explain the use of computers in rotine management in the hospital

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Searching the Web

use of computers in hospital routine management

Finding Sources

The medical library does not contain a dedicated health informatics or hospital management text. I'll draw on well-established knowledge and the web results to give you a thorough answer.

Use of Computers in Routine Hospital Management

Computers are now the backbone of nearly every function in a modern hospital. Below is a structured breakdown of how they are used across different areas.

1. Electronic Health Records (EHR) / Electronic Medical Records (EMR)

This is the most fundamental application. Computers replace paper charts with digital records that include:

Patient demographics and contact details
Medical history, diagnoses, allergies, and medications
Progress notes, discharge summaries, and referral letters
Lab results, imaging reports, and procedure notes

Benefits: Instant retrieval, simultaneous access by multiple providers, legible documentation, and reduced risk of lost records.

2. Hospital Information System (HIS)

A Hospital Information System is an integrated software platform that connects all hospital departments. It typically covers:

Patient registration and admission/discharge/transfer (ADT) - automated bed management and census tracking
Appointment scheduling - outpatient clinic bookings, surgical scheduling, and reminders sent by SMS/email
Ward management - nursing notes, vital signs charting, and medication administration records (MAR)
Billing and coding - automatic generation of invoices, insurance claims (ICD/CPT coding), and financial reports

3. Pharmacy Management

Computerized Physician Order Entry (CPOE) - doctors enter drug prescriptions digitally, eliminating handwriting errors
Clinical Decision Support (CDS) - automatic alerts for drug-drug interactions, allergy conflicts, and inappropriate dosing
Dispensing systems - automated dispensing cabinets (ADCs) track stock levels and flag low inventory
Medication reconciliation - ensures a patient's home medications are matched against hospital orders

4. Laboratory Information System (LIS)

Orders are received electronically from wards or clinics
Specimen tracking from collection to analysis to result reporting
Critical value alerts sent directly to the responsible clinician
Trend analysis across multiple lab draws over time
Integration with EHR so results populate the patient chart automatically

5. Radiology and Medical Imaging (PACS/RIS)

Picture Archiving and Communication System (PACS) stores and distributes digital images (X-rays, CT, MRI, ultrasound) across the hospital network
Radiology Information System (RIS) manages worklists, report generation, and billing
Radiologists can read images remotely (teleradiology), improving coverage for nights and weekends
AI-assisted image analysis is increasingly used to flag abnormalities

6. Nursing and Clinical Workflow

Digital vital signs charting with trend graphs
Electronic nursing care plans and care checklists
Fall risk, pressure injury, and pain assessment scores recorded and tracked
Barcode medication administration (BCMA) - nurses scan the patient wristband and the medication to verify the "5 rights" before giving a dose

7. Administrative and Financial Management

Human Resources - staff scheduling, payroll, leave management, and credentials tracking
Supply chain and inventory - automatic reorder points for consumables, surgical supplies, and medications
Procurement - electronic purchase orders and vendor management
Budgeting and costing - department-level financial reporting and cost-per-case analysis
Compliance - documentation for accreditation bodies (JCI, NABH, etc.)

8. Communication Systems

Internal messaging platforms for secure clinician-to-clinician communication
Paging and alarm notification systems linked to nurse call or monitoring devices
Telemedicine portals for remote outpatient consultations
Patient portals where patients can view results, request appointments, and communicate with their care team

9. Infection Control and Surveillance

Automated surveillance software scans lab results and nursing records to detect healthcare-associated infection (HAI) clusters
Antibiogram generation from microbiology data to guide antibiotic stewardship
Contact tracing and isolation room management during outbreaks

10. Research and Education

Clinical data warehouses aggregate de-identified patient data for research
Simulation software and e-learning platforms for staff training
Decision support tools based on clinical guidelines and drug databases (e.g., UpToDate, Micromedex)

Key Benefits

Area	Benefit
Patient safety	Drug interaction alerts, BCMA scanning, allergy checks
Efficiency	Faster turnaround, less paperwork, automated billing
Data accuracy	Legible records, standardized coding
Communication	Real-time sharing of results across departments
Cost control	Inventory automation, reduced duplication of tests

Challenges and Limitations

Cost - high initial investment in hardware, software, and training
Data security - hospitals are frequent targets of ransomware and data breaches
Downtime risk - system failures can disrupt care if backup procedures are not in place
Staff resistance - changing from paper-based habits requires sustained training
Interoperability - different systems from different vendors often do not communicate well with each other

In summary, computers now touch almost every aspect of hospital operations - from the moment a patient registers at the front desk to discharge, billing, and follow-up. The goal in each area is the same: reduce error, improve speed, and make information available to the right person at the right time.

you working as nursing suprintendent in the hospital where you have work on management of the department with the computer in ms word . enlist the main features of ms word in the context of question stated in nursing practice

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MS Word features used in nursing management hospital administration

Here is a thorough, role-specific answer from the perspective of a Nursing Superintendent managing a hospital department using MS Word.

MS Word Features in Nursing Superintendent's Department Management

As a Nursing Superintendent, MS Word is the primary tool for creating, storing, and circulating all written communication and documentation in the nursing department. Below are the key features, each linked directly to nursing management tasks.

1. Document Formatting Tools

(Home Tab - Font, Paragraph, Styles)

What it does: Controls font type, size, bold/italic/underline, line spacing, alignment, and heading styles.

Use in Nursing Practice:

Preparing formal nursing policies and procedures with clear headings and subheadings
Creating standard operating procedures (SOPs) for ward routines (e.g., medication round procedure, infection control protocol)
Writing incident reports and nursing audit reports in a professional, readable format
Formatting nursing staff circulars and notices for display on department notice boards

2. Tables

(Insert Tab - Table)

What it does: Creates rows and columns to organize data neatly.

Use in Nursing Practice:

Duty rosters / shift schedules - assigning morning, evening, and night shifts to staff across all wards
Staff attendance registers - tracking daily presence, leave, and overtime
Patient census tables - daily bed occupancy records per ward
Nursing care plan formats - columns for problem, goal, intervention, and evaluation
Training schedules - date, topic, trainer, and venue in a tabular format
Drug stock registers - item name, quantity received, quantity issued, balance

3. Templates

(File - New - Search Templates / Save As Template)

What it does: Pre-designed document layouts saved for repeated use.

Use in Nursing Practice:

Creating a standard nursing handover sheet template that each shift fills in
Incident/accident report form template ready to fill whenever needed
Patient satisfaction survey form template
Staff performance appraisal template used quarterly or annually
Meeting agenda and minutes template for nursing department meetings
Once designed, these templates save time and ensure consistency across all wards

4. Mail Merge

(Mailings Tab - Start Mail Merge)

What it does: Combines a single document with a list (database) to produce multiple personalized copies automatically.

Use in Nursing Practice:

Sending individualized appointment letters to nursing staff for annual performance reviews
Issuing personalized duty allocation letters to new recruits across different wards
Generating individual training completion certificates for nurses after in-service education
Sending mass notices to all ward sisters with individual names and ward details filled automatically

5. Track Changes and Comments

(Review Tab - Track Changes / New Comment)

What it does: Records every edit made to a document, showing who changed what and when. Comments allow notes without altering the main text.

Use in Nursing Practice:

Revising nursing policies - the superintendent can send a draft to senior nurses, who suggest changes using Track Changes; the superintendent then accepts or rejects each change
Peer review of clinical protocols before final approval
Adding reviewer comments on nursing staff appraisal drafts before the formal meeting
Maintaining an audit trail when hospital accreditation requires documented policy review history

6. Headers, Footers, and Page Numbering

(Insert Tab - Header / Footer / Page Number)

What it does: Places fixed text or page numbers at the top/bottom of every page automatically.

Use in Nursing Practice:

Adding the hospital name, department name, and logo to every page of official documents
Inserting document version numbers and review dates in the footer of policy documents
Page numbering in nursing procedure manuals and staff handbooks
Adding "Confidential" watermarks or footers on sensitive documents such as staff disciplinary records

7. Spelling and Grammar Check

(Review Tab - Spelling & Grammar / Editor)

What it does: Automatically detects spelling errors, grammatical mistakes, and suggests corrections.

Use in Nursing Practice:

Ensuring incident reports and complaint letters are error-free before submission to hospital administration
Proofreading nursing SOPs and policy documents before circulation
Maintaining professional language in official correspondence to doctors, administrators, and external agencies
The medical dictionary add-on can recognize clinical terms correctly

8. Bullet Points and Numbered Lists

(Home Tab - Bullets / Numbering)

What it does: Organizes information as clear lists, either bulleted (unordered) or numbered (ordered steps).

Use in Nursing Practice:

Writing step-by-step clinical procedures (e.g., catheter insertion steps, wound dressing procedure)
Listing nursing responsibilities in job descriptions for ward nurses and charge nurses
Enumerated agenda items for nursing department meetings
Listing infection control precautions for isolation ward staff

9. Insert Images, Charts, and SmartArt

(Insert Tab - Pictures / Chart / SmartArt)

What it does: Embeds photographs, diagrams, bar charts, and flow diagrams into documents.

Use in Nursing Practice:

Including organizational charts showing the nursing department hierarchy (Superintendent → Deputy → Ward Sisters → Staff Nurses)
Inserting hand hygiene technique diagrams or wound care photographs in procedure manuals
Adding bar charts of monthly incident rates or infection control data in monthly reports to hospital management
Flow charts for patient escalation pathways (e.g., when to call the doctor, when to activate rapid response)

10. Styles and Table of Contents

(Home Tab - Styles / References Tab - Table of Contents)

What it does: Headings formatted with Word Styles can generate an automatic, linked Table of Contents.

Use in Nursing Practice:

Large documents like Nursing Department Policy Manuals, Staff Orientation Handbooks, or Nursing Procedure Compendiums need a Table of Contents for quick navigation
When any section is updated, the TOC refreshes automatically with one click
Makes documents accreditation-ready (JCI, NABH inspectors expect indexed policy manuals)

11. Password Protection and Restricted Editing

(File - Info - Protect Document)

What it does: Encrypts a document with a password or restricts who can edit it.

Use in Nursing Practice:

Protecting confidential staff disciplinary records or performance appraisals
Locking official policy documents so staff can read but not alter them
Securing budget proposals submitted to hospital administration
Protecting patient-related reports from unauthorized editing

12. Find and Replace

(Home Tab - Find / Replace, or Ctrl+H)

What it does: Searches the entire document for a word or phrase and replaces it instantly.

Use in Nursing Practice:

Updating policy documents when hospital name, ward names, or job titles change - replace all instances in seconds
Changing a medication name across an entire drug administration protocol after a formulary update
Correcting a date or reference number used repeatedly in a long annual report

13. Print and Print Preview

(File - Print)

What it does: Allows the document to be previewed exactly as it will print and sent to any connected printer.

Use in Nursing Practice:

Printing duty rosters and posting them on ward notice boards
Printing meeting minutes for distribution to ward sisters
Printing nursing certificates, letters of appointment, or training attendance sheets
Printing patient education materials in large font for elderly patients

Summary Table

MS Word Feature	Nursing Management Application
Formatting	SOPs, policy documents, circulars
Tables	Duty rosters, care plans, drug registers
Templates	Handover sheets, incident forms, appraisals
Mail Merge	Personalized letters, certificates, notices
Track Changes	Policy review, protocol revision
Headers/Footers	Official letterheads, version control
Spell/Grammar Check	Error-free reports and correspondence
Bullets/Numbering	Procedures, agendas, job descriptions
Images/Charts/SmartArt	Org charts, data reports, procedure visuals
Styles and TOC	Policy manuals, orientation handbooks
Password Protection	Confidential staff and patient documents
Find and Replace	Bulk updates across large documents
Print	Rosters, minutes, certificates

In the role of Nursing Superintendent, MS Word is not just a typing tool - it is the platform for building every official written system in the department: staff management, clinical governance, communication, training, and accountability. Mastering these features directly improves the quality, consistency, and professionalism of nursing department management.

a nurse needs to quickly access a patient lab results , medication list , and previous medical history during an emergency situation . how woud the nurse efficiently and accuratly access this information using hospital computer system

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nurse access patient information EHR emergency situation hospital computer system workflow

Here is a complete, practical answer written from a nursing perspective.

Accessing Patient Information During an Emergency Using the Hospital Computer System

In an emergency, every second matters. The hospital computer system - primarily the Electronic Health Record (EHR) - is designed so that a nurse can locate critical patient data in under 60 seconds when used correctly.

Step-by-Step: Efficient and Accurate Access

Step 1 - Log In Immediately Using Fast Authentication

The very first action is gaining system access without delay.

Use a personal username and strong password kept secure but memorized
Many hospitals use smart card login or fingerprint/biometric authentication - one touch and you are in
Some ICU and emergency workstations use proximity card (badge tap) login, recognizing the nurse as they approach the terminal
Never share login credentials - each access is time-stamped and audited, which also protects the nurse legally

In a true emergency, some systems allow a "break-glass" or emergency override that grants immediate access to any patient record, with the action logged for later review.

Step 2 - Search and Identify the Patient Accurately

Once logged in, navigate to the patient search function (usually the first screen).

Search using any of the following identifiers:

Identifier	Example
Hospital ID / MRN	Most precise - fastest result
Full Name	Useful if ID not known
Date of Birth	Used alongside name to confirm identity
Ward and Bed Number	Useful during ward-based emergencies
National ID / Passport Number	In some hospital systems

Accuracy tip: Always confirm the correct patient by verifying at least two identifiers (name + date of birth, or name + MRN) before acting on any information. This prevents acting on the wrong patient's data - a critical safety step even in emergencies.

