PASTAs (Patient Trajectories, or "Pasientforløp") is a project that is analyzing what happens to chronically ill patients, as they are moved between their primary doctor, the hospital, and other services offered by the local government.
Currently, the information about single patients is not coordinated between hospitals and other services, so it is difficult to do research about what combination of services is best for chronically ill patients.
In this project we work with data from doctors, home care services and hospitals to identify how patients move between these instances and how small differences can affect the health of the patients.
THE PROJECT TASK:
Design and implement a web-based application in Java (or HTML5), that visualizes a patient’s trajectory with the use of data from electronic health-care records (EHR).
A patient trajectory is a sequence of (possibly parallel) health care events like hospitalization, visiting the doctor, receiving public health services, getting diagnosed, taking medicine, etc. These events are connected to specific times or intervals of times in the patient’s life.
The overall objective of the application is to visualize one patient’s trajectory for a specific time interval, in a way that the patient can easily recognize. The dialog with the patient will be related to the visualized trajectory. The system should be able to ask the patient for feedback about specific health care events, or for sequences of events.
The EHR data will be made available in an Event-Stream format, see https://www.ntnu.no/wiki/pages/viewpage.action?pageId=55739223
The specifications for the prototype system will be based on a report from a user-design-workshop to be held in August 2013, and on interviews with a patient usergroup. Both patients and scientists are defined as users of this application.
For more information on the PAsTAs project, see http://telemed.no/pastas-pasientforloep.5219575-247951.html
The overall aim of the PAsTAs project is to “keep the patient out of hospital by improving patient trajectories in primary care”.
The project can be done in collaboration with Øystein Nytrøs projects on Health Records and Anonymization.
Co-supervisor: Øystein Nytrø