The Delphi 7 Extraction Crisis: Modernizing Healthcare Diagnostics Without Losing Clinical Logic

Your most critical diagnostic tool is likely running on a Windows XP virtual machine or a "frozen" Windows 7 environment because no one dares touch the Delphi 7 source code. In the healthcare sector, these legacy systems aren't just technical debt; they are the backbone of patient care, managing everything from MRI scheduling to real-time telemetry. However, the specialized VCL (Visual Component Library) components used in these systems are often undocumented, and the original developers have long since retired.

According to Replay’s analysis, 67% of legacy healthcare systems lack any form of updated documentation, making traditional "rip and replace" strategies a recipe for disaster. When you attempt manual delphi component extraction healthcare projects, you aren't just moving buttons; you are trying to preserve complex clinical validation logic embedded directly into the UI layer.

TL;DR:

• •The Problem: Delphi 7 healthcare systems are "black boxes" with critical logic trapped in the UI.
• •The Risk: 70% of legacy rewrites fail due to documentation gaps and manual errors.
• •The Solution: Replay uses Visual Reverse Engineering to convert recorded workflows into documented React components.
• •Efficiency: Reduce modernization timelines from 18 months to weeks by cutting manual screen recreation from 40 hours to 4 hours.

The High Stakes of Delphi Component Extraction Healthcare#

In a diagnostic environment, the UI is more than an interface; it is a data visualization engine. Delphi 7 was remarkably efficient at low-level graphics via the

object, which is why many 20-year-old ECG and imaging suites still outperform modern web apps in raw rendering speed.

However, the global technical debt has ballooned to $3.6 trillion, and healthcare providers are feeling the squeeze. Maintaining these systems requires niche expertise that is increasingly expensive and rare. When performing delphi component extraction healthcare, teams often realize that the business rules—such as how a specific pixel density correlates to a diagnostic measurement—are hardcoded into the Delphi

files and forms.

The Documentation Vacuum#

Industry experts recommend a "documentation-first" approach, but the reality is stark. With two-thirds of systems lacking documentation, developers are forced to "pixel-hunt"—manually measuring margins, colors, and behavior. This manual process takes an average of 40 hours per screen. With Replay, this is reduced to 4 hours, as the platform captures the "truth" of the running application rather than relying on stale source code.

Why Manual Extraction Fails in Regulated Environments#

The traditional path to modernization involves hiring a team of analysts to watch clinicians use the Delphi app, followed by developers trying to recreate those components in React or Angular.

delphi component extraction healthcare is particularly difficult because of:

1. •State Management: Delphi’s two-way data binding in VCL components behaves differently than React’s unidirectional flow.
2. •Clinical Precision: A rounding error during component migration in a dosage calculator can have fatal consequences.
3. •Regulatory Compliance: Any change to the UI of a medical device may require FDA re-certification.

Manual vs. Replay: The Modernization Comparison#

Video-to-code is the process of recording a legacy application’s user interface in action and using machine learning to transform those visual patterns, interactions, and data flows into clean, modular React code.

Technical Deep Dive: Extracting a Diagnostic Telemetry Component#

Let's look at a typical scenario. You have a Delphi 7

or a custom-drawn used for displaying real-time heart rate data. In Delphi, the logic might look like this:

pascal
// Legacy Delphi 7 Logic for Heart Rate Visualization
procedure TDiagForm.DrawTelemetry(Sender: TObject);
var
  i: Integer;
begin
  with TelemetryCanvas.Canvas do
  begin
    Pen.Color := clGreen;
    MoveTo(0, LastValue);
    for i := 1 to DataBuffer.Count - 1 do
    begin
      LineTo(i * ScaleX, DataBuffer[i] * ScaleY);
      if DataBuffer[i] > AlarmThreshold then
        Pen.Color := clRed
      else
        Pen.Color := clGreen;
    end;
  end;
end;

Extracting this manually requires understanding the

and constants, which might be buried in a global file. When you use Replay, the platform records the component's behavior across various states (normal, alarm, disconnected) and generates a modern, accessible React component that mirrors this behavior exactly.

The Modernized React Output#

Replay’s AI Automation Suite analyzes the recording and produces a component that fits into your new Design System. Here is how that same telemetry component looks after delphi component extraction healthcare via Replay:

typescript
import React, { useMemo } from 'react';
import { LinePath } from '@visx/shape';
import { scaleLinear } from '@visx/scale';

interface TelemetryProps {
  data: number[];
  threshold: number;
  width: number;
  height: number;
}

export const DiagnosticChart: React.FC<TelemetryProps> = ({ data, threshold, width, height }) => {
  const xScale = useMemo(() => scaleLinear({
    domain: [0, data.length],
    range: [0, width],
  }), [data.length, width]);

  const yScale = useMemo(() => scaleLinear({
    domain: [Math.min(...data), Math.max(...data)],
    range: [height, 0],
  }), [data, height]);

  return (
    <svg width={width} height={height}>
      {data.map((d, i) => (
        i > 0 && (
          <line
            key={i}
            x1={xScale(i - 1)}
            y1={yScale(data[i - 1])}
            x2={xScale(i)}
            y2={yScale(d)}
            stroke={d > threshold ? '#ef4444' : '#22c55e'}
            strokeWidth={2}
          />
        )
      ))}
    </svg>
  );
};

By focusing on the visual output, Replay bypasses the need to decipher 20-year-old Pascal code while ensuring the "Flows" (the architectural logic of how data moves through the screen) remain intact. For more on this, see our guide on Reverse Engineering UI.

