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Data Collection I01:30

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Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...
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Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
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The physical assessment examines the patient for objective data that defines the patient's condition, and aids in formulating the nursing care plan. The purpose of physical assessment is a health status appraisal, which includes identifying health problems, and establishing a database for nursing intervention.
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The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
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From Numbers to Insights: Developing a Visual Cohort Explorer for Feasibility Requests.

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Summary
This summary is machine-generated.

This study developed a visual tool for local FDPG feasibility portal data, enhancing cohort understanding while maintaining patient anonymity. The SQL method proved faster than FHIR for data extraction and visualization.

Keywords:
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Area of Science:

  • Medical Informatics
  • Health Data Visualization
  • Clinical Research Infrastructure

Background:

  • The German Portal for Medical Research Data (FDPG) feasibility portal aids national patient cohort identification.
  • Local installations of the FDPG feasibility portal address site-specific queries.
  • Visualizing local cohort data enhances interpretation and comprehensibility while preserving anonymity.

Purpose of the Study:

  • To develop a visual representation of local FDPG feasibility portal cohorts.
  • To address the challenge of providing cohort insights while ensuring data anonymity.
  • To enhance the accuracy and comprehensibility of local feasibility data.

Main Methods:

  • Utilized Medical Informatics Initiative (MII) tools and the local feasibility portal.
  • Developed an interactive R Shiny dashboard using fhircrackr, echarts4r, and plotly.
  • Visualized patient data including gender, diagnoses (ICD-10-GM), labs (LOINC), procedures (OPS), and medication (ATC).

Main Results:

  • Two data extraction variants (FHIR and SQL) were developed and successfully visualized cohort data.
  • The interactive Shiny app provided visualizations validated by clinical experts.
  • Both methods enabled effective visualization of local patient cohort characteristics.

Conclusions:

  • The SQL approach demonstrated superior processing time compared to FHIR for large-scale data.
  • FHIR offers greater flexibility for cross-site deployment.
  • The developed visualization tool is suitable for local deployment, though national implementation requires further development and infrastructure improvements.