With the Centers for Medicare and Medicaid (CMS) changing their reimbursement model in the coming years from the Risk Adjustment Processing System (RAPS) to the Encounter Data System (EDS), it is imperative for provider organizations to be prepared. Key to these preparations is the model for encounter, claims, and submissions data from a business and clinical perspective.

Master data management (MDM) is an essential approach to address this critical issue. MDM is a foundational capability for data-driven, high-performing organizations.

Data-driven healthcare organizations are better positioned to deliver healthier patients and healthier bottom lines.

Three primary focus areas that span from the higher level healthcare organization down to PCPs as end users of the data:

  • Quality (correctness and accuracy)
  • Timeliness and Accessibility
  • Authority (end users fully understand the data and its usefulness)

In the first of this three part series on Master Data Management for Healthcare, we start with a focus on the ever-important data quality.

The journey to superior data quality starts with establishing a “single version of the truth”. Multiple disparate data silos are a significant roadblock. It requires stringing together pieces of data from various locations in attempt to consolidate a holistic view. Exponentially more documentation and technology needs to be updated every time a change is made, or worst, the knowledge resides in silos with individuals and not in documented sources. Organizations in this scenario struggle with what data source to trust and scramble to create reliable analytics in the timely manner needed to make informed business decisions.

Investing in building data assets, not data silos. Investing in a data strategy that drives towards a single data repository provides significant data quality improvement opportunities:

  • Information becomes more readily-accessible and usability increases
  • Data feedback loops are more easily developed
  • Tracking data in and out of the repository is more succinct
  • Understanding data transformations comes with more ease
  • Quality assurance becomes a simpler process with fewer variables
  • Data-driven processes and technology systems gain efficiencies

Correct data delivers accurate submissions and reimbursements. For healthcare organizations, “clean” data refers to ensuring patient data (gender, DOB, first and last name, claims, etc.) all line up with eligibility, encounters and submissions received and submitted, with duplicate data eliminated. Without this data cleanliness, an organization risks losing revenue that they have for the good work they’ve done.

MDM provides data efficacy. It enables an organization to manage data in such a way to drive informed decisions

For instance, accurate suspect logic can provide meaningful diagnosis data points as decision support to PCPs and other members of the care team based on a total patient profile that contains multiple and longitudinal sources of data (claims, pharmacy, lab, radiology, etc.) to show a more complete picture of a patient’s health.

Another example, with ICD-10 coding that contains more specificity of diagnoses and CMS requirements that will soon deny claims with the word “unspecified,” better suspect logic can be employed that presents diagnosis options that do not contain the word “unspecified”. This type of logic also has the ability to take many disparate data points from pharmacy claims and lab claims to suggest an unrecorded accurate diagnosis.

Driving better informed decisions can result in:

  • PCPs who code more accurately, more efficiently and are generally happier because of the time saved
  • Accurate coding that protects the revenue of the organization

MDM and a single data repository drive transparency in claims submission systems and processes. The single data repository provides a better view of the disparate data sources coming into the repository and in what format. Data outputs can be standardized in specific formats to send to a TPA or to CMS. Feedback loops and automated updating can occur more readily. Without a deep understanding of the claims submission process and a single version of truth, organizations create a more chaotic environment when submission deadlines approach.

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