Difference between revisions of "BingBong"
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We are to clean the DHIS2 Tracker module. This will be done by finding possible duplicate entries of the same patient, and presenting these findings to an admin. Who can choose to mark them for reconciliation or dismiss the finding. We see that we can also assist in the reconciliation. | We are to clean the DHIS2 Tracker module. This will be done by finding possible duplicate entries of the same patient, and presenting these findings to an admin. Who can choose to mark them for reconciliation or dismiss the finding. We see that we can also assist in the reconciliation. | ||
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| + | To find duplicate entries we have planned to make an algorithm which will find duplicates, also taking into account that there might be typos and such. Then, to present the results we have discussed and planned on setting up a single page frontend UI consisting of multiple react components and depending on the complexity and reusability of the data at hand we might introduce a flux structure to the project as well. | ||
Revision as of 12:23, 28 October 2016
List of group members
August Haug Hem,
Åvald Åslaugson Sommervoll,
Mahasty Assi
Summary of requirements
A Cleaning and Deduplication of Events The DHIS2 Tracker module allows people to collect individual level data. These come in two forms: 1) “Singelton” cases that are recorded only once without registration or follow-up (e.g. Outpatient data). DHIS2 calls this a single event. 2) Events linked to a person (the DHIS2 term is a Tracked Entity Instance - TEI) where you first look up a person (or register a new) who is enrolled in a health program and then follow the patient over a period, with each visit to the doctor recorded as an event, linked to the program (e.g. a TB patient). However, patients often go to different clinics for the same thing, and a lot of data is collected offline, without the possibility to check if the patient is already in the system. Therefore, there is a need to A) identify duplicate people and B) reconcile the data belonging to the same person. The task is to make a webapp which helps administrators to easily identify clear and potential duplicates (e.g. slight misspellings) and mark them for reconciliation (which the app could also assist in). A combination of automated and manual filtering/navigation. You can initially assume the number of persons and events is small enough to be handled in the client. For more advanced functionality, it is also interesting to link to server side procedures.
Time schedule
Thursday 10-12
How you are dividing tasks within the group
Wiki start: Åvald
Screenshots and screen flows
Documented learning during project
Suggested improvements to APIs etc
Link to repository
https://github.com/lax1n/INF5750-Project
Download link to sample web app
Architecture
- react
- flux (redux/alt.js)
- html, css, and javascript (ofc)
(-Bootstrap)
(-http://www.material-ui.com/#/)
Understanding
We are to clean the DHIS2 Tracker module. This will be done by finding possible duplicate entries of the same patient, and presenting these findings to an admin. Who can choose to mark them for reconciliation or dismiss the finding. We see that we can also assist in the reconciliation.
To find duplicate entries we have planned to make an algorithm which will find duplicates, also taking into account that there might be typos and such. Then, to present the results we have discussed and planned on setting up a single page frontend UI consisting of multiple react components and depending on the complexity and reusability of the data at hand we might introduce a flux structure to the project as well.
