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D159 Improving CMS Star Ratings: Specialized Education & OASIS Training

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Western Governors University

D159 Evidence-Based Measures for Evaluating Healthcare Improvements

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D159 Improving CMS Star Ratings: Specialized Education & OASIS Training

This project aims to evaluate the effectiveness of a documentation quality improvement initiative focused on enhancing CMS Quality of Care Star Ratings. The approach involves delivering a specialized educational program combined with cross-training for clinicians. The team has identified three key data points to assess success: clinician attendance rates, corridor intervention rates, and Star Rating scores.

Clinician attendance rates in the two-part training sessions are critical for evaluation. Without active participation, clinicians cannot acquire the knowledge necessary to improve care quality and documentation accuracy. It is not enough for clinicians to simply be present; they must engage in discussions and practical workshop activities to fully understand the new CMS-aligned standards and requirements. Insufficient attendance risks continued misinformation and poor documentation, which contributes to maintaining low Star Rating scores at Pathways Healthcare (PHC).

Corridor intervention rates serve as a vital metric by showing the frequency of patient records that require correction after initial documentation submission. PHC collaborates with Corridor Group, a leading provider of tech-enabled coding and clinical documentation review. Their goal is to reduce inaccuracies in coding and documentation. A decrease in corridor interventions following clinician training would indicate successful knowledge transfer and improved coding accuracy, particularly in functional assessments during patient admissions and follow-ups, which reflect patient outcomes upon discharge.

Finally, Star Rating scores themselves provide a direct measure of project success. These ratings will reveal whether the educational interventions have effectively raised PHC’s quality scores. The overarching purpose of this initiative is to assess whether a specialized OASIS education course can elevate CMS Star Ratings. Since CMS updates these scores quarterly—January, July, and October—training is scheduled from December 2, 2024, to January 28, 2025, followed by a practical application period from January 29 to March 28, 2025. Comparison will be made between scores published in January 2025 and those published in April 2025. CMS also offers a 15-day preview each quarter, typically in February for the April scores, but the limited OASIS submissions during this period may affect its accuracy as a forecast.


Data Management Strategy

What data will be collected and how?

  1. Clinician Attendance Rates:
    Attendance will be tracked using sign-in sheets during the training sessions. The target is 95% attendance and participation from clinicians across all four teams in the M01 branch. Each team’s manager will ensure rosters are submitted to the Project Manager.

  2. Corridor Intervention Rates and Star Ratings:
    Data on corridor interventions and Star Ratings will be sourced from PHC’s Quality Assurance and Performance Improvement (QAPI) Committee. Weekly meetings provide data updates, with the QA nurse presenting trends. The Project Manager will attend these meetings to collect relevant data to evaluate the impact of clinician re-education.


Key Performance Indicators (KPIs)

KPI NumberFocus AreaDescriptionMeasurement PeriodSuccess Indicator
KPI #1Training CompletionTracks the percentage of clinicians completing the two-part training to ensure they have the necessary skillsBy January 28, 202595% clinician attendance and engagement
KPI #2Employee Performance ProgressMeasures the quality of clinical documentation post-training to evaluate skill applicationJanuary 29 – March 28, 2025Improved OASIS documentation quality with higher accuracy and congruence across disciplines

Project Goal and Timeline

The central goal is to increase PHC’s CMS Quality of Care Star Rating from 2.5 to 4 by enhancing clinicians’ skills in OASIS assessments and documentation. This will be measured against the seven core CMS process and outcome metrics:

CMS Quality MeasuresPHC Baseline Score (Out of 5)
1. Timely Initiation of Care (TIOC)2.0
2. Improvement in Ambulation2.5
3. Improvement in Bed Transferring1.5
4. Improvement in Bathing1.5
5. Improvement in Dyspnea1.5
6. Management of Oral Medications2.0
7. Potentially Preventable Hospitalizations4.0
Overall Star Rating2.5

Clinicians will be trained from December 2, 2024, through January 28, 2025. Following training, clinicians will implement their learning from January 29 to March 28, 2025. Data from this period will be compared to prior performance to evaluate progress.


Data Collection and Security

Clinician attendance data will be collected in real time, and corridor intervention and Star Rating data will be extracted from Strategic Healthcare Programs (SHP). SHP offers real-time analytics and alerts that allow PHC to address documentation inconsistencies proactively before CMS submission.

To protect privacy, patient identifiers will be replaced with numerical codes, and clinicians will be anonymized in records. All collected data will be securely stored, both physically and digitally, with restricted access limited to project team members.

Data parameters include:

  • Education delivery: 12/2/24 to 1/28/25

  • Practice implementation: 1/29/25 to 3/28/25

  • Separate tracking for late attendees

Data will be analyzed using descriptive statistics such as averages and percentages to understand attendance, corridor intervention prevalence, and Star Rating changes. Weekly reports will monitor trends and address any barriers encountered.


Success Criteria and Potential Challenges

The project will be considered successful if:

  • 95% of clinicians attend and engage fully in the training.

  • Corridor intervention rates decline, indicating improved documentation accuracy.

  • Star Rating scores increase beyond the baseline of 2.5.

However, success depends heavily on active clinician participation. Merely attending without meaningful engagement may result in no significant improvement. Clinician motivation is therefore crucial for the project’s effectiveness.


Importance of the Project

This initiative aligns with the healthcare goal of improving patient outcomes. Continuous professional education enhances clinical decision-making and care quality, thereby benefiting patients with treatments consistent with CMS standards.

As noted by MCG Health (2025), effective provider education reduces clinical practice variations and improves patient outcomes. Enhanced patient care naturally leads to improved CMS Star Ratings, reflecting better agency performance.


Results Dissemination Plan

The project team plans to present findings on April 15, 2025, through a PowerPoint presentation showcasing detailed data visualizations, including charts and graphs that illustrate the effectiveness of the educational program. Attendance will be facilitated both in person and virtually via Teams, with a recorded option available. The Project Manager will be available to address any questions.


Project Closure and Sustainability

Upon project completion, the team will formally recognize all contributors and thank PHC for organizational support. The specialized education program will be incorporated into ongoing clinician training, aiming for long-term sustainability.

Post-project, data collection will transition to monthly reporting, with quarterly meetings in the first year to review progress. This continuous evaluation cycle is essential, particularly due to high staff turnover rates in healthcare, ensuring ongoing education and quality improvement.


References

MCG Health. (2025, February 20). Provider education: Evidence-based tools and tactics. https://www.mcg.com/blog/2022/12/20/provider-education/#:~:text=Effective%20provider%20education%20can%20be,and%20promote%20cost%20savings%20downstream

Strategic Healthcare Programs. (2024, May 30). Data analytics and benchmarking. https://www.shpdata.com/home-health/data-analytics-benchmarking

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