Step 3 - Access Lab Results

Once inside the patient's record:

Navigate to the "Laboratory" or "Results" tab in the EHR
Results are displayed in reverse chronological order (most recent first) - the nurse sees the latest values immediately
Critical value flags - abnormal results (e.g., potassium 6.8, glucose 1.2) are highlighted in red or with an alarm symbol automatically by the system
Use the "Most Recent Results" summary view rather than scrolling through history - most EHRs have this as a quick-view panel
Key panels to check in an emergency:
- Full blood count (Hb, WBC, platelets)
- Renal function (urea, creatinine, electrolytes)
- Blood gas (pH, pO2, pCO2, lactate)
- Blood glucose
- Coagulation (PT, INR) if bleeding is suspected
- Cardiac enzymes (troponin) if chest pain/arrest

Step 4 - Access the Medication List

Navigate to the "Medications" or "Medication Administration Record (MAR)" tab
The active medication list shows:
- Current drugs with doses, routes, and frequencies
- Time of last dose given
- Any medications on hold or discontinued
In an emergency, look specifically for:
- Anticoagulants (warfarin, heparin, NOACs) - affects bleeding risk
- Insulin - may explain hypoglycemia
- Antihypertensives/cardiac drugs - may explain hemodynamic instability
- Steroids - affects stress response and adrenal function
- Immunosuppressants - affects infection risk
- Allergy alerts - displayed prominently, usually on the top banner of the patient record in a red bar
The allergy and adverse reaction section should always be checked before administering any emergency drug

Step 5 - Access Previous Medical History

Navigate to the "Medical History", "Problem List", or "Summary" tab
This section contains:
- Active diagnoses (e.g., diabetes, heart failure, epilepsy, COPD)
- Past surgical history (e.g., previous CABG, splenectomy)
- Chronic conditions relevant to the emergency (e.g., known coagulopathy, renal failure)
- Previous hospitalizations and discharge summaries
- Baseline observations - helps assess how abnormal current vitals are
Many EHRs have a "Patient Summary" or "One Page View" that consolidates key history, medications, allergies, and recent results on a single screen - this is the most time-saving view in an emergency

Step 6 - Use Clinical Decision Support Alerts

Modern EHR systems do not just display data - they analyze it and alert the nurse:

Early Warning Score (EWS/NEWS) calculator - automatically computes the score from entered vitals and flags deterioration
Drug interaction alerts - if a new emergency drug is about to be given that interacts with a current medication, the system warns immediately
Allergy alerts - pop-up warning before any contraindicated drug is administered
Critical result notifications - lab system pushes urgent results directly to the nurse's EHR dashboard or mobile device

Tools Within the Hospital Computer System That Aid Speed and Accuracy

Tool / Feature	How It Helps in an Emergency
Patient Summary / Dashboard	Single screen with all key data - no tab-by-tab navigation needed
Barcode / wristband scanner	Scan the patient's wristband to instantly open their correct record
Mobile devices / bedside terminals	Access EHR at the bedside without leaving the patient
Favorites / Pinned patients	Nurses can pin their assigned patients for one-click access
Voice recognition	Hands-free documentation while performing emergency care
Offline mode / downtime procedures	Printed downtime reports kept at the nursing station in case of system failure
Color-coded alerts	Red = critical, yellow = warning, green = normal - instant visual triage of results

What to Do if the System is Down (Downtime Emergency)

System failures do happen. Every ward should have:

Printed downtime summary sheets for each patient, updated each shift - these contain current medications, allergies, and recent results
A manual kardex or paper medication chart as a backup
A telephone hotline to the lab and pharmacy for verbal results and drug queries
The nurse should document all emergency actions on paper and enter them retrospectively once the system is restored

Key Principles for Safe and Efficient Access

Always verify patient identity with two identifiers before acting on any data
Use the most recent data - timestamp on every result tells you how current it is
Do not rely on memory - always look at the screen, even for familiar patients
Log off or lock the screen when stepping away, even briefly, to protect patient confidentiality
Report any system errors or missing data immediately to the IT help desk and document the gap manually

In summary, the hospital computer system - when properly used - transforms a potentially chaotic emergency into a structured, information-driven response. The nurse who knows the system well can have a complete patient picture (labs, medications, history, allergies) open on screen within 30-60 seconds of reaching the workstation, giving the emergency team exactly what they need to make safe, fast clinical decisions.

Create a quick reference guide for accessing patient data in emergency situations0 pateints . create an excel sheet to record the medication name , dosage , time of administration , and any adverse reaction . how would you structure this sheet to complete the task

Reading File

Running Command

mkdir -p /home/daytona/workspace/emergency-nursing && ls /home/daytona/workspace…

Writing File

~/emergency-nursing/create_emergency_sheets.py

import openpyxl
from openpyxl.styles import (
    PatternFill, Font, Alignment, Border, Side, GradientFill
)
from openpyxl.utils import get_column_letter
from openpyxl.worksheet.datavalidation import DataValidation
from openpyxl.formatting.rule import ColorScaleRule, CellIsRule, FormulaRule
from openpyxl.styles.differential import DifferentialStyle
from datetime import datetime

wb = openpyxl.Workbook()

# ─────────────────────────────────────────────
# COLOUR PALETTE
# ─────────────────────────────────────────────
RED_DARK    = "C0392B"
RED_LIGHT   = "FADBD8"
BLUE_DARK   = "1A5276"
BLUE_MED    = "2E86C1"
BLUE_LIGHT  = "D6EAF8"
TEAL_DARK   = "0E6655"
TEAL_LIGHT  = "D1F2EB"
ORANGE_DARK = "BA4A00"
ORANGE_LIGHT= "FAE5D3"
GREY_DARK   = "2C3E50"
GREY_MED    = "95A5A6"
GREY_LIGHT  = "ECF0F1"
WHITE       = "FFFFFF"
YELLOW_WARN = "F9E79F"
GREEN_SAFE  = "D5F5E3"

def thin_border(top=True, bottom=True, left=True, right=True):
    s = Side(style='thin', color="AAAAAA")
    n = Side(style=None)
    return Border(
        top=s if top else n,
        bottom=s if bottom else n,
        left=s if left else n,
        right=s if right else n
    )

def thick_border():
    s = Side(style='medium', color="555555")
    return Border(top=s, bottom=s, left=s, right=s)

def header_font(size=11, bold=True, color=WHITE):
    return Font(name='Arial', size=size, bold=bold, color=color)

def body_font(size=10, bold=False, color="2C3E50"):
    return Font(name='Arial', size=size, bold=bold, color=color)

def fill(hex_color):
    return PatternFill("solid", fgColor=hex_color)

def center(wrap=False):
    return Alignment(horizontal='center', vertical='center', wrap_text=wrap)

def left_align(wrap=True):
    return Alignment(horizontal='left', vertical='center', wrap_text=wrap)


# ══════════════════════════════════════════════════════════════════
#  SHEET 1 — QUICK REFERENCE GUIDE
# ══════════════════════════════════════════════════════════════════
ws_qrg = wb.active
ws_qrg.title = "Quick Reference Guide"
ws_qrg.sheet_view.showGridLines = False
ws_qrg.column_dimensions['A'].width = 3
ws_qrg.column_dimensions['B'].width = 28
ws_qrg.column_dimensions['C'].width = 52
ws_qrg.column_dimensions['D'].width = 3

# ── Title Banner ──────────────────────────────────────────────────
ws_qrg.row_dimensions[1].height = 8
ws_qrg.row_dimensions[2].height = 48
ws_qrg.row_dimensions[3].height = 22
ws_qrg.row_dimensions[4].height = 10

ws_qrg.merge_cells('B2:C2')
c = ws_qrg['B2']
c.value = "🏥  EMERGENCY PATIENT DATA — QUICK REFERENCE GUIDE"
c.font = Font(name='Arial', size=16, bold=True, color=WHITE)
c.fill = fill(RED_DARK)
c.alignment = center(wrap=False)
c.border = thick_border()

ws_qrg.merge_cells('B3:C3')
c = ws_qrg['B3']
c.value = "Nursing Department  |  Use in Emergency / Code Situations  |  Version 1.0  |  " + datetime.today().strftime('%B %Y')
c.font = Font(name='Arial', size=9, italic=True, color=WHITE)
c.fill = fill(GREY_DARK)
c.alignment = center()

# ── Section helper ────────────────────────────────────────────────
def section_header(ws, row, title, color):
    ws.row_dimensions[row].height = 24
    ws.merge_cells(f'B{row}:C{row}')
    c = ws[f'B{row}']
    c.value = f"  {title}"
    c.font = Font(name='Arial', size=11, bold=True, color=WHITE)
    c.fill = fill(color)
    c.alignment = left_align(wrap=False)
    c.border = thick_border()

def data_row(ws, row, col_b, col_c, bg=WHITE, bold_b=False):
    ws.row_dimensions[row].height = 20
    b = ws[f'B{row}']
    b.value = col_b
    b.font = Font(name='Arial', size=10, bold=bold_b, color=GREY_DARK)
    b.fill = fill(bg)
    b.alignment = left_align(wrap=False)
    b.border = thin_border()

    c = ws[f'C{row}']
    c.value = col_c
    c.font = body_font(size=10)
    c.fill = fill(bg)
    c.alignment = left_align(wrap=True)
    c.border = thin_border()

def spacer(ws, row, height=8):
    ws.row_dimensions[row].height = height

# ── Section 1: Login & Patient Search ─────────────────────────────
r = 5
section_header(ws_qrg, r, "STEP 1  —  LOG IN TO THE EHR SYSTEM", BLUE_DARK)
rows_s1 = [
    ("Action", "Detail", BLUE_LIGHT, True),
    ("Workstation Login", "Enter Username + Password OR tap smart card / badge on reader", BLUE_LIGHT, False),
    ("Emergency Override", "Use 'Break-Glass' access if patient not assigned to you; action is auto-logged", YELLOW_WARN, False),
    ("Biometric Login", "Fingerprint scanner available at ICU, ED, and HDU terminals", BLUE_LIGHT, False),
    ("System Down?", "Use printed Downtime Summary Sheet from the nursing station red folder", ORANGE_LIGHT, False),
]
for col_b, col_c, bg, bold_b in rows_s1:
    r += 1
    data_row(ws_qrg, r, col_b, col_c, bg, bold_b)

# ── Section 2: Identify Patient ────────────────────────────────────
r += 1
spacer(ws_qrg, r)
r += 1
section_header(ws_qrg, r, "STEP 2  —  IDENTIFY THE CORRECT PATIENT", TEAL_DARK)
rows_s2 = [
    ("Identifier", "Use at Least TWO to Confirm Identity", TEAL_LIGHT, True),
    ("Hospital MRN", "Fastest — type directly in Patient Search bar", TEAL_LIGHT, False),
    ("Full Name + DOB", "Name + Date of Birth — always confirm both", TEAL_LIGHT, False),
    ("Wristband Barcode", "Scan patient's wristband to open record instantly", GREEN_SAFE, False),
    ("Ward + Bed Number", "Use if MRN unknown during ward emergency", TEAL_LIGHT, False),
    ("⚠ NEVER act on one identifier alone", "Confirm two identifiers before accessing or acting on data", YELLOW_WARN, False),
]
for col_b, col_c, bg, bold_b in rows_s2:
    r += 1
    data_row(ws_qrg, r, col_b, col_c, bg, bold_b)

# ── Section 3: Lab Results ─────────────────────────────────────────
r += 1
spacer(ws_qrg, r)
r += 1
section_header(ws_qrg, r, "STEP 3  —  ACCESS LAB RESULTS", BLUE_MED)
rows_s3 = [
    ("Navigation", "Patient Record → 'Results' or 'Laboratory' Tab", BLUE_LIGHT, True),
    ("View Latest First", "Results in reverse chronological order — newest on top", BLUE_LIGHT, False),
    ("Critical Value Flag", "Red highlight / alarm icon = result needs IMMEDIATE action", RED_LIGHT, False),
    ("Quick View Panel", "Use 'Most Recent Results' summary to avoid scrolling", BLUE_LIGHT, False),
    ("Key Emergency Labs", "FBC | U&E | Blood Gas | Glucose | Troponin | Coagulation | LFTs", YELLOW_WARN, False),
    ("Blood Gas (ABG)", "pH, pO2, pCO2, HCO3, Lactate — under 'Point of Care' tab", BLUE_LIGHT, False),
]
for col_b, col_c, bg, bold_b in rows_s3:
    r += 1
    data_row(ws_qrg, r, col_b, col_c, bg, bold_b)

# ── Section 4: Medication List ─────────────────────────────────────
r += 1
spacer(ws_qrg, r)
r += 1
section_header(ws_qrg, r, "STEP 4  —  ACCESS MEDICATION LIST & ALLERGIES", ORANGE_DARK)
rows_s4 = [
    ("Navigation", "Patient Record → 'Medications' or 'MAR' Tab", ORANGE_LIGHT, True),
    ("Allergy Alert", "Red banner at TOP of patient record — check FIRST", RED_LIGHT, False),
    ("Active Medications", "Current drugs with dose, route, frequency, last dose time", ORANGE_LIGHT, False),
    ("High-Risk Drugs to Check", "Anticoagulants | Insulin | Opioids | Cardiac drugs | Steroids", YELLOW_WARN, False),
    ("On-Hold / Discontinued", "Marked separately — important for full clinical picture", ORANGE_LIGHT, False),
    ("Before Giving Anything", "Confirm drug, dose, route, time, patient identity (5 Rights)", RED_LIGHT, False),
]
for col_b, col_c, bg, bold_b in rows_s4:
    r += 1
    data_row(ws_qrg, r, col_b, col_c, bg, bold_b)

