• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

相似文献

1
Online Reviews of Specialized Drug Treatment Facilities-Identifying Potential Drivers of High and Low Patient Satisfaction.专业药物治疗机构的在线评价——确定患者高满意度和低满意度的潜在驱动因素
J Gen Intern Med. 2020 Jun;35(6):1647-1653. doi: 10.1007/s11606-019-05548-9.
2
Association Between Online Reviews of Substance Use Disorder Treatment Facilities and Drug-Induced Mortality Rates: Cross-Sectional Analysis.物质使用障碍治疗机构的在线评论与药物所致死亡率之间的关联:横断面分析
JMIR AI. 2023 Dec 29;2:e46317. doi: 10.2196/46317.
3
Online Ratings of the Patient Experience: Emergency Departments Versus Urgent Care Centers.在线患者体验评分:急诊科与紧急护理中心。
Ann Emerg Med. 2019 Jun;73(6):631-638. doi: 10.1016/j.annemergmed.2018.09.029. Epub 2018 Nov 2.
4
Patient Experience and Satisfaction in Online Reviews of Obstetric Care: Observational Study.产科护理在线评论中的患者体验与满意度:观察性研究
JMIR Form Res. 2022 Mar 31;6(3):e28379. doi: 10.2196/28379.
5
Online Reviews of Mental Health Treatment Facilities: Narrative Themes Associated With Positive and Negative Ratings.心理健康治疗机构的在线评论:与正面和负面评价相关的叙事主题。
Psychiatr Serv. 2021 Jul 1;72(7):776-783. doi: 10.1176/appi.ps.202000267. Epub 2021 May 21.
6
Association Between Crowdsourced Health Care Facility Ratings and Mortality in US Counties.美国县的众包医疗保健机构评级与死亡率之间的关联
JAMA Netw Open. 2021 Oct 1;4(10):e2127799. doi: 10.1001/jamanetworkopen.2021.27799.
7
Evaluation of Dermatology Practice Online Reviews: Lessons From Qualitative Analysis.皮肤科在线评论评价:定性分析的启示。
JAMA Dermatol. 2016 Feb;152(2):153-7. doi: 10.1001/jamadermatol.2015.3950.
8
Describing the patient experience from Yelp reviews of community pharmacies.描述社区药店 Yelp 评论中的患者体验。
J Am Pharm Assoc (2003). 2019 May-Jun;59(3):349-355. doi: 10.1016/j.japh.2019.02.004. Epub 2019 Apr 15.
9
What do patients say about emergency departments in online reviews? A qualitative study.患者在在线评论中如何评价急诊科?一项定性研究。
BMJ Qual Saf. 2016 Jan;25(1):14-24. doi: 10.1136/bmjqs-2015-004035. Epub 2015 Jul 24.
10
Social media ratings of nursing homes associated with experience of care and "Nursing Home Compare" quality measures.与护理体验及“疗养院比较”质量指标相关的疗养院社交媒体评级
BMC Health Serv Res. 2019 Apr 27;19(1):260. doi: 10.1186/s12913-019-4100-7.

