Patient engagement & telehealth · Behavioral health operations platform
Mend
Mend is operations software for behavioral health organizations that automates scheduling, digital intake, reminders, and coordination so more patients complete their visits.
Strong fit
- Community behavioral health centers, CMHCs, CCBHCs, and FQHCs that lose revenue to no-shows and slow intake
- Organizations that want patients to schedule, complete intake, and get reminders on their phones
- Behavioral health teams measuring utilization, no-show rate, and patient experience together
Weak fit
- Acute hospitals shopping for inpatient EHR modules
- Solo therapists who only need a simple booking link
- Buyers who need a published per-seat price list
Bottom line
Mend, based in Orlando, Florida, is operations software for behavioral health organizations that automates access, intake, reminders, and coordination so more scheduled patients show up. Customers report average no-show rates around 7.4%, down from industry norms above 20%. It fits community behavioral health centers that want more completed visits without adding front-office headcount.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Matt McBride founded Mend in Orlando to close the gap between a scheduled behavioral health appointment and a completed visit.
Warren Bates had run multi-site ABA therapy operations and then served as Mend's president and COO. He became CEO in April 2023, and McBride moved to chief technology officer.
Mend's platform covers scheduling and access, patient reminders, care coordination and risk signals, and analytics for measuring care. Patients complete intake on their phones instead of long paper packets. The system fills open slots when cancellations appear.
Mend says more than 40 million patient appointments have run on the platform. It cites an average no-show rate of 7.4%, against industry averages above 20%, and patient Net Promoter Scores around +60.
It sells to CCBHCs, CMHCs, and FQHCs. Mend sits beside the clinical record as the operations layer, not as a replacement EHR. The pitch is more paid visits from fewer no-shows and less staff time on each intake.
Spruce Health or OhMD fit when the main need is secure messaging for outpatient practices. Curogram or Emitrr fit when text reminders and two-way texting are enough.
Dialog Health fits when mass and conversational texting is the main buy. Upheal or Blueprint fit a buyer who mainly wants AI notes inside behavioral health visits rather than front-office tools.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| Mend | 7.8 | 7.6 |
| OhMD | 7.5 | 7.4 |
| Curogram | 7.5 | 7.3 |
| Spruce Health | 7.3 | 7.4 |
| Emitrr | 7.2 | 7.1 |
| Dialog Health | 7.0 | 7.1 |
Pricing
| Item | Detail |
|---|---|
| Model | A subscription quoted by Mend, sized to your sites, providers, and modules. |
| What usually drives cost | The number of locations and providers, which modules you turn on (access, engage, coordinate, signal), appointment volume, and connections to your EHR or practice system. |
| What to ask before you buy | Monthly cost at your appointment volume, what intake automation and analytics add, and how pricing changes if you add sites. |
| Published pricing | Mend 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.