Falster Michael O, Jorm Louisa R, Leyland Alastair H
Centre for Big Data Research in Health, University of New South Wales Australia, Sydney, Australia.
MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK.
BMJ Open. 2016 Sep 7;6(9):e012031. doi: 10.1136/bmjopen-2016-012031.
To explore patterns of health service use in the lead-up to, and following, admission for a 'preventable' hospitalisation.
266 950 participants in the 45 and Up Study, New South Wales (NSW) Australia
Linked data on hospital admissions, general practitioner (GP) visits and other health events were used to create visual representations of health service use. For each participant, health events were plotted against time, with different events juxtaposed using different markers and panels of data. Various visualisations were explored by patient characteristics, and compared with a cohort of non-admitted participants matched on sociodemographic and health characteristics. Health events were displayed over calendar year and in the 90 days surrounding first preventable hospitalisation.
The visualisations revealed patterns of clustering of GP consultations in the lead-up to, and following, preventable hospitalisation, with 14% of patients having a consultation on the day of admission and 27% in the prior week. There was a clustering of deaths and other hospitalisations following discharge, particularly for patients with a long length of stay, suggesting patients may have been in a state of health deterioration. Specialist consultations were primarily clustered during the period of hospitalisation. Rates of all health events were higher in patients admitted for a preventable hospitalisation than the matched non-admitted cohort.
We did not find evidence of limited use of primary care services in the lead-up to a preventable hospitalisation, rather people with preventable hospitalisations tended to have high levels of engagement with multiple elements of the healthcare system. As such, preventable hospitalisations might be better used as a tool for identifying sicker patients for managed care programmes. Visualising longitudinal health data was found to be a powerful strategy for uncovering patterns of health service use, and such visualisations have potential to be more widely adopted in health services research.
探讨在因“可预防的”住院治疗入院前及入院后的医疗服务使用模式。
澳大利亚新南威尔士州45岁及以上研究中的266950名参与者
利用与住院、全科医生(GP)就诊及其他健康事件相关联的数据,创建医疗服务使用情况的可视化呈现。对于每位参与者,将健康事件按时间进行绘制,使用不同的标记和数据面板并列展示不同的事件。通过患者特征对各种可视化呈现进行探究,并与在社会人口统计学和健康特征方面匹配的未入院参与者队列进行比较。健康事件在日历年以及首次可预防住院治疗前的90天内进行展示。
可视化呈现揭示了在可预防住院治疗前及之后全科医生会诊的聚集模式,14%的患者在入院当天进行了会诊,27%的患者在前一周进行了会诊。出院后死亡和其他住院情况存在聚集现象,尤其是住院时间长的患者,这表明患者可能处于健康状况恶化的状态。专科会诊主要集中在住院期间。因可预防住院治疗入院的患者所有健康事件的发生率高于匹配的未入院队列。
我们未发现证据表明在可预防住院治疗前初级保健服务的使用有限,相反,可预防住院治疗的患者往往与医疗保健系统的多个环节有高度接触。因此,可预防住院治疗或许可更好地用作识别病情较重患者以纳入管理式护理项目的工具。发现可视化呈现纵向健康数据是揭示医疗服务使用模式的有力策略,此类可视化呈现有可能在医疗服务研究中得到更广泛的应用。