AI for Hospital Operations

Bed Occupancy Prediction

import numpy as np

class BedOccupancyPredictor:
    def predict_occupancy(self, current, admissions_rate, discharge_rate, days=7):
        predictions = []
        occ = current
        for day in range(days):
            predicted_admissions = admissions_rate * (1 + 0.1 * np.sin(2 * np.pi * day / 7))
            occ = occ + predicted_admissions - discharge_rate
            predictions.append(max(0, occ))
        return predictions

Patient Flow Optimization

Queueing Theory

class PatientFlowSimulator:
    def optimize_staffing(self, n_staff, target_wait=30):
        best = None
        min_wait = float('inf')
        for alloc in self._generate_allocations(n_staff):
            avg_wait = self._simulate(alloc)
            if avg_wait < min_wait and avg_wait < target_wait:
                min_wait = avg_wait
                best = alloc
        return best

Staff Scheduling

Constraint Satisfaction