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Related Concept Videos

Censoring Survival Data01:09

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different reasons...
Ethical Standards I01:25

Ethical Standards I

The American Nurses Association (ANA) created and implemented the first nationally accepted Code of Ethics for Nurses with Interpretive Statements. The Code of Ethics is a living document regularly updated by the ANA and establishes an ethical standard that is non-negotiable for nurses in all roles and settings.
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Data Reporting and Recording01:24

Data Reporting and Recording

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...
Data Collection I01:30

Data Collection I

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 data...
Data: Types and Distribution01:19

Data: Types and Distribution

In biostatistics, data are the observations collected for analysis. There are two main types: parametric and non-parametric. Parametric data, which include continuous (e.g., weight) and discrete numerical data (e.g., number of tablets), assume a particular distribution pattern, often the normal distribution. Non-parametric data do not adhere to a specific distribution and typically comprise nominal (e.g., gender) and ordinal categorical data (e.g., pain scale ratings).
Distributions in...
How Data are Classified: Numerical Data00:59

How Data are Classified: Numerical Data

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.
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Related Experiment Video

Updated: Jul 5, 2026

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

In defense of data.

Andy Slavitt1, David Ostler

  • 1UnitedHealth Group's Ingenix, USA.

AHIP Coverage
|May 21, 2008
PubMed
Summary
This summary is machine-generated.

Ingenix aims to improve healthcare by providing better health care information. This includes addressing how out-of-network physician charges are calculated for consumer reimbursement.

Related Experiment Videos

Last Updated: Jul 5, 2026

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

Area of Science:

  • Health Services Research
  • Health Economics
  • Health Information Systems

Background:

  • Ingenix is involved in providing health care information.
  • The company is under scrutiny regarding the use of physician billed charge data.
  • This data is used to determine out-of-network reimbursement rates.

Purpose of the Study:

  • To highlight the importance of accurate health care information.
  • To address the issue of calculating out-of-network physician charges and reimbursement.
  • To advocate for improvements in the healthcare system through enhanced information availability.

Main Methods:

  • Analysis of physician billed charge data.
  • Investigation into "reasonable and customary" charge calculations.
  • Examination of healthcare information dissemination.

Main Results:

  • The use of physician billed charge data for out-of-network reimbursement is a contentious issue.
  • Current methods for calculating "reasonable and customary" charges are under review.
  • There is a recognized need to improve the quality and quantity of health care information.

Conclusions:

  • Improving health care information accessibility is crucial for participants.
  • Addressing out-of-network reimbursement is part of a larger effort to enhance the healthcare system.
  • Enhanced data transparency and availability can lead to a more efficient and equitable healthcare system.