Patient Data Capture
Patient Data Capture - Related Videos
08:40
Methyl-binding DNA capture Sequencing for Patient Tissues
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Cited by 1 •
2016
Here we present a protocol to investigate genome wide DNA methylation in large scale clinical patient screening studies using the Methyl-Binding DNA Capture sequencing (MBDCap-seq or MBD-seq) technology and the subsequent bioinformatics analysis pipeline.
12:44
CD4+ T-Lymphocyte Capture Using a Disposable Microfluidic Chip for HIV
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Cited by 5 •
2007
13:21
Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients
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Cited by 2 •
2017
This work describes an optimized methyl-CpG-binding domain (MBD) sequencing protocol and a computational pipeline to identify differentially methylated CpG-rich regions in chronic lymphocytic leukemia (CLL) patients.
06:05
The Participant-Reported Implementation Update and Score (PRIUS): A Novel Method for Capturing Implementation-Related Data Over Time
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2021
This protocol describes a novel method for collecting and analyzing data related to ongoing implementation called the Participant-Reported Implementation Update and Score (PRIUS). The PRIUS method allows for the efficient and systematic capture of data over time and from multiple viewpoints in healthcare settings.
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...
FAQs
Standardized data entry gives clinicians a consistent way to record health information, measurements, symptoms, and treatment details. Consistency makes records easier to organize, review, and validate, which helps reduce documentation errors and improves data quality. The resulting information is more usable for care planning, treatment monitoring, communication among care teams, and evidence-based decisions.
Validation checks whether recorded information is clear, organized, and suitable for clinical use. It helps identify documentation problems before data guide diagnosis, care planning, treatment monitoring, or research. When information is validated and securely handled, clinicians can use the record with greater confidence while preserving its value for communication and longitudinal care.
Different sources contribute different parts of the clinical record. Interviews provide reported symptoms and care history, while observations, clinical assessments, measurements, laboratory results, electronic health records, and connected monitoring devices add documented findings or ongoing information. Bringing these inputs together creates a more complete basis for diagnosis, treatment monitoring, and care planning.
Clear documentation preserves the meaning of patient information as care progresses and as different professionals review the record. Secure handling protects the information while it is used, and standardized entry supports consistency across records. Together, these practices help maintain data quality for longitudinal care, team communication, evidence-based decision-making, and clinical research.
Clinicians first gather relevant information through interviews, observations, assessments, laboratory results, electronic health records, or connected monitoring devices. They then record and organize the findings, apply validation to support accurate documentation, and handle the information securely. This workflow turns separate observations and results into usable records for diagnosis, planning, monitoring, and communication.
Clinical capture may include a person’s symptoms, health measurements, care history, and treatment information. Sources and tools can include patient interviews, direct observations, clinical assessments, laboratory results, electronic health records, and connected monitoring devices. These inputs support diagnosis, care planning, treatment monitoring, and the maintenance of records for longitudinal care.
It is important whenever care decisions depend on accurate, usable information, including diagnosis, care planning, and monitoring a treatment over time. It also supports communication among care teams, clinical research, and longitudinal care. Reliable records allow information gathered at different points in care to remain available for evidence-based decision-making.