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Medicus

EMT In-Call App

We created an app to make the job of EMT's easier. The app features any information gathered from the initial 911 call, a place to take handwritten notes about the accident and patients, a place to take pictures of the scene and upload EKG's and allows all of this information to be sent to the hospital. Medicus also logs each call and all of the filled out information.

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Medicus was created by a group of four team members:

Kayla Haselein: Visual Design / UX Prototyper

​Jasmine Ana: Team Lead / UX Prototyper

​Isha Ray: Product Designer

​Madeline Walz: UX Copywriter​

When arriving at the scene of an emergency,

EMS have a very important job to do but they usually aren't given a lot of information. Most of the information has to be gathered at the location and the most successful outcome is expected. 

EMT Journey

911 operator receives call and notifies the next available ambulance. The operator gives the accident location & minimal patient information. 

Emergency Medical Service (EMS) teams are enroute to the accident site

At the scene , EMTs & paramedics will evaluate patients. Accident scene notes & pictures are taken for the hospital & authorities.

Once evaluated, patients are taken to the hospital in order of severity. Paramedics will try to get any and all information from the patient.

 

EMTs & paramedics will treat the patient following their plan until they reach the hospital.

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How Might We

improve the ineffective communication between teams when receiving and relaying information?

37 years old

Brewster, MA

EMT - Paramedic

Married, 3 Kids

Steve Whittiker

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Pain Points:

  • Works 16 - 36 hour shifts

  • Limited information

  • Limited time

  • Limited resources

  • Ineffective communication

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Goals:

  • Efficient patient care

  • Patient safety

  • Patient trust

  • Effective communication (with patient and hospital)

Focus Area

Build an ecosystem that works to better the communication from the cabin EMT to the driver of the ambulance, and in turn to the hospital.

How?

     An infared camera with AI technology accompanied by a tablet and application

Sprint 1:

App MVP (mid-fi wireframes)

  • functionality

  • ease of use/intuitiveness

  • validation of features

  • desired features

  • practical use of application

  • validation for sizing/desired size

Sprint 2:

Camera (on tablet)

  • placement

  • plausibility

  • validation of feature

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Camera (inside ambulance)

  • placement

  • visual

    • hidden version/non-hidden

  • plausibility

  • level of aid given

  • validation of feature

Sprint 3:

Communication System

  • ease of use / intuitiveness

  • practical application

  • plausibility

  • level of aid given

  • validation of feature

During the first sprint,

we received a lot of great feedback.

  • add acronymns for easier recognition:

  • SAMPLE (signs & symptoms, allergies, medications, past medical history, last oral intake, events)

  • OPQRST (onset, provocation, quality, radiates, severity, time)

  • add to database for autofill frequent flyers

  • add traffic feature

During the second sprint,

the changes we made were received well and we were able to receive more feedback on the app and camera.

  • tablet camera placement is convenient

  • make sure cabin camera doesn’t block light

  • typically type notes instead of handwriting them

  • “send to hospital” needs to be its own button

  • iPad pro 11” best size – almost same as paper

During the third and final sprint,

the changes we made were received well and we were able to receive more feedback on the app and camera.

  • EMT ID and password

  • heart rate & pulse oximetry

  • EKG chart picture

  • camera on ceiling disguised as vent

  • combine scene and ambulance notes into one

After all of the feedback, 

we made the final changes and created the final wireframes and camera. 

The app has light and dark mode and the camera is disguised as a vent on the ceiling of the ambulance.

How does the camera work?

The camera in the cabin of the ambulance and on the back of the tablet both have infrared scanners and are able to detect patient conditions naked to the human eye. This includes pregnancy, internal bleeding, broken bones and much more. After the scans are complete, they are inputed into the app as suggestions to the EMT for further and more optimal care for the patient.

Final Walkthrough

Here is a look at what the app would be like when in use.

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