Clinical systems · Measurement-based care and collaborative care platform
Mirah
Mirah is a Boston company whose platform runs measurement-based care and the Collaborative Care Model for behavioral health and primary care organizations, with assessments, registries and outcome reporting.
Strong fit
- Primary care groups and health systems running the Collaborative Care Model
- Behavioral health organizations that want measurement-based care across many programs
- Pediatric and youth programs that need assessments for children and parents
Weak fit
- Solo therapists who want a low-cost assessment tool
- Buyers who want an EHR or note-writing tool
- Buyers who need a posted price
Bottom line
Mirah is a good choice for health systems and behavioral health organizations that want to run collaborative care and measurement-based care with real data. Its focus on collaborative care is a real strength, and customers praise its team. Small practices and buyers looking for a full EHR should look elsewhere.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Mark Potter and Hugh Barrigan founded Mirah in Boston in 2015 to bring data and analytics to behavioral health. Potter is chief executive and Barrigan is chief technology officer. Its advisors include psychiatrists from McLean Hospital and Harvard Medical School.
Mirah sends patients clinically validated assessments before visits, from a library of more than 540 measures, and shows clinicians the scores, trends and risk flags in time for the session. Leaders can compare outcomes across programs, clinicians and services.
For the Collaborative Care Model, in which a primary care team works with a behavioral health care manager and a psychiatric consultant, Mirah gives the whole team the same assessment data and progress tracking for each patient, and it works with staffing partners that supply care managers.
Mirah says more than 10,000 providers use it and that it has measured more than 627,000 patients with over 7.4 million assessments. Customers such as Eliot Community Human Services and Woodland Centers praise its data and its responsive team. It holds SOC 2 Type II and HITRUST certification.
Mirah does not post prices. It is built for organizations, so solo clinicians and small practices may find it more than they need.
Greenspace Health fits behavioral health organizations that want measurement-based care, intake and waitlist tools across many clinics. Blueprint fits therapists who want AI notes and treatment plans with published per-session pricing.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| Blueprint | 8.0 | 8.2 |
| Greenspace Health | 7.8 | 7.6 |
| Mirah | 7.6 | 7.4 |
Pricing
| Item | Detail |
|---|---|
| Model | Mirah sells its platform by subscription to organizations, priced by contract. |
| What usually drives cost | For Mirah, cost depends on the number of providers and patients measured, whether you run collaborative care, measurement-based care or both, and EHR integration. |
| What to ask before you buy | Ask Mirah for a price per provider or per patient, how it supports collaborative care billing in your EHR, and outcome data from programs like yours. |
| Published pricing | Mirah does not publish a price list. |
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.