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Nursing Clinical Information System01:27

Nursing Clinical Information System

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Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
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Methods of Documentation VI: Case Management Model01:15

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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.
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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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Nursing documentation encompasses various formats designed to capture precise patient data, facilitate communication among healthcare team members, and ensure comprehensive and accurate patient records. Let's explore each of these formats in detail:
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Data Collection III01:05

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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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A simple versatile solution for collecting multidimensional clinical data based on the CakePHP web application

Martin Biermann1

  • 1Nuclear Medicine and PET Centre, Department of Radiology, Haukeland University Hospital, N-5021 Bergen, Norway; Section for Radiology, Clinical Institute I, University of Bergen, Bergen, Norway.

Computer Methods and Programs in Biomedicine
|February 11, 2014
PubMed
Summary
This summary is machine-generated.

A new web-based database application offers a flexible, low-cost solution for managing research data in non-Good Clinical Practice (GCP) clinical studies. This system simplifies data handling for researcher-initiated projects, improving efficiency and accessibility.

Keywords:
CakePHPClinical Data Management SystemInvestigator-initiated clinical researchPHPWeb application framework

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Area of Science:

  • Clinical Research Informatics
  • Database Management Systems
  • Web Application Development

Background:

  • Good Clinical Practice (GCP) compliant Clinical Data Management Systems (CDMS) are ill-suited for small, researcher-initiated non-GCP studies.
  • Managing multidimensional research data in non-GCP projects presents unique challenges.

Purpose of the Study:

  • To develop a flexible, low-cost, and user-friendly database application for managing research data in non-GCP clinical studies.
  • To provide a solution that addresses the limitations of traditional CDMS in smaller research settings.

Main Methods:

  • Developed a client-server database application using the CakePHP framework and a MySQL backend with a five-table data model.
  • Implemented a web-based graphical user interface accessible within hospital networks, featuring data validation and interactive import.
  • Integrated automatic data anonymization and secure key list management, with data analysis via an Open Database Connectivity (ODBC) interface.

Main Results:

  • The application has been successfully applied to seven diverse clinical research projects since its 2011 pilot.
  • Demonstrated feasibility in managing data for various conditions, including thyroid and prostate cancer.
  • The system proved to be a feasible, flexible, low-cost, and user-friendly solution for non-GCP data management.

Conclusions:

  • Generic web application frameworks offer a viable approach for developing effective data management solutions in researcher-initiated non-GCP clinical projects.
  • The developed application provides a practical and efficient method for handling complex research data, enhancing data integrity and accessibility.
  • This approach lowers the barrier for conducting well-managed clinical research outside of strict regulatory frameworks.