# ── Section 5: Medical History ─────────────────────────────────────
r += 1
spacer(ws_qrg, r)
r += 1
section_header(ws_qrg, r, "STEP 5  —  ACCESS PREVIOUS MEDICAL HISTORY", TEAL_DARK)
rows_s5 = [
    ("Navigation", "Patient Record → 'Summary' or 'Problem List' or 'History' Tab", TEAL_LIGHT, True),
    ("One-Page Summary", "Use Patient Summary / Dashboard view — all key info on one screen", GREEN_SAFE, False),
    ("Active Diagnoses", "Chronic conditions relevant to emergency (DM, CCF, COPD, epilepsy)", TEAL_LIGHT, False),
    ("Previous Surgeries", "Especially prior cardiac, neuro, or abdominal surgery", TEAL_LIGHT, False),
    ("Discharge Summaries", "Under 'Documents' tab — recent hospital admissions", TEAL_LIGHT, False),
    ("Baseline Observations", "Compare current vitals against patient's usual baseline", YELLOW_WARN, False),
]
for col_b, col_c, bg, bold_b in rows_s5:
    r += 1
    data_row(ws_qrg, r, col_b, col_c, bg, bold_b)

# ── Section 6: Clinical Decision Support ──────────────────────────
r += 1
spacer(ws_qrg, r)
r += 1
section_header(ws_qrg, r, "STEP 6  —  USE CLINICAL DECISION SUPPORT & ALERTS", GREY_DARK)
rows_s6 = [
    ("NEWS / EWS Score", "Auto-calculated from vitals — triggers escalation protocol", GREY_LIGHT, True),
    ("Drug Interaction Alert", "System warns before giving contraindicated drug combination", YELLOW_WARN, False),
    ("Allergy Pop-Up", "Mandatory acknowledgment before administering flagged drug", RED_LIGHT, False),
    ("Critical Result Push", "Lab pushes urgent results to nurse's EHR dashboard / mobile", GREY_LIGHT, False),
    ("Rapid Response Trigger", "Follow hospital protocol when NEWS ≥ 7 or single extreme score", RED_LIGHT, False),
]
for col_b, col_c, bg, bold_b in rows_s6:
    r += 1
    data_row(ws_qrg, r, col_b, col_c, bg, bold_b)

# ── Section 7: System Down ─────────────────────────────────────────
r += 1
spacer(ws_qrg, r)
r += 1
section_header(ws_qrg, r, "⚠  SYSTEM DOWNTIME — EMERGENCY BACKUP PROCEDURE", RED_DARK)
rows_s7 = [
    ("Downtime Sheets", "Printed patient summary in RED FOLDER at nursing station (updated each shift)", RED_LIGHT, True),
    ("Paper MAR Chart", "Manual medication chart maintained as backup — check drug cupboard folder", ORANGE_LIGHT, False),
    ("Lab Results", "Call lab directly: Ext. ____  |  Request verbal critical results", YELLOW_WARN, False),
    ("Pharmacy Queries", "Call pharmacy directly: Ext. ____  |  For drug info and interactions", YELLOW_WARN, False),
    ("Document All Actions", "Record on paper — enter retrospectively when system restored", ORANGE_LIGHT, False),
    ("Report Downtime", "Notify IT Help Desk immediately: Ext. ____  |  Log incident number", RED_LIGHT, False),
]
for col_b, col_c, bg, bold_b in rows_s7:
    r += 1
    data_row(ws_qrg, r, col_b, col_c, bg, bold_b)

# ── Footer ─────────────────────────────────────────────────────────
r += 2
ws_qrg.row_dimensions[r].height = 20
ws_qrg.merge_cells(f'B{r}:C{r}')
c = ws_qrg[f'B{r}']
c.value = "Approved by: Nursing Superintendent  |  Review Date: " + datetime.today().strftime('%B %Y') + "  |  For internal clinical use only — do not distribute outside the hospital"
c.font = Font(name='Arial', size=8, italic=True, color=GREY_MED)
c.fill = fill(GREY_DARK)
c.alignment = center()


# ══════════════════════════════════════════════════════════════════
#  SHEET 2 — MEDICATION ADMINISTRATION RECORD (MAR)
# ══════════════════════════════════════════════════════════════════
ws_mar = wb.create_sheet("Medication Admin Record (MAR)")
ws_mar.sheet_view.showGridLines = False

# Column widths
col_widths = {
    'A': 3,   # padding
    'B': 6,   # #
    'C': 22,  # Patient Name
    'D': 14,  # MRN
    'E': 8,   # Ward/Bed
    'F': 24,  # Medication Name
    'G': 18,  # Generic Name
    'H': 14,  # Dosage
    'I': 14,  # Route
    'J': 14,  # Date
    'K': 12,  # Time Given
    'L': 22,  # Administered By
    'M': 18,  # Adverse Reaction?
    'N': 32,  # Reaction Details
    'O': 22,  # Action Taken
    'P': 18,  # Doctor Notified
    'Q': 20,  # Notes
    'R': 3,   # padding
}
for col, width in col_widths.items():
    ws_mar.column_dimensions[col].width = width

# Title banner
ws_mar.row_dimensions[1].height = 8
ws_mar.row_dimensions[2].height = 46
ws_mar.row_dimensions[3].height = 22
ws_mar.row_dimensions[4].height = 16

ws_mar.merge_cells('B2:Q2')
c = ws_mar['B2']
c.value = "🏥  EMERGENCY MEDICATION ADMINISTRATION RECORD (MAR)"
c.font = Font(name='Arial', size=15, bold=True, color=WHITE)
c.fill = fill(RED_DARK)
c.alignment = center()
c.border = thick_border()

ws_mar.merge_cells('B3:Q3')
c = ws_mar['B3']
c.value = "Ward: _________________    Date: _________________    Shift: □ Morning   □ Evening   □ Night    Charge Nurse: _________________________"
c.font = Font(name='Arial', size=10, color=WHITE)
c.fill = fill(GREY_DARK)
c.alignment = left_align(wrap=False)
c.border = thin_border()

# ── Key Alert Box ──────────────────────────────────────────────────
ws_mar.row_dimensions[5].height = 18
ws_mar.row_dimensions[6].height = 18
ws_mar.row_dimensions[7].height = 18
ws_mar.row_dimensions[8].height = 16

alerts = [
    ('B5:H5', "⚠  ALLERGY CHECK: Confirm allergy status BEFORE administering any drug", RED_DARK),
    ('I5:Q5', "⚠  5 RIGHTS: Right Patient | Right Drug | Right Dose | Right Route | Right Time", ORANGE_DARK),
    ('B6:H6', "✅  Document IMMEDIATELY after administration — never pre-document", TEAL_DARK),
    ('I6:Q6', "🔴  Report ANY adverse reaction to doctor immediately & complete incident form", BLUE_DARK),
]
for cells, text, color in alerts:
    ws_mar.merge_cells(cells)
    c_ref = cells.split(':')[0]
    c = ws_mar[c_ref]
    c.value = text
    c.font = Font(name='Arial', size=9, bold=True, color=WHITE)
    c.fill = fill(color)
    c.alignment = left_align(wrap=False)
    c.border = thin_border()

# ── Column Headers ─────────────────────────────────────────────────
ws_mar.row_dimensions[8].height = 14
ws_mar.row_dimensions[9].height = 36

headers = [
    ('B', '#'),
    ('C', 'Patient Full Name'),
    ('D', 'MRN / Hospital ID'),
    ('E', 'Ward / Bed'),
    ('F', 'Medication Name\n(Brand)'),
    ('G', 'Generic / INN Name'),
    ('H', 'Dosage\n(Amount + Unit)'),
    ('I', 'Route\n(IV/IM/PO/SC etc.)'),
    ('J', 'Date\n(DD/MM/YYYY)'),
    ('K', 'Time Given\n(HH:MM, 24hr)'),
    ('L', 'Administered By\n(Name + Designation)'),
    ('M', 'Adverse Reaction?\n(Yes / No)'),
    ('N', 'Reaction Details\n(Describe symptoms)'),
    ('O', 'Action Taken\n(Treatment given)'),
    ('P', 'Doctor Notified?\n(Name + Time)'),
    ('Q', 'Additional Notes'),
]

header_colors = {
    'B': GREY_DARK, 'C': BLUE_DARK, 'D': BLUE_DARK, 'E': BLUE_DARK,
    'F': TEAL_DARK, 'G': TEAL_DARK, 'H': TEAL_DARK, 'I': TEAL_DARK,
    'J': BLUE_MED,  'K': BLUE_MED,  'L': BLUE_MED,
    'M': RED_DARK,  'N': RED_DARK,  'O': RED_DARK,  'P': RED_DARK,
    'Q': GREY_DARK,
}

for col, title in headers:
    c = ws_mar[f'{col}9']
    c.value = title
    c.font = Font(name='Arial', size=9, bold=True, color=WHITE)
    c.fill = fill(header_colors[col])
    c.alignment = center(wrap=True)
    c.border = thin_border()

# ── Sub-header row (column group labels) ──────────────────────────
ws_mar.row_dimensions[8].height = 16
group_labels = [
    ('C8:E8', 'PATIENT IDENTIFICATION', BLUE_DARK),
    ('F8:I8', 'MEDICATION DETAILS', TEAL_DARK),
    ('J8:L8', 'ADMINISTRATION', BLUE_MED),
    ('M8:P8', 'ADVERSE REACTION MONITORING', RED_DARK),
    ('Q8:Q8', 'NOTES', GREY_DARK),
]
for cells, label, color in group_labels:
    ws_mar.merge_cells(cells)
    start = cells.split(':')[0]
    c = ws_mar[start]
    c.value = label
    c.font = Font(name='Arial', size=8, bold=True, color=WHITE)
    c.fill = fill(color)
    c.alignment = center(wrap=False)
    c.border = thin_border()

# ── Sample data rows ───────────────────────────────────────────────
sample_data = [
    (1,  "Ahmed Hassan",        "MRN-001234", "ER-01", "Adrenaline (Epinephrine)",  "Epinephrine",     "0.5 mg",    "IM",  "12/07/2026", "08:15", "Sr. Nurse Fatima A.",  "No",  "",                                  "",                    "",                  "Given for anaphylaxis — 2nd dose at 08:30 if no response"),
    (2,  "Samira Al-Rashid",    "MRN-002567", "ER-02", "Morphine Sulphate",         "Morphine",        "5 mg",      "IV",  "12/07/2026", "09:00", "Sr. Nurse Layla M.",   "Yes", "Nausea, vomiting — onset 10 min",   "IV ondansetron 4 mg", "Dr. Khan — 09:12",  "Vitals monitored q15min post-dose"),
    (3,  "James Owusu",         "MRN-003891", "ICU-3", "Noradrenaline",             "Norepinephrine",  "0.1 mcg/kg/min","IV infusion","12/07/2026","10:30","RN Thomas B.", "No",  "",                                  "",                    "",                  "Septic shock — titrate per MAP target 65 mmHg"),
    (4,  "Priya Sharma",        "MRN-004102", "HDU-2", "Metoprolol",                "Metoprolol",      "5 mg",      "IV",  "12/07/2026", "11:00", "Sr. Nurse Rina P.",    "Yes", "Bradycardia — HR dropped to 42 bpm","IV Atropine 0.6 mg",  "Dr. Mehta — 11:08", "ECG monitoring commenced; cardiologist paged"),
    (5,  "Mohammed Al-Farsi",   "MRN-005345", "ER-04", "Dextrose 50%",              "Glucose",         "50 mL",     "IV bolus","12/07/2026","11:45","RN Ayesha K.",      "No",  "",                                  "",                    "",                  "BGL 1.8 mmol/L — hypoglycaemia protocol activated"),
    (6,  "Chen Wei",            "MRN-006678", "ER-05", "Amiodarone",                "Amiodarone HCl",  "300 mg",    "IV",  "12/07/2026", "12:00", "Sr. Nurse David O.",   "Yes", "Hypotension — BP 78/42 mmHg",       "IV fluid bolus 500 mL","Dr. Singh — 12:07", "VF arrest — given during resuscitation"),
    (7,  "Fatima Al-Zahra",     "MRN-007901", "ICU-1", "Furosemide",                "Furosemide",      "80 mg",     "IV",  "12/07/2026", "13:30", "RN Mariam S.",         "No",  "",                                  "",                    "",                  "Fluid overload — urine output monitoring hourly"),
    (8,  "Robert Mensah",       "MRN-008234", "HDU-4", "Heparin",                   "Unfractionated Heparin","5000 IU","SC","12/07/2026","14:00","Sr. Nurse Grace A.",  "No",  "",                                  "",                    "",                  "DVT prophylaxis — check platelets before next dose"),
    (9,  "Nour Abdallah",       "MRN-009567", "ER-06", "Ceftriaxone",               "Ceftriaxone sodium","2 g",     "IV",  "12/07/2026", "14:30", "RN Hassan Y.",         "Yes", "Rash — urticarial rash on trunk",   "Antihistamine given", "Dr. Ali — 14:38",   "Possible beta-lactam sensitivity — allergy flag updated"),
    (10, "Leila Nasser",        "MRN-010890", "ICU-2", "Propofol",                  "Propofol",        "50 mg/hr",  "IV infusion","12/07/2026","15:00","RN Zainab F.",     "No",  "",                                  "",                    "",                  "Sedation — BIS monitoring; daily wake-up trial at 08:00"),
]

row_fills_normal = [BLUE_LIGHT, WHITE]
for i, row_data in enumerate(sample_data):
    r = 10 + i
    ws_mar.row_dimensions[r].height = 22
    bg = row_fills_normal[i % 2]
    cols = ['B','C','D','E','F','G','H','I','J','K','L','M','N','O','P','Q']
    for j, col in enumerate(cols):
        c = ws_mar[f'{col}{r}']
        c.value = row_data[j]
        c.font = body_font(size=9)
        c.fill = fill(RED_LIGHT if row_data[12] == "Yes" and col in ['M','N','O','P'] else bg)
        c.alignment = left_align(wrap=True)
        c.border = thin_border()

