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Clinical Data Flow in Botswana Clinics: Protocol for a Mixed-Methods Assessment
The World Health Organization has further emphasized the importance of electronic health records (EHRs) toward the achievement of Universal Health Coverage and health-related sustainable development goals [3]. In the United States and other high-income countries, EHRs capture 90% or more of these data. However, in low- and middle-income countries, the percentage is much smaller but steadily increasing. Despite the documented benefits of EHRs, a number of concerns have been raised.
JMIR Res Protoc 2024;13:e52411
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To achieve a more objective, cost-effective, and resource-efficient identification of patients with postoperative infections, it is imperative to leverage the electronic health records (EHRs) to automatically detect patients with infections without human checking on high-risk patients based on readily available EHR data. Different types of data are present within the EHR, including structured, tabular, and free-text records in which diagnoses and clinical symptoms are reported.
JMIR Med Inform 2024;12:e57195
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Typically, health care data such as captured in EHRs are collected for continuity of clinical care, coding, and billing purposes, and not necessarily to answer specific research questions. Thus, the quality of data collected in EHRs may be sufficient for clinical purposes but may not meet the needs of a researcher or population health intervention.
JMIR Med Inform 2024;12:e56734
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The DICs are crucial in gathering, harmonizing, and integrating clinical data from various source systems, including electronic health records (EHRs), clinical imaging systems, and other health-related databases. Additionally, the DICs’ efficient data pipelines support uniform and secure data storage, enabling significant privacy-preserved sharing and analysis of patient data.
JMIR Med Inform 2024;12:e57153
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Absent complete (or a representative random) sampling of a population of people living with HIV, one may turn to EHRs from various clinics to estimate population VL. A given health department might wish to know the distribution of VL among people living with HIV in its jurisdiction but only have a single HIV care program that serves the community. As such, the ability to estimate population VL from a single EHR may be of value.
Online J Public Health Inform 2024;16:e58058
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Using electronic source data opens a new path to extract patients’ data from electronic health records (EHRs) and transfer it directly to EDC systems (often the method is referred to as e Source) [4]. e Source technology in a clinical trial data flow can improve data quality without compromising timeliness [5]. At the same time, improved data collection efficiency reduces clinical trial costs [6].
e Source can be divided into two levels.
JMIR Med Inform 2024;12:e52934
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In many countries, health care professionals are legally obligated to share information from electronic health records (EHRs), including clinical notes, medications, and test results with patients [1,2]. This information is often shared through patient portals and aligns with the growing focus on patient-centered care and patient engagement to improve health care services and individual health outcomes, such as quality of life and mental health status [3,4].
JMIR Ment Health 2024;11:e57965
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