Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Hospitals-I01:28

Hospitals-I

2.2K
Hospitals offer medical and surgical care to the sick and injured, along with accommodation while they recover. At the same time, they also provide outpatient, emergency, psychiatric, and rehabilitation services to meet various community needs. In addition to providing medical care, hospitals also act as hubs for medical research and training. Hospitals use clinical procedures and evidence-based practice standards to deliver patient care. To deliver safe and efficient care, a nurse must stay up...
2.2K
Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

1.9K
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...
1.9K
Hospitals-II00:59

Hospitals-II

1.3K
Hospitals provide inpatient and outpatient services. Inpatient services provide care to patients that stay in the hospital for an extended period, ranging from days to months. Examples of inpatient services include intensive care units, hospital wards, or surgeries. Outpatient services provide care to patients who come to a hospital for a diagnostic or treatment but do not stay overnight —for example, diagnostic tests, surgical procedures, or health education.
Nurses that work in...
1.3K
Wilcoxon Signed-Ranks Test for Matched Pairs01:09

Wilcoxon Signed-Ranks Test for Matched Pairs

638
The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
638
Errors occurring during blood pressure monitoring01:25

Errors occurring during blood pressure monitoring

1.8K
Blood pressure monitoring is a crucial clinical procedure in diagnosing and managing various cardiovascular conditions. Despite its significance, the accuracy of blood pressure measurements can be compromised by multiple factors, potentially leading to either falsely high or low readings. These inaccuracies are critical as they can significantly impact patient care. So, it is vital to understand these challenges deeply and adopt strategic approaches to minimize errors.
Several factors...
1.8K
Ethical Standards II01:23

Ethical Standards II

1.4K
Ethical standards are the backbone of nursing practice, guiding nurses as they interact with patients, families, and colleagues. These standards are crucial for providing safe, empathetic care centered on the patient's needs.
Nurses are entrusted with upholding various ethical principles and standards. Nurses forge solid therapeutic relationships using trust, empathy, autonomy, confidentiality, and professional competence.
Confidentiality is crucial, embodying respect for individual privacy...
1.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Mortality Risk Between Ages 11 and 22 Years Among Young People With Neurodisability in England: A National Cohort Study Using Linked Health and Education Data.

Paediatric and perinatal epidemiology·2026
Same author

Migraine and risk of adverse obstetric outcomes: a matched cohort study of English linked electronic health records.

BMC medicine·2026
Same author

Prevalence of multiple morbidities and cancers in individuals with Down syndrome: A matched descriptive study using linked electronic health record data.

PloS one·2026
Same author

Autoimmune diseases and risk of adverse pregnancy outcomes: a population-based cohort study of five million pregnancies in the UK.

BMC medicine·2026
Same author

Is health human resource strain associated with the prevalence of healthcare-associated infections in England? Analysis of a national point prevalence survey.

The Journal of hospital infection·2026
Same author

Whole population cohorts vs sampled comparators designs for evaluating health and educational outcomes of children with inborn rare conditions: a simulation study.

Journal of clinical epidemiology·2026

Related Experiment Video

Updated: Apr 19, 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

15.5K

Identifying Possible False Matches in Anonymized Hospital Administrative Data without Patient Identifiers.

Gareth Hagger-Johnson1, Katie Harron2, Arturo Gonzalez-Izquierdo3

  • 1Centre for Paediatric Epidemiology and Biostatistics, UCL Institute of Child Health, Centre of Paediatric Epidemiology and Biostatistics, London, UK.

Health Services Research
|December 20, 2014
PubMed
Summary
This summary is machine-generated.

This study identified data linkage errors in UK hospital records, finding rare false matches. Simultaneous admissions at different hospitals were the most common error, particularly for infants with missing data or preterm births.

Keywords:
Computerized patient medical recordsdata linkagedata qualitymedical errors

Related Experiment Videos

Last Updated: Apr 19, 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

15.5K

Area of Science:

  • Health Informatics
  • Data Quality Management
  • Clinical Data Linkage

Background:

  • Accurate patient identification is crucial for healthcare data analysis.
  • Data linkage algorithms aim to connect patient records but can introduce errors.
  • False matches, where different patients share an identifier, pose a significant challenge.

Purpose of the Study:

  • To identify data linkage errors, specifically false matches, within large-scale UK hospital administrative data.
  • To investigate the frequency and characteristics of implausible clinical scenarios indicative of false matches.

Main Methods:

  • Utilized Hospital Episode Statistics (HES) data for infants and adolescents in England.
  • Applied a pseudo-anonymization algorithm for record linkage.
  • Defined six clinically implausible scenarios to detect potential false matches, including simultaneous admissions and re-admission after death.

Main Results:

  • Possible false matches were rare (0.1% in infants).
  • Simultaneous admission at different hospitals was the most frequent false match scenario for both infants and adolescents.
  • Factors influencing false matches included missing data, preterm birth, ethnicity, sex, and patient age.

Conclusions:

  • Clinically implausible scenarios can effectively identify potential data linkage errors.
  • Proactive identification and mitigation of false matches during data cleaning are essential for data integrity.
  • Understanding the characteristics of false matches aids in refining data linkage processes.