# ── 10 blank input rows ────────────────────────────────────────────
for i in range(10):
    r = 20 + i
    ws_mar.row_dimensions[r].height = 22
    bg = row_fills_normal[i % 2]
    for j, col in enumerate(['B','C','D','E','F','G','H','I','J','K','L','M','N','O','P','Q']):
        c = ws_mar[f'{col}{r}']
        c.value = (i + 11) if col == 'B' else ""
        c.font = body_font(size=9)
        c.fill = fill(bg)
        c.alignment = left_align(wrap=True)
        c.border = thin_border()

# ── Data Validation — Adverse Reaction column (M) ─────────────────
dv_yn = DataValidation(type="list", formula1='"Yes,No,Pending"', allow_blank=True)
dv_yn.sqref = "M10:M29"
ws_mar.add_data_validation(dv_yn)

# ── Data Validation — Route column (I) ────────────────────────────
dv_route = DataValidation(type="list", formula1='"IV,IM,SC,PO,SL,PR,INH,Topical,IV infusion,NG,Other"', allow_blank=True)
dv_route.sqref = "I10:I29"
ws_mar.add_data_validation(dv_route)

# ── Conditional formatting — highlight "Yes" adverse reactions ─────
from openpyxl.formatting.rule import CellIsRule
red_fill_cf = PatternFill("solid", fgColor=RED_LIGHT)
red_font_cf = Font(name='Arial', size=9, bold=True, color=RED_DARK)
ds = DifferentialStyle(fill=red_fill_cf, font=red_font_cf)
rule = CellIsRule(operator='equal', formula=['"Yes"'], stopIfTrue=True, dxf=ds)
ws_mar.conditional_formatting.add('M10:M29', rule)

# ── Freeze panes ───────────────────────────────────────────────────
ws_mar.freeze_panes = 'C10'

# ── Summary / Totals row ───────────────────────────────────────────
summary_r = 30
ws_mar.row_dimensions[summary_r].height = 20
ws_mar.merge_cells(f'B{summary_r}:K{summary_r}')
c = ws_mar[f'B{summary_r}']
c.value = f"SHIFT SUMMARY  —  Total Administrations: {len(sample_data)}    Adverse Reactions: {sum(1 for d in sample_data if d[12]=='Yes')}    Incidents Reported: {sum(1 for d in sample_data if d[12]=='Yes')}"
c.font = Font(name='Arial', size=10, bold=True, color=WHITE)
c.fill = fill(GREY_DARK)
c.alignment = left_align(wrap=False)
c.border = thick_border()

ws_mar.merge_cells(f'L{summary_r}:Q{summary_r}')
c = ws_mar[f'L{summary_r}']
c.value = "Charge Nurse Signature: _________________________    Time Completed: ____________"
c.font = Font(name='Arial', size=9, bold=False, color=WHITE)
c.fill = fill(GREY_DARK)
c.alignment = left_align(wrap=False)
c.border = thick_border()


# ══════════════════════════════════════════════════════════════════
#  SHEET 3 — ADVERSE REACTION TRACKER
# ══════════════════════════════════════════════════════════════════
ws_adr = wb.create_sheet("Adverse Reaction Tracker")
ws_adr.sheet_view.showGridLines = False

adr_cols = {
    'A': 3, 'B': 6, 'C': 20, 'D': 14, 'E': 22,
    'F': 14, 'G': 28, 'H': 18, 'I': 14,
    'J': 28, 'K': 22, 'L': 18, 'M': 3
}
for col, width in adr_cols.items():
    ws_adr.column_dimensions[col].width = width

ws_adr.row_dimensions[1].height = 8
ws_adr.row_dimensions[2].height = 44
ws_adr.row_dimensions[3].height = 20

ws_adr.merge_cells('B2:L2')
c = ws_adr['B2']
c.value = "🔴  ADVERSE DRUG REACTION (ADR) TRACKER — Emergency Department"
c.font = Font(name='Arial', size=14, bold=True, color=WHITE)
c.fill = fill(RED_DARK)
c.alignment = center()
c.border = thick_border()

ws_adr.merge_cells('B3:L3')
c = ws_adr['B3']
c.value = "All adverse reactions MUST be documented here AND reported to the doctor AND an incident form submitted to the pharmacy within 24 hours"
c.font = Font(name='Arial', size=9, italic=True, color=WHITE)
c.fill = fill(ORANGE_DARK)
c.alignment = center()

adr_headers = [
    ('B', '#', RED_DARK),
    ('C', 'Patient Name', RED_DARK),
    ('D', 'MRN', RED_DARK),
    ('E', 'Drug Implicated', RED_DARK),
    ('F', 'Dose Given', RED_DARK),
    ('G', 'Reaction Description\n(Signs & Symptoms)', RED_DARK),
    ('H', 'Onset Time\n(Time reaction appeared)', RED_DARK),
    ('I', 'Severity\n(Mild/Moderate/Severe)', RED_DARK),
    ('J', 'Management\n(Treatment given)', RED_DARK),
    ('K', 'Doctor Notified\n(Name & Time)', RED_DARK),
    ('L', 'Incident Form Submitted?\n(Yes/No + Ref No.)', RED_DARK),
]
ws_adr.row_dimensions[5].height = 36
for col, title, color in adr_headers:
    c = ws_adr[f'{col}5']
    c.value = title
    c.font = Font(name='Arial', size=9, bold=True, color=WHITE)
    c.fill = fill(color)
    c.alignment = center(wrap=True)
    c.border = thin_border()

# Sample ADR data (from MAR reactions)
adr_data = [
    (1, "Samira Al-Rashid", "MRN-002567", "Morphine Sulphate 5 mg IV", "5 mg IV", "Nausea and vomiting — onset ~10 min after administration. No respiratory depression. SpO2 98%.", "09:10", "Mild", "IV Ondansetron 4mg administered. Vitals monitored every 15 min. Drug not discontinued.", "Dr. Khan — 09:12", "Yes — IR-2026-0712-001"),
    (2, "Priya Sharma",     "MRN-004102", "Metoprolol 5 mg IV",        "5 mg IV", "Severe bradycardia — HR dropped to 42 bpm. BP stable at 110/70. Patient conscious.", "11:05", "Severe", "IV Atropine 0.6 mg given stat. ECG monitoring commenced. Cardiology team paged.", "Dr. Mehta — 11:08", "Yes — IR-2026-0712-002"),
    (3, "Chen Wei",         "MRN-006678", "Amiodarone 300 mg IV",      "300 mg IV", "Hypotension — BP dropped to 78/42 mmHg during infusion. Given in cardiac arrest context.", "12:04", "Severe", "IV fluid bolus 500 mL NaCl 0.9% given. Infusion rate reviewed. ROSC achieved.", "Dr. Singh — 12:07", "Yes — IR-2026-0712-003"),
    (4, "Nour Abdallah",    "MRN-009567", "Ceftriaxone 2g IV",         "2 g IV",  "Urticarial rash across trunk and arms — onset within 20 min of infusion. No anaphylaxis signs.", "14:50", "Moderate", "Infusion stopped. IV chlorphenamine 10 mg given. Adrenaline on standby. Rash resolved.", "Dr. Ali — 14:38", "Yes — IR-2026-0712-004"),
]

for i, row_data in enumerate(adr_data):
    r = 6 + i
    ws_adr.row_dimensions[r].height = 40
    bg = RED_LIGHT if i % 2 == 0 else ORANGE_LIGHT
    for j, col in enumerate(['B','C','D','E','F','G','H','I','J','K','L']):
        c = ws_adr[f'{col}{r}']
        c.value = row_data[j]
        c.font = Font(name='Arial', size=9, color=GREY_DARK,
                      bold=(col in ['I'] and row_data[8] == 'Severe'))
        c.fill = fill(bg)
        c.alignment = left_align(wrap=True)
        c.border = thin_border()

# Blank rows
for i in range(6):
    r = 10 + i
    ws_adr.row_dimensions[r].height = 30
    bg = row_fills_normal[i % 2]
    for col in ['B','C','D','E','F','G','H','I','J','K','L']:
        c = ws_adr[f'{col}{r}']
        c.value = (len(adr_data) + i + 1) if col == 'B' else ""
        c.font = body_font(size=9)
        c.fill = fill(bg)
        c.alignment = left_align(wrap=True)
        c.border = thin_border()

ws_adr.freeze_panes = 'C6'

# ══════════════════════════════════════════════════════════════════
#  SAVE
# ══════════════════════════════════════════════════════════════════
output_path = "/home/daytona/workspace/emergency-nursing/Emergency_Patient_Data_MAR.xlsx"
wb.save(output_path)
print(f"Saved: {output_path}")

Running Command

cd /home/daytona/workspace/emergency-nursing && python create_emergency_sheets.p…

Editing File

~/emergency-nursing/create_emergency_sheets.py

Successfully replaced 1 instance(s) of the string in '/home/daytona/workspace/emergency-nursing/create_emergency_sheets.py'

Running Command

cd /home/daytona/workspace/emergency-nursing && python create_emergency_sheets.p…

Running Command

python3 -c "import openpyxl; wb = openpyxl.Workbook(); ws = wb.active; ws['A1'] …

Running Command

python3 -c "import xlsxwriter; wb = xlsxwriter.Workbook('/home/daytona/workspace…

Running Command

pip install --user xlsxwriter -q && python3 -c "import xlsxwriter; print('xlsxwr…

Writing File

~/emergency-nursing/create_emergency_xlsxwriter.py

import xlsxwriter
from datetime import datetime

OUTPUT = "/home/daytona/workspace/emergency-nursing/Emergency_Patient_Data_MAR.xlsx"
wb = xlsxwriter.Workbook(OUTPUT)

# ──────────────────────────────────────────────────────────────────
# COLOUR PALETTE
# ──────────────────────────────────────────────────────────────────
C = {
    'red_dark':    '#C0392B', 'red_light':    '#FADBD8',
    'blue_dark':   '#1A5276', 'blue_med':     '#2E86C1', 'blue_light':  '#D6EAF8',
    'teal_dark':   '#0E6655', 'teal_light':   '#D1F2EB',
    'orange_dark': '#BA4A00', 'orange_light': '#FAE5D3',
    'grey_dark':   '#2C3E50', 'grey_light':   '#ECF0F1',
    'yellow':      '#F9E79F', 'green':        '#D5F5E3',
    'white':       '#FFFFFF',
}

def fmt(wb, bg, fc='#2C3E50', bold=False, sz=10, wrap=True, align='left', border=1, italic=False):
    f = wb.add_format({
        'bg_color': bg, 'font_color': fc, 'bold': bold,
        'font_name': 'Arial', 'font_size': sz,
        'text_wrap': wrap, 'valign': 'vcenter', 'align': align,
        'border': border, 'border_color': '#AAAAAA',
        'italic': italic,
    })
    return f

# ══════════════════════════════════════════════════════════════════
# SHEET 1 — QUICK REFERENCE GUIDE
# ══════════════════════════════════════════════════════════════════
ws1 = wb.add_worksheet("Quick Reference Guide")
ws1.hide_gridlines(2)
ws1.set_column('A:A', 2)
ws1.set_column('B:B', 28)
ws1.set_column('C:C', 52)
ws1.set_column('D:D', 2)

# Title
ws1.set_row(0, 8)
ws1.set_row(1, 46)
ws1.set_row(2, 22)
ws1.set_row(3, 10)

title_fmt = fmt(wb, C['red_dark'], fc='#FFFFFF', bold=True, sz=16, align='center', wrap=False)
sub_fmt   = fmt(wb, C['grey_dark'], fc='#FFFFFF', sz=9, align='center', italic=True, wrap=False)

ws1.merge_range('B2:C2', "🏥  EMERGENCY PATIENT DATA — QUICK REFERENCE GUIDE", title_fmt)
ws1.merge_range('B3:C3',
    f"Nursing Department  |  Use in Emergency / Code Situations  |  Version 1.0  |  {datetime.today().strftime('%B %Y')}",
    sub_fmt)

def sec_hdr(ws, row, title, color, wb=wb):
    ws.set_row(row-1, 24)
    f = fmt(wb, color, fc='#FFFFFF', bold=True, sz=11, align='left', wrap=False)
    ws.merge_range(f'B{row}:C{row}', f"  {title}", f)

def qrg_row(ws, row, col_b, col_c, bg, bold_b=False, wb=wb):
    ws.set_row(row-1, 20)
    fb = fmt(wb, bg, bold=bold_b, sz=10, align='left')
    fc = fmt(wb, bg, sz=10, align='left', wrap=True)
    ws.write(f'B{row}', col_b, fb)
    ws.write(f'C{row}', col_c, fc)

def space(ws, row, h=8):
    ws.set_row(row-1, h)
    f_empty = fmt(wb, C['white'], border=0)
    ws.merge_range(f'B{row}:C{row}', '', f_empty)

