Related Experiment Video

Updated: Jan 27, 2026

In Vivo Protocol of Controlled Subconcussive Head Impacts for the Validation of Field Study Data
06:14

In Vivo Protocol of Controlled Subconcussive Head Impacts for the Validation of Field Study Data

Published on: April 18, 2019

6.9K

Impact of Prescription Data on Administrative Data Case Definitions of Pediatric Type 1 and 2 Diabetes: A Validation

Jeffrey N Bone1, Qian Zhang2, Joseph Leung3

  • 1British Columbia Children's Hospital Research Institute, Vancouver, British Columbia, Canada; Department of Statistics, University of British Columbia, Vancouver, British Columbia, Canada.

Canadian Journal of Diabetes
|January 25, 2026
PubMed

Insights

The Canadian Chronic Disease Surveillance System (CCDSS) definition underestimates pediatric diabetes cases in British Columbia. An expanded definition, including prescription data, improves case identification and accuracy for public health surveillance.

Area of Science:

  • Pediatric Endocrinology
  • Public Health Surveillance
  • Health Informatics

Background:

  • Accurate diabetes case definitions are crucial for population surveillance and public health decision-making.
  • Administrative data is commonly used for diabetes surveillance.
  • The Canadian Chronic Disease Surveillance System (CCDSS) utilizes specific case definitions.

Purpose of the Study:

  • To compare the existing CCDSS diabetes definition with an expanded definition in a pediatric population in British Columbia (BC).
  • To assess the accuracy and completeness of the CCDSS definition for pediatric diabetes cases.

Main Methods:

  • Retrospective, population-level study using linked administrative databases in BC (1996-2024).
  • Linked a sub-cohort with the BC Pediatric Database Registry (BCPDR) for validation.
  • Compared the CCDSS definition (hospital/physician claims) with an expanded BC definition (including prescription data).

Main Results:

  • The CCDSS definition identified 6716 diabetes cases.
  • The expanded BC definition identified 1074 additional cases (16.0% increase).
  • The expanded definition showed higher sensitivity (94.0%) compared to the CCDSS definition (72.7%) against the gold standard BCPDR.

Conclusions:

  • The CCDSS definition undercounts pediatric diabetes cases and includes false positives.
  • An expanded definition incorporating prescription data enhances case ascertainment for pediatric diabetes.
  • Improved case definitions are necessary for accurate public health surveillance of pediatric diabetes.
Abstract

Keywords:
administrative datadiabète pédiatriquedonnées administrativespediatric diabetesvalidation

More Related Videos

A High-Throughput Multiplexed Screening for Type 1 Diabetes, Celiac Diseases, and COVID-1906:46

A High-Throughput Multiplexed Screening for Type 1 Diabetes, Celiac Diseases, and COVID-19

Published on: July 5, 2022

3.2K
Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance04:58

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance

Published on: December 13, 2024

4.0K

Related Concept Videos

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...
6.4K
Data Validation01:15

Data Validation

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:
750
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...
1.6K
Diabetes Mellitus: Type 2 and Gestational01:22

Diabetes Mellitus: Type 2 and Gestational

Type 2 diabetes, characterized by insulin resistance, arises when the insulin receptors on cells lose responsiveness to insulin, diminishing the cell's capacity to take up glucose, resulting in elevated blood glucose levels. To receive a diagnosis of Type 2 diabetes, a series of blood glucose tests are necessary to assess whether the blood glucose falls within normal parameters. If the result is out of the normal range, a patient may be diagnosed as prediabetic or diabetic, depending on the...
4.4K
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.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
37.2K
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

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...
43.3K