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Related Concept Videos

Data Reporting and Recording01:24

Data Reporting and Recording

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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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Health Literacy01:21

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Health literacy is an individual's or a community's capacity to comprehend, receive, read, and use relevant healthcare information and services. The World Health Organization (WHO, 2018) defines health literacy as the cognitive and social skills that determine the ability of individuals to gain access to, understand, and use information in ways that promote and maintain good health. As a result, the WHO helps individuals manage long-term health concerns, participate in preventative...
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How Data are Classified: Categorical Data01:11

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A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
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How Data are Classified: Numerical Data00:59

How Data are Classified: Numerical Data

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Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
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Purpose of Health Records I01:11

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The vital purpose of health records is to provide a complete and accurate account of a patient's medical history, including communication, diagnostic and therapeutic orders, care planning, research, and quality review.
Here's a breakdown of how health records serve these purposes:
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Purpose of Health Records II01:19

Purpose of Health Records II

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Health records serve various essential purposes in the healthcare system. Here are some key purposes:
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[Generalize the experimental approach provided for in Article 51].

Soins; la revue de reference infirmiere·2022
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[Health data].

Dominique Polton1

  • 1Institut national des données de santé (INDS), 19, rue A. Croquette, 94220 Charenton, France.

Medecine Sciences : M/S
|June 15, 2018
PubMed
Summary

Big data in healthcare offers innovation for patients and systems by accelerating research and improving treatments. However, ethical considerations and data integration challenges must be addressed for successful implementation.

Area of Science:

  • Health Informatics
  • Big Data Analytics
  • Healthcare Management

Background:

  • Big data applications in healthcare promise significant innovation for patient benefit and system efficiency.
  • Healthcare analytics can accelerate research, enhance disease understanding, refine treatments, and support personalized medicine and clinical decision-making.
  • Patient data access empowers individuals and informs public discourse, but raises societal, economic, and ethical concerns regarding digitization, data usage, algorithms, and artificial intelligence.

Purpose of the Study:

  • To highlight the strategic importance of collecting and analyzing healthcare system data.
  • To discuss the potential and challenges of big data in healthcare innovation.
  • To evaluate the role of national health data systems in leveraging healthcare data.

Main Methods:

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  • Review of the potential applications and implications of big data in the healthcare sector.
  • Analysis of the French National System of Health Data as a case study for national data warehousing.
  • Identification of challenges and areas for improvement in healthcare data collection and analysis.

Main Results:

  • Big data analytics offers substantial potential to revolutionize healthcare through improved R&D, personalized medicine, and clinical decision support.
  • The French National System of Health Data represents a valuable national asset for population-level health data analysis.
  • There is a recognized need to augment existing national data systems with electronic health record data for a more comprehensive view of patient care pathways.

Conclusions:

  • The strategic collection and analysis of healthcare data are crucial for national health systems.
  • Integrating diverse data sources, including electronic health records, is essential to fully realize the benefits of big data in healthcare.
  • Addressing ethical and societal impacts is paramount for the responsible advancement of data-driven healthcare innovation.