Healthcare Analytics

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Healthcare Fraud Detection

2017-10-23T23:43:49+00:00

Case Description Our customer received medical claims for reimbursement. All claims are coming from insurance companies, clinics, and hospitals and pharmacies. Claims were increasing day by day and there was no system to measure a claim is a genuine or fraud. We aided the prevention and early detection of medical insurance fraud, fraudulent claims [...]

$80 Million Savings

2017-10-23T23:44:38+00:00

Client: US-based diversified managed healthcare company Industry: Healthcare Business needs to be addressed: Improve fraud detection capabilities to reduce revenue leakage and ensure payment integrity AMSTAT Consulting solution: AMSTAT Consulting implemented a sophisticated and adaptable fraud detection model along with process improvements for dynamic responsiveness. Business impact: $80 million in total savings within the [...]

Medical Fraud Detection

2017-10-23T23:45:31+00:00

Case Description A state Medicaid agency covering about one million people throughout the state wanted to identify and reduce the number of fraudulent medical transactions. To accomplish the task of fraud detection, the agency hired us. The Medicaid agency wanted to identify and flag suspicious providers and collections of transactions, which could indicate fraud [...]

Will The Company Pay a Trade Account?

2017-10-23T23:51:35+00:00

The purpose of the study was to provide the probability that the company will pay a trade account in a “severely delinquent” manner (90+ days beyond terms) within the next 12 months. The research question was as follows: What is the probability that the company will pay a trade account in a “severely delinquent” [...]

Predictive Analytics for Audits Can Help Identify Missing Revenue

2017-10-23T23:50:28+00:00

The purpose of the study was to review the charges on the claim with an application that could predict errors using the analytics from outpatient Medicare claim data. We examined the medical record to determine if there was a charge omission or if there was a charge error made. We used predictive analytics to [...]

Predict Where Denials Are Likely to Occur Next

2017-10-23T23:50:47+00:00

The purpose of the study was to predict where denials are likely to occur next. The research question was as follows: RQ1: Where are denials likely to occur next? We built predictive models. We predicted where denials are likely to occur next by analyzing big data. We helped them generate more than $970 million. [...]

Will Patients Pay On Time?

2017-10-23T23:46:26+00:00

The purpose of the study was to identify the probability that patients will pay on time. The research question being tested was: Research Question 1: What is the probability that patients will pay on time? We built predictive models. There is a 54.31% probability that patients will pay on time. We helped our client [...]

Is A Charge Missing?

2017-10-23T23:48:26+00:00

The purpose of the study was to predict the probability that a charge is missing. The research question being tested was: Research Question 1: What is the probability that a charge is missing? We built predictive models. There is a 73% probability that a charge is missing. We helped them generate more than 2 billion. [...]

Will Patients Be Readmitted?

2017-10-23T23:47:07+00:00

The purpose of the study was to predict the probability that patients will be readmitted. The research question being tested was: Research Question 1: What is the probability that patients will be readmitted? We built predictive models. There is a 69.53% probability that patients will be readmitted. We helped them generate more than 2 [...]

Will Patients Pay Their Part of the Bill?

2017-10-23T23:49:10+00:00

The purpose of this study was to predict the probability that patients will pay their part of the bill by analyzing data sources. The research question being tested was: Research Question 1: What is the probability that patients will pay their part of the bill? We built predictive models. There is an 82% probability that patients [...]