Picture a developer at a health tech startup staring at a patient scheduling screen inside eClinicalWorks. The task is straightforward: pull appointment data into a new AI scribe tool so visit notes can be generated automatically. There is no REST endpoint. There is no webhook. There is no documented integration path. The only way to get data out of this system is the same way the front desk staff does it, clicking through the interface one screen at a time.
This is not an edge case. It is the default state of healthcare IT. Optexity exists because the vast majority of healthcare systems (EHRs, payer portals, billing platforms) were built in an era before APIs were standard practice. The result is an industry sitting on decades of critical patient data locked inside interfaces that only humans were supposed to use.
Understanding why the wall exists, and what your options are for getting around it, is the first step toward building healthcare integrations that actually work.
Why Legacy Healthcare Systems Were Never Built for APIs
The absence of APIs in legacy healthcare platforms is not an oversight. It is a consequence of when and how these systems were designed.
Pre-interoperability architecture
Systems like eClinicalWorks, PracticeSuite, and AdvancedMD were built when healthcare software meant standalone applications. Data models were proprietary. Communication between systems happened through HL7 v2 messages, a standard from the late 1980s that uses pipe-delimited text rather than the structured JSON or XML that modern APIs expect. A systematic review of FHIR implementations found that 95% of US healthcare organizations still rely on HL7 v2 as their primary interoperability standard.[1]
Regulatory and technical barriers
HIPAA and other healthcare regulations create legitimate caution around modifying production systems. Any change to a system handling protected health information triggers:
- Compliance review and security assessment
- Re-certification processes
- Vendor risk analysis
For vendors maintaining legacy codebases, the risk calculus of adding API layers to systems that already work (even if they work poorly) rarely justifies the engineering investment.
The technical barriers run just as deep. Many legacy EHRs run on outdated technology stacks like COBOL, Visual Basic, and early .NET frameworks that were never designed to support external API consumers. Retrofitting an API onto a system built with tightly coupled components, hardcoded business logic, and no service layer is not a feature request. It is a re-architecture project.
No incentive to change
For most of their existence, these platforms operated as closed ecosystems. Clinics bought one EHR, and that vendor controlled the entire workflow. The demand for third-party integration from AI scribes, patient intake tools, and RCM platforms is a recent phenomenon driven by the AI wave. Legacy vendors are responding slowly because their architectures cannot respond quickly.
Some vendors have attempted to add API layers, but the results are often partial: a handful of read-only endpoints covering the most common data requests but leaving out the complex workflows developers actually need. Full-featured APIs require re-architecting the data layer, which for a system serving thousands of active clinics, carries enormous operational risk.
The Consequences of the API Gap
The absence of APIs does not just inconvenience developers. It creates systemic problems across healthcare operations that compound over time.
Data silos that resist connection
A single hospital commonly operates hundreds of disconnected health IT systems:
- Patient data lives in the EHR
- Insurance information sits in payer portals
- Billing data resides in practice management software
- Lab results arrive through separate channels
Without APIs, moving data between these systems requires manual re-entry or brittle file-based integrations. ONC data shows that by 2021, only 74% of hospitals could integrate external data into their EHRs. More than one in four hospitals still could not.[2]
Manual workarounds that drain staff
When systems lack APIs, human operators become the integration layer. Billing teams log into Availity for one patient, Aetna for the next, then cycle through UnitedHealthcare and Cigna before switching to Humana. That process alone can take ten or more minutes per patient on eligibility verification.
Clinical staff copy-paste between systems. Schedulers toggle between platforms to find open slots. The labor cost of manual integration is enormous and largely invisible in operating budgets because it is distributed across every department that touches patient data.
Compliance exposure from manual processes
Manual data transfer is error-prone data transfer. Every time a staff member re-keys patient information, there is a chance of transcription error. In healthcare, those errors affect:
- Claim accuracy and reimbursement timing
- Patient safety when clinical data is misrecorded
- Regulatory compliance when audit trails have gaps
- Denial rates when eligibility data is entered incorrectly
Denied claims require rework. Misrecorded clinical data triggers patient safety reviews. Missing audit trails create liability during compliance audits.
Innovation bottleneck for health tech
The most immediate casualty is the developer building something new. AI scribes need to write notes back into EHRs. Patient intake tools need to schedule appointments across platforms. RCM automation needs to verify eligibility across payer portals.
