The recent, rapid development of digital technologies offers new possibilities for more efficient implementation of electronic health record (EHR) and personal health record (PHR) systems. A growing volume of healthcare data has been the hallmark of this digital transformation. The large healthcare datasets' complexity and their dynamic nature pose various challenges related to processing, analysis, storage, security, privacy, data exchange, and usability. We performed a systematic review of systematic reviews to assess technological progress in EHR and PHR systems. We searched MEDLINE, Cochrane, Web of Science, and Scopus for systematic literature reviews on technological advancements that support EHR and PHR systems published between January 1, 2010, and October 06, 2020. The searches resulted in a total of 2,448 hits. Of these, we finally selected 23 systematic reviews. Most of the included papers dealt with information extraction tools and natural language processing technology (n = 10), followed by studies that assessed the use of blockchain technology in healthcare (n = 8). Other areas of digital technology research included EHR and PHR systems in austere settings (n = 1), de-identification methods (n = 1), visualization techniques (n = 1), communication tools within EHR and PHR systems (n = 1), and methodologies for defining Clinical Information Models that promoted EHRs and PHRs interoperability (n = 1). Technological advancements can improve the efficiency in the implementation of EHR and PHR systems in numerous ways. Natural language processing techniques, either rule-based, machine-learning, or deep learning-based, can extract information from clinical narratives and other unstructured data locked in EHRs and PHRs, allowing secondary research (i.e., phenotyping). Moreover, EHRs and PHRs are expected to be the primary beneficiaries of the blockchain technology implementation on Health Information Systems. Governance regulations, lack of trust, poor scalability, security, privacy, low performance, and high cost remain the most critical challenges for implementing these technologies.

中文翻译：

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电子健康档案系统优化技术进展：系统文献综述

最近数字技术的快速发展为更有效地实施电子健康记录（EHR）和个人健康记录（PHR）系统提供了新的可能性。不断增长的医疗数据量是这一数字化转型的标志。大型医疗数据集的复杂性及其动态特性带来了与处理、分析、存储、安全、隐私、数据交换和可用性相关的各种挑战。我们对系统评价进行了系统回顾，以评估 EHR 和 PHR 系统的技术进步。我们检索了 MEDLINE、Cochrane、Web of Science 和 Scopus，查找 2010 年 1 月 1 日至 2020 年 10 月 6 日期间发表的有关支持 EHR 和 PHR 系统的技术进步的系统文献综述。搜索结果总共有 2,448 个匹配项。其中，我们最终选出了23篇系统评价。大多数纳入的论文涉及信息提取工具和自然语言处理技术（n = 10），其次是评估区块链技术在医疗保健中的使用的研究（n = 8）。数字技术研究的其他领域包括严峻环境下的 EHR 和 PHR 系统 (n = 1)、去识别化方法 (n = 1)、可视化技术 (n = 1)、EHR 和 PHR 系统内的通信工具 (n = 1) ，以及定义促进 EHR 和 PHR 互操作性的临床信息模型的方法 (n = 1)。技术进步可以通过多种方式提高 EHR 和 PHR 系统的实施效率。自然语言处理技术，无论是基于规则、机器学习还是基于深度学习，都可以从锁定在 EHR 和 PHR 中的临床叙述和其他非结构化数据中提取信息，从而允许进行二次研究（即表型分析）。此外，EHR 和 PHR 预计将成为健康信息系统区块链技术实施的主要受益者。治理法规、缺乏信任、可扩展性差、安全性、隐私、低性能和高成本仍然是实施这些技术的最关键挑战。