ACOs & CINs
Population stratification and gap closure across networks.
Population Health
Population health management
We build platforms that turn scattered clinical and claims data into a ranked view of who needs care next: risk stratification, care-gap detection, and value-based-care analytics on a governed FHIR R4 foundation.
HIPAA-ReadyFHIR R4HEDIS-AlignedAudit Logged
Trusted by global innovators
What is population health management software?
Population health management software brings claims, EHR, lab and ADT data for a defined population into one record, ranks patients by risk, and flags open care gaps so care teams know who to contact first. Agnotic Technologies builds these platforms on a governed FHIR R4 data layer for ACOs, health plans and provider groups.
Population health management is a targeting problem: with limited care-management capacity, which patients get outreach first? We stratify claims, EHR, ADT, lab and SDOH data on a governed FHIR R4 foundation, so every care-gap list traces back to the data that produced it.
What it is
Knowing who needs care before they need the ER
Population health management software unifies data across a population and ranks patients by risk and actionability so limited care-management capacity goes where it moves outcomes and cost the most.
It succeeds when the lists it produces are trusted and acted on. We build platforms on governed, traceable data so risk stratification and VBC analytics survive clinical and financial scrutiny.
From raw feeds to a ranked care list
Risk stratification, care-gap detection, and VBC analytics on one governed data layer, so outreach goes where it matters.
What goes into a population health platform?
Each capability pairs a population-health outcome with the data standard or model behind it.
Risk stratification & rising-risk models
Predictive and rules-based risk stratification across the population, HCC and clinical risk scores plus rising-risk identification, so care management targets patients before they escalate to high-cost events.
Care-gap detection
Open-measure detection against HEDIS and eCQM specifications, surfacing overdue screenings, uncontrolled conditions, and missed follow-ups with prioritized worklists for outreach teams.
VBC analytics & cost insights
Value-based-care analytics on total cost of care, utilization, and quality performance, tied back to the risk-adjusted population so trends are meaningful rather than raw counts.
FHIR R4 data aggregation
A governed data layer unifying EHR data via FHIR R4, HL7 v2 feeds, claims, ADT event streams, and lab results, with patient matching and lineage so every metric is traceable.
SDOH & equity insights
Social-determinants data integrated into stratification so risk models reflect access, housing, and food-security factors, with equity-stratified reporting for accountable programs.
Registries & outreach workflows
Condition and program registries (diabetes, CHF, hypertension) with campaign and outreach tooling so identified patients move into action, not just a dashboard.
Where it runs
Who uses population health software?
Health plans
Member risk targeting and Star-measure improvement.
Provider groups
Panel-level risk and care-gap management for clinics.
FQHCs & community health
SDOH-aware outreach for underserved populations.
Chronic disease programs
Diabetes, CHF, and hypertension registries and outreach.
Public health
Population surveillance and program targeting.
Where population health software delivers
Impact comes from targeting the right patients with limited capacity. We build for actionable, traceable stratification: targets are defined against your programs in discovery.
FHIR R4
Governed multi-source data foundation
HCC
Risk-adjusted stratification
HEDIS
Care gaps detected to measure spec
Compliance-First Healthcare App Development Services Backed by Global Standards
15-Minute Scoping Call01
HIPAA
Health Insurance Portability and Accountability Act
Protect PHI with privacy-first architecture, encrypted storage and transmission, strict access controls, and traceable audit logs.
02
GDPR
General Data Protection Regulation
Implement lawful consent flows, data minimization, retention controls, and secure processing for sensitive health data.
03
FHIR
Fast Healthcare Interoperability Resources
Enable standardized health data exchange across apps, care teams, and systems through standards-based FHIR APIs.
04
HL7
Health Level Seven International
Support enterprise-grade interoperability with HL7-based integrations for records, events, and clinical messaging workflows.
05
HITRUST
Health Information Trust Alliance
Align security programs to healthcare-specific control and risk management practices trusted by providers and ecosystem partners.
06
HITECH
Health Information Technology for Economic and Clinical Health Act
Design with breach notification readiness, digital record safeguards, and operational controls that support regulated care programs.
07
SaMD
FDA Software as a Medical Device
Plan software quality, traceability, and documentation pathways for products that may require SaMD review and submission.
08
MDR (EU)
Medical Device Regulation (European Union)
Prepare EU market-ready processes for risk classification, evidence tracking, and lifecycle governance under MDR expectations.
09
SAMHSA
Substance Abuse and Mental Health Services Administration
Apply confidentiality controls and consent-aware sharing models for behavioral and mental health data experiences.
Standards we build against
Which standards does population health software use?
