Leveraging Azure Machine Learning to improve billing accuracy and consistency
Hello
โ This is the beginning of how we
will change the way we work
with data โ
GM - Pharmacy
Case Study
Industry
Health Care
Company Size
10,001+ employees
Problem Space
Predictive Analytics
Azure
Insights
Machine Learning
Billing
Technology Used
Python
AzureSQL
AzureVNet
AzureDataFactory
AzureMachineLearning
Business Context
The ability to provide accurate invoicing for patient stays in hospital is a significant challenge for the
healthcare industry. Inaccurate billing often results in unpaid claims from medical aids or patient
dissatisfaction and a poor patient experience.
Challenge
Improve the billing process through
insights and predictive analytics
High number of touch points involved in every
case that is billed resulted in slow billing,
billing errors and write-offs from stale claims
not actioned timeously.
Solution
Azure machine learning solution that
validates a patientโs bill in near real-time
A custom-built rules engine to enable business
to prevent known billing issues before a patient
is discharged or final billed.
PowerBI dashboard to support
operationalisation and adoption of the solution.
Billing quality assurance
solution
Improved billing efforts resulting in higher
quality bills that are paid faster
๐ฐ
Reduced medical aid claim
rejections and short payments
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Reduced number of touch points
for the majority of cases and
directed focus on complex cases
๐
Improved billing accuracy and
efficiency resulting in reduced
days sales outstanding