引用本文的文献

1
Relationship between evaluation factors and star ratings for Japanese community healthcare institutions in electronic word-of-mouth reviews: an observational study.电子口碑评价中日本社区医疗机构评价因素与星级评级之间的关系:一项观察性研究。
BMC Prim Care. 2024 Dec 5;25(1):413. doi: 10.1186/s12875-024-02668-y.
2
Disparities by Race and Urbanicity in Online Health Care Facility Reviews.在线医疗设施评价中的种族和城市化差异。
JAMA Netw Open. 2024 Nov 4;7(11):e2446890. doi: 10.1001/jamanetworkopen.2024.46890.
3
Association Between Online Reviews of Substance Use Disorder Treatment Facilities and Drug-Induced Mortality Rates: Cross-Sectional Analysis.物质使用障碍治疗机构的在线评论与药物所致死亡率之间的关联:横断面分析
JMIR AI. 2023 Dec 29;2:e46317. doi: 10.2196/46317.
4
State and Federal Legislators' Responses on Social Media to the Mental Health and Burnout of Health Care Workers Throughout the COVID-19 Pandemic: Natural Language Processing and Sentiment Analysis.州和联邦立法者在社交媒体上对整个新冠疫情期间医护人员心理健康和职业倦怠问题的回应:自然语言处理与情感分析
JMIR Infodemiology. 2023 Feb 24;3:e38676. doi: 10.2196/38676. eCollection 2023.
5
COVID-19 contact tracing app reviews reveal concerns and motivations around adoption.新冠接触者追踪应用程序评估揭示了人们对采用该应用程序的担忧和动机。
PLoS One. 2022 Sep 9;17(9):e0273222. doi: 10.1371/journal.pone.0273222. eCollection 2022.
6
Association Between Crowdsourced Health Care Facility Ratings and Mortality in US Counties.美国县的众包医疗保健机构评级与死亡率之间的关联
JAMA Netw Open. 2021 Oct 1;4(10):e2127799. doi: 10.1001/jamanetworkopen.2021.27799.
7
Online Reviews of Mental Health Treatment Facilities: Narrative Themes Associated With Positive and Negative Ratings.心理健康治疗机构的在线评论:与正面和负面评价相关的叙事主题。
Psychiatr Serv. 2021 Jul 1;72(7):776-783. doi: 10.1176/appi.ps.202000267. Epub 2021 May 21.
8
State Legislators' Divergent Social Media Response to the Opioid Epidemic from 2014 to 2019: Longitudinal Topic Modeling Analysis.2014 年至 2019 年,州立法者对阿片类药物泛滥的社交媒体反应存在分歧:纵向主题建模分析。
J Gen Intern Med. 2021 Nov;36(11):3373-3382. doi: 10.1007/s11606-021-06678-9. Epub 2021 Mar 29.
9
Analyzing Online Reviews of Substance Use Disorder Treatment Facilities in the USA Using Machine Learning.使用机器学习分析美国物质使用障碍治疗机构的在线评论
J Gen Intern Med. 2022 Mar;37(4):977-980. doi: 10.1007/s11606-021-06618-7. Epub 2021 Mar 16.
10
Patient and Caregiver Perceptions of Nursing Home Physicians: Insight from Yelp Reviews, 2009-2018.患者和护理人员对养老院医生的看法:Yelp 评论的见解,2009-2018 年。
J Am Geriatr Soc. 2020 Sep;68(9):2101-2105. doi: 10.1111/jgs.16634. Epub 2020 Jun 16.

本文引用的文献

1
Consumer Response to Composite Ratings of Nursing Home Quality.消费者对养老院质量综合评级的反应。
Am J Health Econ. 2019 Spring;5(2):165-190. doi: 10.1162/ajhe_a_00115. Epub 2019 Apr 23.
2
"Told": the Word Most Correlated to Negative Online Hospital Reviews.“告知”:与负面在线医院评价关联度最高的词汇。
J Gen Intern Med. 2019 Jul;34(7):1079-1080. doi: 10.1007/s11606-019-04870-6.
3
Drug and Opioid-Involved Overdose Deaths - United States, 2013-2017.药物和阿片类药物滥用相关的过量死亡-美国,2013-2017 年。
MMWR Morb Mortal Wkly Rep. 2018 Jan 4;67(5152):1419-1427. doi: 10.15585/mmwr.mm675152e1.
4
Protecting the Value of Medical Science in the Age of Social Media and "Fake News".在社交媒体和“假新闻”时代保护医学科学的价值
JAMA. 2018 Dec 18;320(23):2415-2416. doi: 10.1001/jama.2018.18416.
5
Online Ratings of the Patient Experience: Emergency Departments Versus Urgent Care Centers.在线患者体验评分:急诊科与紧急护理中心。
Ann Emerg Med. 2019 Jun;73(6):631-638. doi: 10.1016/j.annemergmed.2018.09.029. Epub 2018 Nov 2.
6
What Consumers Say About Nursing Homes in Online Reviews.消费者在在线评论中对养老院的评价。
Gerontologist. 2018 Jul 13;58(4):e273-e280. doi: 10.1093/geront/gny025.
7
Patient narratives in Yelp reviews offer insight into opioid experiences and the challenges of pain management.Yelp评论中的患者叙述提供了对阿片类药物使用体验以及疼痛管理挑战的洞察。
Pain Manag. 2018 Mar 1;8(2):95-104. doi: 10.2217/pmt-2017-0050. Epub 2018 Feb 16.
8
Website Characteristics and Physician Reviews on Commercial Physician-Rating Websites.商业医生评级网站的网站特性与医生评价
JAMA. 2017 Feb 21;317(7):766-768. doi: 10.1001/jama.2016.18553.
9
Transparency and Trust - Online Patient Reviews of Physicians.透明度与信任——医生的在线患者评价
N Engl J Med. 2017 Jan 19;376(3):197-199. doi: 10.1056/NEJMp1610136.
10
Increases in Drug and Opioid-Involved Overdose Deaths - United States, 2010-2015.药物和阿片类药物滥用相关过量死亡人数增加 - 美国,2010-2015 年。
MMWR Morb Mortal Wkly Rep. 2016 Dec 30;65(50-51):1445-1452. doi: 10.15585/mmwr.mm655051e1.

