A Practical Approach to Digital Transformation: A Guide to Health Institutions in Developing Countries
A Practical Approach to Digital Transformation: A Guide to Health Institutions in Developing Countries
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数字化转型的实用方法：发展中国家卫生机构指南
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发表时间：
2020
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通讯作者：
A. Marcelo
中科院分区：
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作者：
A. Marcelo
在地方、国家和国际层面上，大多数医疗保健组织都渴望开始数字化转型，但却不知道如何开始这一过程。本章提出了一种实用的方法，首先为强有力的治理奠定基础，以指导机构走向这一复杂的过程。该方法从治理(G)开始——为整个企业设置清晰的决策结构和战略指令。随后采用框架(F)，为所有利益相关者在经历各自的变化时提供共同参考。由于几乎所有医疗保健数据都是敏感的，应该保密，因此必须实施道德(E)流程，以确保患者的安全，并将他们的福利放在首位。然后，数据治理(D)开始发挥作用，为数据管理提供明确的指导方针、系统和结构。一旦具备了上述基础，就应该具备云和遵从性(C)功能，以确保有一个安全的基础设施来存储、处理和保护大量信息。这种弹性基础设施能够以比大多数分析工具实时管理更快的速度积累大数据(B)，从而为可视化信息提供了机会。有了这些海量的数据，就为人工智能(A)奠定了先决条件，并且可以发现以前未知的新见解，并将其用于为企业创建新产品和服务，以及作为改进治理的决策输入。
Most healthcare organizations, at the local, national, and international levels aspire to commence their digital transformation but are at a loss on how to start the process. This chapter presents a practical approach that begins with laying down the foundations for strong governance to guide institutions towards this complex process. The approach begins with Governance (G)—setting clear decision-making structures and strategic directives to the whole enterprise. This is followed by adoption of Frameworks (F) that provide a common reference for all stakeholders as they undergo their respective changes. Because almost all healthcare data are sensitive and should be kept confidential, Ethical (E) processes must be in place to ensure that patients are safe and that their welfare is of the utmost priority. Data governance (D) then comes into play providing clear guidelines, systems, and structures in the management of data. Once these aforementioned fundamentals are in place, cloud and compliance (C) capabilities should be available to ensure that a secure infrastructure is in place to store, process, and protect large volumes of information. This elastic infrastructure enables the accumulation of big data (B) at a rate faster than what most analytical tools can manage in real-time opening up opportunities for visualizing information. With this tremendous amounts of data, the prerequisits are laid out for Artificial Intelligence (A) and new insights, previously unknown, can be discovered and used for creating new products and services for the enterprise and as input for decision-making for improved governance.