Patient-Driven Groupings Model (PDGM)
PDGM is the Medicare home health prospective payment methodology effective January 2020, classifying 30-day payment periods into one of 432 payment groups based on clinical characteristics, functional impairment level, comorbidities, and admission source.
What is PDGM?
PDGM replaced the prior OASIS-based Prospective Payment System for home health agencies effective January 1, 2020, shifting from a visit-count model to a clinically-driven classification system. Under PDGM, each home health episode is divided into 30-day payment periods, and each period is assigned to one of 432 payment groups based on five classification dimensions. First, timing: whether the period is early (the initial 30 days) or late (subsequent 30-day periods), with early periods reimbursed at a higher rate. Second, admission source: community (patient was not discharged from an acute or post-acute facility in the 14 days preceding the start of care) versus institutional (patient was discharged from an acute hospital, long-term acute care, or skilled nursing facility within 14 days), with institutional admissions also receiving a higher rate. Third, clinical grouping: one of 12 clinical categories based on the primary ICD-10 diagnosis, including musculoskeletal rehabilitation, neuro/stroke rehabilitation, wound care, complex nursing interventions, and behavioral health. Fourth, functional impairment level: low, medium, or high, derived entirely from the OASIS GG functional assessment items. Fifth, comorbidity adjustment: none, low, or high, based on secondary diagnoses that increase care complexity. LUPA (Low-Utilization Payment Adjustment) applies when the number of visits in a 30-day period falls below the diagnosis-specific threshold — triggering a per-visit rate instead of the full PDGM group payment.
Why It Matters for Healthcare Analytics
Under PDGM, accurate OASIS coding and correct primary diagnosis selection have direct, quantifiable payment consequences — a wrong clinical grouping or undercoded functional impairment level can shift a patient to a substantially lower payment group. LUPA prevention requires active monitoring of visit counts as episodes progress, identifying patients approaching the visit threshold before the period closes.
How Vizier Tracks PDGM
Upload your home health claim and OASIS data, then ask "What is our HIPPS code distribution and how many current episodes are at risk of LUPA?" — Vizier analyzes PDGM payment group assignments, flags episodes approaching LUPA thresholds, and identifies clinical grouping or comorbidity coding gaps affecting reimbursement accuracy.