AI-POWERED HOSPITAL OPERATIONS
Intelligent solutions are transforming healthcare, allowing organisations to achieve operational excellence with advanced AI and machine learning through the entire patient flow
Healthcare is in transition, and hospital operations are being taken to another level with advanced AI-driven technologies. By accurately predicting admission rates, surgical emergencies, patient Length-of-Stay and readmission risks, we deliver a powerful tool for hospital planning and operational excellence. Explore Sumo Analytics' ALZA CARE hospital operations platform.
CUTTING EDGE INSIGHTS AND PREDICTIONS
Sumo Analytics' ALZA CARE healthcare operations platform helps hospitals adopt data science and AI technologies to optimise patient flow and hospital resources with advanced predictive models. We work with hospitals to establish cutting-edge analytics environments to foster better decision-making, by turning ever-growing volumes of data into actionable insights. Go to the ALZA CARE site to learn more, here.
Reduced ED boarding, OR optimisation, reduced waiting lists, and general operational excellence
FORECASTING ED VISITS WITH SUPERIOR ACCURACY
ED congestion is a global problem where hospitals have difficulties forecasting the level of visits. Not knowing how many visits are expected can both lead to understaffing scenarios which can cause major crowding and congestion, and overstaffing which leads to a waste of resources.
Since about 70% of patients admitted each day come through the ED, it's critical for hospitals to have accurate forecasts of how many are arriving.
Leverage SUMO Analytics' Automated AI for hospitals to forecast emergency department visits with superior accuracy.
ACCURATELY FORECASTING PATIENT ADMISSIONS
Bed management is only based on the current situation, i.e. the constant monitoring of hospital admissions, discharges and patient flow within a hospital at any given moment. But that doesn’t allow for any planning since the future is always unknown, which causes major organisational challenges within hospitals.
About 18% of all ED visitors are admitted and become inpatients, but accurately knowing how many each and every day is extremely valuable for bed management and general resource planning.
SURGICAL EMERGENCIES
Hospitals and outpatient surgery centres strive to optimise OR utilisation and staff management, but when not knowing how many will require surgery, nursing scheduling and optimised operational planning become merely impossible.
Over 60% of total hospital costs are related to staffing, making the ability to forecast accurately essential for hospitals to plan efficiently and ensure maximum OR utilisation.
Our advanced AI-driven technology forecasts the number of emergency surgeries and accurately predicts the duration of surgical procedures, allowing for optimised planning and organisational excellence.
SURGERY CANCELLATION PREDICTIONS
There’s a common practice that surgeons with block time only use a portion of the block time they’ve been allocated. And when block time is released back to the OR, it’s often at the last minute, which forces OR management to scramble to fill the time with any available case.
Sumo Analytics' advanced AI-powered prediction technology predicts weeks in advance with unprecedented accuracy which elective surgeries are likely to be cancelled, automatically confirming block time usage.
With Sumo Analytics’ superior AI-driven perioperative solution, hospitals will optimise OR access, grow case volume, and significantly reduce waiting lists.
PATIENT LENGTH-OF-STAY PREDICTIONS
Patient Length of Stay (LOS) is considered one of the most critical monitoring and performance indicators in hospitals.
Difficulties with predicting LOS lead to the consumption of hospital resources, manpower, and equipment. Predicting LOS, especially in ICUs, is beneficial from different aspects in terms of the hospital organisational efficiency and planning, the patient's medical plan and family, and insurance companies.
With SUMO Analytics' advanced AI-driven LOS models, hospitals have all patients' LOS times updated hourly for effective patient management.
READMISSION RISK PREDICTIONS
Unplanned readmission after discharge is an important measure of a hospital’s service and quality levels, as it often indicates problems with patient care during the hospitalisation, and is a key indicator of the effectiveness of a patient's treatment plan.
Readmissions can be dramatically decreased, if additional attention is on patients with high readmission risk and with preventive measures taken.
Early prediction of hospital readmissions risks with SUMO Analytics' advanced AI models significantly improve operational planning, reduce unnecessary cost, and improve patient experience.
As hospitals strive to increase operational efficiency and remove bottlenecks in patient flow, data-driven technologies are playing an important supporting role.
BLOOD DEMAND FORECASTING
Preventing blood shortages by accurately forecasting blood demand
Our AI-driven approach takes multiple variables into account and forecasts short- and long-term blood demand with superior accuracy, allowing blood banks to proactively prevent blood shortages of different blood types.
We pioneer innovation and development in forecast technology and lead the field when it comes to forecast accuracy across industries.
Learn more about our AI-powered forecast technologies here HERE