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Related Concept Videos

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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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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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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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 Validation01:03

Data Validation

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Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
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Data Validation01:15

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Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
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Gold Nanoparticle Synthesis
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Data is the New Gold!

Ashit V Hegde1

  • 1Department of Critical Care Medicine, PD Hinduja Hospital and Medical Research Centre, Mumbai, Maharashtra, India.

Indian Journal of Critical Care Medicine : Peer-Reviewed, Official Publication of Indian Society of Critical Care Medicine
|August 23, 2019
PubMed
Summary
This summary is machine-generated.

Data is crucial in modern healthcare, offering valuable insights for improved patient care and medical advancements. Leveraging data effectively can revolutionize critical care medicine and drive innovation.

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Area of Science:

  • Critical Care Medicine
  • Health Informatics
  • Data Science in Healthcare

Background:

  • The abstract emphasizes the immense value of data in contemporary medical practice.
  • It highlights data as a fundamental asset, akin to 'gold,' for advancing healthcare.
  • The context is the Indian Journal of Critical Care Medicine, indicating a focus on intensive care settings.

Discussion:

  • The article posits that data is the new gold, underscoring its transformative potential.
  • This perspective suggests a shift towards data-driven decision-making in critical care.
  • The implications span from operational efficiency to clinical outcomes.

Key Insights:

  • Data holds significant, untapped potential in critical care medicine.
  • Effective utilization of data can lead to substantial improvements in patient management.
  • The concept positions data as a primary resource for medical innovation.

Outlook:

  • Future research should focus on data analytics and interpretation in critical care.
  • Developing robust data infrastructure is essential for realizing data's full potential.
  • The integration of data science principles will likely shape the future of critical care medicine.