Patient Data Management
Patient Data Management - Related Videos
03:47
Workflow and Framework for Collecting and Implementing Point-of-Care Ultrasound Data in the Management of Heart Failure Patients
0 Views •
2024
This protocol presents a scalable workflow for the use of point-of-care ultrasound in the management of hospitalized and outpatient heart failure patients.
01:24
Data Reporting and Recording
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2023
Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
09:43
Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
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Cited by 5 •
2019
Many researchers generate "medium-sized", low-velocity, and multi-dimensional data, which can be managed more efficiently with databases rather than spreadsheets. Here we provide a conceptual overview of databases including visualizing multi-dimensional data, linking tables in relational database structures, mapping semi-automated data pipelines, and using the database to elucidate data meaning.
10:23
A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management
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Cited by 5 •
2023
Here, we present a protocol to utilize machine-vision software to stabilize dynamic processes during TEM imaging, while concurrently indexing multiple streams of metadata to each image into a navigable timeline. We demonstrate how this platform enables automated calibration and mapping of the electron dose over the course of an experiment.
06:43
Esophageal Heat Transfer for Patient Temperature Control and Targeted Temperature Management
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Cited by 6 •
2017
This study presents a novel method to provide efficient patient temperature control for cooling or warming patients. A single use, triple lumen device is placed into the esophagus, analogous to a standard orogastric tube, and connects to existing heat exchange units to perform automatic patient temperature management.
FAQs
Standardized data entry gives clinicians and researchers consistent ways to record the same types of information. This consistency makes records easier to compare, reduces ambiguity, and supports validation before data are used. In practice, it helps limit documentation errors and duplicated records, improving the reliability of information used for diagnosis, treatment planning, research, and population health analysis.
Data validation checks whether recorded information is sufficiently accurate and consistent for its intended use, while duplicate-record control helps prevent the same patient information from being represented multiple times. Together, these safeguards improve data quality and reduce the risk of incomplete or conflicting information influencing care coordination, clinical decisions, or institutional analyses.
Controlled access limits patient information to authorized users and supports confidentiality throughout its use and storage. Privacy safeguards are especially important because clinical data may support care, research, and population analysis while remaining sensitive. Combined with governance practices, they help institutions use information responsibly and meet regulatory requirements without treating availability and confidentiality as competing goals.
Interoperability protocols allow information to remain usable across different healthcare settings and systems. Their value extends beyond simple data exchange: they support continuity, reduce repeated documentation, and help clinicians access relevant information for coordinated care. Reliable interoperability also strengthens research and population health analysis by making information more consistent across institutional boundaries.
A reliable workflow begins with standardized entry, followed by validation and organization of the information. Data are then maintained in secure electronic health records, with access controlled according to governance and privacy requirements. Interoperability protocols help make the information available across appropriate settings. This sequence supports accurate, confidential data throughout clinical and research use.
Clinicians rely on well-managed information for diagnosis, treatment planning, and care coordination, while researchers use it for clinical studies and population health analysis. The same foundation can support evidence-based decisions and personalized care. Its usefulness depends on information remaining accurate, available to authorized users, and sufficiently consistent for the purpose being addressed.
Strong governance and reliable data quality give digital health technologies a more trustworthy information base. They also help institutions use clinical information to support evidence-based decisions and personalized care rather than relying on poorly organized records. In medicine, this connection links day-to-day documentation with broader research, population analysis, and responsible technology development.