OData exploration and analytic cuts
Scope: global method; website edition; worked case numbers are UNVERIFIED examples, not live evidence
Revision SHA-256: a52ec7a9e2391ef086ff492548500dd303515333527a7fa0cd80bc22c9bc3c78

OData exploration and analytic cuts

Open /odata/ using the session-bound link supplied below. Follow its redirect and
retain that pinned service root. Read $metadata before constructing a query.
The service document names every entity set and its original published source.
SourceName annotations map EDM-safe properties back to exact original columns.
HTML data and OData use the same source records and physical row identities.

GET entity sets with $filter, $select, $orderby, $top, $skip, $count=true,
$search, $compute and $apply. Follow @odata.nextLink without dropping query
parameters. $top is a total requested limit, not a request to silently truncate.
Read EntitySet(RowId), EntitySet(RowId)/Property and primitive /$value.
Use entity-set /$count for the same filtered selection. A row count is source
records at the declared grain; it is not automatically unique patients.

Use single-quoted OData string literals, doubling embedded apostrophes. Keep
facility identifiers and procedure codes as text when the schema says text.
Never convert 001463 or 00100 to numeric values by guessing from their appearance.
Parameter aliases such as @facility='001463' are supported. Percent-encode query
values. Nested nullable collection properties use the metadata-declared Items
wrapper so null, empty collection and null elements remain distinct.

For an actual cohort: discover facility, year and grouper columns; filter all of
them together; compare filtered count with sum of grouped payer counts, including
null or other groups. Fetch rows and verify actual identifiers before aggregation.
Example shape, not a source finding:
$apply=filter(Facility eq '001463' and Year eq 2024)/groupby((Payer),aggregate($count as Records,Cost with sum as TotalCost))
Names in this example must be replaced by properties declared in $metadata.
For mean cost use individual source costs or sum/count with the appropriate
non-null denominator. Do not average group means without their weights.

Standard aggregate methods include sum, min, max, average and countdistinct.
Coverage.median and Coverage.p90 are declared service extensions using continuous
quantiles. Their denominator excludes null values; report total and non-null
counts separately. A percentile is not an expected or risk-adjusted outcome.
Aggregated results have no physical source-row identity. Their saved result and
evidence receipt identify the exact cut and transformation.

Nodes and Edges are canonical graph entities. Nodes(RowId)/Outgoing and Incoming
enumerate directed edges. Edges(RowId)/Source and Target resolve their endpoint.
$expand can include these relationships with nested filter/select/orderby/top/
skip/count/expand options. Source relationships are not proof of causation,
billing eligibility, contract identity or patient-level outcomes.
URL parameter aliases carry into expansions and their continuation links.
Outer $it references inside $expand return an explicit unsupported error.
For that cut, follow the parent relationship link and bind its known value as an
explicit parameter alias. Ordinary graph any/all scopes remain supported.

JSON and multipart $batch accept bounded reads within the same pinned service.
Data modification and change tracking are not supported for immutable snapshots.
Unsupported operators, paths or transformations return explicit OData errors;
do not treat an unsupported query as an empty result. Read declared capabilities.

Request application/json;IEEE754Compatible=true when your client cannot retain
large integer and exact decimal JSON numbers. Metadata declares their types.
Naive timestamps remain source wall-clock strings; no UTC timezone is invented.
Arrow export links retain the primary selection's types. JSON retains expanded
relationships. Receipts, saved results and transcript links preserve evidence.

For OneStep-style analysis, distinguish whole-spine discharges from a fusion
cohort. A mixed APR bucket creates bounds; it does not become an exact MS-DRG
TEAM episode count. Match facility, year, grouper, rule year and payment units.
Keep hospital-filed prices separate from payer network records and actual paid
claims. Public medians are not NYU contract rates. Institutional discharge share,
LOS tail, published post-acute payment exposure and avoidable savings differ.

Enrollment, monthly RTM qualification, furnishing clinician, product effect,
local marginal cost, and realized payment remain needs until supplied. Submit
precise claims to claim_check and judgement_check through the linked analysis
pages and inspect their verdicts before building a sourced workbook.


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