5 Healthcare Apps You Can Build with ClinikAPI (with Code Examples)

Quick Answer

You can build production-ready healthcare apps in days using ClinikAPI. This post walks through 5 real app ideas with working TypeScript code: (1) AI clinical notes generator, (2) patient intake and consent system, (3) prescription management tool, (4) lab results dashboard, and (5) multi-clinic appointment scheduler. Each example uses the @clinikapi/sdk and shows the exact API calls you need. All code is copy-pasteable. All data is FHIR R4 compliant and HIPAA-ready.

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App 1: AI Clinical Notes Generator

What it does: A clinician types or dictates a brief session summary. Your app sends it to an AI model (OpenAI, Anthropic, etc.), which generates a structured SOAP note. The note is saved to the patient's record in ClinikAPI.

ClinikAPI resources used: clinik.patients, clinik.encounters, clinik.notes

Why it is valuable: Clinicians spend 5-8 hours per week on documentation. An AI notes tool that saves 15 minutes per note is worth $50K-80K per year in recovered time per provider.

The Code

Step 1: Create an encounter for the session

import { Clinik } from '@clinikapi/sdk';

const clinik = new Clinik(process.env.CLINIKAPI_SECRET_KEY!);

// Start a new encounter when the session begins
const { data: encounter } = await clinik.encounters.create({
  patientId: 'pt_abc123',
  practitionerId: 'pr_xyz789',
  type: 'therapy-session',
  status: 'in-progress',
});

Step 2: Generate the note with AI (using OpenAI as an example)

import OpenAI from 'openai';

const openai = new OpenAI();

const completion = await openai.chat.completions.create({
  model: 'gpt-4o',
  messages: [
    {
      role: 'system',
      content: `You are a clinical documentation assistant. 
        Generate a structured SOAP note from the clinician's summary. 
        Use professional clinical language. Do not include patient names.`,
    },
    {
      role: 'user',
      content: `Session summary: 45yo female, 3rd session. 
        Depression improving, PHQ-9 down from 18 to 12. 
        Sleep better with trazodone 50mg. 
        Still struggling with work stress. 
        Discussed coping strategies. Continue current meds. 
        Follow up 4 weeks.`,
    },
  ],
});

const soapNote = completion.choices[0].message.content;

Step 3: Save the note to the patient's record

const { data: note } = await clinik.notes.create({
  patientId: 'pt_abc123',
  encounterId: encounter.id,
  type: 'soap-note',
  content: soapNote,
  author: 'pr_xyz789',
  status: 'preliminary', // clinician reviews before finalizing
});

// After clinician reviews and approves:
await clinik.notes.update(note.id, {
  status: 'final',
});

What you just built: A complete AI documentation pipeline. The clinician dictates a 60-second summary, AI generates a structured note, and it is saved as a FHIR-compliant DocumentReference linked to the patient and encounter. The clinician reviews, edits, and finalizes.

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App 2: Patient Intake and Consent System

What it does: New patients fill out intake forms and sign consent documents online before their first visit. The data flows directly into their clinical record.

ClinikAPI resources used: clinik.patients, clinik.intakes, clinik.consents

Why it is valuable: Paper intake forms waste 15-20 minutes per new patient. Digital intake saves time, reduces errors, and gives clinicians the information they need before the patient walks in.

The Code

Step 1: Create the patient record

const { data: patient } = await clinik.patients.create({
  firstName: 'Marcus',
  lastName: 'Johnson',
  email: '[email protected]',
  phone: '555-0456',
  gender: 'male',
  birthDate: '1985-07-22',
});

Step 2: Save the intake form responses

const { data: intake } = await clinik.intakes.create({
  patientId: patient.id,
  responses: [
    {
      question: 'What brings you in today?',
      answer: 'Anxiety and difficulty sleeping for the past 3 months',
    },
    {
      question: 'Current medications?',
      answer: 'None',
    },
    {
      question: 'Allergies?',
      answer: 'Penicillin — causes rash',
    },
    {
      question: 'Previous mental health treatment?',
      answer: 'Therapy in 2022 for 6 months, found it helpful',
    },
    {
      question: 'Emergency contact?',
      answer: 'Sarah Johnson (wife) — 555-0457',
    },
  ],
});

