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The G4ID solution allows customers to determine the infection’s relationship to other infections within the hospital and investigate how the infection may have spread via a transmission vector from Patient A to Patient B based on the closeness of the infecting pathogens. G4ID’s clinical data analytics framework extensively uses Philips’ unique Patient Analytics Platform (PAP) system which can interface with all of the hospital’s Electronic Health records – including EMR, Pharmacy, clinical Lab, logistics, etc.

An algorithm created by Philips Research was under pilot study in one of a major healthcare facility in the US (Umass memorial hospital). Research approached the Design team to make a UX framework and develop a solution around it along with Engineers in SAFe Agile along with the UMASS Memorial Hospital so to generate timely feedbacks and improvements areas.

Genomics as a subject was very new to me, There was no POC to look up to or improve upon. As homework, I started investing time in talking with Subject Matter Experts (SME’s) who were Genome scientists at Umass hospital(US). It was quite a revelation for me that the hospitals can be one of the major sources of infections as people with various infections & diseases come to get treated and they do leave traces of infections on the bed, the nearby touchable areas. These infections can travel through caregivers to other patients and other people in the hospital. Hence hospitals take utter care by ensuring proper cleaning and timely infection control using antibiotics.

Traditionally, Hospitals collect samples from patients, caregivers, devices, and with an environment at regular intervals and feed into DNA Sequencers. These DNA Sequencers identify the infection if present in any sample by performing a pathogen study.

The design challenge was the need for a visual representation of infection pattern, how it may or may have spread across patients, environment caregivers. A rich dynamic antibiogram chart suggests the right antibiotic for the identified pathogen. Last but not least a history and a dashboard of all sequences running in the DNA Sequencers.

As a starting point, the design team (I & a US-based UX Designer created an experience flow of the process, we identified two phases “Surveillance: A task of collecting samples and DNA Sequencing.” & “Cluster Investigation: A task of identifying the infection and cure the infection using the right antibiotic. The users who perform these two tasks are different hence it was a rationale behind keeping these two tasks separate in UI as well

We divide our role as per geography permit, it was easier for US-based designer to visit Umass facility and understand from the users itself. Similarly, I was located in India with dev-teams, so I helped them to understand the story better, presented the experience flows, we created several sketches/wireframes showing the charts. Particularly in the project, the navigation pattern and information architecture was never a concern in the beginning. We wanted to crack the representation first then we moved to create a very simple information architecture with 4-5 screens.

“Aurora” solution offers two features

1. Sequencing Analysis : Using which sample list can be uploaded in sequencers, and can be matched with the existing list of products, caregivers, and patients automatically.
On Dashboard, the running and completed sequences were shown with status and other necessary information.

2. Infection control : On clicking on Infection control and selecting the completed sequence, a tree view shows the infection may have progressed across devices and floors, who or what is the possible source and career of infection by showing direct matching and inferred matching. Aurora also shows digitally EpiGenome of infections and possible antibiotic in what phases with respect to time.

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