Pulse Admissions

Intelligent documentation improvement for accurate coding and reimbursements

Pulse Admissions brings patient data to life by intelligently surfacing key points from referral documentation, assessments, and clinical notes.

Clinical Decision Making

Powered by Machine Learning

Each piece of the Pulse platform drives valuable improvements
to planning, patient care, and documentation throughout the patient journey:

Pre-Admit

Pulse Referrals

Intelligently condenses lengthy referral records into a single-page, source-linked Referral Summary for review, improving time to admission and care planning.

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Days ~ 1-10

Pulse Admissions

Leverages LLM AI to compare and align referral documents, the OASIS assessment, and clinical notes for evidence-based documentation and accurate coding and reimbursements.

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Days 5-60

Pulse Episodes

Evaluates clinical data
to stratify patients by risk
for optimal utilization. Provides visit-by-visit
patient snapshots to guide proactive care and improve end-of-episode decisions.

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Pulse Transitions

Compares patients against unmatched industry-wide data to identify those most likely to require end-of-life care, helping providers ensure compassionate end-of-life planning for families.

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Intelligent, transparent insights for improved
clinical documentation and accurate coding

  1. Intelligent admission summary and recommendations: Ensure PDGM accuracy with AI-powered recommendations for each contributing element.
  2. AI supporting insights: Supporting evidence from the referral summary, assessments, and clinician notes
  3. Streamlined collaboration: Share notes both between team members (Sticky Notes) and into the EMR (Coordination Notes)
  4. Generative AI-assisted clinical grouping and comorbidity recommendations for easy clinician review
  5. Cross-linked insight sourcing: Easily review surfaced insights for simplified clinical decisions.
  6. AI Conflicting Insights: Surfaces clinical evidence that suggests the need for correction or addition to OASIS

Intelligent clinical

decision support through CDI

Pulse Referrals brings powerful new tools for informed,
seamless care coordination across the whole team. 

Admission 

The admitting clinician
makes post-visit adjustments, updating Focus of Care as appropriate and working with the clinical manager to publish the Admission Summary. 

Scrubbing

The quality team leverages PDGM Summary data to ensure OASIS accuracy and updates OASIS in the EMR as needed.

Coding

The coding team references
the PDGM Summary with other clinical documentation for accurate, evidence-based coding. 

Efficiencies that free care teams
to focus on patient care

Immense time and manual labor savings for OASIS scrubbing.

Intelligent recommendations on every element of PDGM drive evidence-based documentation.

Substantiating data around diagnoses reduces need for coding queries.

Improved OASIS and coding accuracy for more appropriate case mix and reimbursement.

Historical episode processing empowers organizations to more confidently respond to audits.

More accurate quality metrics that reflect outcomes vs. true patient acuity.

Our Expertise

Announces Release of Pulse Referrals & Admissions Modules Backed by Generative AI

Pulse modernizes admissions workflows with proprietary documentation imp…

Improving Hospice Care with Data-Driven Insights: A Conversation with Knute Nelson Hospice

Providing compassionate and high-quality support to patients and their f…

The FY 2024 Hospice Payment Rate Update Proposed Rule: Why Quality Matters Even More

By: Cyndi Rizzitello, MSN, RN, BC On March 31, 2023, the Centers …

CY2025 Hospice Final Rule presents challenges, opportunities for agencies 

The CMS 2025 Hospice Final Rule furthers CMS’s multiyear trajectory towa…

Navigating CY 2025 Home Health Reimbursement Cuts: Medalogix Offers Innovative Solutions to Enhance Efficiency and Outcomes 

As the Home Health industry grapples with the CY 2025 proposed rule, we …

Solving the Home Health Maze: Referral & Intake

The CMS Office of Burden Reduction & Health Informatics (OBRHI) coll…

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