.hospital-occupancy-calculator-container {
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Helvetica, Arial, sans-serif;
max-width: 800px;
margin: 0 auto;
padding: 20px;
background: #f9fbfd;
border: 1px solid #e1e4e8;
border-radius: 8px;
color: #2c3e50;
}
.hoc-header {
text-align: center;
margin-bottom: 30px;
}
.hoc-header h2 {
color: #0056b3;
margin-bottom: 10px;
}
.hoc-grid {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 20px;
}
@media (max-width: 600px) {
.hoc-grid {
grid-template-columns: 1fr;
}
}
.hoc-input-group {
margin-bottom: 15px;
}
.hoc-input-group label {
display: block;
margin-bottom: 5px;
font-weight: 600;
font-size: 0.9em;
color: #4a5568;
}
.hoc-input-group input {
width: 100%;
padding: 10px;
border: 1px solid #cbd5e0;
border-radius: 4px;
font-size: 1em;
box-sizing: border-box;
}
.hoc-input-group input:focus {
border-color: #0056b3;
outline: none;
box-shadow: 0 0 0 3px rgba(0, 86, 179, 0.1);
}
.hoc-btn {
background-color: #0056b3;
color: white;
border: none;
padding: 12px 20px;
font-size: 1em;
font-weight: bold;
border-radius: 4px;
cursor: pointer;
width: 100%;
margin-top: 10px;
transition: background-color 0.2s;
}
.hoc-btn:hover {
background-color: #004494;
}
.hoc-results {
background: white;
padding: 20px;
border-radius: 6px;
box-shadow: 0 2px 4px rgba(0,0,0,0.05);
margin-top: 20px;
display: none;
border-left: 5px solid #0056b3;
}
.hoc-result-item {
margin-bottom: 15px;
padding-bottom: 15px;
border-bottom: 1px solid #edf2f7;
}
.hoc-result-item:last-child {
border-bottom: none;
margin-bottom: 0;
padding-bottom: 0;
}
.hoc-result-label {
font-size: 0.9em;
color: #718096;
margin-bottom: 5px;
}
.hoc-result-value {
font-size: 1.5em;
font-weight: bold;
color: #2d3748;
}
.hoc-badge {
display: inline-block;
padding: 4px 8px;
border-radius: 4px;
font-size: 0.8em;
font-weight: bold;
margin-left: 10px;
vertical-align: middle;
}
.status-low { background-color: #fed7d7; color: #c53030; }
.status-optimal { background-color: #c6f6d5; color: #2f855a; }
.status-high { background-color: #feebc8; color: #c05621; }
.status-critical { background-color: #fc8181; color: #742a2a; }
.hoc-article {
margin-top: 40px;
line-height: 1.6;
color: #333;
}
.hoc-article h3 {
color: #0056b3;
margin-top: 25px;
}
.hoc-article ul {
padding-left: 20px;
}
.hoc-article li {
margin-bottom: 8px;
}
.formula-box {
background: #f0f4f8;
padding: 15px;
border-left: 4px solid #4a5568;
margin: 15px 0;
font-family: monospace;
}
function calculateOccupancy() {
// Get input values
var serviceDaysInput = document.getElementById('serviceDays');
var bedCountInput = document.getElementById('bedCount');
var periodDaysInput = document.getElementById('periodDays');
var resultsDiv = document.getElementById('resultsDisplay');
var serviceDays = parseFloat(serviceDaysInput.value);
var bedCount = parseFloat(bedCountInput.value);
var periodDays = parseFloat(periodDaysInput.value);
// Validation
if (isNaN(serviceDays) || isNaN(bedCount) || isNaN(periodDays)) {
alert("Please enter valid numbers for all fields.");
return;
}
if (bedCount <= 0 || periodDays <= 0) {
alert("Bed count and period days must be greater than zero.");
return;
}
if (serviceDays < 0) {
alert("Service days cannot be negative.");
return;
}
// Calculations
var potentialBedDays = bedCount * periodDays;
// Safety check: Service days shouldn't typically exceed potential bed days significantly,
// but we allow it for edge cases (surge capacity/overcrowding) but warn if illogical.
// No strict block, just calculation.
var occupancyRate = (serviceDays / potentialBedDays) * 100;
var averageDailyCensus = serviceDays / periodDays;
// Update UI
document.getElementById('occupancyRateResult').innerText = occupancyRate.toFixed(2) + "%";
document.getElementById('adcResult').innerText = averageDailyCensus.toFixed(1);
document.getElementById('capacityResult').innerText = potentialBedDays.toLocaleString();
// Status Logic
var statusSpan = document.getElementById('occupancyStatus');
statusSpan.className = 'hoc-badge'; // Reset classes
if (occupancyRate = 75 && occupancyRate 85 && occupancyRate 100%
statusSpan.classList.add('status-critical');
}
// Show results
resultsDiv.style.display = "block";
}
Hospital Occupancy Rate Calculator
Calculate the efficiency of bed utilization and inpatient capacity.
Sum of days all patients occupied beds in the period.
Number of staffed and available beds.
Use 1 for daily census, 30 for monthly, 365 for yearly.
Occupancy Rate
0%
Average Daily Census (ADC)
0
Average patients per day
Potential Bed Days (Capacity)
0
Maximum bed days available in period
How to Calculate Occupancy Rate in a Hospital
The hospital occupancy rate is a critical key performance indicator (KPI) for healthcare administrators. It measures the percentage of available beds that are occupied by patients over a specific period. This metric helps determine if a facility is underutilized, operating efficiently, or facing overcrowding issues that could impact patient safety.
The Formula
To calculate the occupancy rate, you need three pieces of data: the total inpatient service days, the total number of beds available, and the number of days in the reporting period.
Occupancy Rate (%) = (Total Inpatient Service Days ÷ (Total Bed Count × Days in Period)) × 100
Variables Defined:
- Inpatient Service Days: The cumulative sum of days that all patients have occupied a bed during the period. Also known as "Census Days."
- Total Bed Count: The number of staffed beds available for inpatient use.
- Days in Period: The timeframe for the calculation (e.g., 30 days for a month, 91 days for a quarter).
Step-by-Step Example
Let's assume a hospital has 100 beds and wants to calculate the occupancy rate for the month of September (30 days).
- Calculate Capacity: Multiply the bed count by the days in the period.
100 beds × 30 days = 3,000 Potential Bed Days. - Determine Usage: The records show a total of 2,400 Inpatient Service Days for the month.
- Apply Formula: Divide usage by capacity.
2,400 ÷ 3,000 = 0.80. - Convert to Percentage: Multiply by 100.
0.80 × 100 = 80% Occupancy Rate.
Interpreting the Results
Understanding the percentage is vital for operational planning:
- Under 75%: Indicates underutilization. The hospital may have excess staffing costs or unused resources relative to patient demand.
- 75% – 85%: Often considered the optimal range. It ensures resources are used efficiently while leaving enough surge capacity for emergencies.
- Over 85%: Signals potential congestion. High occupancy can lead to increased wait times, bed blockages in the ER, and staff burnout.
Average Daily Census (ADC)
This calculator also provides the Average Daily Census, which is calculated by dividing the Total Inpatient Service Days by the number of days in the period. This tells you the average number of inpatients present in the hospital on any given day.