Capabilities
Applied research on the data agencies already hold.
Three capabilities, one field. We design the study, run the analysis, and say what the result does and does not support — on existing clinical, claims, and public-health data, under one standard: pre-specified methods, reproducible analysis, and evidence a review board can read.
The consoles on this page are illustrative product concepts, not screenshots of delivered systems.
NAICS 541715· Primary
Life & Health Sciences R&D
Study design and analysis on data agencies already hold. From forecasting an outbreak to measuring whether a treatment worked: retrospective and observational research, clinical outcomes, epidemiological modeling, and health services research for government health programs. Scenario models that quantify what an intervention buys, time-to-event analysis that shows who benefits, and statistics rigorous enough to publish and reproducible enough to audit.
Hale MDS · Population health
SYNDROMIC · WK 36
Surge probability
78%
12wk · P(≥28/100k) · peak wk 43
Projected peak
31.4
per 100k · wk 43 · CI 26–37
Lead time
6 wk
median crossing · wk 42
Respiratory admissions per 100k — 12-week surge outlook
Hale MDS · Geo surveillance
TAMPA BAY · WK 30 · PER 100K
Choropleth map of the Tampa Bay region — real Census ZIP-code boundaries for Hillsborough, Pinellas, and southern Pasco counties — shaded light to dark blue by weekly syndromic rate per 100,000. A three-ZIP cluster in East Tampa is flagged in amber and under review; a milder rise shows in south St. Petersburg. Illustrative rates over real geography.
Hale MDS · Outcomes research
TIME-TO-EVENT · 24-MO FOLLOW-UP
Time to readmission after discharge — % remaining event-free
Adjusted hazard ratios — Cox proportional-hazards model
Filled marker · CI excludes 1.0
What we deliver
- Retrospective and observational study design on existing data
- Clinical outcomes and comparative-effectiveness research
- Epidemiological modeling, surveillance and geospatial analysis
- Health services research: access, utilization and cost
- Time-to-event analysis and hazard estimation
- Publication-grade statistical analysis, reproducible end to end
NAICS 541714
Applied Analytic Methods
Methods that make secondary data answer a question defensibly — phenotyping, confounding control, bias analysis, and privacy-preserving analytics. Data collected for care and payment was not collected for the question in front of you; the method is what closes that gap, and it is written down before the first query runs. Every workflow is reproducible end to end, because research that can't be rerun can't be trusted.
Hale MDS · Cohort comparison
IPTW · N = 2,418 vs 2,391
Standardized mean differences — before and after weighting
Hollow · before Filled · after
Effect on 30-day readmission — care-transition programme vs usual care
Risk difference · 95% CI
- Crude
- −7.8 pp (−9.6 pp to −6.0 pp)
- Weighted
- −3.2 pp (−5.1 pp to −1.3 pp)
The crude comparison credits the programme with more than it did: it enrolled the sicker patients. Balancing the cohorts is what makes the two numbers comparable — and the adjusted interval still excludes zero.
What we deliver
- Cohort and case definition on EHR and claims data
- Confounding control: propensity methods, weighting and matching
- Bias analysis and sensitivity analysis
- Missing-data methods and measurement-error assessment
- Privacy-preserving analytics and de-identification
- Methods documentation a reviewer can audit
NAICS 541690
Scientific & Technical Consulting
Physician-led advisory to federal health programs: framing the clinical question, designing the protocol that can answer it, and serving as principal investigator or subject-matter expert on the work that follows. The judgment being sold is clinical — what an outcome measure actually captures, which confounders matter in a population, and what a result does and does not license a programme to conclude.
What we deliver
- Clinical advisory and protocol design for federal health research
- Principal investigator and subject-matter expert support
- Outcome-measure selection and endpoint definition
- Study feasibility, sample-size and power assessment
- Independent review of research designs and analytic plans
- Translation of research findings into programme decisions
Reproducible analysis pipelines
Analysis that can be rerun is analysis that can be trusted. Versioned data and code, engineered pipelines with full lineage, documented decisions, and interfaces designed to Section 508 from the first sketch — so a reviewer can regenerate every figure from source and see how it was made.
What we deliver
- Engineered data and analysis pipelines with full lineage
- Versioned data and code; every figure regenerates from source
- Analysis plans written before the first query runs
- Accessible interfaces designed to Section 508 / WCAG 2.2 AA
- API design and modernization of legacy service layers
- Automated testing and documentation as first-class deliverables
Secure research environments
Health data deserves infrastructure built for it. We design the platforms that ingest, process, and serve clinical and claims data at scale — and the research enclaves where sensitive datasets can be analyzed without leaving governed boundaries. Accreditation is treated as an engineering problem: controls as code, evidence generated automatically, environments reproducible from day one.
Hale MDS · Platform operations
US-EAST · ENCLAVE 03
Uptime · 90d
99.996%
SLO 99.95 · enclave fleet
API p95
38 ms
FHIR R4 · trailing 24h
Ingest lag
1.8 s
event → queryable · p95
Error budget
72%
remaining · 30d window
Streaming ingest — trailing 4h, all pipelines
Σ 32.5k ev/s
HL7v2 ADT/ORU · X12 837 claims · FHIR R4 bulk · registry extracts — k events/s
Query latency — p95 by hour of day
Enclave storage — used vs provisioned
What we deliver
- Enclave architectures that inherit their controls from the hosting environment
- Research enclaves for sensitive and limited datasets
- Streaming and batch ingestion from legacy and modern sources
- Clinical and claims data processing at population scale
- NIST SP 800-171 aligned controls with automated evidence collection
- Observability, monitoring, and documented incident response procedures
Health data engineering & interoperability
Data exchange is where health IT programs go to die. Hale MDS works natively in the standards — FHIR, HL7v2, X12, OMOP — and have connected systems that were never designed to talk. On top of that plumbing we design the intelligence: clinical decision support at the point of care, and AI-driven medical systems that survive contact with government oversight — documented, monitored, bias-tested, and explainable to a review board.
Hale MDS · Health-data interoperability
IFACE ENGINE · TERM SVCS · CDS
Feed volume
393k
messages/day · 5 live feeds
Code-map hit
99.8%
SNOMED↔ICD-10 · LOINC · RxNorm
End-to-end p95
1.1 s
feed arrival → CDS card
Hover or tab through feeds, services, and links for protocol, daily volume, and p95 latency.
Hale MDS · Claims integrity
RISK MODEL · AUC 0.98
Claims embedding — anomaly surface
ROC — drag the operating point
Operating point at t = 0.50
Precision
69%
35 true of 51 flagged
Recall
83%
35 of 42 fraud caught
Flag rate
10.0%
51 of 512 claims held
Why this flag — feature contributions (top claim)
base risk 0.08 → model score 0.83
What we deliver
- Clinical decision support embedded in daily workflow
- FHIR R4 servers, facades, and bulk-data pipelines
- HL7v2, C-CDA, and X12 interface engineering
- Terminology services: SNOMED CT, LOINC, RxNorm, ICD-10 mapping
- Risk models with model cards, drift monitoring, and bias testing
- Health IT modernization — incremental strangler-fig, not big-bang
How we work
Compliance is part of the study design, not a stage after it.
HIPAA
Privacy by design
De-identification, minimum-necessary access, and audit trails built into every data flow.
NIST SP 800-171
Controls as code
Security controls implemented as code with evidence collected automatically, so accreditation is not a retrofit.
Section 508
Accessible by default
WCAG 2.2 AA conformance designed in and tested with assistive technology.