Uses the FHIR api (http://hapi.fhir.org/) to calculate the current Quality of Life of a patient.
- Install nodeJS
- Navigate to repo using terminal e.g.
cd /dir/to/repo/QoL - In the terminal:
npm install - In the terminal:
npm start - In the browser (Chrome/Firefox/etc):
http://localhost:3000/ - In the browser (Chrome/Firefox/etc):
http://localhost:3000/Patient/<put Patient ID here>
Build docker image
docker build -t qol:latest .
Run Docker in detached head mode
docker run -p 49160:3000 -d qol:latest
Make sure docker is running and find the PORTS mapped to host machine
docker ps will present something similar to below data
# Example output
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
19bad986b95b qol:latest "docker-entrypoint.s…" 4 minutes ago Up 4 minutes 0.0.0.0:49160->3000/tcp optimistic_blackburn
In the example above under PORTS you can see 0.0.0.0:49160->3000/tcp, Docker mapped the 3000 port inside of the container to the port 49160 on your machine.
This means on your host computer you can navigate to http://0.0.0.0:49160/ to test out the app. You can also use: http://localhost:49160/ to access the site.
To find QoL for specific patient: http://0.0.0.0:49160/Patient/<put Patient ID here> e.g. http://0.0.0.0:49160/Patient/1188890
To inspect the server logs take the docker logs <CONTAINER ID> an example using the above data docker logs 19bad986b95b
docker ps # Get info on containers that are running
docker stop <CONTAINER ID> # Stop container using container id found with "docker ps"
docker images # Show a list of all images on system
docker rmi <IMAGE ID> # Delete an image pass the ID returned by "docker images" to "docker rmi". If image is being used then "docker rm <stopped container>"
docker ps -a # Get info on all containers
docker logs <container id> # Print app output
docker exec -it <container id> /bin/bash # Enter the container
Below is an example of the Quality of Life (QoL) Score. The "Health Impact" shows the negative impact the patient experiences due to various illnesses and health conditions. Ideally, patients want to have small to no "Health Impact". The smaller the "Health Impact" the greater the over all Quality of Life.
Results calculated using a patient's medical data pulled using the FHIR api.
Below are factors used to calculate QoL score
- Patient's age: Reasoning: older people tend to have more problems, the weight of their problems is less. Younger peoples with longer lasting severe health problems have a bigger impact on QoL.
- Total number of conditions: Reasoning: The more problems a person has the worse their QoL tends to be. Person with many health problems has a lot more to deal with.
- Sever Problems: Reasoning: Sever conditions have the greatest impact on health
- Moderate Problems: Reasoning: Moderate conditions impact on health is between Severe and Mild
- Mild Problems: Reasoning: This has the least impact, but many small problems still can add up.
- Accumulative: Reasoning: this measure the amount of time the patient has been inflected with the problem. The longer the inflection the greater the impact on QoL. This takes into account the severity of the conditions as well.
The site pulls a list of patients with various conditions and gives clickable links for user to test.
If you have a specific patient ID you would like to get a QoL score for, you can by navigating to: http://localhost:3000/patient/<put id number here>
Return data for specific patient
http://localhost:3000/api/patient/<put id number here> e.g. http://localhost:3000/api/Patient/1182759
Return data for default patient
http://localhost:3000/api
Sample data for PatientID: 1182759
{
"title": "QoL",
"title2": "Factor weights for score",
"pieData": [
[
"QoL",
"Quality of Life Score"
],
[
"Health Impact",
37.41394417323821
],
[
"Quality of Life",
62.58605582676179
]
],
"pieData2": [
[
"QoL",
"Explanation of QoL scoring"
],
[
"Patients Age",
91.09127345600291
],
[
"Total number of conditions",
63.01991429291655
],
[
"Number of severe problems",
63.379389022689814
],
[
"Number of moderate problems",
64.02868485081316
],
[
"Number of mild problems",
62.664494297531014
],
[
"Accumulative years of all severe conditions",
62.821962558110314
],
[
"Accumulative years of all moderate conditions",
63.46788525006346
],
[
"Accumulative years of all mild conditions",
62.60956674179815
]
],
"qualityOfLifeData": {
"ageDing": 0.5,
"totalCon": 0.011,
"svrCount": 0.02,
"modCount": 0.036,
"mildCount": 0.002,
"svrTotal": 0.006,
"modTotal": 0.0222,
"mildTotal": 0.0006,
"sum": 0.5978000000000001,
"endScore": 62.58605582676179,
"impact": {
"ageDingImpact": {
"value": 91.09127345600291,
"desc": "Patients Age"
},
"totalConImpact": {
"value": 63.01991429291655,
"desc": "Total number of conditions"
},
"svrCountImpact": {
"value": 63.379389022689814,
"desc": "Number of severe problems"
},
"modCountImpact": {
"value": 64.02868485081316,
"desc": "Number of moderate problems"
},
"mildCountImpact": {
"value": 62.664494297531014,
"desc": "Number of mild problems"
},
"svrTotalImpact": {
"value": 62.821962558110314,
"desc": "Accumulative years of all severe conditions"
},
"modTotalImpact": {
"value": 63.46788525006346,
"desc": "Accumulative years of all moderate conditions"
},
"mildTotalImpact": {
"value": 62.60956674179815,
"desc": "Accumulative years of all mild conditions"
}
}
},
"samplePatients": [
"Patient/1188771",
"Patient/1188771",
"Patient/1188771",
"Patient/1188771",
"Patient/1188771",
"Patient/1188771",
"Patient/1188771",
"Patient/1188890",
"Patient/1188890",
"Patient/1188890",
"Patient/1188890",
"Patient/1188890",
"Patient/1188890",
"Patient/1188890",
"Patient/1188890",
"Patient/1188890",
"Patient/1188890",
"Patient/1188890",
"Patient/1189141",
"Patient/1189141"
]
}