Technological progress in electronic health record system optimization: Systematic review of systematic literature reviews.

BACKGROUND: 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. MATERIALS AND METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.

Transforming health care through Bhutan's digital health strategy: progress to date.

Bhutan, a landlocked country in the eastern Himalayas with some of the most rugged and mountainous terrain in the world, is actively engaged in digital health strategy reforms aimed at improving the efficiency of the health information system. Aligned with Bhutan's e-Government master plan, the National eHealth strategy and action plan aims to improve health by empowering health-care providers and citizens through technology and by enabling data exchange for service delivery. The strategy has four primary areas of focus: (i) ensuring digital health governance arrangements; (ii) concentrating on strong foundations in terms of infrastructure and standards; (iii) prioritizing improvements in the current health system in a phased, selective manner; and (iv) building the digital skills and knowledge of health workers. With support from the Asian Development Bank and the World Health Organization, phase 1 of the strategy has been completed and the blueprint for the digital health information system is in development. Phase 2 of the strategy will be implemented during 2020­2023 and will include work on (i) identity management for the health workforce; (ii) the implementation of a master patient index and a secure longitudinal patient information system; and (iii) enabling all health facilities to access the systems. Bhutan's eHealth strategy has the potential to fundamentally transform the delivery of health services, strengthen primary health care and enable the development of a "One Health" public health surveillance system.

Zimbabwe's Human Resources for health Information System (ZHRIS)-an assessment in the context of establishing a global standard.

INTRODUCTION: There have been numerous global calls to action to utilize human resources information systems (HRIS) to improve the availability and quality of data for strengthening the regulation and deployment of health workers. However, with no normative guidance in existence, the development of HRIS has been inconsistent and lacking in standardization, hindering the availability and use of data for health workforce planning and decision making (Riley et al., 2012). CDC and WHO partnered with the Ministry of Health in several countries to conduct HRIS functional requirements analyses and establish a Minimum Data Set (MDS) of elements essential for a global standard HRIS. As a next step, CDC advanced a study to examine the alignment of one of the HRIS it supports (in Zimbabwe) against this MDS. METHOD: For this study, we created a new data collection and analysis tool to assess the extent to which Zimbabwe's CDC-supported HRIS was aligned with the WHO MDS. We performed systematic "gap analyses" in order to make prioritized recommendations for addressing the gaps, with the aim of improving the availability and quality of data on Zimbabwe's health workforce. RESULTS: The majority of the data elements outlined in the WHO MDS were present in the ZHRIS databases, though they were found to be missing various applicable elements. The lack of certain elements could impede functions such as health worker credential verification or equitable in-service training allocation. While the HRIS MDS treats all elements equally, our assessment revealed that not all the elements have equal significance when it comes to data utilization. Further, some of the HRIS MDS elements exceeded the current needs of regulatory bodies and the Ministry of Health and Child Care (MOHCC) in Zimbabwe. The preliminary findings of this study helped inspire the development of a more recent HRH Registry MDS subset, which is a shorter list of priority data elements recommended as a global standard for HRIS. CONCLUSION: The field-tested assessment methodology presented here, with suggested improvements to the tool, can be used to identify absent or unaligned elements in either an HRH Registry or a full HRIS. Addressing the prioritized gaps will increase the availability of critical data in the ZHRIS and can empower the MOHCC and councils to conduct more strategic analyses, improving health workforce planning and ultimately public health outcomes in the country.