Healthcare excess — GL and umbrella, with professional liability placed separately — turns on facilities and workforce: how many sites, what services, and a loss picture of premises and patient-handling claims. We ran a real 28-facility health system, Cedarcrest Health Network, through InsightXtract.
Why healthcare is an excess casualty risk
A health system's GL/umbrella tower is distinct from its med-mal program. The excess sits over premises liability across hospitals, clinics and surgery centers, plus a very large patient-handling workers-comp book. Facility count and mix, clinical payroll, and the premises loss picture drive it — and the coded record keeps the excess GL view cleanly separate from professional liability.
The submission packet
A real healthcare placement is rarely one clean file. This one is five, in four different shapes — the everyday reality an underwriting team has to re-key by hand today:
- broker_email.pdf — the renewal narrative: account description, requested limits, exposure snapshot, and the excess-layer options to quote.
- rfq.pdf — the umbrella/excess application: general information, coverage requested, and the exposure bases.
- exposure_workbook.xlsx — the heart of the file: a 28-facility SOV (hospitals, clinics, surgery centers), GL exposure by facility class, clinical WC payroll by class, and an affiliated-entity schedule.
- loss_run.pdf — five years of currently-valued losses, premises general liability plus a large clinical workers-comp book.
- schedule_of_underlying.pdf — the primary casualty and lead umbrella the excess attaches over.
Step 1 — Classification
Every file is routed to a document type first — evidence-bearing, with a confidence, not a black-box label:
Step 2 — Coverage structure, with citations
The requested tower is read from the email and application, every value grounded to its page:
| Coverage | Requested | Source |
|---|---|---|
| General Liability — each occurrence | $1,000,000 | rfq p.2 |
| General Aggregate | $3,000,000 | rfq p.2 |
| Products / Completed-Ops Aggregate | $3,000,000 | rfq p.2 |
| Commercial Auto — CSL | $1,000,000 | rfq p.3 |
| Employers Liability | $1,000,000 | rfq p.3 |
| Lead Umbrella | $25M | email p.1 |
Step 3 — Exposure schedules, typed & normalized
The workbook is where template OCR falls over — many sheets, hundreds of rows, broker-specific wording. InsightXtract reads every sheet, maps each to a typed schedule, and normalizes the codes against governed glossaries. A slice of the GL exposure schedule:
| State | WC Code | Description | Revenue | Payroll |
|---|---|---|---|---|
| OH us_state_codes | 68706 ncci | Hospital - general & surgical | $26,800,000 | $4,824,000 |
| IN us_state_codes | 68707 ncci | Outpatient clinic operation | $12,400,000 | $2,232,000 |
| KY us_state_codes | 62003 ncci | Medical office building | $8,100,000 | $1,458,000 |
| … 44 GL rows · workers_compensation 58 · named_insured_mix 30 · location_list 28 | ||||
Column bindings: state → us_state_codes, class → ncci_wc_class_codes / iso_gl_class_codes, occupancy → occupancy_types. Out-of-vocabulary values are flagged by validation, not silently kept — and fuzzy column resolution means a rule written for payroll still binds a broker’s “Total Payroll” column.
Step 4 — Derived exposures (deterministic, not guessed)
The account is rated on totals. Rather than ask a model to eyeball-sum hundreds of rows, the document type declares deterministic sum / count / group_by rules that reduce the extracted schedules exactly — the same numbers every run, each traceable to its source table:
Step 5 — The loss run
For a health system's GL/umbrella, the loss run is premises injuries, visitor claims, security incidents and a heavy patient-handling WC book. Every claim is extracted — coverage line, status and cause normalized — and rolled up, with a by-line split for the loss pick:
| Claim # | Coverage | Cause | Status | Incurred |
|---|---|---|---|---|
| CED-3110 | GL coverage_lines | Premises slip/fall | Closed claim_statuses | $96,000 |
| CED-3088 | GL coverage_lines | Visitor injury | Open claim_statuses | $142,000 |
| CED-3051 | WC coverage_lines | Patient-handling injury | Open claim_statuses | $188,000 |
| … 16 claims across 5 policy years, currently valued | ||||
What the underwriter reads first
The coded record surfaces exactly the drivers that move this class of business:
- Facility count & mix from the SOV — acute vs. outpatient drives the premises exposure.
- Clinical WC payroll — the patient-handling book that dominates severity.
- Excess GL kept separate from the professional-liability tower placed elsewhere.
- Premises & security loss frequency by facility, from the coded loss run.
Why it holds up in production
- Every value is cited — page/region provenance on fields and schedules; a file review can click any number to its source.
- Codes are normalized against governed glossaries; out-of-vocabulary values are validated, not hidden.
- Totals are computed, not guessed — deterministic derived fields over the extracted rows, exact and reproducible.
- Configuration is versioned — document types, glossaries and rules pinned to a published version, so an output made today reproduces tomorrow.
- Nothing is dropped — the all-sheets extractor surfaces every schedule, even ones the base schema didn’t anticipate.
Any casualty class, one agent
Construction, trucking, healthcare, and more — the same Excess Casualty agent, configured with document types and glossaries, not per-account code. See the end-to-end walkthrough → or talk to us about your own submissions.