Step 3: Record consent

const { data: consent } = await clinik.consents.create({
  patientId: patient.id,
  type: 'treatment-consent',
  status: 'active',
  description: 'Informed consent for psychiatric evaluation and treatment',
  signedAt: new Date().toISOString(),
});

// Add a telehealth-specific consent
const { data: telehealthConsent } = await clinik.consents.create({
  patientId: patient.id,
  type: 'telehealth-consent',
  status: 'active',
  description: 'Consent for telehealth services including video consultations',
  signedAt: new Date().toISOString(),
});

Step 4: Display it with a React widget

import { IntakeForm, ConsentManager } from '@clinikapi/react';

export default function NewPatientOnboarding() {
  return (
    <div className="max-w-2xl mx-auto p-6 space-y-8">
      <h1 className="text-2xl font-bold">Welcome! Please complete your intake.</h1>

      <IntakeForm
        proxyUrl="/api/clinik/intakes"
        onError={(err) => console.error(err)}
      />

      <ConsentManager
        proxyUrl="/api/clinik/consents"
        onError={(err) => console.error(err)}
      />
    </div>
  );
}

What you just built: A complete digital intake system. Patients fill out forms on their phone or computer, sign consents electronically, and everything is stored as FHIR-compliant resources linked to their patient record. The clinician sees it all before the first session.

---

App 3: Prescription Management Tool

What it does: Providers create, view, and manage prescriptions for their patients. Includes medication tracking, dosage information, and prescription history.

ClinikAPI resources used: clinik.patients, clinik.practitioners, clinik.medications, clinik.prescriptions

Why it is valuable: Medication errors are a leading cause of patient harm. A clean prescription management tool with interaction checking and clear dosage tracking reduces errors and improves patient safety.

The Code

Step 1: Create a prescription

const { data: rx } = await clinik.prescriptions.create({
  patientId: 'pt_abc123',
  practitionerId: 'pr_xyz789',
  medication: 'Sertraline 50mg',
  dosage: 'Take 1 tablet by mouth once daily in the morning',
  frequency: 'once daily',
  status: 'active',
});

Step 2: Add another medication

const { data: rx2 } = await clinik.prescriptions.create({
  patientId: 'pt_abc123',
  practitionerId: 'pr_xyz789',
  medication: 'Trazodone 50mg',
  dosage: 'Take 1 tablet by mouth at bedtime as needed for sleep',
  frequency: 'at bedtime as needed',
  status: 'active',
});

Step 3: View all prescriptions for a patient

const { data: meds } = await clinik.prescriptions.search({
  patientId: 'pt_abc123',
  status: 'active',
});

for (const med of meds.data) {
  console.log(`${med.medication} — ${med.dosage}`);
}
// Output:
// Sertraline 50mg — Take 1 tablet by mouth once daily in the morning
// Trazodone 50mg — Take 1 tablet by mouth at bedtime as needed for sleep

Step 4: Discontinue a medication

await clinik.prescriptions.update(rx2.id, {
  status: 'stopped',
});

Step 5: Display with a React widget

import { PrescriptionWidget, PrescriptionForm } from '@clinikapi/react';

export default function MedicationsPage({ patientId }: { patientId: string }) {
  return (
    <div className="space-y-6">
      <h2 className="text-xl font-bold">Current Medications</h2>
      <PrescriptionWidget
        proxyUrl={`/api/clinik/patients/${patientId}/prescriptions`}
        onError={(err) => console.error(err)}
      />

      <h2 className="text-xl font-bold">New Prescription</h2>
      <PrescriptionForm
        proxyUrl="/api/clinik/prescriptions"
        onError={(err) => console.error(err)}
      />
    </div>
  );
}

What you just built: A prescription management system where providers can create, view, update, and discontinue medications. All prescriptions are stored as FHIR MedicationRequest resources with full audit trails.

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App 4: Lab Results Dashboard

What it does: A dashboard that displays lab results for patients with interpretation flags (normal, high, low), trend charts over time, and the ability to order new tests.

