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基于驾驶时间确定专科护理覆盖范围的差距:以德国的神经炎性疾病为例。

Driving time-based identification of gaps in specialised care coverage: An example of neuroinflammatory diseases in Germany.

作者信息

Masanneck Lars, Räuber Saskia, Schroeter Christina B, Lehnerer Sophie, Ziemssen Tjalf, Ruck Tobias, Meuth Sven G, Pawlitzki Marc

机构信息

Department of Neurology, Medical Faculty University Hospital Düsseldorf, Düsseldorf, Germany.

Hasso Plattner Institute, University of Potsdam, Potsdam, Germany.

出版信息

Digit Health. 2023 Jan 27;9:20552076231152989. doi: 10.1177/20552076231152989. eCollection 2023 Jan-Dec.

Abstract

OBJECTIVE

Due to the growing complexity in monitoring and treatment of many disorders, disease-specific care and research networks offer patients certified healthcare. However, the networks' ability to provide health services close to patients' homes usually remains vague. Digital Health Technologies (DHTs) help to provide better care, especially if implemented in a targeted manner in regions undersupplied by specialised networks. Therefore, we used a car travel time-based isochrone approach to identify care gaps using the example of the neuroinflammation-focused German healthcare and research networks for multiple sclerosis (MS), myasthenia gravis (MG), myositis and immune-mediated neuropathy.

METHODS

Excellence centres were mapped, and isochrones for 30, 60, 90 and 120 minutes were calculated. The resulting geometric figures were aggregated and used to mask the global human settlement population grid 2019 to estimate German inhabitants that can reach centres within the given periods.

RESULTS

While 96.48% of Germans can drive to an MS-focused centre within one hour, coverage is lower for the rare disease networks for MG (48.3%), myositis (43.1%) and immune-mediated neuropathy (56.7%). Within 120 minutes, more than 80% of Germans can reach a centre of any network. Besides the generally worse covered rural regions such as North-Eastern Germany, the rare disease networks also show network-specific regional underrepresentation.

CONCLUSION

An isochrone-based approach helps identify regions where specialised care is hard to reach, which might be especially troublesome in the case of an often disabled patient collective. Patient care could be improved by focusing deployments of disease-specific DHTs on these areas.

摘要

目的

由于许多疾病的监测和治疗日益复杂,特定疾病护理和研究网络为患者提供了经过认证的医疗服务。然而,这些网络在患者家附近提供健康服务的能力通常仍不明确。数字健康技术(DHTs)有助于提供更好的护理,特别是如果以有针对性的方式在专业网络供应不足的地区实施。因此,我们以专注于神经炎症的德国多发性硬化症(MS)、重症肌无力(MG)、肌炎和免疫介导性神经病的医疗保健和研究网络为例,采用基于汽车行驶时间的等时线方法来识别护理差距。

方法

绘制卓越中心地图,并计算30、60、90和120分钟的等时线。将生成的几何图形进行汇总,并用于掩盖2019年全球人类住区人口网格,以估计在给定时间内能够到达中心的德国居民。

结果

虽然96.48%的德国人可以在一小时内开车到达专注于MS的中心,但MG(48.3%)、肌炎(43.1%)和免疫介导性神经病(56.7%)的罕见病网络覆盖范围较低。在120分钟内,超过80%的德国人可以到达任何网络的中心。除了德国东北部等普遍覆盖较差的农村地区外,罕见病网络在特定区域也存在代表性不足的情况。

结论

基于等时线的方法有助于识别难以获得专科护理的地区,这对于通常残疾的患者群体来说可能尤其麻烦。通过将特定疾病的DHTs部署集中在这些地区,可以改善患者护理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce26/9903011/f2dca99d043b/10.1177_20552076231152989-fig1.jpg

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