Without APIs, each of these use cases requires a custom workaround for every legacy system. The list is long: eClinicalWorks, drchrono, PracticeSuite, AdvancedMD, AthenaOne, Optimantra, and more.
Current Approaches and Where They Fall Short
Several strategies exist for bridging the API gap. Each solves part of the problem while introducing new limitations.
FHIR and HL7 modernization
FHIR is the industry's long-term answer to healthcare data exchange. In theory, it provides a modern, RESTful API framework for reading and writing clinical data. In practice, adoption is uneven and incomplete.
Many legacy platforms support only a subset of FHIR resources, and the implementations that exist often lack the custom operations developers actually need: prior auth submission, appointment booking across specific provider schedules, or complex eligibility queries. FHIR also assumes both systems participate willingly. When the legacy vendor has no incentive to build FHIR endpoints, your organization is stuck waiting.
Healthcare data aggregators
Platforms like Stedi and various FHIR intermediaries attempt to provide a single API connecting to multiple healthcare systems. The pitch is compelling: one integration point for dozens of platforms. The reality is less clean:
- Aggregators only work with systems that support their standards
- Legacy portals like Ambetter, Peachstate, or Modemed often lack the required infrastructure
- Coverage is incomplete and pricing scales per transaction
- Data is often stale and does not reflect actual current answers, since aggregators rely on cached or periodically synced information rather than live portal data
- Reliability depends on the weakest link in the chain
Direct database access and middleware
Some organizations build custom middleware layers or negotiate direct database access with vendors. This approach is fragile, expensive to maintain, and often violates vendor licensing agreements.
Even when direct access is available, legacy data models are rarely documented for external consumers. Field names are cryptic. Relationships between tables are implicit. Building a reliable integration against an undocumented schema is a maintenance nightmare.
Traditional RPA
Robotic process automation tools like UiPath and Automation Anywhere can script interactions with healthcare portals. But traditional RPA scripts are brittle. When a portal updates its interface, scripts break. For an organization automating across a dozen payer portals, one UI change on one portal can break the entire batch process.
What to Do About It: Browser Automation as the API Layer
The pattern that solves the legacy healthcare API gap is browser automation, but not the brittle scripting of traditional RPA. Modern browser automation records human workflows and converts them into deterministic, API-triggered processes that adapt when portal interfaces change.
The core idea: if a human can do it in a browser, a deterministic automation can do it faster, without errors, at scale. No vendor permission required. No waiting for them to build an API. You work with the interface that already exists.
How it works in practice
- Record the workflow. A developer demonstrates the task (logging into a payer portal, running an eligibility check, extracting patient coverage details) using a browser extension. The platform captures every interaction as a structured sequence.
- Generate a deterministic automation. The recording converts into a structured automation that executes the same steps reliably on every run. No large language model deciding what to click next. No random variation between executions.
- Deploy as an API endpoint. The automation becomes callable via API. Your application sends a request with patient parameters and receives structured data back. The same data your staff would have extracted manually, delivered programmatically.
- Self-heal on UI changes. When a portal updates its interface (moved buttons, renamed fields, layout changes), self-healing locator systems maintain multiple identification strategies for each UI element and adapt without manual intervention.
This approach works with any portal that has a web interface. On the EHR side, that includes eClinicalWorks and drchrono. On the payer side, Availity, Aetna, and UnitedHealthcare. If your team can navigate it in a browser, it can become an API endpoint.
The Peachstate Medicaid automation is a concrete example: a legacy Medicaid portal with no API, fully automated through browser interaction. No middleware. No vendor cooperation. No waiting for a FHIR endpoint that may never arrive.
Why Optexity for Legacy Healthcare Integration
Optexity built its platform around the specific challenges health tech developers face when integrating with legacy systems.
Record once, deploy as API
You demonstrate the workflow once using Optexity's browser extension. The platform converts your recording into a deterministic automation callable via API endpoint. No scripting. No prompt engineering. No weeks-long integration projects.
Most AI browser agents use large language models on every step, deciding what to click, what to type, and where to navigate. Each LLM call adds latency and cost while introducing unpredictability. Optexity takes the opposite approach: automations execute the same steps reliably every time, which matters when compliance-sensitive healthcare data is involved. The result is 3x faster execution than comparable AI-driven alternatives at 10x lower cost.
