30-day hospital readmission RISK FOR CHF PATIENTS
Objective
To create a risk stratification app for health systems and hospital network to identity at-risk-patients by analyzing structured and unstructured data contained in EHR (Electronic Health Records) and doctor's notes for 30-day hospital readmission risk for Congestive Heart Failure (CHF).
Role
UX/Visual Design. Collaborated with a team of product manager, UI engineers, Informaticist and business consultants to create proof of concept.
Dashboard
Overview of number of patients/percentage and risk score in each risk group calculated by the factors ranging from patients' clinical and diagnostic test parameters, socioeconomic and behavioral health factors.
Patients in High Risk Group
After you select the risk group category from the dashboard, it displays all the patients in this group sorted by risk score.
Background
Congestive Heart Failure (CHF) which is one of the top conditions with highest rate of hospital readmission is shown as a case study to demonstrate how this analysis tool can surface patients who maybe more at risk for rehospitalization. There are numbers of factors ranging from age, gender, other contributing health problems like hypertension or diabetes, also family history which can be captured from structured data in EHR, also socioeconomic and behavioral health factors like living status, employment, marital/family status in unstructured notes which can uncover other contributing factors that puts certain patients more at risk for getting readmitted due to not being able to follow through with discharge instruction on medication, monitoring diets and or ability to receive followup care after discharge.
Patient detail - Notes tab
Healthline's NLP engine highlights terms and modifiers associated with risk factors, symptoms like breathing difficulty, fatigue, or medication and previous hospitalizations for CHF and smoking history, also social/family status that he is widowed, lives alone and his immediate family member is out of state.
