AutoGov is a software company that thrives on creating operational efficiencies that provide significant hard and soft dollar cost savings to our private and public sector clients. We enable business process strategy through tactical technology solutions that directly impact the decision-making paradigm for a host of core functions.
AutoGov recognizes that the nature of our business necessarily entails detailed analysis and evaluation of our clients' processes and procedures. However, our revenue models are not built upon consulting services. Our core business is to provide business process SaaS solutions to our customers that enable them to achieve a laser sharp focus in their business strategy.
Big Data is a term used to describe data sets that are too large to be processed using traditional methods. AutoGov encounters big data commonly in our analysis of our clients' business processes. We tackle big data challenges head-on with a variety of sophisticated predictive analytic tools that enable us to create models that change the way our clients approach critical business areas such as risk evaluation.
CaseVue is a web-enabled software that represents AutoGov’s pioneering approach to business process redesign. The software fuses data inputs from numerous sources to provide a reliable and fast decision support tool to business managers in the Long Term Care industry and to Health and Human Services departments for state governments. The software takes advantage of big data by harnessing the power of more than 30 million scores into a highly advanced predictive model that assesses risk and provides guidance to admissions professionals.
No installation is required. CaseVue is accessed via the web providing you with the simplest, fastest access to decision support.
Each CaseVue scoring engine is uniquely configured. Government-assistance programs (Medicaid, LTC, Food Stamps, SCHIP, TANF) have data sets that reflect the separate rules and distinct business processes used in determining eligibility. AutoGov owns and maintains a “base engine” for each of these programs. While common factors exist among the various scoring engines, there are factors that are unique to a specific program. Generally, the type of information common across programs relates to identity, residency, citizenship, income and assets.
A typical CaseVue scoring engine consists of more than 400 lines of code. Each case passes through the scoring engine algorithm which evaluates the accompanying data. A typical case is scored in less than a second. The CaseVue scoring engines and their exact contents are the intellectual property of AutoGov and are considered proprietary.
CaseVue fuses data from a variety of data sources to provide real time scores to users. Basic case data originates from the case management system of record. AutoGov supplements this information by incorporating third party data available from its strategic business partners into a single data source. In addition, AutoGov holds agreements with specialty data providers for use in unique circumstances.
Almost all eligibility systems have “rules engines” that help facilitate a case as it moves through the process of determining eligibility. This fact is especially true with state-based eligibility systems. Program rules are very specific and have certain thresholds – rules – designed to support a business process that results in a YES or NO decision. While CaseVue’s scoring engines consider the rules as a critical component, they are not necessarily part of the risk score. The predictive factors weigh risk and provide guidance to decision makers. For example, a state may have a rule that limits total assets to $2,000 in long term care eligibility. A case with $1,700 in assets, while not a disqualifying factor according to the state rule, may still be determined to be risky.
Identifying risk at any point in time during the life of a case or application is critical to addressing timeliness and accuracy issues. Eligibility determination is a dynamic process. Cases remain “in motion” as more information becomes available. Any case may become more or less risky based on its substantive facts, the amount of information in the case, and the amount of time that the case has been in process before a final decision. Generally, as cases age their risk level increases, particularly if critical pieces of information remain missing. CaseVue’s scoring engines are designed to encourage usage that ensures that the level of risk is measured as a case moves through the information accumulation life cycle.
As part of our desire to sharpen our business focus, AutoGov made the decision to discontinue distance learning programs in 2012.