Population Health Management to identify and characterise ongoing health need for high-risk individuals shielded from COVID-19: a cross-sectional cohort study.
Population Health Management to identify and characterise ongoing health need for high-risk individuals shielded from COVID-19: a cross-sectional cohort study.
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DOI：
10.1136/bmjopen-2020-041370
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发表时间：
2020-09-28
期刊：
影响因子：
2.9
通讯作者：
Cooper JA
中科院分区：
文献类型：
--
作者：
Kenward C;Pratt A;Creavin S;Wood R;Cooper JA
使用人口健康管理（PHM）方法识别和确认需要屏蔽的严重COVID-19高风险个体，以管理持续的健康需求并减轻潜在的屏蔽引起的伤害。使用公布的国家“屏蔽患者名单”标准确定了COVID-19“高风险”个人。使用PHM方法对该组进行描述性分析，包括当前慢性病、历史医疗保健利用以及人口统计学和社会经济状况等个人水平信息。分割采用k-原型聚类分析。英格兰西南部的一个主要医疗保健系统，其关联的初级，二级，社区和心理健康数据可在系统范围的数据集中获得。该研究是在英国COVID-19大流行相对较早的时候进行的。来自78个诊所的1 013 940名个人提供了服务。与被认为处于“低”和“中等”风险的群体相比，（即符合每年流感疫苗接种资格），高风险个体年龄较大（中位年龄：68岁（IQR：55-77岁），cf 30岁）（18-44岁）和63岁（分别为38-73岁），在上一年有较多的基层护理/社区接触（中位接触：5（2-10），cf 0（0-2）和2（0-5）），合并症负担较高（中位Charlson评分：4（3-6），cf 0（0-0）和2（1-4））。地理空间分析显示，3.3%的农村和半农村居民属于高危人群，而城市和内城居民为2.91%（p<0.001）。细分发现了六个不同的集群，包括高风险人群，关键的区别是基于年龄和癌症，呼吸和精神健康状况的存在。PHM方法对于描述需要屏蔽的个人的需求很有用。对高风险人群的细分确定了具有不同特征的群体，这些群体可能受益于卫生和保健提供者和决策者更有针对性的应对措施。
To use Population Health Management (PHM) methods to identify and characterise individuals at high-risk of severe COVID-19 for which shielding is required, for the purposes of managing ongoing health needs and mitigating potential shielding-induced harm. Individuals at ‘high risk’ of COVID-19 were identified using the published national ‘Shielded Patient List’ criteria. Individual-level information, including current chronic conditions, historical healthcare utilisation and demographic and socioeconomic status, was used for descriptive analyses of this group using PHM methods. Segmentation used k-prototypes cluster analysis. A major healthcare system in the South West of England, for which linked primary, secondary, community and mental health data are available in a system-wide dataset. The study was performed at a time considered to be relatively early in the COVID-19 pandemic in the UK. 1 013 940 individuals from 78 contributing general practices. Compared with the groups considered at ‘low’ and ‘moderate’ risk (ie, eligible for the annual influenza vaccination), individuals at high risk were older (median age: 68 years (IQR: 55–77 years), cf 30 years (18–44 years) and 63 years (38–73 years), respectively), with more primary care/community contacts in the previous year (median contacts: 5 (2–10), cf 0 (0–2) and 2 (0–5)) and had a higher burden of comorbidity (median Charlson Score: 4 (3–6), cf 0 (0–0) and 2 (1–4)). Geospatial analyses revealed that 3.3% of rural and semi-rural residents were in the high-risk group compared with 2.91% of urban and inner-city residents (p<0.001). Segmentation uncovered six distinct clusters comprising the high-risk population, with key differentiation based on age and the presence of cancer, respiratory, and mental health conditions. PHM methods are useful in characterising the needs of individuals requiring shielding. Segmentation of the high-risk population identified groups with distinct characteristics that may benefit from a more tailored response from health and care providers and policy-makers.
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