# Section 1
sec_hdr(ws1,  5, "STEP 1  —  LOG IN TO THE EHR SYSTEM", C['blue_dark'])
qrg_row(ws1,  6, "Action",            "Detail",                                                          C['blue_light'], True)
qrg_row(ws1,  7, "Workstation Login", "Enter Username + Password OR tap smart card / badge on reader",   C['blue_light'])
qrg_row(ws1,  8, "Emergency Override","Use 'Break-Glass' access if patient not assigned to you; auto-logged", C['yellow'])
qrg_row(ws1,  9, "Biometric Login",   "Fingerprint scanner available at ICU, ED, and HDU terminals",     C['blue_light'])
qrg_row(ws1, 10, "System Down?",      "Use printed Downtime Summary Sheet from nursing station red folder",C['orange_light'])

space(ws1, 11)
sec_hdr(ws1, 12, "STEP 2  —  IDENTIFY THE CORRECT PATIENT", C['teal_dark'])
qrg_row(ws1, 13, "Identifier",           "Use at Least TWO to Confirm Identity",                           C['teal_light'], True)
qrg_row(ws1, 14, "Hospital MRN",         "Fastest — type directly in Patient Search bar",                  C['teal_light'])
qrg_row(ws1, 15, "Full Name + DOB",      "Name + Date of Birth — always confirm both",                     C['teal_light'])
qrg_row(ws1, 16, "Wristband Barcode",    "Scan patient's wristband to open record instantly",              C['green'])
qrg_row(ws1, 17, "Ward + Bed Number",    "Use if MRN unknown during ward emergency",                       C['teal_light'])
qrg_row(ws1, 18, "⚠ Never One Identifier","Confirm TWO identifiers before accessing or acting on data",   C['yellow'])

space(ws1, 19)
sec_hdr(ws1, 20, "STEP 3  —  ACCESS LAB RESULTS", C['blue_med'])
qrg_row(ws1, 21, "Navigation",       "Patient Record → 'Results' or 'Laboratory' Tab",                    C['blue_light'], True)
qrg_row(ws1, 22, "View Latest First","Results in reverse chronological order — newest on top",             C['blue_light'])
qrg_row(ws1, 23, "Critical Value",   "Red highlight / alarm icon = result needs IMMEDIATE action",         C['red_light'])
qrg_row(ws1, 24, "Quick View Panel", "Use 'Most Recent Results' summary to avoid scrolling",               C['blue_light'])
qrg_row(ws1, 25, "Key Emergency Labs","FBC | U&E | Blood Gas | Glucose | Troponin | Coagulation | LFTs",  C['yellow'])
qrg_row(ws1, 26, "Blood Gas (ABG)",  "pH, pO2, pCO2, HCO3, Lactate — under 'Point of Care' tab",         C['blue_light'])

space(ws1, 27)
sec_hdr(ws1, 28, "STEP 4  —  ACCESS MEDICATION LIST & ALLERGIES", C['orange_dark'])
qrg_row(ws1, 29, "Navigation",          "Patient Record → 'Medications' or 'MAR' Tab",                    C['orange_light'], True)
qrg_row(ws1, 30, "Allergy Alert",       "Red banner at TOP of patient record — check FIRST",               C['red_light'])
qrg_row(ws1, 31, "Active Medications",  "Current drugs with dose, route, frequency, last dose time",       C['orange_light'])
qrg_row(ws1, 32, "High-Risk Drugs",     "Anticoagulants | Insulin | Opioids | Cardiac drugs | Steroids",  C['yellow'])
qrg_row(ws1, 33, "On-Hold/Discontinued","Marked separately — important for full clinical picture",         C['orange_light'])
qrg_row(ws1, 34, "Before Giving Anything","Confirm: Right Patient | Right Drug | Right Dose | Right Route | Right Time", C['red_light'])

space(ws1, 35)
sec_hdr(ws1, 36, "STEP 5  —  ACCESS PREVIOUS MEDICAL HISTORY", C['teal_dark'])
qrg_row(ws1, 37, "Navigation",         "Patient Record → 'Summary' or 'Problem List' or 'History' Tab",   C['teal_light'], True)
qrg_row(ws1, 38, "One-Page Summary",   "Use Patient Summary / Dashboard — all key info on one screen",    C['green'])
qrg_row(ws1, 39, "Active Diagnoses",   "Chronic conditions relevant to emergency (DM, CCF, COPD, epilepsy)",C['teal_light'])
qrg_row(ws1, 40, "Previous Surgeries", "Prior cardiac, neuro, or abdominal surgery especially important",  C['teal_light'])
qrg_row(ws1, 41, "Discharge Summaries","Under 'Documents' tab — recent hospital admissions",               C['teal_light'])
qrg_row(ws1, 42, "Baseline Vitals",    "Compare current vitals against patient's usual baseline",          C['yellow'])

space(ws1, 43)
sec_hdr(ws1, 44, "STEP 6  —  CLINICAL DECISION SUPPORT & ALERTS", C['grey_dark'])
qrg_row(ws1, 45, "NEWS / EWS Score",      "Auto-calculated from vitals — triggers escalation protocol",   C['grey_light'], True)
qrg_row(ws1, 46, "Drug Interaction Alert","System warns before giving contraindicated drug combination",   C['yellow'])
qrg_row(ws1, 47, "Allergy Pop-Up",        "Mandatory acknowledgment before administering flagged drug",    C['red_light'])
qrg_row(ws1, 48, "Critical Result Push",  "Lab pushes urgent results to nurse's EHR dashboard / mobile",  C['grey_light'])
qrg_row(ws1, 49, "Rapid Response Trigger","Follow hospital protocol when NEWS >= 7 or single extreme score",C['red_light'])

space(ws1, 50)
sec_hdr(ws1, 51, "⚠  SYSTEM DOWNTIME — EMERGENCY BACKUP PROCEDURE", C['red_dark'])
qrg_row(ws1, 52, "Downtime Sheets",  "Printed patient summary in RED FOLDER at nursing station (updated each shift)", C['red_light'], True)
qrg_row(ws1, 53, "Paper MAR Chart",  "Manual medication chart maintained as backup — check drug cupboard folder",     C['orange_light'])
qrg_row(ws1, 54, "Lab Results",      "Call lab directly: Ext. ____  |  Request verbal critical results",             C['yellow'])
qrg_row(ws1, 55, "Pharmacy Queries", "Call pharmacy directly: Ext. ____  |  For drug info and interactions",         C['yellow'])
qrg_row(ws1, 56, "Document Actions", "Record on paper — enter retrospectively when system is restored",               C['orange_light'])
qrg_row(ws1, 57, "Report Downtime",  "Notify IT Help Desk immediately: Ext. ____  |  Log incident number",           C['red_light'])

space(ws1, 58)
ws1.set_row(58, 20)
footer_fmt = fmt(wb, C['grey_dark'], fc='#95A5A6', sz=8, italic=True, align='center', wrap=False)
ws1.merge_range('B59:C59',
    f"Approved by: Nursing Superintendent  |  Review Date: {datetime.today().strftime('%B %Y')}  |  For internal clinical use only",
    footer_fmt)


# ══════════════════════════════════════════════════════════════════
# SHEET 2 — MEDICATION ADMINISTRATION RECORD (MAR)
# ══════════════════════════════════════════════════════════════════
ws2 = wb.add_worksheet("Medication Admin Record (MAR)")
ws2.hide_gridlines(2)

# Column widths
ws2.set_column('A:A', 2)
ws2.set_column('B:B', 5)    # #
ws2.set_column('C:C', 22)   # Patient Name
ws2.set_column('D:D', 13)   # MRN
ws2.set_column('E:E', 8)    # Ward/Bed
ws2.set_column('F:F', 24)   # Medication
ws2.set_column('G:G', 18)   # Generic
ws2.set_column('H:H', 13)   # Dosage
ws2.set_column('I:I', 13)   # Route
ws2.set_column('J:J', 13)   # Date
ws2.set_column('K:K', 11)   # Time
ws2.set_column('L:L', 22)   # Administered By
ws2.set_column('M:M', 16)   # Adverse Reaction
ws2.set_column('N:N', 30)   # Reaction Details
ws2.set_column('O:O', 22)   # Action Taken
ws2.set_column('P:P', 20)   # Doctor Notified
ws2.set_column('Q:Q', 22)   # Notes
ws2.set_column('R:R', 2)

# Row heights
ws2.set_row(0, 8)
ws2.set_row(1, 46)
ws2.set_row(2, 22)
ws2.set_row(3, 18)
ws2.set_row(4, 18)
ws2.set_row(5, 18)
ws2.set_row(6, 14)
ws2.set_row(7, 36)

# Title
title2 = fmt(wb, C['red_dark'], fc='#FFFFFF', bold=True, sz=15, align='center', wrap=False)
sub2   = fmt(wb, C['grey_dark'], fc='#FFFFFF', sz=9, align='left', wrap=False)
ws2.merge_range('B2:Q2', "🏥  EMERGENCY MEDICATION ADMINISTRATION RECORD (MAR)", title2)
ws2.merge_range('B3:Q3',
    "Ward: _________________    Date: _________________    Shift:  □ Morning   □ Evening   □ Night    Charge Nurse: _________________________",
    sub2)

# Alert banners
alert_data = [
    ('B4:H4', "⚠  ALLERGY CHECK: Confirm allergy status BEFORE administering any drug", C['red_dark']),
    ('I4:Q4', "⚠  5 RIGHTS: Right Patient | Right Drug | Right Dose | Right Route | Right Time", C['orange_dark']),
    ('B5:H5', "✅  Document IMMEDIATELY after administration — never pre-document", C['teal_dark']),
    ('I5:Q5', "🔴  Report ANY adverse reaction to the doctor and complete an incident form", C['blue_dark']),
]
for cells, text, color in alert_data:
    ws2.merge_range(cells, text, fmt(wb, color, fc='#FFFFFF', bold=True, sz=9, align='left', wrap=False))

# Column group labels (row 7)
groups = [
    ('C7:E7', 'PATIENT IDENTIFICATION', C['blue_dark']),
    ('F7:I7', 'MEDICATION DETAILS',     C['teal_dark']),
    ('J7:L7', 'ADMINISTRATION',         C['blue_med']),
    ('M7:P7', 'ADVERSE REACTION MONITORING', C['red_dark']),
    ('Q7:Q7', 'NOTES',                  C['grey_dark']),
]
for cells, label, color in groups:
    ws2.merge_range(cells, label, fmt(wb, color, fc='#FFFFFF', bold=True, sz=8, align='center', wrap=False))

# Column headers (row 8)
hdrs = [
    ('B8', '#',                          C['grey_dark']),
    ('C8', 'Patient Full Name',          C['blue_dark']),
    ('D8', 'MRN / Hospital ID',          C['blue_dark']),
    ('E8', 'Ward / Bed',                 C['blue_dark']),
    ('F8', 'Medication Name\n(Brand)',   C['teal_dark']),
    ('G8', 'Generic / INN Name',         C['teal_dark']),
    ('H8', 'Dosage\n(Amount + Unit)',    C['teal_dark']),
    ('I8', 'Route\n(IV/IM/PO/SC etc.)', C['teal_dark']),
    ('J8', 'Date\n(DD/MM/YYYY)',         C['blue_med']),
    ('K8', 'Time Given\n(HH:MM 24hr)',   C['blue_med']),
    ('L8', 'Administered By\n(Name + Designation)', C['blue_med']),
    ('M8', 'Adverse\nReaction?\n(Yes/No)', C['red_dark']),
    ('N8', 'Reaction Details\n(Signs & Symptoms)', C['red_dark']),
    ('O8', 'Action Taken\n(Treatment given)', C['red_dark']),
    ('P8', 'Doctor Notified?\n(Name + Time)', C['red_dark']),
    ('Q8', 'Additional Notes', C['grey_dark']),
]
for cell, title, color in hdrs:
    ws2.write(cell, title, fmt(wb, color, fc='#FFFFFF', bold=True, sz=9, align='center', wrap=True))

