While healthcare has always been dependent on data, the transition to value-based reimbursement dramatically raises the stakes. Specifically, it requires a degree of integration between data sources that previously was not required under a fee-for services regime. It also raises the ante for data quality. It is not enough to simply bring disparate sources of data together and hope that the inherent variability of the sources is somehow reconciled. To be useful, integrated data must adhere to a common set of standards and nomenclature so that it can be effectively put to work. This is especially critical for Accountable Care Organizations (ACOs). One approach to this issue is the deployment of a Master Data Management system (MDM). An MDM solution allows a healthcare enterprise to standardize and pool critical data into a single database, providing a common point of reference for ACO reporting and management. This white paper discusses 7 questions to consider in preparing for and implementing an MDM for ACOs.
What Does Implementation Look Like? How Long Does It Take?
While an MDM project will be new to most organizations, the implementation steps are like other IT projects. They include:
One of the biggest areas of impact for automation is simply in claims processing. Payer websites allow for claims data on the payer’s risk to be pulled and stored into your systems. This can be done manually, using multiple FTEs to navigate, pull, save, identify issues, and all the rest, or it can be done automatically, in some cases freeing up full teams of people to be utilized in more value add roles. The CAQH estimates the use of online portals to manage the processing of transactions increased 55% in 2017. What’s more, setting up a claims processing automation solution facilitates an improved ability to analyze the claims being processed.
Analysis of Existing IT infrastructure
An MDM is an add-on to an existing IT infrastructure, not only consuming and transforming data but also populating third party tools. Mapping the existing systems and how they will interact with the MDM provides a practical guide to deployment.
In order to realize an efficiency gain on a process like this, you’ll want to consider how to successfully employ technology to manage the flow of claims. The most crucial part of functionality you’ll want is the automated distribution of claims to Managed Care Coordinators (MCCs). A robust solution would also give managers the ability to manage the distribution by editing the members on a given distribution list, reassign claims for unexpected conflicts, and exclude members from receiving claims for certain periods (e.g. for PTO). Additionally, automating this workflow facilitates additional business intelligence on the process: you’ll be able to more closely manage turnaround times, get insight into high or low volume periods, and see how efficiently your team members are reviewing claims. All of these things will help keep claims moving without having to rely on clunky Excel workbooks.
The plan brings together your findings into a blueprint for deployment. The duration of the project is related to its complexity (i.e. the number of data feeds, variability among data sources, scope of requirements, and the status of the IT infrastructure). Project timelines can vary from 4 to 18 months. An MDM project plan should be a detailed but dynamic document, subject to modifications as issues present themselves during deployment.
Making the transition from planning to implementation immediately tests all the core assumptions about the project. In the early stages, implementation offers the opportunities to refine and hone working relationships, both internally and with third party service providers. Practical considerations reign, such as providing data access to third party service providers (and completing required paperwork) and overcoming the inevitable system obstacles that are part of probing a complex and secure IT system. Iterations are likely, putting a premium on securing nimble and agile internal teams and external service providers.
How Much Will This Project Cost?
Third Party Service and Software Providers
A vendor quote should provide a clear understanding of how it is priced (project vs. hours), what is included (list of services), what is not included and change order management if the scope of the project changes. Additional fees for software and related maintenance should be included.
MDM is a processing and storage intensive system that may exceed the capabilities of your current resources. Your MDM service provider should be able help you scope IT requirements so that you can budget and procure.
An MDM project requires internal leadership and active participation of key staff members, particularly in the planning stage where requirements are being scoped and defined. As the heavy lifting of planning transitions to implementation, project leads and staff will need to be allocated to work in concert with third party service providers. Since the plan will be iterative based on implementation activity, overall project leadership needs to remain in place through go-live, ultimately transitioning to an active support mode (data stewardship and governance) charged with maintaining the health and vitality of the MDM system.
What Is the Return on Investment?
The cost of low quality data is very high. Managing and correcting exceptions is labor intensive and often complex. Persistent data anomalies also undermine confidence in the data and may constrain the organization in its ability to comply with ACO reporting or management requirements. An MDM solution promises higher quality data with less rework, more efficient data management tools and a foundation for improved ACO management and reporting. The net return: lower labor costs for exception handling and more effective performance against ACO contracts. While ultimately it is the success of clinical operations that will determine return on ACO contracts, it is impossible to assess clinical effectiveness without high-quality data. The two are inextricably entwined.
ACOs and other value-based reimbursement methods increase the importance of data quality. However, variability among data sources makes achieving this difficult using traditional ETL (extract, transform, load) methodologies. A Master Data Management system increases the quality of incoming data while providing more efficient data management when exceptions occur. Deploying an MDMS system is both a technical and organization endeavor that involves internal project leadership, careful requirements planning among the various stakeholders, and a clear understanding of the existing IT infrastructure. MDM service providers can assist in both the planning and implementation process. Services providers should have rich healthcare domain expertise in addition to technical capabilities. Additionally, they should be both nimble and technically creative in response to both challenges and obstacles that can occur within the project. Master Data Management provides a return on investment by lowering the cost of managing data quality issues and by increasing the ability of the organization to effectively monitor and report on ACO related performance objectives.
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