ExactData - Next Generation Systems Testing

Case Study: Healthcare Claims Payer

Healthcare Claims Payer Current Operations

Testing today is primary through sophisticated testing software, a manual audit process or use of production data. The business rules associated with claims processing systems are extremely complex, and constantly change. This drives the need and use of sophisticated testing software. Certain processes, at a system test level, at a procurement or development level or before the actual processing of the claim would lend themselves to automation and will be the focus of this proposal.

Preliminary Business Analysis

Problem Statement

Healthcare Claims Payer does not test new processes or outsourcing proposals, does not always perform system testing, performs the testing manually, or utilizes production data sets for system testing. Issues with current testing processes include:

• Lost opportunity due to lack of de-identified data sets that can be given to vendors and suppliers to test processes and outsourcing proposals.
• Risk of non compliance utilizing systems that have not been tested
• Lengthy and expensive audit processes from outside agencies
• Cost associated with manual inspection processes
• Time to complete manual inspection processes
• High error rates inherent in current processes
• Cost of high error rates of current system

Proposed Solution

A Common Data Set of Non-Identifiable information will be created consisting of 1 million Patient and Physician Records. Digital Test Decks will be created from this Common Data Set to perform the following functions:

• Ad Hoc Testing: New web portals, potential service providers or any other immediate testing needs.
• Ingest Testing before processing of claim files. Files will be tested before processing that they are cleansed, related (linked) and correct before processing.
• System Testing: Establish baseline, show net chances for any system change, establish system impacts for changes, and perform load testing and test other system level processing factors such as processing times.

High Level Business Analysis

• Ability to manage risk and non compliance
• Improved development and procurement processes
• Reduction of 5 full time test personnel to 2.5 persons.
• Reductions of 2-3% estimated error rate for ingest process by 50% and associated cost of error reduction.
• Significantly faster turn around times for system testing and ingest file processing
• Eliminate inherent variability and errors associated with testing with production data

Payback to investment will be measure in weeks.

Cost Savings Estimates

It is estimated that with the newly implemented Quality Data Management Processes, QA costs will be reduced by 50% due to automated of current manually processes. With $100K for a fully burdened QA Manager as the annual costs, and 5 Full Time Equivalents or FTE’s, annual savings would be $250,000. Reduction in error for the claims processing origin ingest process is estimated to be a 50% reduction from current 2-3% levels to 1.5%. This estimate is based on our experience with manual data entry processes. With 10M data field processed annually, 1.5% would equal a reduction in 150,000 incorrect field errors annually. At $10/field to correct after the ingest process, a conservative estimate, annual savings to Healthcare Claims Payer would be $1.5M.

Business Justification/Return on Investment

The new process implementation would have a payback of approximately 5 months based solely on automating the current manual QA processes for the ingest audit process. There is a high probability of a reduction in errors due to precise measurement tools and ability to perform a root cause failure analysis and implement a closed loop corrective action process. Potential additional annual savings to Healthcare Claims Payer $1.5M by reducing current ingest error rates. Overall, the probability of a Return on Investment that will be measured in weeks is very high.

Other Business Reasons Include:

• Ability to Market DTD^® Engineered Test Materials as Healthcare Claims Payer advanced quality assurance processes.
• Knowledge transfer on advanced data quality tool implementation and use to further differentiate Healthcare Claims Payer solutions from the competition, with the ability to prove it.
• Improved procurement and development processes: better information faster, to benchmark and monitor current and future systems.
• Ability to manage risk and non compliance.
• Reduction of the risk of potential lost revenue. Social Security numbers, along with correct names are selling for $5 each on the black market. Our proposal will significantly reduce the risk of a major public relations fiasco for Healthcare Claims Payer and associate lost member revenue.
• Improved development and procurement processes
• Significantly faster turn around times for system testing and ingest file processing
• Eliminate inherent variability and errors associated with testing with production data.