You own the data
The platform runs in your cloud account under your business associate agreement with us. At the end of the engagement the data never leaves with us.
Healthcare / Insights as a Service
Insights as a service for healthcare payers and providers
An analytics platform starts to drift the month its build team leaves: feeds change, matches pile up and new measure specifications arrive. Agnotic Technologies runs your platform month to month, in your own cloud account, and brings every report and model change to your team for sign-off.
Your account
Data stays with you
Yearly
Measure updates applied
Sign-off
On every report
Trusted by global innovators
Industry Overview
What is insights as a service for healthcare payers and providers?
Insights as a service for healthcare payers and providers is a services engagement in which Agnotic Technologies runs your analytics platform month to month: feed checks, member and provider match review, yearly measure updates, model drift review and reports prepared for sign-off. You keep the data, the measure definitions and every clinical decision.
Ownership
Who owns what in an insights engagement?
The line between your team and ours is written down before the first month starts. It does not move when people change.
You own the measure definitions
Which measures run, which specification year and any local adjustment are your quality lead's decisions. We implement and test them.
You own every clinical and payment decision
Outreach lists, care gap actions and the use of any risk score are decided by your staff. Our outputs are inputs to those decisions.
We run the recurring work
Loads, checks, matching queues, measure runs, drift checks and report preparation, on the schedule in the table below.
Industry Challenges
Why do analytics platforms decay after the build?
The build usually goes well. The trouble starts in the months after, when nobody owns the recurring work.
New HEDIS specifications arrive for the measurement year and nobody owns the update, so last year's logic runs on this year's data.
Uncertain member matches pile up in a queue nobody reviews, quietly splitting one member into two records.
A risk model keeps scoring after an upstream coding change, and its outputs shift without anyone noticing.
Reports go out without a named approver, so a definition change surprises a provider group.
A vendor ends its contract and the data and code sit in its account, not yours.
Alerts still route to the inbox of someone who left last year.
Our Approach
How is an insights engagement set up?
Three things are in place before we take on the first month.
Your account, your keys
The platform, code repository and keys belong to you. Our engineers work through role-based access you can review and revoke.
A definition register
Every measure, model and report is listed with its owner, version and approver, so a change always has a name attached.
An exit plan from day one
Runbooks and code live in your repository, and the contract sets how PHI is returned or destroyed if the engagement ends.
Capabilities
What does the monthly analytics work include?
The recurring tasks behind the table, described as we run them. The platform build itself is covered on our healthcare data analytics page.
Feed and load checks
Each claims, eligibility and clinical load is checked for arrival, volume and schema change before downstream jobs run.
Matching review queue
Member and provider pairs the matching rules could not settle, shown side by side for your staff to merge, split or leave apart.
Measurement year update
New, changed and retired measures built in a test environment, run against last year's data and compared before your quality lead approves.
Drift review
Input distributions and score distributions compared month on month, with a short note on each model for your reviewer.
Report pack and sign-off
Reports versioned with the measure and data cut they used, sent to the named approver, and released only after approval.
Definition register upkeep
Owners, versions and approvals updated whenever a measure, model or report changes.
De-identified extracts
Data sets for research or outside partners prepared by the method your privacy officer chooses, with the method recorded.
Change requests
New measures, dashboards or feeds scoped, estimated and built under change control, separate from the monthly run.
How It Works
What does a month of insights work look like?
The cycle we run each month, with your team's decisions marked in each step.
Loads and checks
Feeds arrive and are checked; exceptions go to your data steward with what was found and what it affects.
01
1
Matching queue
Your staff work the queue of uncertain member and provider matches before the measure runs start.
02
2
Measure and model runs
Measures and models run on the frozen data cut, and their outputs are compared with the previous month.
03
3
Variance and drift notes
Every large change gets a short explanation: new data, a definition change, or something to investigate.
04
4
Report sign-off
The report pack goes to its named approvers, and nothing is released outside your organization without their approval.
05
5
Monthly review
We walk through issues, open change requests and next month's measure work with your analytics lead.
06
6
Engineering Stack
Systems and standards an insights engagement runs on
We work in the platform you already have, or the one we built with you.
