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Related Concept Videos

Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

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 illness...
Documentation in Long-Term and Home Healthcare Setting01:29

Documentation in Long-Term and Home Healthcare Setting

Documentation in long-term care facilities and home healthcare settings is crucial for ensuring continuous, coordinated, and comprehensive care for patients. Each setting has its specific documentation processes and tools:
Long-Term Care Facilities
Guidelines for Nursing Documentation I01:30

Guidelines for Nursing Documentation I

Quality documentation and reporting share essential characteristics that ensure they are practical and valuable resources for those who use them. These characteristics are:
Factual:  
The following points emphasize the significance of upholding accurate and unbiased documentation in healthcare.
Data Validation01:03

Data Validation

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.
Nursing assessment guides are generally based on holistic models rather than medical...
Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters assessment...

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Related Experiment Video

Updated: Jun 6, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
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Published on: January 8, 2020

Algorithm for Improving Beneficiary Identifier Quality in Medicaid Administrative Data.

Konstantin Kunze1, Meredith C B Adams2, Robert W Hurley2

  • 1University of Rochester.

Research Square
|June 5, 2026
PubMed
Summary
This summary is machine-generated.

Linking Medicaid beneficiaries accurately across files is crucial for health policy. This study identifies and corrects key identifier problems, creating a reliable composite identifier for improved data analysis.

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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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Published on: January 11, 2020

Related Experiment Videos

Last Updated: Jun 6, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

Area of Science:

  • Health Services Research
  • Health Informatics
  • Public Health Policy

Background:

  • Accurate linkage of Medicaid beneficiaries across administrative data is vital for health policy research.
  • Existing identifiers, such as the Chronic Conditions Warehouse (CCW) and state-assigned identifiers, suffer from systematic data quality issues.
  • These data quality problems can lead to inaccurate beneficiary linkages and biased research findings.

Purpose of the Study:

  • To identify and document systematic data quality problems with Medicaid beneficiary identifiers.
  • To develop and present a structured algorithm for correcting these identifier issues.
  • To create a reliable composite identifier for accurate longitudinal tracking of Medicaid beneficiaries.

Main Methods:

  • Utilized MAX Person Summary files (1999-2015) and T-MSIS Analytic Files (2014-2022).
  • Documented four key identifier problems: reassignment, missing identifiers, discordant identifiers, and identifier clustering.
  • Developed and applied a structured algorithm to correct identified identifier defects.

Main Results:

  • Identified systematic issues including identifier reassignment, missing data, discordant values, and clustering.
  • Successfully applied a correction algorithm to enrollment, utilization, and mortality files.
  • Generated a composite identifier enabling unique and reliable tracking of beneficiaries across datasets.

Conclusions:

  • Systematic identifier problems in Medicaid data can significantly bias health policy research.
  • The developed algorithm effectively corrects these issues, enhancing data integrity.
  • The resulting composite identifier provides a robust solution for longitudinal Medicaid beneficiary tracking.