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lwjohnst86 committed Mar 8, 2024
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Expand Up @@ -27,3 +27,48 @@ These are the guiding principles for this package:
is a data frame, the output is a data frame).
4. Functions have consistent naming based on their action.
5. Functions have limited additional arguments.

## Use cases

We make these assumptions on how this package will be used, based on our
experiences and expectations for use cases:

- Entirely used within the Denmark Statistics (DST) or the Danish
Health Authority's (SDS) servers, since that is where their data are
kept.
- Used by researchers within or affiliated with Danish research
institutions.
- Used specifically within a Danish register-based context.

Below is a set of "narratives" or "personas" with associated needs that
this package aims to fulfil:

- "As a researcher, ..."
- "... I want to determine which registers and variables to
request from DST and SDS, so that I am certain I will be able to
classify diabetes status of individuals in the registers."
- "... I want to easily and simply create a dataset that contains
data on diabetes status in my population, so that I can begin
conducting my research that involves persons with diabetes
without having to tinker with coding the correct algorithm to
classify them."
- "... I want to be informed early and in a clear way whether my
data fits with the required data type and values, so that I can
fix and correct these issues without having to do extensive
debugging of the code and/or data."

## Core functionality

This is the list of functionality we aim to have in the osdc package

1. Classify individuals type 1 and type 2 diabetes status and create a
data frame with that information.
2. Provide helper functions to check and process individual registers
for the variables required to enter into the classifier.
3. Provide a list of required variables and registers in order to
calculate diabetes status.
4. Provide validation helper functions to check that variables match
what is expected of the algorithm.
5. Provide a common and easily accessible standard for determining
diabetes status within the context of research using Danish
registers.

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