Actors
Who and which systems are involved? Make actors “real”, since details matter. Some example actors:
Researcher AliceTiana, a PhD student doing a small single-center KWF project at the NKI (shares dataset)Postdoc, is setting up a new study project in a patient population
Amsterdam UMC
Health-RI Servicedesk
Keep in mind:
If it turns out a scenario is the same for NKI, Amsterdam UMC, or any other UMC, we can point that out or merge them. And if there are relevant differences it’s perfectly fine to have seperate scenarios.
The actors are very important. If, for example, Alice is part of a huge multi-center consortium, the steps could be very different and this may lead to a new scenario.
we can create a new scenario if this changes the scenario in a major way or create an Alternative Flow if the changes are minor
Description
Describe the scenario in textual fashion. What is the user trying to achieve?
Conditions
Are there any assumptions when we enter the scenario? For example, in a scenario where a user Alice wants to enter clinical data in an Electronic Data System, a condition could be “Alice can log into the system”. This condition itself could be the outcome of another scenario in which a login is created.
Actor perspective
Describe the scenario step-wise. How is the user interacting with other actors and the system? Break it down, keep it simple and make it really practical!
Number the steps, since this will make it more easy to refer to them and to define alternative flows. For example:
...
Alice goes to the CASTOR EDC website
...
Alice logs into CASTOR
...
She goes to the XYZ-study
...
She opens the eCRF
...
Description
Tiana wants to make sure that her data will be available for future research and wants to make sure that others understand her data and that the dataset can be used to link to other datasets as well
Conditions
Tiana is using validated data capturing software (Castor EDC) to collect her data
She is collecting different types of data that may need different types of terminology standards:
Diagnosis
symptoms
medication
co-morbidities
Values from collected blood samples
Saliva, urine, and feaces
Actor perspective
Tiana contacts Amsterdam UMC’s local Research Support to ask whether knowledge and support in choosing and applying a terminology standard or multiple terminology standards.
During a support intake, the goal of applying such standards are discussed:
As the data collection will span several years and will include 2000 patients, these data are very valuable, also for other researchers outside if the project group. Applying such standards will facilitate interoperability so that others, humans or machines, can find, interoperate, and reuse them (source: I2: (Meta)data use vocabularies that follow the FAIR principles - GO FAIR (go-fair.org))
Research Support refers the researcher:
To internal experts. Colleagues who have knowldege on systems such as CDISC (SDTM, SEND, CDASH), SNOMED CT, LOINC, etc. Not sure how much hands-on experience is present within Amsterdam UMC.
To EVA Service Center (service desk Electronic Health Record (EHR)). In the EHR (Epic), the ICD-10 codes are partially applied to some data fields. It is possible to extract parts of the data that contains standardized variables.
Might be possible to map other standards to one chosen standards.
Might be possible to use existing codebooks → referral to Jeroen Beliën and Sander de Ridder for advice on the iCRF Generator
Might be possible to collect data with standardized CRFs from Castor EDC Form Exchange. Preferably forms that have been approved by Amsterdam UMC (working group in process of evaluation).
Alternative Flow
Describe alternatives, basically when things don’t go according to your normal flow.
...