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Related Concept Videos

Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

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The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic...
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Data Reporting and Recording01:24

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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...
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Methods of Documentation I: Source-Oriented Records01:18

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Source-oriented records, or SOR, are medical record-keeping organized by the data source. The SOR system was first developed in the mid-1900s to organize the growing patient data in hospitals and other healthcare facilities.
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Key Attributes include the following:
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Formats for Nursing Documentation01:28

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• It includes patient demographics, medical history,...
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Methods of Documentation IV: Focus Charting01:26

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Focus Charting, also known as the focus charting system or "focus documentation," is a systematic documentation approach used in healthcare to organize patient information in medical records.
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Methods of Documentation VII: EMR01:30

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Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare...
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Related Experiment Video

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Routine Collection of High-Resolution cryo-EM Datasets Using 200 KV Transmission Electron Microscope
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rBEFdata: documenting data exchange and analysis for a collaborative data management platform.

Claas-Thido Pfaff1, Birgitta König-Ries2, Anne C Lang1

  • 1Department of Special Botany and Functional Biodiversity, University of Leipzig Johannisallee 21, 04103, Leipzig, Germany.

Ecology and Evolution
|August 26, 2015
PubMed
Summary
This summary is machine-generated.

The rBEFdata R package enhances scientific reproducibility by linking primary research data with derived data products. This tool facilitates data discovery, download, and upload, improving the documentation of data postprocessing steps.

Keywords:
Biodiversity ecosystem functioningRdata postprocessingdata sharingecological metadata languagemetadataopen scienceopen sourcepaper proposalsreproducible sciencesemantic integrationworkflow

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Area of Science:

  • Data Science
  • Bioinformatics
  • Ecological Informatics

Background:

  • A significant gap exists between primary research data and derived data products used in scientific publications.
  • Current publication practices often lose the crucial link between derived data products and their original primary data sources.
  • Improved documentation of data postprocessing is essential for enhancing scientific accuracy and reproducibility.

Purpose of the Study:

  • Introduce the rBEFdata R package as a companion to the BEFdata platform.
  • Provide programmatic access to BEFdata features for data management and analysis within R.
  • Address the challenge of documenting data postprocessing to link primary data with derived products.

Main Methods:

  • Developed the rBEFdata R package for programmatic interaction with the BEFdata platform.
  • Implemented features for data and metadata searching, including integration with external thesauri.
  • Enabled data and metadata download/upload functionalities, including batched downloads and integration with a paper proposal mechanism.
  • Demonstrated package utility through an ecological analysis example.

Main Results:

  • The rBEFdata R package offers seamless data discovery, download, and import into R for analysis.
  • The package facilitates batched downloads and integrates with BEFdata's paper proposal mechanism for collaborative research.
  • Upload functionality allows direct attachment of derived data products and scripts from R, improving postprocessing documentation.

Conclusions:

  • The rBEFdata R package significantly enhances the ability to document data postprocessing, linking primary data with derived products.
  • Improved documentation through tools like rBEFdata increases the accuracy and reproducibility of scientific findings.
  • The package supports collaborative research by streamlining data management and discussion around research ideas.