Overcoming the "18-Month Rewrite" Trap#

The average enterprise rewrite takes 18 months. In healthcare, where system uptime is critical, an 18-month window is often too risky to approve. This leads to "Patchwork Architecture," where new web modules are iframe-d into old Delphi shells, creating a disjointed user experience and increasing security vulnerabilities.

Industry experts recommend moving toward a centralized Component Library early in the process. Replay facilitates this by allowing you to record specific UI elements—like a patient search grid or a diagnostic slider—and instantly adding them to your Replay Library. This becomes your new Design System, grounded in the proven utility of the legacy system but built with modern CSS and TypeScript.

The Role of "Blueprints" in Healthcare Modernization#

One of the most powerful features of Replay is the Blueprints (Editor). When performing delphi component extraction healthcare, you often find that while the logic is sound, the UX is dated. Blueprints allow architects to:

• •Modify the extracted React code in a visual environment.
• •Apply new branding (Design System) to the legacy logic.
• •Map legacy data fields to modern FHIR or HL7 G2 API endpoints.

This ensures that the modernization effort isn't just a visual facelift, but a structural upgrade. You can read more about Legacy Modernization Strategies to understand how to balance visual fidelity with architectural improvements.

Security and Compliance in Delphi Extraction#

Healthcare data is subject to intense scrutiny. Any tool used for delphi component extraction healthcare must respect HIPAA and SOC2 requirements. Replay is built for these regulated environments, offering:

• •On-Premise Deployment: Keep your sensitive diagnostic recordings within your own firewall.
• •PII Masking: Automatically blur or redact patient identifiers during the recording process.
• •Audit Trails: Track every component extraction and code generation step for regulatory reporting.

When you record a workflow in Replay, the platform doesn't just "see" pixels; it understands the underlying structure. This allows it to generate code that is not only functional but also accessible (A11Y compliant), which is a legal requirement for many healthcare systems and government contracts.

Scaling the Extraction Process#

If your diagnostic suite has 500+ screens, manual extraction is impossible. You would need a small army of developers. Replay’s AI Automation Suite allows for parallel processing. While a clinician performs their standard daily tasks, Replay records the "Flows."

Flows are the architectural maps of your application. They define how a user moves from "Patient Selection" to "Imaging View" to "Diagnostic Report." By capturing these flows visually, Replay generates the routing logic for your new React application automatically.

According to Replay's analysis, teams using automated flow capture see a 70% average time savings compared to those trying to map application state manually. This is the difference between a project that gets funded and one that is seen as an endless money pit.

Frequently Asked Questions#

Can Replay handle custom VCL components that aren't standard in Delphi 7?#

Yes. Because Replay uses visual reverse engineering, it doesn't matter if the component is a standard Borland

or a highly customized third-party component like those from DevExpress or TMS. If it renders on the screen and responds to user input, Replay can capture its behavior and convert it into a React component.

How does "video-to-code" handle complex data-grid interactions?#

Replay’s AI Suite analyzes the visual changes in the grid during sorting, filtering, and scrolling. It then maps these behaviors to a modern React Data Grid (like AG Grid or TanStack Table). The generated code includes the necessary hooks to connect these UI actions to your backend APIs, preserving the user's expected workflow.

Is the generated React code maintainable, or is it "spaghetti code"?#

The code generated by Replay is structured according to modern enterprise standards. It uses TypeScript for type safety, modular CSS (or Tailwind) for styling, and functional React components. Since the output is integrated into your Replay Library, it follows a consistent pattern that your internal team can easily maintain and extend.

Do we need the original Delphi source code for this to work?#

No. While having the source code can be helpful for back-end logic, Replay’s primary strength is extracting the UI and frontend behavior without needing to compile or even access the original

or files. This is ideal for systems where the source code has been lost or is too fragile to modify.

Conclusion: The Path Forward for Healthcare IT#

The transition from Delphi 7 to a modern React-based architecture is no longer an 18-month gamble. By leveraging visual reverse engineering, healthcare organizations can protect their clinical logic while shedding the constraints of legacy hardware and unmaintainable codebases.

delphi component extraction healthcare is about more than just moving to the web; it’s about ensuring that the diagnostic tools doctors rely on are fast, secure, and ready for the next decade of medical innovation. With Replay, you can turn your legacy "black box" into a documented, modern component library in a fraction of the time.

Ready to modernize without rewriting? Book a pilot with Replay