ClinikAPI resources used: clinik.patients, clinik.labs, clinik.observations

Why it is valuable: Lab results are one of the most frequently accessed pieces of clinical data. A clean, fast dashboard that shows results with context saves clinicians time and helps patients understand their health.

The Code

Step 1: Record lab results

// Complete blood count results
const { data: cbc } = await clinik.labs.create({
  patientId: 'pt_abc123',
  type: 'complete-blood-count',
  status: 'final',
  results: [
    { name: 'WBC', value: 7.2, unit: 'K/uL', range: '4.5-11.0', flag: 'normal' },
    { name: 'RBC', value: 4.8, unit: 'M/uL', range: '4.0-5.5', flag: 'normal' },
    { name: 'Hemoglobin', value: 14.2, unit: 'g/dL', range: '12.0-16.0', flag: 'normal' },
    { name: 'Hematocrit', value: 42, unit: '%', range: '36-46', flag: 'normal' },
    { name: 'Platelets', value: 245, unit: 'K/uL', range: '150-400', flag: 'normal' },
  ],
  orderedBy: 'pr_xyz789',
  performedAt: '2026-04-25T10:00:00Z',
});

Step 2: Record a metabolic panel with an abnormal result

const { data: bmp } = await clinik.labs.create({
  patientId: 'pt_abc123',
  type: 'basic-metabolic-panel',
  status: 'final',
  results: [
    { name: 'Glucose', value: 142, unit: 'mg/dL', range: '70-100', flag: 'high' },
    { name: 'BUN', value: 18, unit: 'mg/dL', range: '7-20', flag: 'normal' },
    { name: 'Creatinine', value: 1.0, unit: 'mg/dL', range: '0.7-1.3', flag: 'normal' },
    { name: 'Sodium', value: 140, unit: 'mEq/L', range: '136-145', flag: 'normal' },
    { name: 'Potassium', value: 4.2, unit: 'mEq/L', range: '3.5-5.0', flag: 'normal' },
  ],
  orderedBy: 'pr_xyz789',
  performedAt: '2026-04-25T10:00:00Z',
});

Step 3: Search for a patient's lab history

const { data: labHistory } = await clinik.labs.search({
  patientId: 'pt_abc123',
  count: 20,
});

for (const lab of labHistory.data) {
  const abnormal = lab.results.filter((r: any) => r.flag !== 'normal');
  console.log(`${lab.type} — ${abnormal.length} abnormal results`);
}

Step 4: Display with a React widget

import { LabResultsWidget } from '@clinikapi/react';

export default function LabsPage({ patientId }: { patientId: string }) {
  return (
    <div className="max-w-4xl mx-auto p-6">
      <h1 className="text-2xl font-bold mb-6">Lab Results</h1>

      <LabResultsWidget
        proxyUrl={`/api/clinik/patients/${patientId}/labs`}
        onError={(err) => console.error(err)}
      />
    </div>
  );
}

What you just built: A lab results system that stores structured results with interpretation flags, supports trend tracking over time, and displays everything in a clean dashboard. All stored as FHIR DiagnosticReport resources.

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App 5: Multi-Clinic Appointment Scheduler

What it does: A scheduling platform that manages appointments across multiple clinic locations, with per-clinic data isolation and centralized reporting.

ClinikAPI resources used: clinik.appointments, clinik.patients, clinik.practitioners, clinik.practitionerRoles

Why it is valuable: Multi-location practices need scheduling that works across sites while keeping data organized. ClinikAPI's sub-organization feature provides built-in data isolation per clinic.