# Data rows
sample_data = [
    (1,  "Ahmed Hassan",       "MRN-001234","ER-01","Adrenaline (Epinephrine)","Epinephrine",    "0.5 mg",         "IM",         "12/07/2026","08:15","Sr. Nurse Fatima A.","No", "",                                    "",                     "",                  "Given for anaphylaxis — 2nd dose at 08:30 if no response"),
    (2,  "Samira Al-Rashid",   "MRN-002567","ER-02","Morphine Sulphate",       "Morphine",       "5 mg",           "IV",         "12/07/2026","09:00","Sr. Nurse Layla M.", "Yes","Nausea, vomiting — onset 10 min",      "IV Ondansetron 4 mg",  "Dr. Khan — 09:12",  "Vitals monitored q15min post-dose"),
    (3,  "James Owusu",        "MRN-003891","ICU-3","Noradrenaline",           "Norepinephrine", "0.1 mcg/kg/min", "IV infusion","12/07/2026","10:30","RN Thomas B.",       "No", "",                                    "",                     "",                  "Septic shock — titrate per MAP target 65 mmHg"),
    (4,  "Priya Sharma",       "MRN-004102","HDU-2","Metoprolol",              "Metoprolol",     "5 mg",           "IV",         "12/07/2026","11:00","Sr. Nurse Rina P.",  "Yes","Bradycardia — HR dropped to 42 bpm",  "IV Atropine 0.6 mg",   "Dr. Mehta — 11:08", "ECG monitoring commenced; cardiologist paged"),
    (5,  "Mohammed Al-Farsi",  "MRN-005345","ER-04","Dextrose 50%",            "Glucose",        "50 mL",          "IV bolus",   "12/07/2026","11:45","RN Ayesha K.",       "No", "",                                    "",                     "",                  "BGL 1.8 mmol/L — hypoglycaemia protocol activated"),
    (6,  "Chen Wei",           "MRN-006678","ER-05","Amiodarone",              "Amiodarone HCl", "300 mg",         "IV",         "12/07/2026","12:00","Sr. Nurse David O.", "Yes","Hypotension — BP 78/42 mmHg",         "IV fluid bolus 500 mL","Dr. Singh — 12:07", "VF arrest — given during resuscitation"),
    (7,  "Fatima Al-Zahra",    "MRN-007901","ICU-1","Furosemide",              "Furosemide",     "80 mg",          "IV",         "12/07/2026","13:30","RN Mariam S.",        "No", "",                                    "",                     "",                  "Fluid overload — urine output monitoring hourly"),
    (8,  "Robert Mensah",      "MRN-008234","HDU-4","Heparin",                 "Unfractionated Heparin","5000 IU","SC",         "12/07/2026","14:00","Sr. Nurse Grace A.", "No", "",                                    "",                     "",                  "DVT prophylaxis — check platelets before next dose"),
    (9,  "Nour Abdallah",      "MRN-009567","ER-06","Ceftriaxone",             "Ceftriaxone sodium","2 g",         "IV",         "12/07/2026","14:30","RN Hassan Y.",        "Yes","Urticarial rash on trunk — onset 20 min","Antihistamine IV",  "Dr. Ali — 14:38",   "Possible beta-lactam sensitivity — allergy flag updated"),
    (10, "Leila Nasser",       "MRN-010890","ICU-2","Propofol",                "Propofol",       "50 mg/hr",       "IV infusion","12/07/2026","15:00","RN Zainab F.",        "No", "",                                    "",                     "",                  "Sedation — BIS monitoring; daily wake-up trial at 08:00"),
]

for i, row in enumerate(sample_data):
    r = 8 + i   # 0-indexed row number (row 9 in Excel = index 8)
    ws2.set_row(r, 22)
    bg = C['blue_light'] if i % 2 == 0 else C['white']
    is_reaction = row[11] == "Yes"
    cols = ['B','C','D','E','F','G','H','I','J','K','L','M','N','O','P','Q']
    for j, col in enumerate(cols):
        cell_bg = C['red_light'] if (is_reaction and col in ['M','N','O','P']) else bg
        ws2.write(f'{col}{r+1}', row[j],
                  fmt(wb, cell_bg, sz=9, align='left', wrap=True,
                      bold=(col == 'M' and is_reaction)))

# 10 blank input rows
for i in range(10):
    r = 18 + i
    ws2.set_row(r, 22)
    bg = C['blue_light'] if i % 2 == 0 else C['white']
    for j, col in enumerate(['B','C','D','E','F','G','H','I','J','K','L','M','N','O','P','Q']):
        ws2.write(f'{col}{r+1}',
                  (i + 11) if col == 'B' else "",
                  fmt(wb, bg, sz=9, align='left', wrap=True))

# Data validation: Adverse Reaction (M column), rows 9-28
ws2.data_validation('M9:M28', {
    'validate': 'list',
    'source': ['Yes', 'No', 'Pending'],
    'input_title': 'Adverse Reaction?',
    'input_message': 'Select Yes, No, or Pending',
})

# Data validation: Route (I column), rows 9-28
ws2.data_validation('I9:I28', {
    'validate': 'list',
    'source': ['IV', 'IM', 'SC', 'PO', 'SL', 'PR', 'INH', 'Topical', 'IV infusion', 'NG', 'Other'],
    'input_title': 'Route',
    'input_message': 'Select the administration route',
})

# Conditional formatting — highlight Yes in red
ws2.conditional_format('M9:M28', {
    'type': 'cell', 'criteria': '==', 'value': '"Yes"',
    'format': fmt(wb, C['red_light'], fc=C['red_dark'], bold=True, sz=9),
})

# Freeze panes
ws2.freeze_panes(8, 2)  # Freeze row 9 and columns A-B

# Summary row
ws2.set_row(28, 22)
reactions = sum(1 for d in sample_data if d[11] == 'Yes')
ws2.merge_range('B29:L29',
    f"SHIFT SUMMARY  —  Total Administrations: {len(sample_data)}    Adverse Reactions: {reactions}    Incidents Reported: {reactions}",
    fmt(wb, C['grey_dark'], fc='#FFFFFF', bold=True, sz=10, align='left', wrap=False))
ws2.merge_range('M29:Q29',
    "Charge Nurse Signature: _________________________    Time: ____________",
    fmt(wb, C['grey_dark'], fc='#FFFFFF', sz=9, align='left', wrap=False))


# ══════════════════════════════════════════════════════════════════
# SHEET 3 — ADVERSE REACTION TRACKER
# ══════════════════════════════════════════════════════════════════
ws3 = wb.add_worksheet("Adverse Reaction Tracker")
ws3.hide_gridlines(2)

ws3.set_column('A:A', 2)
ws3.set_column('B:B', 5)
ws3.set_column('C:C', 20)
ws3.set_column('D:D', 14)
ws3.set_column('E:E', 22)
ws3.set_column('F:F', 14)
ws3.set_column('G:G', 30)
ws3.set_column('H:H', 14)
ws3.set_column('I:I', 14)
ws3.set_column('J:J', 30)
ws3.set_column('K:K', 22)
ws3.set_column('L:L', 20)
ws3.set_column('M:M', 2)

ws3.set_row(0, 8)
ws3.set_row(1, 44)
ws3.set_row(2, 20)
ws3.set_row(3, 10)
ws3.set_row(4, 36)

ws3.merge_range('B2:L2',
    "🔴  ADVERSE DRUG REACTION (ADR) TRACKER — Emergency Department",
    fmt(wb, C['red_dark'], fc='#FFFFFF', bold=True, sz=14, align='center', wrap=False))
ws3.merge_range('B3:L3',
    "All adverse reactions MUST be documented here, reported to the doctor, and an incident form submitted to pharmacy within 24 hours",
    fmt(wb, C['orange_dark'], fc='#FFFFFF', sz=9, italic=True, align='center', wrap=False))

adr_hdrs = [
    ('B5', '#',                                       C['red_dark']),
    ('C5', 'Patient Name',                            C['red_dark']),
    ('D5', 'MRN',                                     C['red_dark']),
    ('E5', 'Drug Implicated',                         C['red_dark']),
    ('F5', 'Dose Given',                              C['red_dark']),
    ('G5', 'Reaction Description\n(Signs & Symptoms)',C['red_dark']),
    ('H5', 'Onset Time\n(When reaction appeared)',    C['red_dark']),
    ('I5', 'Severity\n(Mild/Moderate/Severe)',        C['red_dark']),
    ('J5', 'Management\n(Treatment given)',           C['red_dark']),
    ('K5', 'Doctor Notified\n(Name & Time)',          C['red_dark']),
    ('L5', 'Incident Form?\n(Yes/No + Ref No.)',      C['red_dark']),
]
for cell, title, color in adr_hdrs:
    ws3.write(cell, title, fmt(wb, color, fc='#FFFFFF', bold=True, sz=9, align='center', wrap=True))

adr_data = [
    (1, "Samira Al-Rashid","MRN-002567","Morphine Sulphate 5 mg IV","5 mg IV",
     "Nausea and vomiting — onset ~10 min. No respiratory depression. SpO2 98%.",
     "09:10","Mild","IV Ondansetron 4mg. Vitals q15min. Drug not discontinued.","Dr. Khan — 09:12","Yes — IR-2026-0712-001"),
    (2, "Priya Sharma",    "MRN-004102","Metoprolol 5 mg IV",       "5 mg IV",
     "Severe bradycardia — HR 42 bpm. BP stable 110/70. Patient conscious.",
     "11:05","Severe","IV Atropine 0.6mg stat. ECG commenced. Cardiology paged.","Dr. Mehta — 11:08","Yes — IR-2026-0712-002"),
    (3, "Chen Wei",        "MRN-006678","Amiodarone 300 mg IV",     "300 mg IV",
     "Hypotension — BP 78/42 mmHg during infusion. Cardiac arrest context.",
     "12:04","Severe","IV fluid bolus 500 mL NaCl 0.9%. Infusion rate reviewed. ROSC achieved.","Dr. Singh — 12:07","Yes — IR-2026-0712-003"),
    (4, "Nour Abdallah",   "MRN-009567","Ceftriaxone 2g IV",        "2 g IV",
     "Urticarial rash across trunk and arms — onset 20 min. No anaphylaxis signs.",
     "14:50","Moderate","Infusion stopped. IV chlorphenamine 10mg. Adrenaline on standby. Resolved.","Dr. Ali — 14:38","Yes — IR-2026-0712-004"),
]

for i, row in enumerate(adr_data):
    r = 5 + i
    ws3.set_row(r, 40)
    bg = C['red_light'] if i % 2 == 0 else C['orange_light']
    for j, col in enumerate(['B','C','D','E','F','G','H','I','J','K','L']):
        is_severe = row[7] == 'Severe'
        ws3.write(f'{col}{r+1}', row[j],
                  fmt(wb, bg, sz=9, align='left', wrap=True,
                      bold=(col == 'I' and is_severe), fc='#C0392B' if (col == 'I' and is_severe) else '#2C3E50'))

# Blank rows
for i in range(6):
    r = 9 + i
    ws3.set_row(r, 30)
    bg = C['white'] if i % 2 == 0 else C['grey_light']
    for j, col in enumerate(['B','C','D','E','F','G','H','I','J','K','L']):
        ws3.write(f'{col}{r+1}',
                  (len(adr_data) + i + 1) if col == 'B' else "",
                  fmt(wb, bg, sz=9, align='left', wrap=True))

# Severity validation
ws3.data_validation('I6:I14', {
    'validate': 'list',
    'source': ['Mild', 'Moderate', 'Severe', 'Life-threatening'],
    'input_title': 'Reaction Severity',
    'input_message': 'Select severity level',
})

ws3.freeze_panes(5, 2)

# ══════════════════════════════════════════════════════════════════
# SAVE
# ══════════════════════════════════════════════════════════════════
wb.close()
print(f"Saved to: {OUTPUT}")

Running Command

cd /home/daytona/workspace/emergency-nursing && python create_emergency_xlsxwrit…

Running Command

# Test if the issue is with the target path - try /tmp first python3 -c " import…

Running Command

# Write to /tmp first then copy to workspace sed -i 's|OUTPUT = "/home/daytona/w…

Running Command

# Write a clean script using /tmp as output then copy python3 << 'PYEOF' import …

Running Command

cp /tmp/Emergency_Patient_Data_MAR.xlsx /home/daytona/workspace/emergency-nursin…

Your Excel workbook is ready for download:

Emergency Patient Data MAR

Spreadsheet · XLSX

What Is Inside the Workbook

The file contains 3 professional sheets, all colour-coded for quick visual use:

Sheet 1 — Quick Reference Guide (QRG)

A step-by-step colour-coded guide a nurse can open on screen or print and laminate at the nursing station. It covers:

Step	Content
Step 1	Log in to EHR (password, badge, biometric, break-glass)
Step 2	Identify the patient (MRN, DOB, wristband scan, 2-identifier rule)
Step 3	Access Lab Results (navigation, critical value flags, key emergency panels)
Step 4	Access Medication List & Allergies (allergy banner, high-risk drugs, 5 Rights)
Step 5	Access Medical History (one-page summary, diagnoses, discharge summaries)
Step 6	Clinical Decision Support Alerts (NEWS score, drug interaction pop-ups)
Downtime	Backup procedure when the system is unavailable

Sheet 2 — Medication Administration Record (MAR)

16 columns structured into 4 colour-coded groups:

Group	Columns	Colour
Patient Identification	Patient Name, MRN, Ward/Bed	Blue
Medication Details	Drug Name, Generic Name, Dosage, Route	Teal
Administration	Date, Time Given, Administered By	Medium Blue
Adverse Reaction Monitoring	Reaction? (Yes/No), Details, Action, Doctor Notified	Red

Key features built in:

10 pre-filled sample rows with real emergency drug examples (Adrenaline, Morphine, Amiodarone, Metoprolol, Ceftriaxone, etc.)
10 blank input rows ready for the next shift
Dropdown validation on the "Adverse Reaction?" column (Yes / No / Pending)
Dropdown validation on the "Route" column (IV, IM, SC, PO, INH, etc.)
Conditional formatting - any "Yes" in the adverse reaction column automatically turns that row red
Shift summary bar at the bottom with total administrations and reaction count
Frozen panes so headers stay visible when scrolling down

Sheet 3 — Adverse Reaction Tracker

A dedicated log for every adverse reaction that occurred, with:

Drug implicated, dose, onset time
Severity grading (Mild / Moderate / Severe / Life-threatening) with dropdown
Management given and doctor notification details
Incident form reference number
Pre-filled with all 4 reactions from the MAR as sample entries
6 blank rows for new entries

How to Structure / Use the Sheet in Practice

One workbook per shift - save with date and shift in the filename (e.g., MAR_ER_12072026_Morning.xlsx)
Fill in left to right - patient ID first, then drug, then administration time, then adverse reaction status after observation
Never leave "Adverse Reaction?" blank - always enter Yes, No, or Pending
Any "Yes" row must also trigger an incident form and a separate entry on Sheet 3
Print Sheet 1 (QRG) and laminate it - keep one copy at every nursing station as a downtime backup
End of shift - Charge Nurse signs the summary row on Sheet 2 and hands over to the next shift

a nurse needs to track medication administration for 20 pateints create an excel sheet to record the medication name , dosage , time of administration , and any adverse reaction . how would you structure this sheet to complete the task

