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作为加拿大应对新冠疫情举措的一部分,与科技公司建立合作关系:一项定性案例研究。

Governing partnerships with technology companies as part of the COVID-19 response in Canada: A qualitative case study.

作者信息

Harish Vinyas, Samson Thomas G, Diemert Lori, Tuite Ashleigh, Mamdani Muhammad, Khan Kamran, McGahan Anita, Shaw James A, Das Sunit, Rosella Laura C

机构信息

MD/PhD Program, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada.

Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.

出版信息

PLOS Digit Health. 2022 Dec 14;1(12):e0000164. doi: 10.1371/journal.pdig.0000164. eCollection 2022 Dec.

DOI:10.1371/journal.pdig.0000164
PMID:36812643
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9931354/
Abstract

Cross-sector partnerships are vital for maintaining resilient health systems; however, few studies have sought to empirically assess the barriers and enablers of effective and responsible partnerships during public health emergencies. Through a qualitative, multiple case study, we analyzed 210 documents and conducted 26 interviews with stakeholders in three real-world partnerships between Canadian health organizations and private technology startups during the COVID-19 pandemic. The three partnerships involved: 1) deploying a virtual care platform to care for COVID-19 patients at one hospital, 2) deploying a secure messaging platform for physicians at another hospital, and 3) using data science to support a public health organization. Our results demonstrate that a public health emergency created time and resource pressures throughout a partnership. Given these constraints, early and sustained alignment on the core problem was critical for success. Moreover, governance processes designed for normal operations, such as procurement, were triaged and streamlined. Social learning, or the process of learning from observing others, offset some time and resource pressures. Social learning took many forms ranging from informal conversations between individuals at peer organisations (e.g., hospital chief information officers) to standing meetings at the local university's city-wide COVID-19 response table. We also found that startups' flexibility and understanding of the local context enabled them to play a highly valuable role in emergency response. However, pandemic fueled "hypergrowth" created risks for startups, such as introducing opportunities for deviation away from their core value proposition. Finally, we found each partnership navigated intense workloads, burnout, and personnel turnover through the pandemic. Strong partnerships required healthy, motivated teams. Visibility into and engagement in partnership governance, belief in partnership impact, and strong emotional intelligence in managers promoted team well-being. Taken together, these findings can help to bridge the theory-to-practice gap and guide effective cross-sector partnerships during public health emergencies.

摘要

跨部门伙伴关系对于维持有韧性的卫生系统至关重要;然而,很少有研究试图实证评估公共卫生紧急事件期间有效且负责的伙伴关系的障碍和促进因素。通过一项定性的多案例研究,我们分析了210份文件,并对加拿大卫生组织与私营科技初创企业在新冠疫情期间的三个实际伙伴关系中的利益相关者进行了26次访谈。这三个伙伴关系包括:1)在一家医院部署虚拟护理平台以护理新冠患者;2)在另一家医院为医生部署安全消息平台;3)利用数据科学支持一个公共卫生组织。我们的结果表明,公共卫生紧急事件在整个伙伴关系中造成了时间和资源压力。鉴于这些限制,对核心问题的早期和持续一致对于成功至关重要。此外,为正常运营设计的治理流程,如采购,进行了分类和简化。社会学习,即从观察他人中学习的过程,抵消了一些时间和资源压力。社会学习有多种形式,从同行组织(如医院首席信息官)个人之间的非正式对话到当地大学全市范围的新冠疫情应对会议上的常务会议。我们还发现,初创企业的灵活性和对当地情况的了解使它们能够在应急响应中发挥非常有价值的作用。然而,疫情引发的“超增长”给初创企业带来了风险,比如带来偏离其核心价值主张的机会。最后,我们发现每个伙伴关系在疫情期间都应对了高强度的工作量、倦怠和人员更替。强大的伙伴关系需要健康、积极的团队。对伙伴关系治理的可见性和参与、对伙伴关系影响的信念以及管理者强大的情商促进了团队福祉。综上所述,这些发现有助于弥合理论与实践之间的差距,并指导公共卫生紧急事件期间有效的跨部门伙伴关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2489/9931354/f027847bd128/pdig.0000164.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2489/9931354/b76382568fd6/pdig.0000164.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2489/9931354/8c24a38aa3ac/pdig.0000164.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2489/9931354/f027847bd128/pdig.0000164.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2489/9931354/b76382568fd6/pdig.0000164.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2489/9931354/8c24a38aa3ac/pdig.0000164.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2489/9931354/f027847bd128/pdig.0000164.g003.jpg

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