The Centers for Medicare and Medicaid (CMS) is changing their reimbursement model in the coming years from the Risk Adjustment Processing System (RAPS) to the Encounter Data System (EDS). These change imposes payment reforms that reward quality and value while penalizing inefficiency.

Achieving the objectives of value-based healthcare requires that healthcare organizations capture and manage increasing amounts of data, and put the data to work to enhance the value of healthcare delivery.

Bad data quality means big problems. Unreliable data directly impacts reimbursements, operational efficiency, clinical-decision making, and variation of care.

The success of your organization’s delivery of healthcare quality depends on PCPs operationalizing patient data.

As previously discussed, Master Data Management (MDM) is an essential capability to deliver quality patient data at the point of care. MDM closes a significant gap, but value is limited if the data is not operationalized by Primary Care Providers (PCPs). Realizing the full benefits of a MDM requires a strategy that establishes a level of trust with PCPs.

Scenarios that erode trust in data.

Most PCPs are trained to think clinically and not necessarily from a business perspective. Given that PCPs are the primary consumers of individual patient data, the lack of business perspective can impact their ability to:

  • conceptualize the presentation of population health data
  • understand how data quality impacts quality outcomes
  • manage costs in order to serve the larger goals of the organization

PCPs are thoroughly familiar with their patient’s data and know when it’s incorrect. When a PCP determines not to remediate patient data quality, operational efficiency is undermined. Value is impacted with increased costs due to duplicate or deferred work.

The solution is to drive trust in data with strong data governance in concert with a MDM strategy.

Data governance orchestrates the people, processes, and technology necessary to optimize data quality and unlock value. This requires a symphony of representation across the organization.

Clinical representation is absolutely necessary to include in the group of stakeholders. Clinical representation will ensure PCPs understand the data intimately. When data is not understood, data will not be trusted or used. This leads to organizational goals and initiatives not being met.

Clinical authority should be used and respected. Any presentation or transformation of data needs clinical review and approval. When the transformation or presentation of data does not reduce PCP cognitive load, it won’t be used.

Invest in engaging, educating, and enabling PCPs.

  • Train PCPs on data quality at the point of care
  • Focus on good coding practices
  • Involve PCPs in continuous data validation
  • Communicate the outcomes of data governance

Gaining PCPs trust in the data is critical link in the healthcare data value chain. An accurate, authoritative view of the patient only matters if clinicians can base their decisions on trust at the point of care.

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

How are you influencing your PCPs to operationalize data at the point of care in your organization?

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