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+---
+title: "Published our first externally collaborated R package, osdc"
+description: |
+    Over the last two year, we've collaborated with a researcher at Steno Aarhus on building an
+    R package called osdc. This package, titled
+    *Open Source Diabetes Classifier*, classifies diabetes status in the
+    Danish registers. And finally, we've published it to CRAN!
+author:
+- Luke W. Johnston
+date: "2025-12-18"
+categories:
+  - packaging
+  - publishing
+  - programming
+---
+
+On December 10th, 2025, we finally published our first R package to
+[CRAN](https://cran.r-project.org/)! :tada:
+
+The package is called
+[osdc](https://cran.r-project.org/web/packages/osdc/index.html), or
+"Open Source Diabetes Classifier", and it is our first package that
+we've built in collaboration with an external researcher, [Anders Aasted
+Isaksen](https://www.stenoaarhus.dk/kontakt/anders-aasted-isaksen/). He
+developed an algorithm to classify type 1 and type 2 diabetes using
+Danish registers as data sources, and we worked together to turn this
+algorithm into an R package that others can use. We started the
+collaboration back in 2023, and after a lot of work, we finally got it
+to a stage that we could publish a first version to CRAN.
+
+The package has two aims (as described in the package
+[documentation](https://steno-aarhus.github.io/osdc/)):
+
+1.  To provide an open-source, code-based algorithm to classify type 1
+    and type 2 diabetes using Danish registers as data sources. There
+    are other diabetes algorithms developed in Denmark for the
+    registers, but they are not open source nor packaged into a reusable
+    format.
+2.  To inspire discussions within the Danish register-based research
+    space on the openness and ease of use on the existing tooling and
+    registers, and on the need for an official process for updating or
+    contributing to existing data sources.
+
+## Who is it for and why use it?
+
+The main reason for building the osdc package was to provide a tool for
+researchers doing diabetes research with Danish register data to
+classify diabetes. There are no Danish registers that fully captures the
+different ways that a person could be classified with diabetes, as
+administrative diagnosis data is not always complete nor accurate. So,
+researchers have had to develop different algorithms to get a better
+idea of who has diabetes in the Danish registers.
+
+However, these algorithms have not been open source, and they have not
+been packaged into reusable tools. Which has lead to many researchers
+having different "in-house" solutions for their group or organisation
+that other groups can't really use effectively. We wanted to change
+that.
+
+So, we built the osdc package with all the necessary details for
+researchers to classify diabetes status in their own Danish register
+data. For example, the package provides a list of which registers and
+variables are needed with the use of the `registers()` function. Other
+than a few other helper functions, the main function of the package is
+`classify_diabetes()`, which takes all the required registers and
+outputs a data frame with a list of individuals, their diabetes status,
+and the date when the classification was made.
+
+Aside from those functions, the package provides an `algorithm()`
+function that lists all the specific criteria used in the algorithm.
+This makes it easier for others to assess how exactly the algorithm
+classifies diabetes.
+
+The next step is to start using the osdc package in collaborating
+projects that use Denmark Statistics and register data :tada: