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healthcare-emr-patterns

EMR/EHR development patterns for healthcare applications. Clinical safety, encounter workflows, prescription generation, clinical decision support integration, and accessibility-first UI for medical data entry. Use when building EMR or EHR features such as encounter workflows, prescription generation, or clinical data entry UI.

What is healthcare-emr-patterns?

healthcare-emr-patterns is a Claude Code agent skill that eMR/EHR development patterns for healthcare applications. Clinical safety, encounter workflows, prescription generation, clinical decision support integration, and accessibility-first UI for medical data entry. Use when building EMR or EHR features such as encounter workflows, prescription generation, or clinical data entry UI.

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Documentation

Healthcare EMR Development Patterns

Patterns for building Electronic Medical Record (EMR) and Electronic Health Record (EHR) systems. Prioritizes patient safety, clinical accuracy, and practitioner efficiency.

When to Use

  • Building patient encounter workflows (complaint, exam, diagnosis, prescription)
  • Implementing clinical note-taking (structured + free text + voice-to-text)
  • Designing prescription/medication modules with drug interaction checking
  • Integrating Clinical Decision Support Systems (CDSS)
  • Building lab result displays with reference range highlighting
  • Implementing audit trails for clinical data
  • Designing healthcare-accessible UIs for clinical data entry

How It Works

Patient Safety First

Every design decision must be evaluated against: "Could this harm a patient?"

  • Drug interactions MUST alert, not silently pass
  • Abnormal lab values MUST be visually flagged
  • Critical vitals MUST trigger escalation workflows
  • No clinical data modification without audit trail

Single-Page Encounter Flow

Clinical encounters should flow vertically on a single page — no tab switching:

Patient Header (sticky — always visible)
├── Demographics, allergies, active medications
│
Encounter Flow (vertical scroll)
├── 1. Chief Complaint (structured templates + free text)
├── 2. History of Present Illness
├── 3. Physical Examination (system-wise)
├── 4. Vitals (auto-trigger clinical scoring)
├── 5. Diagnosis (ICD-10/SNOMED search)
├── 6. Medications (drug DB + interaction check)
├── 7. Investigations (lab/radiology orders)
├── 8. Plan & Follow-up
└── 9. Sign / Lock / Print

Smart Template System

interface ClinicalTemplate {
  id: string;
  name: string;             // e.g., "Chest Pain"
  chips: string[];          // clickable symptom chips
  requiredFields: string[]; // mandatory data points
  redFlags: string[];       // triggers non-dismissable alert
  icdSuggestions: string[]; // pre-mapped diagnosis codes
}

Red flags in any template must trigger a visible, non-dismissable alert — NOT a toast notification.

Medication Safety Pattern

User selects drug
  → Check current medications for interactions
  → Check encounter medications for interactions
  → Check patient allergies
  → Validate dose against weight/age/renal function
  → If CRITICAL interaction: BLOCK prescribing entirely
  → Clinician must document override reason to proceed past a block
  → If MAJOR interaction: display warning, require acknowledgment
  → Log all alerts and override reasons in audit trail

Critical interactions block prescribing by default. The clinician must explicitly override with a documented reason stored in the audit trail. The system never silently allows a critical interaction.

Locked Encounter Pattern

Once a clinical encounter is signed:

  • No edits allowed — only an addendum (a separate linked record)
  • Both original and addendum appear in the patient timeline
  • Audit trail captures who signed, when, and any addendum records

UI Patterns for Clinical Data

Vitals Display: Current values with normal range highlighting (green/yellow/red), trend arrows vs previous, clinical scoring auto-calculated (NEWS2, qSOFA), escalation guidance inline.

Lab Results Display: Normal range highlighting, previous value comparison, critical values with non-dismissable alert, collection/analysis timestamps, pending orders with expected turnaround.

Prescription PDF: One-click generation with patient demographics, allergies, diagnosis, drug details (generic + brand, dose, route, frequency, duration), clinician signature block.

Accessibility for Healthcare

Healthcare UIs have stricter requirements than typical web apps:

  • 4.5:1 minimum contrast (WCAG AA) — clinicians work in varied lighting
  • Large touch targets (44x44px minimum) — for gloved/rushed interaction
  • Keyboard navigation — for power users entering data rapidly
  • No color-only indicators — always pair color with text/icon (colorblind clinicians)
  • Screen reader labels on all form fields
  • No auto-dismissing toasts for clinical alerts — clinician must actively acknowledge

Anti-Patterns

  • Storing clinical data in browser localStorage
  • Silent failures in drug interaction checking
  • Dismissable toasts for critical clinical alerts
  • Tab-based encounter UIs that fragment the clinical workflow
  • Allowing edits to signed/locked encounters
  • Displaying clinical data without audit trail
  • Using any type for clinical data structures

Examples

Example 1: Patient Encounter Flow

Doctor opens encounter for Patient #4521
  → Sticky header shows: "Rajesh M, 58M, Allergies: Penicillin, Active Meds: Metformin 500mg"
  → Chief Complaint: selects "Chest Pain" template
    → Clicks chips: "substernal", "radiating to left arm", "crushing"
    → Red flag "crushing substernal chest pain" triggers non-dismissable alert
  → Examination: CVS system — "S1 S2 normal, no murmur"
  → Vitals: HR 110, BP 90/60, SpO2 94%
    → NEWS2 auto-calculates: score 8, risk HIGH, escalation alert shown
  → Diagnosis: searches "ACS" → selects ICD-10 I21.9
  → Medications: selects Aspirin 300mg
    → CDSS checks against Metformin: no interaction
  → Signs encounter → locked, addendum-only from this point

Example 2: Medication Safety Workflow

Doctor prescribes Warfarin for Patient #4521
  → CDSS detects: Warfarin + Aspirin = CRITICAL interaction
  → UI: red non-dismissable modal blocks prescribing
  → Doctor clicks "Override with reason"
  → Types: "Benefits outweigh risks — monitored INR protocol"
  → Override reason + alert stored in audit trail
  → Prescription proceeds with documented override

Example 3: Locked Encounter + Addendum

Encounter #E-2024-0891 signed by Dr. Shah at 14:30
  → All fields locked — no edit buttons visible
  → "Add Addendum" button available
  → Dr. Shah clicks addendum, adds: "Lab results received — Troponin elevated"
  → New record E-2024-0891-A1 linked to original
  → Timeline shows both: original encounter + addendum with timestamps

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

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affaan-m/claude-api

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affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

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affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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