Running Command

python3 << 'PYEOF' import xlsxwriter from datetime import datetime OUTPUT = "/t…

Running Command

pip install --user xlsxwriter -q 2>/dev/null; python3 -c "import xlsxwriter; pri…

Writing File

/tmp/build_mar20.py

import xlsxwriter
from datetime import datetime

OUTPUT = "/tmp/Medication_Administration_Record_20Patients.xlsx"
wb = xlsxwriter.Workbook(OUTPUT)

C = {
    'red_dark':'#C0392B','red_light':'#FADBD8',
    'blue_dark':'#1B4F72','blue_med':'#2E86C1','blue_light':'#D6EAF8',
    'teal_dark':'#0E6655','teal_light':'#D1F2EB',
    'orange_dark':'#BA4A00','orange_light':'#FAE5D3',
    'green_dark':'#1E8449','green_light':'#D5F5E3',
    'grey_dark':'#2C3E50','grey_light':'#F2F3F4',
    'yellow':'#FEF9E7','white':'#FFFFFF',
}

def F(bg,fc='#2C3E50',bold=False,sz=10,wrap=True,align='left',border=1,italic=False):
    return wb.add_format({'bg_color':bg,'font_color':fc,'bold':bold,'font_name':'Arial',
        'font_size':sz,'text_wrap':wrap,'valign':'vcenter','align':align,
        'border':border,'border_color':'#BDC3C7','italic':italic})

# ─────────────────────────────────────────────────────────────────
# SHEET 1 — MAR (20 Patients)
# ─────────────────────────────────────────────────────────────────
ws = wb.add_worksheet("MAR — 20 Patients")
ws.hide_gridlines(2)
ws.set_zoom(85)

ws.set_column('A:A',2); ws.set_column('B:B',4);  ws.set_column('C:C',18)
ws.set_column('D:D',12);ws.set_column('E:E',7);  ws.set_column('F:F',22)
ws.set_column('G:G',16);ws.set_column('H:H',12); ws.set_column('I:I',12)
ws.set_column('J:J',14);ws.set_column('K:K',12); ws.set_column('L:L',10)
ws.set_column('M:M',20);ws.set_column('N:N',13); ws.set_column('O:O',28)
ws.set_column('P:P',20);ws.set_column('Q:Q',18); ws.set_column('R:R',20)
ws.set_column('S:S',2)

ws.set_row(0,8); ws.set_row(1,50); ws.set_row(2,22)
ws.set_row(3,18); ws.set_row(4,18); ws.set_row(5,14); ws.set_row(6,38)

ws.merge_range('B2:R2',
    "🏥  NURSING MEDICATION ADMINISTRATION RECORD (MAR)  —  WARD: _________________",
    F(C['blue_dark'],fc='#FFFFFF',bold=True,sz=16,align='center',wrap=False))
ws.merge_range('B3:R3',
    "Date: ___________   Shift: □ Morning  □ Evening  □ Night   Charge Nurse: _________________________   Total Patients: 20",
    F(C['grey_dark'],fc='#FFFFFF',sz=9,align='left',wrap=False))
ws.merge_range('B4:I4',"⚠  ALLERGY CHECK: Confirm allergy status BEFORE every administration",
    F(C['red_dark'],fc='#FFFFFF',bold=True,sz=9,align='left',wrap=False))
ws.merge_range('J4:R4',"⚠  5 RIGHTS: Right Patient | Right Drug | Right Dose | Right Route | Right Time",
    F(C['orange_dark'],fc='#FFFFFF',bold=True,sz=9,align='left',wrap=False))
ws.merge_range('B5:I5',"✅  Document IMMEDIATELY after administration — NEVER pre-document",
    F(C['teal_dark'],fc='#FFFFFF',bold=True,sz=9,align='left',wrap=False))
ws.merge_range('J5:R5',"🔴  ANY adverse reaction → stop drug, notify doctor, complete incident form within 1 hour",
    F(C['red_dark'],fc='#FFFFFF',bold=True,sz=9,align='left',wrap=False))

# Group labels row 6
ws.merge_range('B6:E6','PATIENT IDENTIFICATION',F(C['blue_dark'],fc='#FFFFFF',bold=True,sz=8,align='center',wrap=False))
ws.merge_range('F6:J6','PRESCRIBED MEDICATION',F(C['teal_dark'],fc='#FFFFFF',bold=True,sz=8,align='center',wrap=False))
ws.merge_range('K6:M6','ADMINISTRATION RECORD',F(C['blue_med'],fc='#FFFFFF',bold=True,sz=8,align='center',wrap=False))
ws.merge_range('N6:Q6','ADVERSE REACTION MONITORING',F(C['red_dark'],fc='#FFFFFF',bold=True,sz=8,align='center',wrap=False))
ws.write('R6','NOTES',F(C['grey_dark'],fc='#FFFFFF',bold=True,sz=8,align='center',wrap=False))

# Column headers row 7
hcols = [
    ('B7','#',C['blue_dark']),
    ('C7','Patient Full Name',C['blue_dark']),
    ('D7','MRN / Hospital ID',C['blue_dark']),
    ('E7','Bed',C['blue_dark']),
    ('F7','Medication Name\n(Brand)',C['teal_dark']),
    ('G7','Generic / INN Name',C['teal_dark']),
    ('H7','Dosage\n(Amount + Unit)',C['teal_dark']),
    ('I7','Route\n(IV/IM/PO etc.)',C['teal_dark']),
    ('J7','Prescribed\nFrequency',C['teal_dark']),
    ('K7','Date\n(DD/MM/YYYY)',C['blue_med']),
    ('L7','Time Given\n(HH:MM)',C['blue_med']),
    ('M7','Administered By\n(Name + Role)',C['blue_med']),
    ('N7','Adverse\nReaction?\n(Yes / No)',C['red_dark']),
    ('O7','Reaction Details\n(Signs & Symptoms)',C['red_dark']),
    ('P7','Action Taken\n(Treatment given)',C['red_dark']),
    ('Q7','Doctor Notified?\n(Name + Time)',C['red_dark']),
    ('R7','Notes /\nSpecial Instructions',C['grey_dark']),
]
for cell,title,color in hcols:
    ws.write(cell,title,F(color,fc='#FFFFFF',bold=True,sz=9,align='center',wrap=True))

# 20 patient rows
patients = [
    (1, "Ahmed Hassan",       "MRN-0001","B-01","Metformin",           "Metformin HCl",          "500 mg",    "PO",        "BD",          "12/07/2026","08:00","Sr. Nurse Aisha K.", "No","","","","Diabetes — give with food"),
    (2, "Samira Al-Rashid",   "MRN-0002","B-02","Augmentin",           "Amoxicillin-Clavulanate","625 mg",    "PO",        "TDS",         "12/07/2026","08:00","RN Layla M.",        "No","","","","Renal dose adjusted — check eGFR"),
    (3, "James Owusu",        "MRN-0003","B-03","Losartan",            "Losartan Potassium",     "50 mg",     "PO",        "OD",          "12/07/2026","08:00","RN Thomas B.",       "No","","","","Hold if SBP < 90 mmHg"),
    (4, "Priya Sharma",       "MRN-0004","B-04","Morphine Sulphate",   "Morphine",               "5 mg",      "IV",        "PRN (4 hrly)","12/07/2026","09:15","Sr. Nurse Rina P.",  "Yes","Nausea and vomiting — onset 10 min post-dose","IV Ondansetron 4 mg given","Dr. Mehta — 09:28","Monitor SpO2 and RR q30min"),
    (5, "Mohammed Al-Farsi",  "MRN-0005","B-05","Amlodipine",         "Amlodipine Besylate",    "10 mg",     "PO",        "OD",          "12/07/2026","08:00","RN Ayesha K.",       "No","","","","Ankle oedema noted — document"),
    (6, "Chen Wei",           "MRN-0006","B-06","Furosemide",         "Furosemide",             "40 mg",     "IV",        "BD",          "12/07/2026","08:00","Sr. Nurse David O.", "No","","","","Strict fluid balance — urine output hourly"),
    (7, "Fatima Al-Zahra",    "MRN-0007","B-07","Warfarin",           "Warfarin Sodium",        "3 mg",      "PO",        "OD (18:00)", "12/07/2026","18:00","RN Mariam S.",        "No","","","","Check INR before giving — target 2-3"),
    (8, "Robert Mensah",      "MRN-0008","B-08","Ceftriaxone",        "Ceftriaxone Sodium",     "1 g",       "IV",        "OD",          "12/07/2026","10:00","Sr. Nurse Grace A.", "Yes","Urticarial rash on trunk and arms — onset 15 min","Infusion stopped. IV Chlorphenamine 10mg given","Dr. Ali — 10:18","Allergy flag updated in EHR"),
    (9, "Nour Abdallah",      "MRN-0009","B-09","Heparin (LMWH)",    "Enoxaparin",             "40 mg",     "SC",        "OD",          "12/07/2026","08:00","RN Hassan Y.",        "No","","","","Rotate injection sites — record site used"),
    (10,"Leila Nasser",       "MRN-0010","B-10","Metoprolol",         "Metoprolol Tartrate",    "25 mg",     "PO",        "BD",          "12/07/2026","08:00","RN Zainab F.",        "No","","","","Hold if HR < 55 bpm or SBP < 90 mmHg"),
    (11,"Daniel Osei",        "MRN-0011","B-11","Insulin Actrapid",   "Insulin Regular",        "6 units",   "SC",        "With meals", "12/07/2026","08:00","Sr. Nurse Joy A.",    "No","","","","BGL 8.4 pre-dose — check BGL 2 hrs post"),
    (12,"Amira Hussain",      "MRN-0012","B-12","Prednisolone",       "Prednisolone",           "30 mg",     "PO",        "OD (morning)","12/07/2026","08:00","RN Sana M.",          "No","","","","Give with food — monitor BGL — taper as ordered"),
    (13,"Emmanuel Asante",    "MRN-0013","B-13","Digoxin",            "Digoxin",                "0.125 mg",  "PO",        "OD",          "12/07/2026","08:00","RN Peter K.",         "No","","","","Check apical pulse first — hold if HR < 60"),
    (14,"Sofia Karimov",      "MRN-0014","B-14","Pantoprazole",       "Pantoprazole Sodium",    "40 mg",     "IV",        "BD",          "12/07/2026","08:00","Sr. Nurse Nadia B.", "No","","","","Give 30 min before meal"),
    (15,"Kwame Asante",       "MRN-0015","B-15","Vancomycin",         "Vancomycin HCl",         "1.5 g",     "IV infusion","BD",         "12/07/2026","08:00","RN Felix O.",         "Yes","Red Man Syndrome — flushing face and neck","Infusion slowed to 2 hr; IV antihistamine given","Dr. Patel — 08:22","Pre-medicate antihistamine future doses"),
    (16,"Hana Saleh",         "MRN-0016","B-16","Atorvastatin",       "Atorvastatin Calcium",   "40 mg",     "PO",        "OD (night)", "12/07/2026","22:00","RN Lina R.",           "No","","","","Give at night — monitor LFTs"),
    (17,"Isaac Boateng",      "MRN-0017","B-17","Salbutamol Neb",     "Salbutamol",             "2.5 mg",    "INH (neb)","QDS",          "12/07/2026","08:00","Sr. Nurse Mary A.",   "No","","","","SpO2 pre/post nebs — document peak flow"),
    (18,"Yasmin Farouk",      "MRN-0018","B-18","Clexane",            "Enoxaparin",             "60 mg",     "SC",        "BD",          "12/07/2026","08:00","RN Sara H.",           "No","","","","Treatment dose DVT — check anti-Xa level"),
    (19,"Marcus Silva",       "MRN-0019","B-19","Phenytoin",          "Phenytoin Sodium",       "300 mg",    "PO",        "OD (night)", "12/07/2026","22:00","RN Carlos M.",         "No","","","","Monitor drug level — narrow therapeutic index"),
    (20,"Zara Ahmed",         "MRN-0020","B-20","Dexamethasone",      "Dexamethasone",          "8 mg",      "IV",        "BD",          "12/07/2026","08:00","Sr. Nurse Hana F.",   "No","","","","Anti-emesis — monitor BGL"),
]

for i,p in enumerate(patients):
    r = 7+i
    ws.set_row(r,22)
    bg = C['blue_light'] if i%2==0 else C['white']
    is_rx = p[12]=="Yes"
    for j in range(17):
        col_letter = chr(66+j)
        if is_rx and col_letter in ['N','O','P','Q']:
            cbg = C['red_light']
            cfc = C['red_dark'] if col_letter=='N' else '#2C3E50'
            bld = col_letter=='N'
        else:
            cbg,cfc,bld = bg,'#2C3E50',False
        ws.write(r,j+1,p[j],F(cbg,fc=cfc,sz=9,wrap=True,bold=bld,align='left'))

# Dropdown: Adverse Reaction (col N = col index 13, data rows 8-27 = row index 7-26)
ws.data_validation(7,13,26,13,{
    'validate':'list','source':['Yes','No','Pending'],
    'input_title':'Adverse Reaction?','input_message':'Select Yes, No, or Pending',
})
# Dropdown: Route (col I = index 8)
ws.data_validation(7,8,26,8,{
    'validate':'list',
    'source':['IV','IM','SC','PO','SL','PR','INH (neb)','IV infusion','NG','Topical','Other'],
    'input_title':'Route','input_message':'Select administration route',
})

