2019年全球疾病负担研究的皮肤病学数据和PatientsLikeMe在线支持社区:比较分析
Mindy D Szeto1, Lina Alhanshali2, Chandler W Rundle3
1Department of Dermatology, University of Minnesota Medical School, Minneapolis, MN, United States.
JMIR dermatology
|December 11, 2024
概括
全球疾病负担 (GBD) 研究和PatientsLikeMe (PLM) 社区数据提供了对皮肤病的补充洞察力. 将这些数据集进行比较,可以发现人口统计学上的差异和相关性,突出了未满足的患者需求.
科学领域:
- 皮肤病学 皮肤病学
- 公共卫生 公共卫生
- 医疗信息学 医疗信息学
背景情况:
- 全球疾病负担 (GBD) 研究量化了疾病的流行率和影响.
- PatientsLikeMe (PLM) 是一个在线平台,用于患者报告的体验.
- 了解皮肤病需要不同的数据来源.
研究的目的:
- 量化比较来自GBD研究和皮肤病的PLM社区的数据.
- 为了确定两个数据集之间的人口差异和相关性.
- 探索这些互补来源在了解未满足的患者需求方面的潜力.
主要方法:
- 量化比较GBD流行/发病率数据与PLM患者生成的数据.
- 在两个数据集中分析人口统计特征.
- 相关性分析以确定 GBD 和 PLM 发现之间的关系.
主要成果:
- 观察到皮肤病的GBD和PLM数据之间的预期人口差异.
- 确定了GBD指标和PLM患者体验之间的显著相关性.
- 证明了 GBD 和 PLM 数据相互补充的潜力.
结论:
- GBD研究和PLM社区数据是皮肤病学研究的宝贵补充资源.
- 将这些数据集进行比较可以阐明皮肤病学中未得到满足的患者需求和优先事项.
- 整合多种数据源可以提高我们对疾病负担和患者体验的理解.
关键词:
DALYY每日的时间在GBDGBDGBDGBDGBD全球疾病负担全球疾病负担在 PLM PLM 中.像我这样的病人进行比较分析.人口统计数据 人口统计数据皮肤学 皮肤学根据残疾调整的寿命年数.在论坛,论坛上.互联网互联网互联网互联网互联网互联网经验是生活的经验,是生活的经验.在线支持社区在线支持社区.患病率的流行情况.社交媒体 社交媒体使用者使用者使用者使用者更多相关视频
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