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RiskCede KNOW platform

KNOW provides a seamless analysis and reporting plat- form, integrating healthcare and related data in real time. The result is a holistic view on all factors that impact on deci- sions and strategy.


Exploratory data analysis

This section provies an overview of the schemes data and performs datamining on claims and membership data. Reports are available to follow monthly trends.

An additional section on Employer group analysis is also available.


Fraud, Waste and Abuse

Various visualisations and machine learning models are used to identify possible areas of fraud, waste and abuse

Users can log actions and investigations to draw reports on progress. The systems will load cases for investigation automatically on each monthly data import


Surveys

The survey mosule includes the designer to design new surveys and all the data analytics and reporting. The results are integratd with the rest of the database.


Product development

A section to simulate future results based on different contribution benefit combinations.


Managed healthcare

Results on the RiskCede MHC application and mobile application.


Admin

Administrators can perform certain tasks themselves.





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Scheme overview

Below is some of the key statistics for the scheme.

No data available.

The table below contains summary data per employer (sorted by number of principal members) for the past 12 months. The province column indicates the province with the most member for the relevant employer.

The plot below illustrates the change in loss ratio relative to the other groups.

Malaria incidents in Africa:


Based on World Health data

No data available.

Overview of claims data

The information below is used to verify claims data and illustrate areas of highest claim volume.

Service dates

Disciplines (Paid amounts)

Products

Rejections


Similar claims submitted by same provider with different PR number

Click on row to view detail data.

Case summary

This section gives an overview of FWA cases loaded and feedback given. It also gives the option to doanload a report.

Download report

to

Summary information



Detail data



Case summary

Below is the aggregated cost and counts of all cases

Hospital networks

The graph below illustrates the differences between networks for in-hospital procedures.

Input:

Accomodation



Below is a summary of weighting per provider within each discipline






Markers based on provider postal code, not physical address.

The objective of the medicine utilisation model is to identify cases of addiction and reselling of drugs. The model identifies the top users of each medicine category.

Membership anti selection

Below is a table of all members with significant claims within the frist three months of joining.




Survey design


Question design



Participants complete surveys on their mobile devices and the results are analised in this app.

The following tabs aim to transform this data into information that can deliver insights into a scheme's business.


Survey activity

Below is a plot to illustrate the participation in the survey.


Top_option


Rand amounts adjusted to new benefit year and outliers removed.



Beneficiaries per disease

Project summary

Below is a table with all relevant projects and the number of participants in each project.
Performance gauges:

Population segmentation

Based on analysis performed, the following segments are identified in the pouation







Loaded user data

The table below contains key info on all users


Read more about the: KNOW platform