专业药物治疗机构的在线评价——确定患者高满意度和低满意度的潜在驱动因素

Online Reviews of Specialized Drug Treatment Facilities-Identifying Potential Drivers of High and Low Patient Satisfaction.

作者信息

Agarwal Anish K, Wong Vivien, Pelullo Arthur M, Guntuku Sharath, Polsky Daniel, Asch David A, Muruako Jonathan, Merchant Raina M

机构信息

Department of Emergency Medicine at the Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

Penn Medicine Center for Digital Health, University of Pennsylvania, Philadelphia, PA, USA.

出版信息

J Gen Intern Med. 2020 Jun;35(6):1647-1653. doi: 10.1007/s11606-019-05548-9.

DOI:10.1007/s11606-019-05548-9
PMID:31755009
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7280415/
Abstract

BACKGROUND

Despite the importance of high-quality and patient-centered substance use disorder treatment, there are no standardized ratings of specialized drug treatment facilities and their services. Online platforms offer insights into potential drivers of high and low patient experience.

OBJECTIVE

We sought to analyze publicly available online review content of specialized drug treatment facilities and identify themes within high and low ratings.

DESIGN

This was a retrospective analysis of online ratings and reviews of specialized drug treatment facilities in Pennsylvania listed within the 2016 National Directory of Drug and Alcohol Abuse Treatment Facilities. Latent Dirichlet Allocation, a machine learning approach to narrative text, was used to identify themes within reviews. Differential Language Analysis was then used to measure correlations between themes and star ratings.

SETTING

Online reviews of Pennsylvania's specialized drug treatment facilities posted to Google and Yelp (July 2010-August 2018).

RESULTS

A total of 7823 online ratings were posted over 8 years. The distribution was bimodal (43% 5-star and 34% 1-star). The average weighted rating of a facility was 3.3 stars. Online themes correlated with 5-star ratings were the following: focus on recovery (r = 0.53), helpfulness of staff (r = 0.43), compassionate care (r = 0.37), experienced a life-changing moment (r = 0.32), and staff professionalism (r = 0.29). Themes correlated with a 1-star rating were waiting time (r = 0.41), poor accommodations (0.26), poor phone communication (r = 0.24), medications given (0.24), and appointment availability (r = 0.23). Themes derived from review content were similar to 9 of the 14 facility-level services highlighted by the Substance Abuse and Mental Health Services Administration's National Survey of Substance Abuse Treatment Services.

CONCLUSIONS

Individuals are sharing their ratings and reviews of specialized drug treatment facilities on online platforms. Organically derived reviews of the patient experience, captured by online platforms, reveal potential drivers of high and low ratings. These represent additional areas of focus which can inform patient-centered quality metrics for specialized drug treatment facilities.

摘要

背景

尽管高质量且以患者为中心的物质使用障碍治疗很重要,但对于专业戒毒治疗机构及其服务,尚无标准化的评级。在线平台能提供关于患者体验高低潜在驱动因素的见解。

目的

我们试图分析专业戒毒治疗机构公开的在线评论内容,并确定高评级和低评级中的主题。

设计

这是一项对2016年《国家药物和酒精滥用治疗机构名录》中列出的宾夕法尼亚州专业戒毒治疗机构在线评级和评论的回顾性分析。潜在狄利克雷分配法(一种用于叙事文本的机器学习方法)被用于确定评论中的主题。然后使用差异语言分析来衡量主题与星级评级之间的相关性。

设置

宾夕法尼亚州专业戒毒治疗机构在谷歌和Yelp上发布的在线评论(2010年7月 - 2018年8月)。

结果

8年期间共发布了7823条在线评级。分布呈双峰状(43%为五星级,34%为一星级)。机构的平均加权评级为3.3星。与五星级评级相关的在线主题如下:专注于康复(r = 0.53)、工作人员的帮助程度(r = 0.43)、关怀护理(r = 0.37)、经历改变人生的时刻(r = 0.32)以及工作人员的专业素养(r = 0.29)。与一星级评级相关的主题有等待时间(r = 0.41)、住宿条件差(0.26)、电话沟通不畅(r = 0.24)、用药情况(0.24)以及预约便利性(r = 0.23)。从评论内容中得出的主题与物质滥用和精神健康服务管理局的全国药物滥用治疗服务调查所强调的14项机构层面服务中的9项相似。

结论

个人在在线平台上分享他们对专业戒毒治疗机构的评级和评论。在线平台捕捉到的关于患者体验的自然生成的评论揭示了高评级和低评级的潜在驱动因素。这些代表了额外的关注领域,可为专业戒毒治疗机构以患者为中心的质量指标提供参考。