Judgment
Executive-style agents frame tradeoffs across strategy, finance, quality, operations, and policy.
Make healthcare intelligence usable.
The U.S. healthcare market is not short on files, dashboards, or expert opinions. It is short on source-grounded intelligence that students, operators, researchers, builders, and communities can actually use.
Healthcare admin agents
Public-data tools with provenance
Profiles and open publishing
The intelligence stack.
A practical framework for turning public records into judgment, evidence, reference work, and competitive analysis.
Evidence
Callable public data keeps analysis tied to CMS, CDC, NIH, HHS, Census, and market sources.
Reference
USHSO turns system research into living public intelligence on finance, quality, strategy, and markets.
Inference
Open evidence becomes competitive intelligence and healthcare economics decision support.
Four connected projects, one market-opening agenda.
Each project is useful on its own. Together, they form a stack for creating, validating, publishing, and distributing healthcare strategy intelligence.
Live
Healthcare Admin Agents
Agents that can reason like a healthcare administration bench.
A portable bench of 51 healthcare administration specialists across 10 operating domains, packaged as prompt and skill files that can move between the tools teams already use.
- Organized like an operating bench: strategy, quality, compliance, revenue cycle, payer, health IT, pharmacy, emergency preparedness, and operations.
- Built for practical work: case analysis, market scans, executive memos, fellowship preparation, operating reviews, and adversarial review.
- Honest limitation: agents are not licensed professionals or magic authorities. Their value comes from structured expertise, transparent reasoning, and connection to verifiable data.
51agents
10divisions
23K+lines
34GitHub stars
6forks
BENCH ROSTER
Specialists for administration work, not generic chat.
Each file is a portable role definition with boundaries, domain memory, and expected deliverables.
Strategy and AdvisoryMarket logic, growth, executive synthesis.
Quality and ComplianceSafety, accreditation, regulatory exposure.
Finance and Revenue CycleMargins, reimbursement, payer economics.
Health IT and InformaticsData systems, interoperability, digital operations.
Managed CareNetworks, capitation, MLR, payer strategy.
OperationsThroughput, staffing, service lines, access.
INSTALLS INTO
Codex
Claude Code
Cursor
Windsurf
Gemini CLI
Cline
Amazon Q
Continue.dev
Markdown
CONTRIBUTORS WANTED
Help turn the bench into shared infrastructure.
Healthcare operators, policy/data people, and engineers can improve agents, add specialties, test examples, and file focused PRs.
Contribute on GitHub
Alpha
Healthcare Data MCP
The connector layer for the scattered public healthcare record.
Public healthcare data is everywhere and nowhere: CMS files, price transparency disclosures, research registries, sanctions lists, provider identifiers, grant databases, contract records, quality programs, demographic context, and market geography.
Healthcare Data MCP is a FastMCP toolkit that turns those sources into callable tools with structured responses, source metadata, bounded caches, and deployment modes for local agents or shared local processes.
Python
FastMCP
Local agents
Shared process
Structured responses
Source metadata
Bounded cache
- 18 MCP servers and 100 tools in the current alpha release.
- Designed for agent workflows that need sourced retrieval instead of hand-waved healthcare claims.
- Honest limitation: the public data layer is incomplete, messy, and frequently delayed. The product does not pretend otherwise; it makes provenance visible.
18servers
100tools
v0.1.1release
6GitHub stars
2forks
0open issues
DATA CONNECTOR COVERAGE
Public sources normalized for agent calls.
Tool responses carry source metadata, bounded cache behavior, and structured outputs instead of unsupported healthcare claims.
CMS and facility dataNPPES, quality, safety, star ratings.
Price and claims contextRates, volumes, service lines, case mix.
Public recordsSAM.gov, CHPL, 340B, breaches, exclusions.
Research and trialsNIH RePORTER, ClinicalTrials.gov profiles.
Market geographyDrive times, service areas, Census context.
Referral networksPhysician flows, leakage, network mapping.
REPOSITORY SIGNAL
Alpha codebase, recently active.
Building
United States Health Systems Observatory
The largest encyclopedia of comparative U.S. health system data.
USHSO is the synthesis layer: a living reference library that compares health systems as organizations, competitors, employers, capital allocators, care delivery networks, and public institutions.
Each report is designed to combine audited filings, CMS quality data, price transparency signals, service-line volumes, market geography, referral behavior, leadership changes, M&A activity, strategy, and public commitments into a single defensible profile.
System profiles
Audited filings
CMS quality
Market geography
Referral behavior
Leadership changes
Student access
- The goal is breadth and depth: system-by-system intelligence that students, operators, researchers, founders, journalists, and communities can actually use.
- Early coverage is intentionally narrow while the report format and data pipeline harden; Jefferson Health and Temple Health are the first visible examples.
- Student access is free. The commercial model exists to fund maintenance without hiding the methodology.
2visible examples
Freestudent access
Sourcemethodology-first
Paidsupport model
PROFILE DOSSIER
Comparative system intelligence with visible methodology.
Reports are meant to read like living dossiers: financial evidence, care quality, market position, and strategic movement in one place.
Financial performanceMargins, cash, debt, payer mix, capital allocation.
Quality and outcomesHCAHPS, readmissions, safety, star ratings.
Market positionShare, service areas, volumes, competitors.
Strategic directionLeadership, M&A, partnerships, expansion.
EARLY COVERAGE
Jefferson Health
Temple Health
Report format hardening
Data pipeline hardening
Live
American Journal of Healthcare Strategy
Open-access healthcare strategy needs serious publishing operations.
AJHCS is the public distribution partner in the portfolio: a journal, media platform, and knowledge institution built around open access to healthcare strategy, leadership, and management thought.
Open-Informatics supports organizations like AJHCS with website publishing, ranking, bookstore infrastructure, discoverability, and digital operations for free. That matters because open knowledge fails when the publishing layer looks amateur, fragile, or invisible.
Open access
Podcasting
Bookstore
Reports
Search
Newsletter
Institutional reach
- AJHCS gives the portfolio a public venue for evidence-based essays, interviews, reports, podcasts, and practical healthcare strategy writing.
- The infrastructure work is deliberately pro bono: the point is to make credible healthcare knowledge easier to publish and easier to find.
- Honest limitation: publishing reach is earned over time. The site is a compounding asset, not a finished institution.
13K+subscribers
500Kmonthly impressions
200+podcast episodes
PUBLISHING OPERATIONS
Open healthcare strategy moves through a durable distribution stack.
AJHCS is treated as live infrastructure: publishing, packaging, and audience channels are supported as one operating surface.
AJHCS.org publishing surface.
INFRASTRUCTURE SIGNAL
AJHCS.org is live and reachable.
HTTP 200 verified; public preview shows the journal, podcast, bookstore, and report infrastructure in one place.
PublishEssays, interviews, reports, and podcast episodes.
PackageBookstore, report pages, feeds, and archives.
DistributeSearch, social, newsletter, and institutional reach.
Impressive is not the same thing as inflated.
The portfolio is ambitious because the problem is large. The claims stay concrete: working repositories, visible publishing infrastructure, specific data sources, defined agent domains, and an explicit admission that public healthcare data is imperfect.
Source-first.
Agents should be pushed toward public evidence, citations, and data retrieval instead of confident unsupported summaries.
Open where possible.
The tools and publishing infrastructure are designed to expand access, not create another closed advisory moat.
Competitive by design.
The end state is a market where more people can compare health systems, challenge assumptions, and build better healthcare organizations.