-
Notifications
You must be signed in to change notification settings - Fork 1
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Merge pull request #63 from steno-aarhus/docs/explanation-docs
- Loading branch information
Showing
3 changed files
with
266 additions
and
3 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,128 @@ | ||
| --- | ||
| title: "Rationale" | ||
| output: rmarkdown::html_vignette | ||
| bibliography: references.bib | ||
| csl: vancouver.csl | ||
| vignette: > | ||
| %\VignetteIndexEntry{Rationale} | ||
| %\VignetteEngine{knitr::rmarkdown} | ||
| %\VignetteEncoding{UTF-8} | ||
| --- | ||
|
|
||
| This document explains the rationale behind the development of this | ||
| algorithm. Many of these text were taken from Anders Aasted Isaksen's | ||
| [PhD Thesis](https://aastedet.github.io/dissertation/) as well as the | ||
| validation paper [@Isaksen2023]. This document is a shorter and more | ||
| concise version of those documents. We cover the: | ||
|
|
||
| - Current state of how diabetes is identified in Danish healthcare | ||
| registers. | ||
| - Challenges faced by researchers in this area, such as the limited | ||
| transparency in how diabetes is exactly classified in these sources | ||
| and how applying or using these approaches isn't very easy. | ||
| - How this algorithm and package contributes to discussions in this | ||
| space about how diabetes in classified in Danish register research | ||
| and how it is implemented. | ||
|
|
||
| ## Identifying type 1 and 2 diabetes cases in Danish healthcare registers | ||
|
|
||
| ### Danish register data infrastructure | ||
|
|
||
| Many individual-level data (e.g. civil registration, public healthcare | ||
| contacts, and drug prescriptions) are automatically collected on all | ||
| residents in Denmark and stored in nationwide Danish registers by | ||
| [Statistics Denmark](https://www.dst.dk/da/) and the [Danish Health Data | ||
| Authority](https://sundhedsdatastyrelsen.dk/da). These agencies are | ||
| legally allowed to give access to the register data for research | ||
| purposes, which provides (authorized) researchers a set of common, | ||
| extensive data sources to use for studies. Any researcher associated | ||
| with an approved Danish research institute (mainly Danish universities) | ||
| can apply for access, but fees and conditions apply. | ||
|
|
||
| Register data is generally accessed and processed by approved | ||
| researchers on remote servers operated by Statistics Denmark and the | ||
| Danish Health Data Authority. The same raw data used by all | ||
| researchers, coupled with a common virtual working environment, | ||
| has the potential to enable reproducible research. This means that | ||
| any data processing workflow | ||
| could be transferable and reusable between research projects if the | ||
| underlying code is designed with reproducibility in mind and the code is | ||
| shared ("open-sourced") [@Marszalek2016]. While reproducibility in | ||
| research relates to transparent reporting of methods to enable others to | ||
| reproduce analyses and experiments, this also applies to a diabetes | ||
| classification program, which - if reproducible - could be reused by any | ||
| researcher with access to the necessary register data to dynamically | ||
| identify a study population of individuals with diabetes for their | ||
| research needs [@Dima2017]. | ||
|
|
||
| ### Current Danish register-based diabetes classifiers | ||
|
|
||
| In Denmark, the National Diabetes Register, established in 2006, was the first resource readily | ||
| available to researchers to use for identifying diabetes cases through register data [@Carstensen2011] . | ||
| However, it was discontinued in 2012. | ||
|
|
||
| The next resource is the [Register of Selected Chronic Diseases](https://www.esundhed.dk/Dokumentation/DocumentationExtended?id=29) (RSCD), | ||
| which was launched in 2014. It is currently the only publicly available | ||
| resource to identify diabetes cases through Danish register data (by | ||
| application to the Danish Health Data Authority). | ||
|
|
||
| ## Challenges in current classifiers | ||
|
|
||
| General-purpose registers and other administrative databases often | ||
| provide the basis of diabetes epidemiology, but they rarely contain | ||
| validated diabetes-specific data, which may introduce bias in studies | ||
| using this data. It is important to have an accurate tool to identify | ||
| individuals with diabetes in the registers, as findings may differ with | ||
| various diabetes definitions [@Nielsen2014; @Rawshani2014]. Considerable | ||
| efforts have been made towards establishing such a tool for diabetes | ||
| research in several countries, including Denmark [@Bak2021; | ||
| @HallgrenElfgren2016; @Cooper2013]. | ||
|
|
||
| In a general population, classification algorithms (classifiers) need to | ||
| not only identify type 1 diabetes as well as type 2 diabetes, but also | ||
| account for events that might lead to inclusion of non-cases, such as | ||
| the use of glucose-lowering drugs in the treatment of other conditions. | ||
| Currently, no type-specific diabetes classifier has been validated in a | ||
| general population, which leaves register-based studies in this area | ||
| vulnerable to biases. | ||
|
|
||
| In Denmark, a limitation (or flaw) of the RSCD is that it has not been | ||
| publicly validated and the source code behind the algorithm has not been | ||
| made publicly available. Notably, the algorithm lacks inclusion based on | ||
| elevated HbA1c levels [@DHDA2016]. Likewise, the National Diabetes | ||
| Register, since discontinued in 2012, had a validation study question | ||
| its validity and called for future registers to adopt inclusion based on | ||
| elevated HbA1c levels [@Green2014]. | ||
|
|
||
| Since the launch of the RSCD, nationwide laboratory data on HbA1c | ||
| testing has become available in the Danish register ecosystem | ||
| [@DHDA2018], but this data is yet to be incorporated into available | ||
| diabetes classifiers. | ||
|
|
||
| ## Diabetes classification algorithms | ||
|
|
||
| The currently available register-based diabetes classifiers have yet to | ||
| incorporate the emerging register data on routine HbA1c testing. Wishing | ||
| to take advantage of this data, we developed the Open Source Diabetes | ||
| Classifier (OSDC). Detailed discussion of the advantages and | ||
| disadvantages of it's design is found in Anders Aasted Isaksen's thesis, | ||
| in the chapter on [discussing the | ||
| methods](https://aastedet.github.io/dissertation/5-discussion-methods.html). | ||
|
|
||
| We aimed on developing this algorithm to: | ||
|
|
||
| 1. Stimulate discussion within Denmark on the openness and ease of use | ||
| of existing classifiers or diabetes registers, and on the need for | ||
| an official process for updating or contributing to existing data | ||
| sources on diabetes status. This algorithm and package may end up | ||
| not being used by official institutions, but it can serve as a | ||
| starting point on how to improve the current state of diabetes | ||
| classification in Denmark or as an inspiration for how they might be | ||
| designed. | ||
| 2. Provide an open-source, code-based algorithm as an R package to | ||
| classify type 1 and type 2 diabetes based on data from Danish | ||
| registers. We implemented it as an R package so that researchers can | ||
| easily build their own database of individuals with diabetes more | ||
| quickly than waiting for an official source to be implemented. | ||
|
|
||
| ## References |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters