Growthcleanr

Growthcleanr

Module 1 Overview
Unit 1
Introduction 
Module 2 Getting started
Unit 1
How to use this toolbox 
Module 3 Audiences/roles
Unit 1
Researchers 
Unit 2
Network partners 
Unit 3
Legal 
Unit 4
Implementers
Unit 5
Participants
Module 4 Tools
Unit 1
Growthcleanr 
Unit 2
GrowthViz 
Unit 3
CODI Prevalence Queries 
Unit 4
Privacy Preserving Record Linkage 
Unit 5
CODI use cases and queries 
Unit 6
CODI Resources 
Module 5 Standards
Unit 1
Data models 
Unit 2
FHIR Implementation Guides
Module 6 References
Unit 1
CODI References

Who should use Growthcleanr?

Anyone who wants to clean height and weight data from electronic health record (EHR) systems should use Growthcleanr.  

These roles should use Growthcleanr:

Researchers and public health organizations that want to use individual tools, processes and standards to leverage the CODI architecture to request data
View Researchers Path
Current and future CODI implementers including network partners
View Network Partners Path
Clinical care providers or community organizations seeking a deeper understanding of the health and data landscape in their region
View Implementers Path

What is Growthcleanr? 

It is an R package with programs for cleaning height and weight data collected from electronic health record (EHR) systems. The tools support cleaning anthropometric measures for individuals 0 to 65 years of age.2 Height and weight measurements are critical for the study of conditions that rely on understanding children’s overall growth pattern. Unfortunately, these measurements are subject to data errors including swapped values, incorrect units and misplaced decimal points. All can result in messy data that muddle the child’s actual growth trajectory over time. The Growthcleanr method helps prepare height and weight data sets for secondary uses such as research or surveillance.

Why use Growthcleanr?

Growthcleanr takes a manual process that typically takes months and automates the process into something that takes minutes or hours depending on the data and compute power. In addition, height and weight datasets from EHRs are often used to facilitate growth research; however, measurement and recording errors can lead to misleading results. Growthcleanr offers an automated method for identifying biologically implausible values in pediatric EHR growth data.3

How to use Growthcleanr

Details on how to get started and advanced topics can be found on the Growthcleanr GitHub page. Select the correct Growthcleanr version for the age group you are working with. To start running Growthcleanr, an R installation with a variety of additional packages is required, as is a growth measurement dataset prepared for use in Growthcleanr. Growthcleanr also comes with a sample synthetic data set which can be used to learn the package and test their code.

R Package

R package contains code, data and documentation that can be installed by users of R. This package processes data to identify biologically implausible height and weight measurements. Results from Growthcleanr include a flag for each measurement indicating whether it is to be included or excluded based on plausibility, of specific types of exclusions identified distinctly. To run Growthcleanr, an R installation is required. Growthcleanr also comes with a sample synthetic data set which can be used to learn the package and test the code. To read more about the specifics of the R package, visit GitHub.
 

User videos

Watch a demonstration with a subject matter expert (SME) that introduces Growthcleanr, a free and open-source program used to clean height/weight values from electronic health record (EHR) data for ages 0-65.

View instructions on how to install Growthcleanr, prepare your data, run the program, and review your results.