The Code

Step 1: Set up providers at different locations

// Assign Dr. Chen to the downtown clinic
const { data: role1 } = await clinik.practitionerRoles.create({
  practitionerId: 'pr_chen',
  organization: 'Downtown Clinic',
  specialty: 'Internal Medicine',
  active: true,
});

// Assign Dr. Park to the suburban clinic
const { data: role2 } = await clinik.practitionerRoles.create({
  practitionerId: 'pr_park',
  organization: 'Suburban Clinic',
  specialty: 'Family Medicine',
  active: true,
});

Step 2: Book appointments at different locations

// Book at downtown clinic
const { data: appt1 } = await clinik.appointments.create({
  patientId: 'pt_abc123',
  practitionerId: 'pr_chen',
  start: '2026-05-01T09:00:00Z',
  end: '2026-05-01T09:30:00Z',
  type: 'Follow-up',
  location: 'Downtown Clinic',
});

// Book at suburban clinic
const { data: appt2 } = await clinik.appointments.create({
  patientId: 'pt_def456',
  practitionerId: 'pr_park',
  start: '2026-05-01T10:00:00Z',
  end: '2026-05-01T10:30:00Z',
  type: 'New Patient',
  location: 'Suburban Clinic',
});

Step 3: Search appointments by provider or location

// Get all appointments for Dr. Chen
const { data: chenAppts } = await clinik.appointments.search({
  practitionerId: 'pr_chen',
  count: 50,
});

console.log(`Dr. Chen has ${chenAppts.data.length} upcoming appointments`);

Step 4: Display with a React widget

import { AppointmentScheduler } from '@clinikapi/react';

export default function SchedulePage() {
  return (
    <div className="max-w-4xl mx-auto p-6">
      <h1 className="text-2xl font-bold mb-6">Book an Appointment</h1>

      <AppointmentScheduler
        proxyUrl="/api/clinik/appointments"
        onError={(err) => console.error(err)}
      />
    </div>
  );
}

What you just built: A multi-location scheduling system with provider assignments, location-based booking, and centralized search. On ClinikAPI's Pro or Team plan, sub-organizations provide full data isolation between clinic locations.

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What All 5 Apps Have in Common

Every app in this post shares the same foundation:

• FHIR R4 compliant — All data is stored as valid FHIR resources
• HIPAA ready — Encryption, audit logging, and BAA included on production plans
• Type-safe — The TypeScript SDK catches errors at compile time
• Searchable — Every resource supports search with pagination
• Audited — Every create, read, update, and delete is logged automatically
• Portable — Export your data as standard FHIR R4 at any time

You do not need to think about any of this. You just call the SDK methods and build your app.

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Getting Started

Step 1: Sign up at clinikapi.com (free sandbox, no credit card)

Step 2: Install the SDK

npm install @clinikapi/sdk @clinikapi/react

Step 3: Pick an app from this list and start building

Step 4: When you are ready for real patient data, upgrade to Starter ($49/month)

The sandbox gives you 1,000 requests per month to prototype. That is enough to build and test any of these apps. Go live when you are ready.

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Frequently Asked Questions

Can I combine multiple apps into one platform? Yes. All 5 apps use the same ClinikAPI account and the same SDK. You can build a platform that includes AI notes, intake forms, prescriptions, lab results, and scheduling — all sharing the same patient records and data layer.

How much does it cost to run these apps in production? ClinikAPI Starter ($49/month) covers 60,000 requests. For a small clinic app with 50 patients and 20 encounters per day, that is roughly 30,000 requests per month — well within the Starter plan. Scale to Pro ($399/month) as you grow.

Do I need to know FHIR to build these apps? No. The SDK uses simplified JSON. You never write FHIR resource structures. If you can write TypeScript, you can build these apps.

Can I use these examples in a hackathon? Absolutely. The free sandbox is perfect for hackathons. Sign up, get API keys, and start building. No credit card, no approval process, no waiting.

Are the React widgets customizable? Yes. All widgets accept a className prop for styling. They are designed to be minimal and composable — wrap them in your own layout and apply your design system.

What AI model should I use for the clinical notes app? Any model that supports structured output works. OpenAI GPT-4o, Anthropic Claude, Google Gemini — the choice depends on your accuracy requirements and budget. ClinikAPI stores the output; the AI generation happens in your application layer.

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Related Reading

• What Is a Healthcare API? Developer's Guide
• FHIR R4 Made Simple
• Build a Patient Portal in a Weekend
• HIPAA Compliance for Developers
• From Idea to MVP: Ship 10x Faster
• ClinikAPI Documentation