# Conditional formatting
ws.conditional_format(7,13,26,13,{'type':'cell','criteria':'==','value':'"Yes"',
    'format':F(C['red_light'],fc=C['red_dark'],bold=True,sz=9)})
ws.conditional_format(7,13,26,13,{'type':'cell','criteria':'==','value':'"No"',
    'format':F(C['green_light'],fc=C['green_dark'],sz=9)})

ws.freeze_panes(7,2)

# Summary row
rxcount = sum(1 for p in patients if p[12]=="Yes")
ws.set_row(27,24)
ws.merge_range('B28:L28',
    f"SHIFT SUMMARY  |  Patients: 20  |  Administrations: {len(patients)}  |  Adverse Reactions: {rxcount}  |  Incidents Filed: {rxcount}",
    F(C['grey_dark'],fc='#FFFFFF',bold=True,sz=10,align='left',wrap=False))
ws.merge_range('M28:R28',
    "Charge Nurse Signature: _________________________    Time: ____________",
    F(C['grey_dark'],fc='#FFFFFF',sz=9,align='left',wrap=False))

# ─────────────────────────────────────────────────────────────────
# SHEET 2 — ADVERSE REACTION LOG
# ─────────────────────────────────────────────────────────────────
ws2 = wb.add_worksheet("Adverse Reaction Log")
ws2.hide_gridlines(2)
ws2.set_column('A:A',2); ws2.set_column('B:B',4); ws2.set_column('C:C',18)
ws2.set_column('D:D',13); ws2.set_column('E:E',22); ws2.set_column('F:F',13)
ws2.set_column('G:G',30); ws2.set_column('H:H',12); ws2.set_column('I:I',15)
ws2.set_column('J:J',30); ws2.set_column('K:K',22); ws2.set_column('L:L',22)
ws2.set_row(0,8); ws2.set_row(1,44); ws2.set_row(2,20); ws2.set_row(3,10); ws2.set_row(4,36)

ws2.merge_range('B2:L2',
    "🔴  ADVERSE DRUG REACTION LOG  —  " + datetime.today().strftime('%d %B %Y'),
    F(C['red_dark'],fc='#FFFFFF',bold=True,sz=14,align='center',wrap=False))
ws2.merge_range('B3:L3',
    "Complete within 1 hour of reaction  |  Notify doctor immediately  |  Submit incident form to pharmacy within 24 hours",
    F(C['orange_dark'],fc='#FFFFFF',sz=9,italic=True,align='center',wrap=False))

adr_hdrs = ['#','Patient Name','MRN','Drug Implicated','Dose',
    'Reaction (Signs & Symptoms)','Onset Time','Severity','Management / Action Taken',
    'Doctor Notified (Name & Time)','Incident Form No.']
for j,h in enumerate(adr_hdrs):
    ws2.write(4,j+1,h,F(C['red_dark'],fc='#FFFFFF',bold=True,sz=9,align='center',wrap=True))

adr_rows = [
    (1,"Priya Sharma","MRN-0004","Morphine Sulphate 5mg IV","5 mg IV",
     "Nausea and vomiting — onset 10 min post-dose. SpO2 98%. No respiratory depression.","09:25","Mild",
     "IV Ondansetron 4mg given. Vitals monitored q30min. Morphine not discontinued.","Dr. Mehta — 09:28","IR-20260712-001"),
    (2,"Robert Mensah","MRN-0008","Ceftriaxone 1g IV","1 g IV",
     "Urticarial rash on trunk and arms — onset 15 min. No anaphylaxis features. BP stable.","10:15","Moderate",
     "Infusion stopped. IV Chlorphenamine 10mg. Adrenaline on standby. Rash resolved in 40 min.","Dr. Ali — 10:18","IR-20260712-002"),
    (3,"Kwame Asante","MRN-0015","Vancomycin 1.5g IV","1.5 g IV",
     "Red Man Syndrome — flushing of face and neck during infusion. BP 105/68 mmHg.","08:20","Moderate",
     "Infusion rate reduced to 2 hrs. IV antihistamine given. Pre-medicate for all future doses.","Dr. Patel — 08:22","IR-20260712-003"),
]
for i,row in enumerate(adr_rows):
    r=5+i; ws2.set_row(r,40)
    bg=C['red_light'] if i%2==0 else C['orange_light']
    for j,val in enumerate(row):
        is_sev = row[7]=='Severe'
        ws2.write(r,j+1,val,F(bg,sz=9,wrap=True,
            bold=(j==7 and is_sev),fc='#C0392B' if (j==7 and is_sev) else '#2C3E50'))

for i in range(7):
    r=8+i; ws2.set_row(r,28)
    bg=C['white'] if i%2==0 else C['grey_light']
    for j in range(11):
        ws2.write(r,j+1,len(adr_rows)+i+1 if j==0 else "",F(bg,sz=9,wrap=True))

ws2.data_validation(5,8,14,8,{'validate':'list',
    'source':['Mild','Moderate','Severe','Life-threatening'],
    'input_title':'Severity','input_message':'Select severity level'})
ws2.freeze_panes(5,2)

# ─────────────────────────────────────────────────────────────────
# SHEET 3 — PATIENT ALLERGY SUMMARY
# ─────────────────────────────────────────────────────────────────
ws3 = wb.add_worksheet("Patient Allergy Summary")
ws3.hide_gridlines(2)
ws3.set_column('A:A',2); ws3.set_column('B:B',4); ws3.set_column('C:C',20)
ws3.set_column('D:D',12); ws3.set_column('E:E',7); ws3.set_column('F:F',28)
ws3.set_column('G:G',22); ws3.set_column('H:H',22); ws3.set_column('I:I',2)
ws3.set_row(0,8); ws3.set_row(1,44); ws3.set_row(2,20); ws3.set_row(3,10)

ws3.merge_range('B2:H2',
    "⚠  PATIENT ALLERGY & HIGH-RISK MEDICATION SUMMARY — Check Before Every Administration",
    F(C['red_dark'],fc='#FFFFFF',bold=True,sz=13,align='center',wrap=False))
ws3.merge_range('B3:H3',
    "Update this sheet immediately when any new allergy is identified. Flag in EHR as well.",
    F(C['orange_dark'],fc='#FFFFFF',sz=9,italic=True,align='center',wrap=False))

al_hdrs=[('#',C['red_dark']),('Patient Name',C['red_dark']),('MRN',C['red_dark']),
    ('Bed',C['red_dark']),('Known Allergies / Adverse Reactions',C['red_dark']),
    ('Current High-Risk Medications',C['red_dark']),('Special Precautions',C['red_dark'])]
ws3.set_row(4,30)
for j,(h,hc) in enumerate(al_hdrs):
    ws3.write(4,j+1,h,F(hc,fc='#FFFFFF',bold=True,sz=9,align='center',wrap=True))

allergy_data=[
    (1,"Ahmed Hassan",     "MRN-0001","B-01","NKDA",                       "Metformin","Renal monitoring — eGFR monthly"),
    (2,"Samira Al-Rashid", "MRN-0002","B-02","NKDA",                       "Augmentin","Renal dose adjustment required"),
    (3,"James Owusu",      "MRN-0003","B-03","ACE Inhibitors (dry cough)", "Losartan","Hold if SBP < 90 mmHg"),
    (4,"Priya Sharma",     "MRN-0004","B-04","Codeine (nausea)",           "Morphine (PRN)","Opioid-sensitive — lowest effective dose"),
    (5,"Mohammed Al-Farsi","MRN-0005","B-05","NKDA",                       "Amlodipine","Document ankle oedema daily"),
    (6,"Chen Wei",         "MRN-0006","B-06","NSAIDs (GI bleed)",          "Furosemide IV","Fluid balance — hourly urine output"),
    (7,"Fatima Al-Zahra",  "MRN-0007","B-07","NKDA",                       "Warfarin","INR before each dose — target 2-3"),
    (8,"Robert Mensah",    "MRN-0008","B-08","** CEFTRIAXONE (urticaria)","Ceftriaxone STOPPED","Avoid ALL cephalosporins — EHR flagged"),
    (9,"Nour Abdallah",    "MRN-0009","B-09","NKDA",                       "Enoxaparin SC","Rotate sites — document location"),
    (10,"Leila Nasser",    "MRN-0010","B-10","Sulphonamides",              "Metoprolol","Hold if HR < 55 bpm"),
    (11,"Daniel Osei",     "MRN-0011","B-11","NKDA",                       "Insulin sliding scale","BGL pre/post meals — hypoglycaemia protocol"),
    (12,"Amira Hussain",   "MRN-0012","B-12","NKDA",                       "Prednisolone","Monitor BGL — taper as prescribed"),
    (13,"Emmanuel Asante", "MRN-0013","B-13","NKDA",                       "Digoxin","Apical pulse before dose — hold if HR < 60"),
    (14,"Sofia Karimov",   "MRN-0014","B-14","NKDA",                       "Pantoprazole IV","Give 30 min before first meal"),
    (15,"Kwame Asante",    "MRN-0015","B-15","** VANCOMYCIN (Red Man)",    "Vancomycin (slow infusion)","Pre-medicate antihistamine — infuse over 2 hrs"),
    (16,"Hana Saleh",      "MRN-0016","B-16","NKDA",                       "Atorvastatin","Give at night — monitor LFTs"),
    (17,"Isaac Boateng",   "MRN-0017","B-17","NKDA",                       "Salbutamol nebuliser","SpO2 and peak flow pre/post nebs"),
    (18,"Yasmin Farouk",   "MRN-0018","B-18","NKDA",                       "Enoxaparin BD (treatment)","Anti-Xa level — check 4 hrs post morning dose"),
    (19,"Marcus Silva",    "MRN-0019","B-19","NKDA",                       "Phenytoin","Monitor drug level — narrow therapeutic index"),
    (20,"Zara Ahmed",      "MRN-0020","B-20","NKDA",                       "Dexamethasone IV","Monitor BGL — document oral intake"),
]
for i,row in enumerate(allergy_data):
    r=5+i; ws3.set_row(r,22)
    has_alert = '**' in str(row[4])
    bg=C['red_light'] if has_alert else (C['blue_light'] if i%2==0 else C['white'])
    for j,val in enumerate(row):
        ws3.write(r,j+1,val,F(bg,sz=9,wrap=True,bold=has_alert,
            fc='#C0392B' if (has_alert and j==4) else '#2C3E50'))
ws3.freeze_panes(5,3)

wb.close()
print("Saved:",OUTPUT)

Running Command

python3 /tmp/build_mar20.py && cp /tmp/Medication_Administration_Record_20Patien…

Your Excel file is ready:

Medication Administration Record 20Patients

Spreadsheet · XLSX

What Is Inside the Workbook

The file has 3 sheets, all colour-coded and ready to use.

Sheet 1 — MAR (20 Patients)

The main working sheet. Here is how it is structured:

Column Groups (colour-coded by purpose):

Group	Columns	Colour	Contents
Patient ID	#, Name, MRN, Bed	Blue	Who the patient is
Prescribed Medication	Drug Name, Generic, Dosage, Route, Frequency	Teal	What was ordered
Administration Record	Date, Time Given, Administered By	Medium Blue	When and who gave it
Adverse Reaction Monitoring	Reaction (Yes/No), Details, Action, Doctor Notified	Red	Safety tracking
Notes	Special Instructions	Grey	Clinical reminders

All 20 patients are pre-filled with real medication examples:

Patients 1-3: Metformin, Augmentin, Losartan (oral medications)
Patient 4: Morphine IV - marked "Yes" adverse reaction (nausea/vomiting) with details filled
Patient 7: Warfarin (INR note), Patient 8: Ceftriaxone - marked "Yes" (urticarial rash)
Patients 11-13: Insulin, Prednisolone, Digoxin (high-alert drugs with safety reminders)
Patient 15: Vancomycin - marked "Yes" (Red Man Syndrome) with action recorded
Patients 17-20: Salbutamol neb, Enoxaparin, Phenytoin, Dexamethasone

Built-in features:

Dropdown menu on the "Adverse Reaction?" column (Yes / No / Pending)
Dropdown menu on the "Route" column (IV, IM, SC, PO, INH, etc.)
Conditional formatting - "Yes" rows turn red automatically; "No" rows turn green
Frozen panes - header rows and patient number column stay fixed when scrolling
Shift summary bar at the bottom showing total administrations and reaction count

Sheet 2 — Adverse Reaction Log

A separate dedicated log with one row per reaction event, capturing:

Drug implicated, dose, reaction signs/symptoms
Onset time and severity (Mild / Moderate / Severe / Life-threatening) with dropdown
Management given, doctor notified, and incident form reference number
Pre-filled with the 3 reactions from Sheet 1 as examples
7 blank rows for additional entries

Sheet 3 — Patient Allergy Summary

A one-page allergy and high-risk medication reference for all 20 patients:

Known allergies (NKDA or specific drug reactions)
Current high-risk medications in use
Special precautions (hold parameters, monitoring requirements)
Patients with known reactions highlighted in red (Robert Mensah - cephalosporins, Kwame Asante - vancomycin)

How to Use This Sheet in Practice

Start of shift - check Sheet 3 (Allergy Summary) before beginning any rounds
During medication rounds - fill in Date, Time Given, Administered By in Sheet 1 as you go
After each administration - select "Yes" or "No" in the Adverse Reaction column immediately
If "Yes" - fill in reaction details, action taken, and doctor notified columns, then add a full entry to Sheet 2
End of shift - Charge Nurse reviews the summary row, signs, and saves the file with date/shift in the filename (e.g. MAR_Ward4_12072026_Morning.xlsx)

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