REPLACE THIS TEXT FROM CAMH: Health departments vary in their current capacity to assess and use data to improve CAMH. Therefore, this playbook has been developed to support all health departments in their CAMH work regardless of whether they are just beginning to develop a CAMH surveillance strategy or already in the process of using surveillance data to implement CAMH interventions. For example, a health department that is just beginning its CAMH work might want to start from the beginning of the playbook, whereas a health department that has already developed partnerships to enhance CAMH might benefit from reviewing the information about proposed indicators and data resources. As a result, users of this playbook are encouraged to jump in at whatever point makes sense for them.
Callouts are used for two purposes: 1) to provide real world examples where an organization has applied a recommendation from this playbook, and 2) to help bring clarity to strategies shared or indicators discussed, allowing users to see them in action. Note that some callouts provide links to additional information which lead to external resources from partners and other organizations.
Quick tips for staff are highlighted throughout the toolkit. These are useful tasks or ideas to consider. The tips appear when the mouse hovers over the icon.
References used throughout this playbook are indicated with numbers in superscript. The playbook provides a list of those references at the end to correspond with the numbers used throughout the text. Refer to this list for citation details.
What is Growthcleanr?
Growthcleanr is an R package with programs for cleaning height and weight data from electronic health record (EHR) systems. The tool supports cleaning anthropometric measures for individuals 2 to 65 years of age. The Growthcleanr method helps prepare height and weight data sets for secondary uses such as research or surveillance.
Why use Growthcleanr? The main reason to use Growthcleanr is height and weight data are prone to errors. 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
Who should use Growthcleanr? Anyone who wants to clean height and weight data from EHRs including clinical researchers, data scientists, epidemiologists and data analysts.
How to use Growthcleanr Details on how to get started and advanced topics can be found on the growthcleanr github page. 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.
R Package This 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 plausibility. To run growthcleanr, an R installation is required. To read more about the specifics of the R package visit the github site.
User Videos: User videos will be developed in the coming months by MITRE. This video will show a live demonstration with a subject matter expert voice overlay. (Recommendation to have them stored on a YouTube or Vimeo channel and then embedded on this page)
Presentation: The user presentation will be developed in the coming months by MITRE. This will be a PDF or PowerPoint file type that provides the same information the User Video provides.
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