Built for healthcare from the ground up
Optexity maintains prebuilt automations for major payer portals and EHR systems with built-in support for:
- Two-factor authentication handling
- Persistent browser sessions
- Concurrent request processing
These are requirements that generic automation tools treat as afterthoughts. The platform also works where aggregators cannot. When Nanonets needed to integrate with multiple EHR platforms that lacked APIs, browser automation provided universal coverage. The integration deployed in under 20 minutes, compared to the weeks or months typical of custom API development.
Coverage that scales predictably
The same recording-based approach works for every portal. Build an automation for Availity, then Aetna, then UnitedHealthcare. Each automation is independent, so a UI change on one portal does not affect the others. Your integration coverage grows predictably with effort, not exponentially with complexity.
The result: your development team stops treating legacy healthcare systems as immovable obstacles. Each portal becomes an API endpoint. Each manual workflow becomes an automated process. The API gap still exists in the software, but it no longer exists in your operations.
FAQs
Why don't legacy EHR vendors just build APIs?
Building APIs for legacy systems is a re-architecture project, not a feature addition. Many platforms run on decades-old technology stacks where internal data models were never designed for external consumption. The engineering investment is massive, and most vendors lack the incentive while their existing customer base still uses the software as-is.
Can FHIR solve the legacy API problem?
FHIR is the right long-term direction, but adoption is slow and uneven. Many legacy platforms support only a subset of FHIR resources, and implementations often lack the custom operations health tech developers need. FHIR also requires vendor cooperation, something that cannot be forced on a vendor's timeline.
How does browser automation differ from traditional RPA?
Traditional RPA scripts break when a portal updates its interface. Modern browser automation uses self-healing locators that maintain multiple identification strategies for each UI element, adapting automatically to layout changes without manual code repairs. The result is dramatically lower maintenance overhead.
Is browser automation reliable enough for production healthcare workflows?
Deterministic browser automation executes the same steps on every run with no random variation. Combined with self-healing locators and 2FA support, it handles the reliability and security requirements of healthcare workflows. The key distinction is deterministic versus AI-driven: deterministic automation does not depend on an LLM making correct decisions at each step.
Which legacy healthcare systems can be automated this way?
Any system with a web interface. That includes EHR platforms like eClinicalWorks and drchrono, practice management tools like PracticeSuite and AdvancedMD, and payer portals like Availity and Aetna. If it runs in a browser, it can be automated.
How long does it take to build an automation for a healthcare portal?
With a recording-based approach, a working automation takes minutes. Record the workflow once with a browser extension, and the platform generates the automation. Complex multi-step workflows like prior auth submissions with clinical attachments may require additional configuration, but the baseline is minutes, not weeks.
What about HIPAA compliance?
Browser automation platforms built for healthcare include encryption, audit logging, and access controls appropriate for handling protected health information. Evaluate any platform's specific compliance certifications and data handling practices against your organization's requirements.
How does browser automation compare to building custom API integrations?
Custom API integrations require vendor cooperation, development resources, and ongoing maintenance agreements. Browser automation requires none of these. You build the automation independently using the portal's existing web interface. For most healthcare organizations, this means weeks-to-months faster deployment with no dependency on the legacy vendor's roadmap.
The API gap in healthcare is not going to close on its own. Legacy vendors move slowly. FHIR adoption takes years. Aggregators cover some portals but not all. The organizations that solve this problem fastest will be the ones that stop waiting for APIs and start building around the interfaces that already exist. Browser automation is how you get there.
References
[1] Muhammad Ayaz, Muhammad F Pasha, Mohammed Y Alzahrani, Rahmat Budiarto, Deris Stiawan. "The Fast Health Interoperability Resources (FHIR) Standard: Systematic Literature Review of Implementations and Applications." JMIR Medical Informatics, July 30, 2021. https://pmc.ncbi.nlm.nih.gov/articles/PMC8367140/
[2] Office of the National Coordinator for Health Information Technology (ONC). "Interoperability and Methods of Exchange Among Hospitals, 2021." HealthIT.gov, 2021. https://healthit.gov/data/data-briefs/interoperability-and-methods-exchange-among-hospitals-2021/