Data movement
FHIR Bulk Data $export with _sinceX12 837 and 835 filesEligibility and roster flat filesHL7 v2 ADT feeds
Platform
Snowflake, BigQuery, Databricks or PostgreSQLdbt models in your repositoryAirflow or Dagster orchestration
Measures and models
Measure logic versioned in codeRegression tests against prior resultsModel monitoring jobs
Governance
Role-based access you controlAudit logsDe-identified extractsBusiness associate agreement
Responsibility table
Which analytics tasks recur, and what do you sign off?
This is the table we agree in the first month. Frequencies are set with you; the ones below are where most engagements begin.
| Task | Who does it | How often | What you sign off |
|---|---|---|---|
| Feed monitoring | Agnotic team | Every load | Any change to how a feed is mapped |
| Data quality checks | Agnotic runs them; your data steward triages exceptions | Every load | Exceptions you accept as known issues |
| Member and provider matching review | Agnotic queues uncertain matches; your staff decide | Weekly, or as volume requires | Each merge or split of a member or provider record |
| Measure specification update | Agnotic builds and tests the new year's logic; your quality lead reviews | Each measurement year | The measure version that goes live and any local change |
| Model drift review | Agnotic measures input and score drift; your analytics or clinical lead reviews | Monthly, and after any upstream data change | Keep, recalibrate or retire each model |
| Report refresh | Agnotic prepares; your named approver reviews | On the agreed report calendar | Every report before it leaves your organization |
| Access review | Agnotic lists accounts and roles; your security lead approves | On an agreed cycle | Who keeps access to the platform |
Measured Impact
Which signals show the platform is healthy?
Signals we watch every month and put in front of your analytics lead.
Freshness
Data as of
How current each source is, so a late feed is visible before a report goes out.
Queue age
Matching backlog
How long uncertain matches have waited for a decision.
Variance
Month on month
Measure rates and model scores that moved more than the agreed threshold.
Sign-off
Reports approved
Reports released with a named approver and the data cut they used.
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LERA Health: Women's Health App Platform
A women’s health product experience focused on guided care journeys, education, and compliance-aware workflows to support long-term engagement.
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Use Cases
When do payers and providers choose this model?
Moments when running the platform as a services engagement makes sense.
01
A measurement year is starting
New specifications need to be built and tested before the first runs.
02
A value-based contract adds measures
A provider group needs new measures run the way the contract defines them.
03
Analysts spend their time on loads
Your analysts should answer questions, not fix pipelines every morning.
04
A new payer or EHR feed joins
A new source needs mapping, matching and checks before it reaches reports.
05
The build vendor is leaving
Someone has to run the platform without moving it out of your account.
06
A model goes into production
A risk or outreach model needs drift review and a named owner from its first month.
Integrations
Which systems does the platform read from and report to?
The sources and destinations we monitor every month.
Payer data
Claims and eligibility from the payer core
Clinical data
EHR exports, including Epic and Oracle Health (Cerner)Health information exchange feedsLab result feeds
Reporting
Power BI, Tableau or Looker
Requests and issues
Your ticketing system
Compliance-First Development Services Backed by Global Standards
We build secure, scalable products designed for privacy, interoperability, and regulatory readiness from day one across every sector we serve.
Health Insurance Portability and Accountability Act
Protect PHI with privacy-first architecture, encrypted storage and transmission, and strict access controls.
Fast Healthcare Interoperability Resources
Enabling standardized health data exchange through standards-based API mappings.
Our Edge
Why Global Leaders Choose Us
We combine deep technical expertise with industry-specific knowledge to deliver solutions that aren't just functional, but transformational.
Enterprise-Grade Security
We implement rigorous security protocols and compliance standards (HIPAA, GDPR, SOC2) across all industrial solutions to protect sensitive data.
High-Performance Scaling
Our architectures are built to handle massive data loads and user bases, keeping performance steady whether you're serving ten or ten million.
Accelerated Time-to-Market
Using our suite of internal tools and proven frameworks, we cut setup work so your first release reaches users sooner.
