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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. The overall aim of the PAsTAs project is to “keep the patient out of hospital by improving patient trajectories in primary care”.
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 PAsTAs use 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.
A In PAsTAs a patient trajectory is defined as 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 patient trajectories consist of data from electronic health-care records (EHR).
The over all objective of the entire PAsTAs project is to the developed final web interface is to visualize one patient’s trajectory for a specific time interval in such a way that the patients can easily recognize and understand their own timelines. It should also be possible to make the trajectories abstract enough that they can be shown to the public without revealing individual patients’ anonymityFor more information on the PAsTAs project, see http://telemed.no/pastas-pasientforloep.5219575-247951.html.
The project task:
In our part of the project we will focus this project the focus will be on identifying the most common trajectories patients with chronic diseases go through. We The project will involve identify dentifying clusters of actual care trajectory, and write a methodology paper on the summarization of patient trajectories.
Method:
Make a complexity-index based on the following variables: Diagnoses, GP visits, Hospital Visits, Days in Hospital, Personal Plan, Number of Public Services, etc. (to summarize the patient trajectories).
Another approach is to look at patients with identical diagnoses, but different care and outcomes.
Co-supervisor: Øystein Nytrø