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Record W4414123075 · doi:10.1097/brs.0000000000005496

Medicare’s Benchmarking Spinal DRGs Have Limited Capacity in Capturing the Nuances of Surgical Invasiveness, Hospital Length of Stay, Discharge Disposition, Key Quality Metrics, and Reimbursement Costs for Adult Spinal Deformity

2025· article· en· W4414123075 on OpenAlexaffabout
Ayush Arora, Jeffrey L. Gum, Eric O. Klineberg, Munish C Gupta, Richard A. Hostin, Khaled Kebaish, Justin K. Scheer, Alan Daniels, Renaud Lafage, Justin S. Smith, Peter G. Passias, Themistocles S. Protopsaltis, Han Jo Kim, Michael P. Kelly, Alex Soroceanu, Christopher I. Shaffrey, Frank Schwab, Robert A. de J. Hart, Douglas Burton, Larry Lenke, Virginie Lafage, Shay Bess, Christopher P. Ames

Bibliographic record

VenueSpine · 2025
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsReimbursementBenchmarkingSpinal deformityQuality (philosophy)Key (lock)Patient careDeformityMEDLINE

Abstract

fetched live from OpenAlex

STUDY DESIGN: Retrospective cohort analysis. OBJECTIVE: Assess the distribution of Medicare's spinal-deformity-specific diagnosis-related group (DRGs) relative to surgical invasiveness, hospital length of stay (LOS), discharge disposition, 90-day postoperative quality metrics, and reimbursement costs for adult spinal deformity (ASD) operations. SUMMARY OF BACKGROUND DATA: Heterogeneity of ASD call into question Medicare's DRGs to accurately capture nuances of ASD surgical episodes of care. METHODS: Adults who underwent thoracic to pelvis instrumentation with associated DRGs were identified from a multicenter database. Demographics, operative details, inpatient course, discharge disposition, 90-day adverse events, and reimbursement costs were compared between spinal deformity-specific DRG codes. Distribution of DRGs for a subset of these patients who fit into one of 6 commonly performed surgical strategies to address ASD was also assessed. RESULTS: Of the 314 patients included for analysis, the majority fell into +CC DRGs, while the minority had +MCC DRGs or no MCC/CC DRG. Within each DRG, there was considerable heterogeneity in regard to patients' ages, ASA, CCI, frailty, surgical invasiveness, postoperative ICU/hospital LOS, discharge disposition, and complication profiles.+MCC DRGs had significantly greater ASA and Edmonton Frailty Scores. While +MCC and +CC had relatively similar surgical invasiveness, +MCC had greater ICU admissions, in-hospital adverse events, and nonhome discharges as well as longer ICU, hospital, and rehab LOS. While reimbursements were significantly higher for +MCC DRG compared with +CC DRGs and DRGs without MCC/CC, there were large ranges in reimbursement within all DRG subgroups.The 7 DRGs varied significantly within and between the subset of 6 commonly performed surgical strategies, although there were no differences in regard to ICU admissions and LOS, hospital LOS, discharge disposition, and number of adverse events (in-hospital, 90-day). CONCLUSIONS: While Medicare's spinal-deformity DRG codes capture average trends in surgical/postoperative episodes of care for ASD patients, each encompasses highly heterogeneous patients and associated surgical operations rendering them unreliable gauges of patient/surgical complexity, early postoperative trajectories, and reimbursement costs. A more granular system is needed to more accurately capture the nuances of ASD operations and their associated quality metrics and reimbursement costs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.328
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes2
Has abstractyes

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