Inspiration

Problem :

Sudden Upsurge of corona Patients to the Emergency rooms.

Emergency doctors are worried about resource allocation and their lives too. They want to control at early spread, so that they are not overburdened and also stressed for their lives too.

Patients / trauma , stress, and panic is severe and also had lead to a suicide in Sweden.

Medical resources are limited. Planning is also a challenge

Challenge how do we address the concern of providing better health care support at early stages, so that early prioritized care helps provide expert level support for curing and thus reduces the spread at early stage. ?

If early medical helpline care, priorities patients based on corona severity rather than the same queue for all the patients, then early care to the patients, can help solve the problems above.

How do we use this data that is collected for impactful planning of systems around health care.?

What it does

Color coding of patients based on the corona stage. On a first call/ request to the medical helpline, the doctor or nurse attending the call analyzes symptoms and assigns a color to the patient. On second call/request to the helpline, color based call routing happens, the patient with severe intensity is prioritized or put to a queue with more expert care.

Analytics on the data collected can be very impactful to various stakeholders -

  1. health care systems- hospitals, emergency rooms, other healthcare systems, National e-health agencies,
  2. immunization & test kit plans
  3. governement bodies - municpallities, National level planning, how do we plan when there is wave2 etc
  4. Economic systems around health care.
  5. citizens panic reduces and can choose areas to go
  6. Other business systems - employers etc

How we built it

STEP1: Problem Identification We discussed with Emergency doctor and deceased patient's wife. Problem: Emergency rooms are overburden, Health care resources are limited and there is trauma in the public.

STEP2 : Problem area identification. Understanding the health care systems, we noticed that if we can tweek a small process in providing early health care support to prioritzed patients, we can reduce the stress and trauma. That process is very simple, easy to implement but should have mainfold implications.

STEP3 : Solution identification Color coding stages of corona by experts at every level of interaction call/request with the medical support doctors/nurses. Prioritized fursther interaction/call to the most needy patient based on the severity.

STEP4: Validation of Stakeholders We discussed this solution with a medical helpline in Sweden , they were willing to apply it. It is a simple tweek in the workflow. But the data it gives can be used by many stakeholders Spoke to National ehealth agency, medical supplies planning team, Community planning for regions in stockholm, Emergy rooms , deceased patients wife, all stakeholders have given very positive testimonials. that can be shared on request

STEP 5: Pilot We have discussed with the medical help line in Stockholm region and they have been interested in implementing the idea. Discussion in progress

STEP 6: Extending pilot to Sweden national regions We have discussed with the medical help line in Stockholm region and they have been interested in implementing the idea. Discussion in progress

STEP 7: Extending pilot to other European countries We have discussed with the medical help line in Stockholm region and they have been interested in implementing the idea. Discussion in progress

Challenges we ran into

Undrestanding healthcare and Government system influencers on health care providers

Accomplishments that we're proud of

Quick stakeholder validations feedback. Quickly gave a feedback to

What we learned

What's next for Colors of Corona

The solution is very scalable and extensible beyond corona, Prirotized health care, is an essential part of providing effective medical care. Triaging the most needy patients will help reduce the burden on all systems. Color coding or categorization of patients based on the symptoms , can help prioritize care

Built With

  • analytics
  • api
  • workflow
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