Kaiser Permanente Division of Research, Oakland, California, USA
The Permanente Medical Group Inc, Oakland, California, USA.
BMJ Open. 2021 Jul 26;11(7):e048211. doi: 10.1136/bmjopen-2020-048211.
To examine the value of health systems data as indicators of emerging COVID-19 activity.
Observational study of health system indicators for the COVID Hotspotting Score (CHOTS) with prospective validation.
An integrated healthcare delivery system in Northern California including 21 hospitals and 4.5 million members.
The CHOTS incorporated 10 variables including four major (cough/cold calls, emails, new positive COVID-19 tests, COVID-19 hospital census) and six minor (COVID-19 calls, respiratory infection and COVID-19 routine and urgent visits, and respiratory viral testing) indicators assessed with change point detection and slope metrics. We quantified cross-correlations lagged by 7-42 days between CHOTS and standardised COVID-19 hospital census using observational data from 1 April to 31 May 2020 and two waves of prospective data through 21 March 2021.
Through 30 September 2020, peak cross-correlation between CHOTS and COVID-19 hospital census occurred with a 28-day lag at 0.78; at 42 days, the correlation was 0.69. Lagged correlation between medical centre CHOTS and their COVID-19 census was highest at 42 days for one facility (0.63), at 35 days for nine facilities (0.52-0.73), at 28 days for eight facilities (0.28-0.74) and at 14 days for two facilities (0.73-0.78). The strongest correlation for individual indicators was 0.94 (COVID-19 census) and 0.90 (new positive COVID-19 tests) lagged 1-14 days and 0.83 for COVID-19 calls and urgent clinic visits lagged 14-28 days. Cross-correlation was similar (0.73) with a 35-day lag using prospective validation from 1 October 2020 to 21 March 2021.
Passively collected health system indicators were strongly correlated with forthcoming COVID-19 hospital census up to 6 weeks before three successive COVID-19 waves. These tools could inform communities, health systems and public health officials to identify, prepare for and mitigate emerging COVID-19 activity.
研究卫生系统数据作为新冠病毒活动新指标的价值。
对新冠热点评分(CHOTS)的卫生系统指标进行前瞻性验证的观察性研究。
北加州一个综合性医疗服务系统,包括 21 家医院和 450 万成员。
CHOTS 纳入了 10 个变量,包括四个主要指标(咳嗽/感冒电话、电子邮件、新的阳性新冠病毒检测、新冠病毒医院普查)和六个次要指标(新冠病毒电话、呼吸道感染和新冠病毒常规和紧急就诊、呼吸道病毒检测),采用变化点检测和斜率指标进行评估。我们通过 2020 年 4 月 1 日至 5 月 31 日的观察性数据和 2021 年 3 月 21 日之前的两个波前瞻性数据,量化了 CHOTS 与标准化新冠病毒医院普查之间滞后 7-42 天的交叉相关性。
截至 2020 年 9 月 30 日,CHOTS 与新冠病毒医院普查之间的峰值交叉相关性出现在 28 天滞后时为 0.78,42 天滞后时为 0.69。一家医疗中心的 CHOTS 与其新冠病毒普查之间的滞后相关性在 42 天最高(0.63),九家医疗中心在 35 天(0.52-0.73),八家医疗中心在 28 天(0.28-0.74),两家医疗中心在 14 天(0.73-0.78)。个别指标的最强相关性为滞后 1-14 天的 0.94(新冠病毒普查)和 0.90(新的阳性新冠病毒检测),以及滞后 14-28 天的 0.83(新冠病毒电话)和紧急诊所就诊。使用 2020 年 10 月 1 日至 2021 年 3 月 21 日的前瞻性验证,滞后 35 天的交叉相关性也相似(0.73)。
被动收集的卫生系统指标与未来新冠病毒医院普查的相关性很强,可提前 6 周预测三次连续新冠病毒波。这些工具可以为社区、卫生系统和公共卫生官员提供信息,以识别、准备和减轻新出现的新冠病毒活动。