Qlik Healthcare User Group

3 Posts authored by: tbh

Healthcare fraud detection involves account auditing and detective investigation. Careful account auditing can reveal suspicious providers and policy holders. Fraudulent claims often develop into patterns that can be detected using predictive models The following techniques are effective in detecting fraud. Auditors should ensure they use these, where appropriate. •     Calculation of statistical parameters (e.g., averages, standard deviations, high/low values) – to identify outliers that could indicate fraud. •     Classification – to find patterns amongst data elements. •     Stratification of numbers – to identify unusual (i.e., excessively high or low) entries. •     Digital analysis using Benford’s Law – to identify unexpected occurrences of digits in naturally occurring data sets. •     Joining different diverse sources – to identify matching values (such as names, addresses, and account numbers) where they shouldn’t exist. •     Duplicate testing – to identify duplicate transactions such as payments, claims, or expense report items. •     Gap testing – to identify missing values in sequential data where there should be none. •     Summing of numeric values – to identify control totals that may have been falsified. •     Validating entry dates – to identify suspicious or inappropriate times for postings or data entry By leveraging the power of QlikView Discovery and data analysis technology, organizations can detect fraud sooner and reduce the negative impact of significant losses owing to fraud. Fraud is a serious financial drain on the healthcare systems in many jurisdictions, and it also drags down the effectiveness of providing care to those in need.

Delivering Value for Healthcare

Posted by tbh Apr 22, 2013

Earlier this month, the Medicare Payment Advisory Commission (MedPAC), the nonpartisan federal agency charged with evaluating Medicare payment issues and making recommendations to Congress, issued its annual March 2013 Report to the Congress: Medicare Payment Policy, a detailed, 435-page document. The report concluded that in total, hospitals lose money on Medicare: The overall Medicare margin for hospitals declined from -4.5 percent in 2010 to -5.8 percent in 2011. In addition, MedPAC projects the overall Medicare margin in 2013 will be -6 percent. However, the report also notes that while Medicare payments are currently less than costs for the average hospital, it is possible for some hospitals to make money on Medicare: The median efficient hospital generated a positive 2 percent Medicare margin in 2011. This begs the question: How can a hospital become more efficient? Data analytics is essential to drive performance management in support of the quest for greater efficiency.   QlikView Discovery is poised to deliver that value.

The end game for ACO's

Posted by tbh Apr 22, 2013

The basic, core technology building blocks of ACOs are threefold: 1) some form of digitized data (e.g., electronic health records); 2) some sort of ability to exchange health information; and 3) data analytics. While it is possible for an ACO to function without these for a short period of time, all three of these are absolutely essential for long-term sustainability and success. The next layer of technology for ACOs leverages the basic building blocks and consists of practical applications for population health management, care coordination and cost reduction.

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