FHIRHL7HEDISeCQMHCCHIPAA
Our Process
How do we build population health software?
Data aggregation, stratification models, and outreach workflows run in parallel toward an actionable platform.
1.
Population & data discovery
We map your populations, programs, and data sources, then design the patient-matching and risk-stratification approach before building.
Population-aware
2.
Data foundation
We build the FHIR R4 data layer aggregating EHR, claims, ADT, and lab feeds, with patient matching and lineage the analytics depend on.
Governed data
3.
Stratification & gaps
Risk models, care-gap detection, and registries, validated against clinical review so the rankings are trusted by the teams that act on them.
Actionable lists
4.
Outreach & go-live
Worklists, outreach tooling, and dashboards, with ongoing tuning as measure specs and programs change.
Always audit-ready
Facts and sources
Which rules shape population health software?
Short facts we design population health platforms around, each linked to its primary source.
The HL7 FHIR Bulk Data Access implementation guide defines a standard, FHIR-based way to export data on a group of patients to a pre-authorized client, for uses such as sending a patient roster's clinical data to an ACO to calculate quality measures.
Source: HL7 International, FHIR Bulk Data Access (STU 3)ONC certification criterion 170.315(g)(10) requires certified EHRs to offer a standardized API for patient and population services based on HL7 FHIR.
Source: 45 CFR 170.315 (eCFR)The HIPAA Security Rule requires administrative, physical and technical safeguards for electronic protected health information.
Source: 45 CFR Part 164 Subpart C (eCFR)A HIPAA covered entity may share protected health information with a business associate, such as a software vendor, only under a business associate agreement that commits the vendor to safeguard it.
Source: 45 CFR 164.502(e) and 164.504(e) (eCFR)
Featured case study
Read Case StudyLera Health: compliant women's health platform
Related proof of compliant delivery: Lera Health isn't a population-health platform, but building its data-driven, personalized care workflow shows how we turn multi-source health data into trustworthy, traceable insight, the same foundation stratification depends on.
Why Partner With Us
15-Minute Scoping CallWhy do care organizations choose Agnotic?
We bring data-engineering depth, measure fluency, and compliance-first design so your risk lists are trusted and your analytics are defensible.
Governed & Traceable
Every risk score and care gap traces back to source data with lineage: care teams trust lists they can inspect.
Data & Measure Fluency
FHIR aggregation, patient matching, HEDIS, and HCC logic are our baseline, not a research project billed to you.
From Dashboard to Action
We build the outreach and worklist layer so identified patients actually get contacted, not just counted.
Equity-Aware Design
SDOH integrated into stratification so programs target need, not just billing signals.
Our relevant experience
Analytics that move patients into care
Frequently Asked Questions
Cost is driven by data-source count, patient-matching complexity, and the depth of risk and measure logic. We scope against your populations, programs, and available feeds in discovery and give a fixed estimate.
The data foundation drives the timeline: how many feeds you have, how clean they are, and how hard patient matching is. We put an initial population and set of care gaps live first so outreach can begin, and validate stratification against clinical review before teams rely on the lists.
Yes. Agnotic signs a business associate agreement before any PHI is shared, and development and test environments use synthetic or de-identified data. HIPAA safeguards such as encryption, role-based access and audit logging are built in from the first sprint.
Yes. We scope the first release to one workflow, usually one population, a small set of care gaps and an outreach worklist fed by your main EHR and claims data. More populations, measures and data sources follow on the same base.
AI tools help our engineers draft code and tests, but a person reviews every change, and it passes the same automated tests and security checks as any other code, including tests on measure and risk logic. Which tools may see your code or data is agreed with you at the start.
Buy when a standard vendor covers your populations and measures and you accept its models. Build when you need custom stratification, SDOH-aware targeting, an owned data layer feeding multiple tools, or integration depth that packaged products don't provide.
We aggregate clinical data via FHIR R4 and HL7 v2, pull population-level data with bulk FHIR $export, and ingest claims and ADT feeds. Patient matching resolves records across sources into a governed FHIR data layer with full lineage back to each origin.
We combine transparent, configurable stratification logic with lineage, so a care manager can see why a patient ranked where they did. Care gaps are computed against HEDIS and eCQM specs, and models are validated against clinical review before they drive outreach.
Yes. PHI is encrypted at rest and in transit, access is role-based and audit-logged, and the data layer is governed with lineage. That record supports program and regulatory reporting.
Ready to target care where it counts?
Tell us your populations and data sources. We'll return a population-health plan with data-foundation scope, stratification approach, and a realistic timeline.
contact@agnotic.com
Partnerships
contact@agnotic.com