Population health & analytics · Health data intelligence
IMAT Solutions
IMAT Solutions provides health data intelligence and population reporting software for payers, HIEs, and provider networks. It is not an EHR replacement.
Strong fit
- Payers, health information exchanges, and provider networks that need health data combined in real time, plus quality reporting
- Teams replacing fragile data warehouses that update in batches
- Buyers comparing mid-sized population health analytics tools, not the largest data platforms
Weak fit
- Small rural clinics that only need a simple EHR quality dashboard
- Buyers looking for AI scribes or patient billing tools, with no need for analytics
- Organizations unwilling to pay to connect their data sources
Bottom line
IMAT Solutions is worth using for mid-sized organizations that need to bring together clinical data for quality reporting and analytics. It suits teams with clean source feeds and clear data governance. Community health centers may prefer Azara, and post-acute analytics buyers may prefer Trella.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
IMAT Solutions is a health data company in Pleasant Grove, Utah, led by CEO Ken Barbe.
Its software brings together clinical and related healthcare data from different systems for quality reporting and analytics. It is population health software, not an EHR.
Results depend on clean data sources and good data rules more than on how the dashboards look.
Setup is a data project. Onboarding and pricing are about as clear as is typical for this kind of software.
Among population health tools we review, IMAT scores below Azara, Persivia, and Trella on how widely known it is. It scores above Lightbeam when a smaller data platform fits better.
Azara suits safety-net clinics using DRVS. Persivia suits buyers considering full population health suites such as CareSpace, and Trella suits analytics for nursing, rehab, and home care.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| Azara Healthcare | 7.6 | 7.2 |
| Cozeva | 7.5 | 7.2 |
| Persivia | 7.4 | 7.1 |
| Syra Health | 7.4 | 7.1 |
| Certilytics | 7.3 | 7.0 |
| Trella Health | 7.3 | 7.0 |
| IMAT Solutions | 7.0 | 6.7 |
| Elligint Health | 6.9 | 6.6 |
| Olio | 6.9 | 6.7 |
| Lightbeam Health Solutions | 6.8 | 6.5 |
| Relevant Healthcare | 6.8 | 6.6 |
| Hexplora | 6.7 | 6.5 |
Pricing
| Item | Detail |
|---|---|
| Model | A subscription platform for health data and population reporting. Prices are quoted by organization size and data volume. |
| What usually drives cost | The number of members or patients, data sources, modules, and support. |
| What to ask before you buy | The full first-year cost, including connecting data and the ongoing subscription at your population size. |
| Published pricing | IMAT does not publish prices. Expect a quote. |
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get IMAT Solutions to function | |
| A named analytics owner for quality and missed-care programs | Dashboards with no owner do not change care. |
| A written list of data sources (EHR, claims, admission and discharge feeds) | Missing data brings back blind spots. |
| Starting numbers for quality and missed care | You cannot show value without a starting number. |
| Data sharing and business associate agreement approved | Blocked data stalls launch. |
| Clinic owners for patient outreach lists | Reports without outreach change nothing. |
| What will maximize your value | |
| Track closed missed-care items every week for 90 days | Counting logins does not show results. |
| Test with one contract or patient group before rolling out everywhere | A small real win is worth more than a broad launch with nothing behind it. |
| Retire duplicate spreadsheets after a month of running both | Entering everything twice doubles the cost. |
| Hold a regular meeting on data feed failures | Problems nobody raises hide bad data. |
| Send clinical leaders a monthly quality summary | Problems no one reports surprise everyone later. |
| Deal-breakers | |
| No one will own connecting data or quality work. | |
| You will not build the connections the platform needs. | |
| You expect an analytics tool to replace your EHR. | |
| Leaders will not act on missed-care lists. | |
| Legal blocks the data sharing it needs. | |
Value creation time frame
| # | Stage | Typical range |
|---|---|---|
| 1 | Plan and measure the starting point | 2-4 weeks. Set measures, list data sources, and sign contracts. |
| 2 | Set up | 6-14 weeks. Connect data, build models, and check results. |
| 3 | Pilot | 1-2 months. One patient group, with an outreach guide. |
| 4 | Expand | 2-6 months. Add contracts and retire side files. |
Leadership
Methodology
| Weight | Factor | What it measures |
|---|---|---|
| 35% | Customer outcomes | Whether buyers get measurable operational or clinical-workflow results after go-live |
| 30% | Product | Capability depth, reliability, and fit for the job the category buys |
| 20% | Implementation | How hard it is to stand up, integrate, train, and stabilize |
| 15% | Pricing clarity | Whether a buyer can model total cost without a mystery quote |
| Label | Meaning |
|---|---|
| Highly recommend | Strong outcomes and product with manageable caveats |
| Recommend | Solid fit for the right buyer; know the tradeoffs |
| Conditional | Only with a specific use case or heavy caveats |
| Not recommended | Avoid for most buyers in this category |
Read our full methodology for how we weight scores and assign recommend labels.