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POLICYCHANGES.APPManage supplier listing
PolicyChanges.app — A structured, change-event time series of US health-payer medical policy and utilization-management changes, monitored daily across 40+ payers. Each policy record is normalized into a comparable schema: payer, state, line of business (e.g. Commercial), policy category (e.g. Prior Auth), impact rating, affected specialties (e.g. Oncology, Rheumatology, Neurology plus further specialties), therapeutic channel (e.g. Pharmacy), effective date, the vendor's own date of detection, days to comply, an AI-generated summary, affected billing codes, and a required-action instruction …
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A structured, change-event time series of US health-payer medical policy and utilization-management changes, monitored daily across 40+ payers. Each policy record is normalized into a comparable schema: payer, state, line of business (e.g. Commercial), policy category (e.g. Prior Auth), impact rating, affected specialties (e.g. Oncology, Rheumatology, Neurology plus further specialties), therapeutic channel (e.g. Pharmacy), effective date, the vendor's own date of detection, days to comply, an AI-generated summary, affected billing codes, and a required-action instruction set for billing teams. The distinctive property is that it captures changes rather than static policy text: it records when a requirement appeared, which payers and geographies it applies to, and what operational response it forces (worked example on the site: Anthem BCBS New York introducing step-therapy try-and-fail requirements on specialty medications, detected 30 May 2026 with no published effective date). This is effectively a step-therapy and prior-authorization protocol library indexed by payer, state, specialty and drug channel — a dataset with no free equivalent, because payers publish these policies as unstructured PDFs and web pages with no change feed and no reliable effective-date metadata.
From 3 yearsCoverage Financials · Health CareAsset class Equities
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PolicyChanges.app — A structured, change-event time series of US health-payer medical policy and utilization-management changes, monitored daily across 40+ payers. Each policy record is normalized into a comparable schema: payer, state, line of business (e.g. Commercial), policy category (e.g. Prior Auth), impact rating, affected specialties (e.g. Oncology, Rheumatology, Neurology plus further specialties), therapeutic channel (e.g. Pharmacy), effective date, the vendor's own date of detection, days to comply, an AI-generated summary, affected billing codes, and a required-action instruction …
PolicyChanges.app offers (Alternative, Reference, Sentiment) — Corpus of at least low tens of thousands of normalized policy records: record identifiers on the site run into the five-digit range (this record is id 1653 while a sibling record on the same entity carries id 27218), implying an ID space of 27,000+ policy entries even allowing for gaps, across 40+ payers, all states, multiple lines of business and specialty categories, refreshed daily. Each record adds an AI summary, extracted billing codes and an action list, so the text corpus is materially larger than the record count alone. Exact current record count is not published and should be requested..
Prior-authorization and step-therapy automation, grounding authorization workflows against current payer rules; revenue-cycle denial prediction and appeals modeling keyed to policy effective dates; provider-side alerting and eligibility-workflow integration; payer-rule extraction benchmark data, since policy text mapped to billing codes and required actions is a high-quality supervised set for regulatory-document extraction and structured-output language models; pharma market access and specialty-pharmacy referral forecasting, because a new try-and-fail requirement immediately redirects dispensing volume; payer utilization-intensity indices as equity-research alpha on managed-care insurers, where tightening medical management is a margin lever visible ahead of earnings; and longitudinal health-policy research on how utilization controls propagate across payers and states.
The data is with 3 years of history.
Coverage spans US; Managed Care, Health Care Technology; alternative, reference, sentiment; equities.
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