Patient Flow Analytics

Historical flow trends · LOS analysis · AI model performance · Ward throughput

Total Admissions (14d)

487

+32vs prior 14 days

Total Discharges (14d)

461

-26admissions exceed discharges

Mean LOS (14d)

4.8days

+0.6dvs NHS 4.2d benchmark

Delayed Discharges (14d)

+18vs prior period

Daily Admissions vs Discharges

14-day trend — net bed pressure visible where admissions exceed discharges

AdmissionsDischarges

Average length of stay vs NHS 4.2-day benchmark

14-day period — 487 total admissions

XGBoost model v2.4.1 — daily prediction accuracy vs actual discharges

14d avg: 87.3%

14-day period — admissions, discharges, LOS vs benchmark, bottleneck count

Ward	Specialty	Capacity	Admissions (14d)	Discharges (14d)	Mean LOS	Benchmark	Delayed D/C	Occupancy	Bottlenecks
Geriatrics	Elderly Care	30	41	35+6	9.4d	8d	19	100%	3
AMU	Acute Medicine	48	134	122+12	4.8d	4.2d	18	97%	3
Respiratory	Respiratory Medicine	24	58	53+5	5.6d	4.9d	11	96%	2
Cardiology	Cardiology	32	71	68+3	5.1d	4.8d	9	94%	2
ITU	Intensive Care	16	28	26+2	8.3d	7.5d	4	88%	1
Surgical	General Surgery	36	62	60+2	3.8d	4d	6	85%	1
Orthopaedics	Orthopaedics	28	44	47	7.2d	6.5d	7	82%	1
Neurology	Neurology	20	32	33	6.1d	5.8d	5	78%	—
Paed's	Paediatrics	18	17	17	2.9d	3.2d	2	72%	—

Total capacity: 252Total admissions: 487Total discharges: 461Total delayed D/C: 81