Embedded AI Integration
Beyond simple wrappers, we build deep-learning integrations and predictive analytics directly into the core of your industry-specific workflows.
Engagement Model
How does an insights engagement start?
We start by reviewing what you run today. Timing depends on scope; we agree the first month's work on the scoping call.
01
Scoping call
We list your sources, measures, models and reports, and who approves each one today.
02
Platform review
We read the code, jobs and access setup, and note what must change before we take it on.
03
Responsibility table
Tasks, frequencies and sign-offs are agreed and written into the engagement.
04
First month
We run the cycle beside your team and adjust the table where reality differs.
05
Steady state
Monthly cycles, yearly measure updates and change requests under agreed change control.
Facts and sources
Rules and standards behind an insights engagement
Short facts the engagement model rests on, each linked to its primary source.
NCQA publishes HEDIS Technical Specifications for each measurement year, with a list of new, changed and retired measures and instructions on data collection and calculation.
Source: NCQA, HEDIS Measures and Technical ResourcesThe HL7 FHIR Bulk Data Access $export operation returns Newline Delimited JSON files and accepts a _since parameter, so a recurring feed can request only resources that changed after the last run.
Source: HL7 FHIR Bulk Data Access IG, ExportA HIPAA business associate contract must require the vendor, at termination and where feasible, to return or destroy all protected health information it still holds and keep no copies.
Source: 45 CFR 164.504(e)(2)(ii)(J) (eCFR)HIPAA allows two ways to de-identify health data: expert determination, or the safe harbor method, which removes 18 categories of identifiers.
Source: 45 CFR 164.514(b) (eCFR)
Voice of success
We don't just build products; we forge lasting partnerships. See how we've helped industry leaders transform their vision into technical reality.
“I can clearly see how Agnotic has a unique way of handling end-to-end development. They are always active on quick chat and provide support quickly.”
Aaron Phelan
Founder, Benchmark
“Agnotic combines deep technical expertise with strong domain knowledge. They understand the business context, anticipate challenges, and make collaboration smooth and effective.”
John Pasmore
Founder, Latimer
“Agnotic is the best technical team we evaluated. Their engineering excellence made our work dramatically easier and allowed us to stay focused on what matters most for maternal care outcomes. They took full ownership of the technical execution, and we are always happy to continue working together.”
Kim Smith
Founder, My Lauren
Related pages
Related analytics and operations pages
This page covers running analytics month to month. These pages cover the build and the systems around it.
Healthcare data analytics platform
Building the PHI-safe analytics platform that this engagement runs.
Payer analytics and AI development
Risk adjustment, HEDIS tracking and care gap models for health plans.
Healthcare managed services
Support, monitoring and releases for live health apps.
Value-based care platform development
Contracts, attribution and performance software for risk-bearing providers.
Software for health plans and payers
Payer core, member and provider systems that feed the analytics platform.
More in Healthcare
More Healthcare Solutions
Explore other production-grade engineering platforms we deliver across healthcare.
Cross-Industry Reach
The Same Engineering Patterns, Across Other Industries
The technical patterns behind this platform translate naturally into adjacent verticals.
Frequently Asked Questions
No. It is a services engagement. The platform, code and data stay in your account, and Agnotic Technologies provides the team that runs the recurring analytics work for you.
The number of sources and loads, the measures and models in scope, the volume of matching review, the report calendar and how many change requests you expect. We explain these drivers on the scoping call instead of quoting a price.
A named approver on your side for each report. We prepare and version the report with the data cut and measure version it used, and it is released only after that person approves it.
We build the new measurement year's logic in a test environment, run it against prior data, explain every difference and bring it to your quality lead. The version that goes live is their decision.
It is already in your account, with the code and runbooks in your repository. Our access is removed, and any PHI we hold is returned or destroyed as the business associate agreement requires.
Yes, after a platform review. We read the code, jobs and access setup first, and agree what has to change before we take on the monthly cycle.
No. Care gap actions, outreach and any use of a risk score are decided by your clinical and operations staff. Agnotic runs the analytics; your team decides what to do with them.
Industries