Inaccurate MDS data is one of the most overlooked threats to quality measures, Five-Star ratings, and Medicare reimbursement in skilled nursing facilities. Because the Minimum Data Set (MDS) drives nearly every quality metric reported to Centers for Medicare & Medicaid Services, even small coding errors can create widespread financial and regulatory consequences.
This article explains how inaccurate MDS data distorts quality measures, why CMS relies so heavily on this data, and how poor MDS accuracy directly impacts reimbursement, audits, and facility risk.
Why MDS Accuracy Matters for Quality Measures
The Minimum Data Set is the primary data source CMS uses to calculate Skilled Nursing Facility (SNF) Quality Measures. These measures influence:
- Public Five-Star Quality Ratings
- Value-Based Purchasing (VBP) scores
- SNF Quality Reporting Program (QRP) compliance
- Survey targeting and audit selection
CMS does not independently observe daily resident care. Instead, it evaluates facility performance based on what is reported in the MDS. When MDS data is inaccurate, quality measures no longer reflect actual care quality.
Quality Measures Most Affected by Inaccurate MDS Data
Errors in MDS coding commonly distort the following CMS Quality Measures:
- Falls with major injury
- Pressure ulcers (Stage 2–4)
- Antipsychotic medication use
- Functional decline and mobility outcomes
- Hospital readmissions
These metrics directly affect public reporting and reimbursement adjustments, making MDS accuracy a financial issue—not just a clinical one.
Common Causes of Inaccurate MDS Data in SNFs
1. Incorrect or Unsupported Diagnosis Coding
Coding diagnoses without physician documentation, carrying forward resolved conditions, or misclassifying active diagnoses can falsely inflate or suppress quality outcomes.
2. Functional Status and Section GG Errors
Inaccurate Section GG coding—whether intentional or due to misunderstanding—can significantly skew functional outcome measures and payment models.
3. ADL Coding Inconsistencies
Discrepancies between nursing documentation, therapy notes, and MDS ADL coding create data mismatches that are easily flagged during audits.
4. Poor Interdisciplinary Communication
When nursing, therapy, and MDS staff do not align, the resulting MDS data becomes unreliable and difficult to defend.
How Inaccurate MDS Data Distorts Five-Star Ratings
CMS Five-Star ratings rely heavily on Quality Measure data pulled directly from the MDS. Inaccurate coding can cause facilities to:
- Appear artificially high-performing (triggering audits)
- Appear lower-performing than reality (hurting referrals and census)
- Show erratic QM trends that draw regulatory attention
Facilities often do not realize their MDS data is distorted until survey findings or audit letters arrive.
The Financial Impact: MDS Accuracy and Reimbursement
SNF Value-Based Purchasing (VBP)
Hospital readmission measures—linked to MDS and claims data—determine VBP incentive payments. Inaccurate MDS data can reduce reimbursement even when care was appropriate.
SNF Quality Reporting Program (QRP)
Failure to accurately report required MDS elements can result in a 2% Medicare payment reduction, regardless of actual quality of care delivered.
Audit Risk and Payment Recoupment
Facilities with inconsistent or unsupported MDS data face:
- Medical review audits
- Targeted probe and educate (TPE) audits
- Large reimbursement recoupments
Short-term payment gains from inaccurate MDS data often lead to long-term financial losses.
Inaccurate MDS Data Increases Regulatory Risk
Facilities with distorted quality measures are more likely to experience:
- Focused infection control or quality surveys
- Data-driven survey selection
- Increased scrutiny during complaint investigations
CMS analytics flag facilities whose data patterns do not align with expected norms.
Why Accurate MDS Data Protects SNFs
Accurate MDS data supports:
- Defensible reimbursement
- Reliable quality scores
- Lower audit exposure
- Improved survey outcomes
Facilities that prioritize MDS accuracy, staff training, and documentation alignment consistently perform better under CMS review.
Final Thoughts: MDS Accuracy Is a Compliance Safeguard
Inaccurate MDS data does more than distort quality measures—it undermines reimbursement integrity and increases regulatory exposure. Accuracy is not optional; it is protective.
At The MDS Integrity Project, we believe that transparency and accurate reporting are essential to restoring trust in the skilled nursing system. Quality measures should reflect reality—not manipulation, shortcuts, or misunderstanding.
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