Discharge Function Score – A Simple Guide

 / Business Intelligence  / Discharge Function Score – A Simple Guide

Discharge Function Score – A Simple Guide

The Discharge Function Score will be used to assess the functional status of patients at discharge.  It is a comparison measure that measures whether a resident’s observed discharge function score meets or exceeds an expected discharge function score. The Discharge Function Score (DFS) will replace the Percentage of Residents Who Made Improvements in Function (Short Stay) measure in the Skilled Nursing Facility (SNF) Quality Reporting Program (QRP). The Discharge Function Score will also be utilized for Five Star starting January 2025 and Value-Based Purchasing (VBP).   Due to the impact this can have on a SNF, the time is now to better understand this metric and form strategies to avoid negative outcomes.

Here’s how it’s calculated:

The Discharge Function Score is based on ten GG codes, which capture the functional abilities of patients at the time of admission and again at discharge. The score is also risk-adjusted to account for patient-specific factors, such as their initial condition. 

The score is a measurement of how well residents can handle daily tasks and activities on their own at the time of discharge. It estimates the percentage of Medicare Part A skilled nursing facility (SNF) stays that meet or exceed an expected Discharge Function Score.

  1. Covariates: These are factors such as age, health conditions, and baseline functional abilities, which influence a resident’s potential for improvement.
  2. Coefficients: Each ability (e.g., mobility, self-care) is assigned a coefficient, which reflects its impact on overall functioning. These coefficients are used to calculate weighted scores for each component.
  3. Imputation: When some data is missing (e.g., parts of the self-care or mobility assessments), imputation techniques fill in the gaps based on available information and statistical models.
  1. Collect Data: The MDS (Minimum Data Set) gathers details about a resident’s abilities, including mobility, self-care, cognitive function and covariates.
  2. Handle Missing Data: If any values are missing, they are estimated through imputation – replacing missing data with estimated values based on other available information using statistical models.
  3. Apply Coefficients: Each MDS value is multiplied by a coefficient to create weighted scores. For example, if mobility has a score of 3 and a coefficient of 2, its weighted score would be 6.
  4. Sum the Scores: Add up all the weighted scores for a final discharge score.  This total score is meant to reflect the resident’s overall ability to function independently.
  5. Risk Adjustment: The score is then adjusted based on the resident’s initial health and expected improvement, making the final score a fair reflection of the care provided.

Medicare Part A Skilled Nursing Facility (SNF) stays are excluded from certain measures under specific conditions. Exclusions apply for incomplete stays (e.g., unplanned discharges, short stays, or resident death), certain severe medical conditions (e.g., coma, severe brain injury), residents under 18, and those discharged to or receiving hospice care.

The Discharge Function Score helps healthcare professionals anticipate the level of care or support a resident may need after discharge. It also allows facilities to track their performance, identify trends, and adjust care practices to improve outcomes. Additionally, it plays a role in quality reporting under programs like the SNF QRP, ensuring accountability and transparency in patient care.

The comparison of the observed scores at discharge with the expected ones gives insights into the patient’s improvement. CMS has implemented this measure in several quality reporting programs to ensure facilities focus on patient outcomes. Tracking these scores can impact a facility’s overall quality ratings and, in some cases, reimbursement structures. 

  1. Daily tracking of GG items:  Many operators have implemented processes to monitor GG items throughout a resident’s stay, using point-of-care solutions, observations, or other standard charting tools within the EHR. Recording this information daily provides ongoing insights into key functional trends—whether improvements or declines—that can help in setting appropriate functional goals and prompt timely interventions. Additionally, it allows for a comparison between the functional status at admission and the current care level, offering valuable insights into expected discharge scores.
  2. Covariates and exclusions:  Become more familiar with these items to ensure they are coded accurately on the MDS.
  3. Reduce the use of dashes:  Instead of allowing the imputation process to fill in missing information, work with the interdisciplinary team to ensure tasks that occurred during the 3-day window are assigned a level-of-care code and not coded incorrectly as “not attempted” due to lack of documentation.

MedaSync goes beyond traditional reports and dashboards—we provide straightforward tools that drive action. Our approach leverages machine learning and big data to deliver proactive, continuous daily insights, now including daily function tracking.

With advanced data processing, MedaSync automatically analyzes documentation from point-of-care systems, assessments, observations, and other EHR charting tools. No more sifting through complex reports to identify gradual changes. MedaSync summarizes the key insights and alerts you to any declines as they occur.


The technical specifications on this measure may be found on the SNF QRP website.