Clinical systems · Shared patient record & data platform
Zus Health
Zus Health is a shared health data platform that gathers a patient's outside records into one continuously updated record for care teams and the software they use.
Strong fit
- Groups paid for outcomes that want outside records in front of clinicians before a visit
- Digital health companies that would rather build on a shared FHIR patient record than build their own data pipes
- Teams working on risk adjustment and quality gap closure from network data
Weak fit
- Groups that only need a single HL7 connection between two systems
- Health systems that only need the outside records their EHR's built-in exchange returns
- Buyers who need a published price list
Bottom line
Zus Health is worth using for care teams and health software companies that want a patient's outside records gathered into one continuously updated record. Care teams use it for pre-visit review and risk adjustment and quality gaps. Teams mainly moving data between two systems should look at Redox.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Zus Health is a health data company founded in 2021 by athenahealth co-founder Jonathan Bush, who leads it. It launched in June 2021 with a $34 million Series A led by Andreessen Horowitz.
Its network finds a patient's records in EHRs, national exchange networks, labs, pharmacies, imaging centers, and payer systems, and removes duplicates.
It keeps one ongoing record that the customer's software can read through APIs or inside the clinician's workflow.
Care teams use that shared record to see outside history before a visit and for risk adjustment and quality work, and software companies build their products on its data platform.
Compare Metriport when an engineering team wants an open-source records API, and Health Gorilla when the team needs a QHIN for TEFCA access.
Redox fits when the work is mainly moving data between two systems.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| Particle Health | 7.4 | 7.0 |
| Kno2 | 7.3 | 7.3 |
| Zus Health | 7.2 | 7.0 |
| Metriport | 7.2 | 7.2 |
| Redox | 7.1 | 6.8 |
| Smile Digital Health | 7.1 | 6.6 |
| Onyx | 7.0 | 7.0 |
| Health Gorilla | 6.9 | 6.8 |
| 1upHealth | 6.7 | 6.5 |
Pricing
| Item | Detail |
|---|---|
| Model | A subscription for larger buyers, quoted by Zus, with terms set by the patients covered and the data services used. |
| What usually drives cost | Number of patients, which data sources are pulled, and whether risk adjustment and quality tools are added. |
| What to ask before you buy | Yearly price for your number of patients, what each data source costs, and fees for EHR or app integration. |
| Published pricing | Zus Health does not publish a price list. |
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get Zus Health to function | |
| Patient roster and identity data | The network needs clean demographics to find records. |
| Use cases picked first | Pre-visit review and risk adjustment need different setups. |
| Clinical workflow owner | Records only help if someone reads them before the visit. |
| Engineering or EHR app plan | Data has to show up where clinicians work. |
| Data use agreements signed | Network rules apply to every query. |
| What will maximize your value | |
| Start with pre-visit preparation for one clinic | Clinicians see the value quickly. |
| Measure gaps closed per month | Ties the data to payments and quality. |
| Drop duplicate vendors that pull records | Two feeds cause conflicting records. |
| Deal-breakers | |
| No clean patient roster | |
| You only need one HL7 connection | |
| No owner for clinical workflow | |
Value creation time frame
| # | Stage | Typical range |
|---|---|---|
| 1 | Data agreements and roster load | 3-6 weeks |
| 2 | First use case live | 4-8 weeks |
| 3 | Add more uses | 2-3 months |
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.