EDIN Case Study

Overview

How might we help nurses and doctors identify, treat, and track early symptoms of delirium without significantly increasing their workload?

Project Overview:
As life expectancy rises, so does the number of elderly admitted to hospitals. Due to the combination of pre-existing conditions and precipitating factors at in-patient units, elderly patients become easily prone to delirium during their stay.

Project Goal:
The aim of this project is to prevent the possibility of missing the early stages of delirium by developing a proactive, holistic system that identifies quantitative and qualitative trends across disturbances and risk factors that precipitate delirium with compiling and comparing patient biometrics, medical history, and environmental stress factors.

Achievements:
Recognized my Dr. Richard Besdine, Former Chief of Geriatrics at Lifespan, and other industry professionals in creating a innovative yet simple solution to combat Delirium in hospital settings.

Delirium

What is Delirium?

Delirium is a sudden, fluctuating, and usually reversible disturbance of mental function.

Subtypes:
Hyperactive: agitated, disoriented, and delusional, and may experience hallucinations.
Hypoactive: subdued, quietly confused, disoriented, and apathetic
Mixed: fluctuations between the hyperactive and hypoactive subtypes

Delirium is characterized by:

Research/ Empathy

Stakeholders

Dr. Austin Quinn from Rhode Island Hospital identified a recurring problem: the high incidence of delirium among hospitalized elders. This inspired us to develop a product/system to address this issue.

Working closely with Dr. Quinn, we gained insights into hospital dynamics and limitations to ensure our solution is practical and effective. Through collaborative efforts, we combined research, expert input, and a deep understanding of the hospital environment to create a promising solution. Our goal is to significantly reduce delirium and enhance the care provided to hospitalized elders.

Secondary & Primary Research

Personas

As we researched we realized that we are not just designing for hospitalized patients but also the people that work with these patients - nurses.

System

EDIN

EDIN is a combination of 3 systems: a physical device, Epic, and CAM.

Data is collected through our physical device and CAM test and input into EPIC for a seamless integration into the current system.

System

EDIN - Physical

EDIN, our physical device, constantly reorients patients by reminding them the date, location, diagnosis.

Our innovative bedside device serves as a constant companion, keeping patients reoriented and assisting with onboarding. It also collects noise and light pollution data to help hospitals minimize distractions and create a peaceful environment.

System

EDIN x CAM

The Confusion Assessment Method (CAM) is the current test that hospital use if they sense that a patient is becoming delirious.

However, the questions on the test are read aloud which increases the level of inaccuracy as elder patients have a hard time hearing.

To address the challenges, we propose administering the test daily upon admission to prevent delirium. This proactive approach improves accuracy and enables early intervention for better patient outcomes.

User Testing

Doctor Feedback

After creating the device we talked to other patients, nurses, and doctors. Through this testing we realized that we did not answer a very important question.

“HOW WILL THIS BE INTEGRATED INTO THE CURRENT HOSPITAL SYSTEM?”

Hospital are very complicated and there are already many devices and, so we needed to figure out how EDIN can be seamlessly integrated into already existing systems.

This lead us to interview more nurses to become more aware of systems that are currently used at hospitals, which lead us to EPIC.

System

EDIN - EPIC

EPIC is a platform that many hospitals use to digitize patient record. We found this as a opportunity to input the data that EDIN collects into EPIC. So, we added 3 new categories added to EPIC that connect with the physical device