Spine cohort and post-acute analysis
Scope: global method; website edition; worked case numbers are UNVERIFIED examples, not live evidence
Revision SHA-256: 917c2d3b6f6747fc7c040ea49ac4a1763bc85b2c81aef146155393efc1be4072

Spine cohort and post-acute analysis method

Read the linked source schema before constructing a cut. These tables are pinned
copies of previously ingested public vintages. Their publication here does not
make them current NYU operating results. Keep the same ledger and snapshot on
every request, including the analysis and claim-check pages.

SPARCS counts inpatient discharge records, not all annual spine patients or
unique people. Filter facility identifier, discharge year and APR grouper codes
together. Keep original source identifiers as text. Confirm their exact spelling
in returned rows. Do not substitute a hospital name for an identifier silently.
Group payer and discharge destination on that same cut. Include missing and other
categories so grouped counts sum to the selected record count. SPARCS payer
categories alone do not establish Medicare Advantage or commercial contract mix.

Whole-spine records and surgical fusion records answer different questions.
State the selected APR code set and its clinical interpretation. A mixed APR
category supports explicit bounds, not an exact TEAM-eligible MS-DRG count.
TEAM participant membership establishes participation only. It does not supply
episode inclusion, exclusions, severity mapping or hospital target prices.

Length-of-stay median and p90 are descriptive continuous quantiles of non-null
observations. Report both selected records and non-null observations. Missing
values and source top-coding need separate treatment. Observed LOS is not
risk-adjusted expected LOS. Institutional discharge and a long LOS tail are
different selections; retain both definitions when comparing them.

Total charges, estimated source costs, scheduled payments and negotiated rates
are different fields. Use source cost sum divided by its non-null count for a
mean; do not average group means without weights. A hospital-filed rate is not
proof of the amount NYU collected or its marginal avoidable cost.

For post-acute exposure, match the source year and provider/geography cut across
SNF, IRF and home health. Read the source payment and episode units. Median of
provider payment-per-episode ratios differs from pooled payments divided by
pooled episodes. Home-health payment periods are not automatically patients.
Published Medicare payment exposure is not a measured intervention saving.

Use OData $apply for grouping and aggregation, $compute for explicit derived
fields, and the returned source and receipt links for audit. Coverage.median and
Coverage.p90 are documented service extensions. Follow every next link before
forming a total. Check numeric claims against receipt paths such as
records[0].Count through /analysis/claim_check/. Inspect the verdict, then review
/session/ before writing conclusions or building a sourced workbook.

The non-surgical population, RTM enrollment, rule-year-specific monthly data
qualification, furnishing/billing clinician, actual collections, intervention
effect and local marginal cost still require matched evidence or owner inputs.
Mark those cells as needs. Do not turn an absent input into zero or an assumed
effect. Read /workflows/spine-rtm/ for those evidence requirements.


HTTP bindings for this session:
Explicit source-reference bindings:
SKILL.md: https://space.hammer.ai/skills/global/building-sourced-excel-models.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
analysis.md: https://space.hammer.ai/skills/global/analysis.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
coverage-website.md: https://space.hammer.ai/skills/global/coverage-website.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba

