Beyond Excel Sheets: How Top SNFs are Automating MDS with AI in 2025

The Minimum Data Set (MDS) is the backbone of skilled nursing facility (SNF) reimbursement under Medicare's Patient-Driven Payment Model (PDPM). Yet, despite advances in technology, many facilities still manage MDS assessments using manual processes - spreadsheets, paper charts, and endless audits. This approach isn't just outdated; it's costly. Errors, missed documentation, staff burnout, and lost revenue are just some of the pitfalls.

But things are rapidly changing. Leading SNFs are increasingly adopting Artificial Intelligence (AI) to automate their MDS workflows - transforming administrative headaches into streamlined, revenue-optimized operations. Let's explore why the traditional Excel-driven process is falling short, how AI-driven automation is revolutionizing SNF reimbursement, and dive into real-world examples and outcomes from facilities leading the charge.

Why Manual MDS Processes Are Costing SNFs Money

Traditional MDS management is highly manual, error-prone, and time-consuming. MDS coordinators spend hours daily reviewing charts, entering data into spreadsheets, and triple-checking details for accuracy. Here's why manual methods hurt your bottom line:

High Error Rates

Manual coding and documentation naturally introduce errors. In fact, Medicare audits reveal error rates ranging from 9% to as high as 27% in MDS submissions. Even minor discrepancies can trigger costly denials, audits, and lost reimbursement opportunities.

Significant Staff Burden

MDS coordinators frequently report spending up to 30% of their time handling denials and re-submissions - wasting valuable hours that could be better spent on clinical oversight or patient care. This administrative overload also contributes significantly to burnout and high turnover rates, nearing 60% annually in recent years.

Revenue Leakage

Missing critical diagnoses or special conditions on assessments can substantially lower PDPM reimbursement rates. A single overlooked comorbidity or clinical trigger can easily cost a facility thousands of dollars per resident per stay. For instance, missing a special-care trigger such as isolation for infection might lead to losing $50 - $80 per resident-day - translating into substantial revenue leakage across an entire facility.

AI in Action: Transforming MDS Workflow

Enter AI. Skilled nursing facilities across the country, both large and small, are now leveraging AI-driven tools to automate tedious MDS tasks, improve coding accuracy, and capture more revenue. Here's how AI is addressing traditional pain points head-on:

Real-Time Data Extraction and Analysis

AI-powered software uses Natural Language Processing (NLP) to scan electronic health records, progress notes, therapy logs, and physician orders in real-time. It identifies diagnoses, treatments, and patient conditions that directly impact MDS assessments and PDPM scoring. Unlike manual chart reviews, AI can accurately and instantly cross-reference multiple documentation sources, ensuring no critical detail goes unnoticed.

Smart Coding and Compliance Checks

AI systems proactively flag coding inconsistencies, missing documentation, or potential compliance issues before MDS submissions. For instance, if a resident is on antidepressants but lacks a corresponding depression diagnosis, the system immediately alerts the coordinator. These real-time validations prevent denials and ensure facilities capture maximum reimbursement.

Optimized ARD Selection and IPA Opportunities

Strategically selecting the Assessment Reference Date (ARD) or deciding when to conduct an Interim Payment Assessment (IPA) can dramatically affect reimbursement. AI-driven tools continuously analyze clinical data to predict the best timing for these assessments. If a resident experiences a significant clinical change - such as starting IV antibiotics - the system instantly recommends conducting an IPA, ensuring SNFs don't miss out on reimbursement increases tied to heightened care needs.

Real-World Case Studies: AI's Impact on SNF Reimbursement

Facilities adopting AI-powered MDS automation are seeing measurable, significant improvements. Let's look at a few real-world examples:

TLC Management: $25 Per Resident-Day Increase

TLC Management, operating 20 SNFs, implemented AI-driven reimbursement automation to monitor resident documentation and optimize Medicaid case-mix scores. Within just two months, six facilities saw their Medicaid reimbursement rates jump by an average of $25 per resident per day. For a 100-bed facility, this translates to nearly $75,000 extra monthly revenue. According to Leslie Piper, TLC's Director of Clinical Reimbursement, "This product is amazing - it doesn't just help capture significantly more reimbursement; it gives our staff back several hours each week."

AHF Ohio: Stable Revenue Growth and Reduced Staff Burden

AHF, a smaller non-profit operating 6 SNFs across Ohio and Pennsylvania, faced consistent challenges due to staff turnover and manual MDS oversight across multiple locations. After deploying AI-driven MDS solutions, each facility reported consistent quarter-over-quarter improvement in reimbursement capture. Cindy Lemasters, AHF's Corporate MDS Consultant, highlighted the impact: "Trying to oversee everything manually just wasn't feasible. The AI system provided crucial support, alerting us to issues proactively and ensuring stable revenue growth."

Carespring Healthcare: Proactive IPA and ARD Optimization

Carespring, operating 15 SNFs, adopted an AI platform that continuously scans patient documentation for reimbursement opportunities. By proactively recommending optimal ARD and timely IPA assessments, Carespring significantly increased captured revenue. The AI became a vigilant reimbursement coach, ensuring facilities consistently leveraged clinical changes to maximize PDPM rates.

Quantifying the ROI: Proven Outcomes from AI Adoption

Facilities adopting AI-driven MDS automation report clear, tangible benefits:

• Reimbursement Boost: AI-driven documentation accuracy typically boosts PDPM revenue by $20–$60 per resident-day.
• Reduced Denial Rates: SNFs leveraging AI have seen denial rates drop by 30–40%, significantly improving cash flow and reducing administrative overhead.
• Time Savings: Automated processes save MDS coordinators an average of 5–10 hours per week, freeing them for clinical care coordination.
• Lower Staff Turnover: Facilities using AI tools report improved staff satisfaction, reduced burnout, and lower turnover rates due to decreased administrative burdens.

Implementing AI: Practical Steps for Your Facility

Ready to automate your MDS processes? Here are practical steps to get started:

1. Evaluate Current Workflows: Identify areas where manual data handling is most problematic or prone to error.
2. Select AI Solutions: Choose AI tools that integrate seamlessly with existing systems and provide real-time, actionable insights.
3. Staff Training: Invest in training to ensure staff fully embrace and effectively use new AI-driven processes.
4. Continuous Improvement: Regularly review the AI outputs, adjust workflows as needed, and use the insights to refine your MDS processes continuously.

Conclusion: The Future of MDS is Here

Manual MDS processes are no longer viable in the demanding PDPM landscape. Facilities sticking with traditional methods face ongoing revenue loss, compliance risk, and staff burnout. Conversely, those adopting AI-driven solutions are enjoying enhanced accuracy, higher reimbursement, reduced denial rates, and happier staff.

In 2025, embracing AI isn't just beneficial - it's essential. Facilities using AI-driven MDS automation tools are fundamentally transforming their operational and financial health, setting new standards for excellence in skilled nursing care.

It's time to move beyond spreadsheets and manual data entry. The future of MDS is intelligent, efficient, and profitable - and it’s here now.