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数字转型下医疗保健领域循证概念模型的开发:综合评价。

Development of an Evidence-Based Conceptual Model of the Health Care Sector Under Digital Transformation: Integrative Review.

机构信息

Institute of Management, Friedrich-Alexander-Universität Erlangen-Nürnberg, Nuremberg, Germany.

出版信息

J Med Internet Res. 2023 Jun 8;25:e41512. doi: 10.2196/41512.

Abstract

BACKGROUND

Digital transformation is currently one of the most influential developments. It is fundamentally changing consumers' expectations and behaviors, challenging traditional firms, and disrupting numerous markets. Recent discussions in the health care sector tend to assess the influence of technological implications but neglect other factors needed for a holistic view on the digital transformation. This calls for a reevaluation of the current state of digital transformation in health care. Consequently, there is a need for a holistic view on the complex interdependencies of digital transformation in the health care sector.

OBJECTIVE

This study aimed to examine the effects of digital transformation on the health care sector. This is accomplished by providing a conceptual model of the health care sector under digital transformation.

METHODS

First, the most essential stakeholders in the health care sector were identified by a scoping review and grounded theory approach. Second, the effects on these stakeholders were assessed. PubMed, Web of Science, and Dimensions were searched for relevant studies. On the basis of an integrative review and grounded theory methodology, the relevant academic literature was systematized and quantitatively and qualitatively analyzed to evaluate the impact on the value creation of, and the relationships among, the stakeholders. Third, the findings were synthesized into a conceptual model of the health care sector under digital transformation.

RESULTS

A total of 2505 records were identified from the database search; of these, 140 (5.59%) were included and analyzed. The results revealed that providers of medical treatments, patients, governing institutions, and payers are the most essential stakeholders in the health care sector. As for the individual stakeholders, patients are experiencing a technology-enabled growth of influence in the sector. Providers are becoming increasingly dependent on intermediaries for essential parts of the value creation and patient interaction. Payers are expected to try to increase their influence on intermediaries to exploit the enormous amounts of data while seeing their business models be challenged by emerging technologies. Governing institutions regulating the health care sector are increasingly facing challenges from new entrants in the sector. Intermediaries increasingly interconnect all these stakeholders, which in turn drives new ways of value creation. These collaborative efforts have led to the establishment of a virtually integrated health care ecosystem.

CONCLUSIONS

The conceptual model provides a novel and evidence-based perspective on the interrelations among actors in the health care sector, indicating that individual stakeholders need to recognize their role in the system. The model can be the basis of further evaluations of strategic actions of actors and their effects on other actors or the health care ecosystem itself.

摘要

背景

数字化转型目前是最具影响力的发展之一。它从根本上改变了消费者的期望和行为,挑战了传统企业,并颠覆了众多市场。最近医疗保健领域的讨论往往评估技术影响,但忽略了全面看待数字化转型所需的其他因素。这需要重新评估医疗保健领域数字化转型的现状。因此,需要从整体上了解医疗保健部门数字化转型的复杂相互依存关系。

目的

本研究旨在考察数字化转型对医疗保健行业的影响。通过提供数字化转型下医疗保健部门的概念模型来实现这一目标。

方法

首先,通过范围审查和扎根理论方法确定医疗保健部门最重要的利益相关者。其次,评估这些利益相关者的影响。在综合审查和扎根理论方法的基础上,对相关学术文献进行了系统整理,并对其进行了定量和定性分析,以评估对利益相关者的价值创造和关系的影响。第三,将研究结果综合为数字化转型下医疗保健部门的概念模型。

结果

从数据库搜索中确定了 2505 条记录;其中,有 140 条(5.59%)被纳入并进行了分析。结果表明,医疗服务提供者、患者、管理机构和支付方是医疗保健部门最重要的利益相关者。就个别利益相关者而言,患者在该行业中经历了技术驱动的影响力增长。提供者越来越依赖中介机构来创造价值和与患者互动的重要部分。支付方预计将试图增加对中介机构的影响力,以利用大量数据,同时看到其商业模式受到新兴技术的挑战。管理医疗保健部门的管理机构越来越受到该部门新进入者的挑战。中介机构越来越多地将所有这些利益相关者相互连接,从而推动了新的价值创造方式。这些合作努力建立了一个几乎整合的医疗保健生态系统。

结论

该概念模型为医疗保健部门参与者之间的相互关系提供了新颖的、基于证据的视角,表明各个利益相关者需要认识到自己在系统中的角色。该模型可以作为进一步评估参与者战略行动及其对其他参与者或医疗保健生态系统本身影响的基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a7b/10288351/28aa6d56db48/jmir_v25i1e41512_fig1.jpg

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