rate_position: https://space.hammer.ai/analysis/rate_position/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
rate_comparison: https://space.hammer.ai/analysis/rate_comparison/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
stack_check: https://space.hammer.ai/analysis/stack_check/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
screening_yield: https://space.hammer.ai/analysis/screening_yield/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
deferred_versus_avoided: https://space.hammer.ai/analysis/deferred_versus_avoided/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
interpretation_requirement: https://space.hammer.ai/analysis/interpretation_requirement/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
cohort_figures: https://space.hammer.ai/analysis/cohort_figures/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
comorbidity_edges: https://space.hammer.ai/analysis/comorbidity_edges/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
fee_components: https://space.hammer.ai/analysis/fee_components/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
filed_charge: https://space.hammer.ai/analysis/filed_charge/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
hypertension_evidence: https://space.hammer.ai/analysis/hypertension_evidence/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
prognostic_association: https://space.hammer.ai/analysis/prognostic_association/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
treatment_effect: https://space.hammer.ai/analysis/treatment_effect/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
regression_to_mean_expectation: https://space.hammer.ai/analysis/regression_to_mean_expectation/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
competing_event_coupling: https://space.hammer.ai/analysis/competing_event_coupling/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
withhold_earnback: https://space.hammer.ai/analysis/withhold_earnback/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
tournament_position: https://space.hammer.ai/analysis/tournament_position/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
measure_reliability: https://space.hammer.ai/analysis/measure_reliability/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
declared_inputs: https://space.hammer.ai/analysis/declared_inputs/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
cost_of_care_exposure: https://space.hammer.ai/analysis/cost_of_care_exposure/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
savings_methodology: https://space.hammer.ai/analysis/savings_methodology/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
hospital_variance: https://space.hammer.ai/analysis/hospital_variance/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
filer_inventory: https://space.hammer.ai/analysis/filer_inventory/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
candidate_screen: https://space.hammer.ai/analysis/candidate_screen/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
frontier: https://space.hammer.ai/analysis/frontier/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
judgement_check: https://space.hammer.ai/analysis/judgement_check/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
claim_check: https://space.hammer.ai/analysis/claim_check/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
deliver: https://space.hammer.ai/analysis/deliver/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
session_trace: https://space.hammer.ai/analysis/session_trace/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
progress_check: https://space.hammer.ai/analysis/progress_check/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
model_advisory: https://space.hammer.ai/analysis/model_advisory/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
knowledge_navigate: https://space.hammer.ai/analysis/knowledge_navigate/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
simulate: https://space.hammer.ai/analysis/simulate/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
sensitivity: https://space.hammer.ai/analysis/sensitivity/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
interval_check: https://space.hammer.ai/analysis/interval_check/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
decision_navigate: https://space.hammer.ai/analysis/decision_navigate/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
network_infer: https://space.hammer.ai/analysis/network_infer/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
hello_world: https://space.hammer.ai/analysis/hello_world/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
say_world: https://space.hammer.ai/analysis/say_world/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba

Read the companion references here (these replace local file references in the source guide):
Build a sourced analysis: https://space.hammer.ai/analysis.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
OData exploration and analytic cuts: https://space.hammer.ai/odata.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
Worked analysis reference: https://space.hammer.ai/skills/global/analysis.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
Building sourced Excel models: https://space.hammer.ai/skills/global/building-sourced-excel-models.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
Coverage website reference: https://space.hammer.ai/skills/global/coverage-website.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
Spine cohort and post-acute analysis: https://space.hammer.ai/skills/spine-analysis.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
hammer-building-the-evidence: https://space.hammer.ai/skills/world/hammer-building-the-evidence.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
hammer-cost-of-care-case: https://space.hammer.ai/skills/world/hammer-cost-of-care-case.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
hammer-coverage-navigate: https://space.hammer.ai/skills/world/hammer-coverage-navigate.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
hammer-provider-contracting: https://space.hammer.ai/skills/world/hammer-provider-contracting.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
hammer-provider-quality: https://space.hammer.ai/skills/world/hammer-provider-quality.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
hammer-savings-classification: https://space.hammer.ai/skills/world/hammer-savings-classification.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
hammer-vendor-evidence: https://space.hammer.ai/skills/world/hammer-vendor-evidence.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
hammer-writing-the-deliverable: https://space.hammer.ai/skills/world/hammer-writing-the-deliverable.skill.txt?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
Data: https://space.hammer.ai/data/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba
Transcript: https://space.hammer.ai/session/?ledger=49ec6090f32b112cd7fc2d39a72e0974&snapshot=7a53af6a9beb58928d4a64dc92db09c9db65433f9909f1a10d16e302adaf86ba