El Khatib Mounir, Hamidi Samer, Al Ameeri Ishaq, Al Zaabi Hamad, Al Marqab Rehab
School of Business and Quality Management, Hamdan Bin Mohammed Smart University, Dubai, United Arab Emirates.
School of Health and Environmental Studies, Hamdan Bin Mohammed Smart University, Dubai, United Arab Emirates.
Clinicoecon Outcomes Res. 2022 Aug 26;14:563-574. doi: 10.2147/CEOR.S369553. eCollection 2022.
As the amount of medical data in the electronic medical records system (EMR) is increasing tremendously, the required time to read it by health providers is growing by the exact proportionality. This means that physicians must increase the time spared for each patient again by the precise proportionality. This may lead to exposing the accuracy and quality of the course of action to be taken for the patients. Increasing the physician's required time for one patient means that the physician can see fewer patients. This will create an issue with the medical management authority as more physicians are needed, and higher expenses will be required.
The two questions that arise here are 1. Identify the potential opportunities and challenges for extensive data analysis in the healthcare sector. 2. Evaluate different ways in which big medical data can be analyzed?
The authors identified the four concerned parties representing the four potential solutions dimensions to answer these two questions. These parties are 1. physicians, 2. health information systems management (HISM) departments, mainly the EMR system, and 3. Health management departments 4. Relevant Health Information Systems (HIS) parties. A literature review and 25 interviews were conducted. The interviews covered 1: Two global organizations: John Hopkins and Joint Commission International (JCI), 2: Three United Arab Emirates-based health organizations: Department of health in Abu Dhabi, SEHA in Abu Dhabi, Dubai health Authority (DHA) in Dubai, 3: 10 Physicians from different specialties, 4: Five EMR managers and 5: Five IT (Information Technology) professionals representing the HIS parties. Qualitative analysis is used as the approach for data analysis.
Identifying the managerial and the technical recommendations to be utilized mainly based on digital disruption technologies, tools, and processes.
Healthcare has been slow in embracing digital disruption and transformation. In most areas, it is still in the initial stages. Recommendations are based on the UAE cases, highlighting the specific technologies and their features.
随着电子病历系统（EMR）中的医疗数据量急剧增加，医疗服务提供者读取这些数据所需的时间也以相同的比例增长。这意味着医生必须再次以精确的比例增加为每位患者节省的时间。这可能会影响针对患者采取的行动方案的准确性和质量。增加医生为一位患者所需的时间意味着医生能看的患者数量减少。这将给医疗管理部门带来问题，因为需要更多医生，且费用也会更高。
这里出现的两个问题是：1. 确定医疗保健领域进行广泛数据分析的潜在机会和挑战。2. 评估分析大型医疗数据的不同方法。
作者确定了代表四个潜在解决方案维度的四个相关方来回答这两个问题。这些相关方分别是：1. 医生；2. 健康信息系统管理（HISM）部门，主要是电子病历系统；3. 健康管理部门；4. 相关健康信息系统（HIS）各方。进行了文献综述并开展了25次访谈。访谈涵盖：1. 两个全球组织：约翰·霍普金斯大学和国际联合委员会（JCI）；2. 三个阿联酋的健康组织：阿布扎比卫生部、阿布扎比SEHA、迪拜卫生局（DHA）；3. 10名不同专业的医生；4. 五名电子病历经理；5. 五名代表HIS各方的信息技术（IT）专业人员。采用定性分析作为数据分析方法。
确定主要基于数字颠覆技术、工具和流程来利用的管理和技术建议。
医疗保健行业在接受数字颠覆和转型方面一直进展缓慢。在大多数领域，仍处于初始阶段。建议基于阿联酋的案例，突出了特定技术及其特点。
