病例和929例症状监测就诊病例（季度中位数（四分位间距）：分别为64.0（26.8 - 117.5）；54.5（28.0 - 132.3））为非故意伤害性溺水。时间序列可视化显示症状监测与医院出院就诊之间具有高度相关性（相关系数：0.93（95%置信区间：0.77至0.98））。在各年龄段、儿科中，按种族、民族和县区划分存在细微差异，而在各年龄段中，按性别划分在数据集中识别出的非故意伤害性溺水医院就诊数量存在较大差异。
症状监测与医院出院数据之间，区域非故意伤害性溺水负担和趋势高度相关。在数据集之间，按种族、民族和县区划分存在细微差异，按性别划分在非故意伤害性溺水医院就诊数量上存在较大差异。症状监测对于非故意伤害性溺水的实时监测很有用。
