Healthcare Sector
Healthcare industry is traditionally data-intensive and data-driven industries. As much as 30% of the entire world's stored data is generated in the healthcare industry. The need for accurate and reliable operational benchmarks has never been greater. Hospital executives, medical officers, and management teams are under constant pressure to balance operational efficiency with increased financial profitability and continued efforts to improve patient care quality. Action-driving insights that can help you better position your organization to assess and manage risk, utilization and quality performance can be achieved with implementing machine learning techniques for data analytics.
Health organizations need to constantly anticipate the future to gain a competitive advantage. AI allows businesses to provide better forecasts for their supply chain, expected products or services demand and therefore design better offerings. Reliably forecasting demand is a way to use AI's ability to digest disparate data and automatically adjust to new information in near real-time. It can discern trends and patterns that can be acted on resulting in an increase in patient access (accommodation of more patients, sooner) and revenue.
Our AI predictive analytics products help you to:
Forecasting demand for the specific quantities of specific medical services at specific locations
Forecasting stock size for the specific medical products at specific locations to minimize waste, reduce storage costs and ensure always-in-stock for all vital components
Develop new strategies for growth (including prediction of future profitability or forecast demand for your services), client service and cost reduction
Define patient profiles, potential markets, service locations
Implement predictive maintenance for utilized medical equipment based on deterioration and failure forecasts
Monitor competitive activity and capitalize on existing and potential customers
Optimize pricing and tailor website displays in real-time
Discover insights from all relevant past and current performance data with objective, fact-based information to make well-informed decisions through gathering, processing and analyzing data in real-time as it flows through the enterprise. At the moment, clinicians spend about half of their time on administration, data entry, and documentation and only 33 percent of the day face-to-face with patients. Analyzing all aspects of care delivery also allows to evolve from volume- to value-based care and thrive in the pay-for-performance environment.
Our AI prescriptive analytics products help you to:
Improve planning, execution, and assessment of key health business processes, including resource management, staff schedules, assets utilization and services gaps identification
Identify your most, and least, costly and profitable services, boost utilization of your most efficient departments
Reduce lost sales due to medical service unavailability
Adapt therapies and drug formulations to patients
Enhance and automate medical services quality assurance programs to maintain the highest standards of medical care
Improve point-of-care decision-making with evidence-based clinical decision support system, including advices on prescriptive decisions and treatment plans, based on organization standards and practices
Many diagnostic tests require manual inputs and analysis, making them time consuming, expensive and leaving room for human error. Embedding AI into diagnostics removes opportunities for human error and saves clinical labs time and money.
Our AI comparative and descriptive analytics products help you to:
Implement predictive maintenance for laboratory equipment based on deterioration and failure forecasts
Automate diagnostic tests and make them faster and more accurate
Forecast stock size for specific laboratory consumables at specific locations to minimize waste and reduce storage costs
Perform laboratory diagnostic quality checks utilizing statistical methods and automated anomalies detection
About 5 percent of adult patients are misdiagnosed each year in the US. The postmortem examination results research shows that diagnostic errors cause approximately 10 percent of patient deaths. It is well known that radiologists differ not only from one another in image interpretations, even the very same examiner may come to different conclusions when a reading is repeated. If only images that actually show pathological changes are considered in the error analysis, the error rate rises as high as around 30%, meaning that in three out of 10 cases pathological structures are either incorrectly interpreted or simply overlooked (false negative findings).
AI raises analysis and interpretation of digital medical images to a whole new level compared with the older algorithms. Combined with AI prescriptive analytics capabilities it leads to significant performance enhancement for healthcare assurance practices.
Our AI descriptive analytics products help you to:
Automate and enhance existing products/services quality assurance programs
Automate digital medical images analysis
Automate delivery of the second opinion for doctors at any location
Facilitate standardization: care variability reduction efforts and, therefore, costs
About 50% of the population by 2020 is anticipated to have 1-2 chronic diseases. Models predicting chronic disease progression are used for disease management and planning. Such models predict the trajectory of a patient's condition to help clinicians decide whether and when to proceed to the next stage in their medical care. Predictive models also notify clinicians about patients who may require interventions to reduce the risk of negative outcomes. These predictions, along with the key factors driving the prediction, are presented to clinicians who can decide if certain interventions might help reduce the patient's risk.
Our AI descriptive and predictive analytics products help you to:
Identify anomalies and deviations in near real-time mode
Provide risk-assessment of disease progression based on electronic health records, diagnosis results, personal social and behaviors factors
Predict trajectory of chronic patients' conditions over time
Care personalization through artificial intelligence insights paves the way for quantitative, personalized diagnostics tailored to the person's health needs, including best patient-specific intervention approaches. Custom-tailored algorithms increase diagnostic accuracy, identify at-risk patients, improve patient monitoring efficiency. AI allows incorporating both clinical and nonclinical information into your analyses to identify patient preferences and specifics. The promise of personalized medicine is a world in which everyone's health recommendations and disease treatments are tailored based on their medical history, genetic lineage, past conditions, diet, stress levels, and more.
Our AI descriptive and predictive analytics products help you to:
Predict patient trajectory over time and discharge to facilitate preventive care delivery
Launch prevention therapies
Focus on patients' risk reduction
Provide wellness monitoring in addition to treatment, enabling proactive care options and preventive health care (50%+ of smartphone owners are estimated to download health apps by 2018)
Any modern laboratory and medical equipment contain a network of sensors, providing a stream Big Data of measurements. Understanding sensors data under different conditions, detecting anomalies and forecasts of the system's behavior are keys for predictive repair and maintenance which delivers early warnings of failure or required maintenance efforts.
Our AI predictive analytics products help you to:
Create a knowledge database of sensors data, assets conditions and repair cases for the utilized equipment
Implement predictive maintenance for utilized medical and laboratory equipment based on equipment deterioration and failure forecasts at certain time and locations
Gauge reliability of integrated assets
Facilitate patient engagement includes a broad range of tasks, from clients profiling and identification of high-risk patients who need care management to patient outreach and online patient communications that enable patients to become full partners in their own care. An artificial intelligence system is capable to study the results of previous communication efforts with similar clients and identifying the most effective approach and content for each patient. Patients who understand their conditions, medications, and treatment are more likely to seek out care when needed, participate in it more fully and be more satisfied with their healthcare experience.
Our AI descriptive analytics products help you to:
Improve the efficacy of automated outreach clients, personalize them, taking into account each person's preferences, and how and when that person prefers to receive what information
Optimize personalized promotions
Provide services for self-check of some conditions including computer vision-based apps
Clinical studies help in connecting research and patient care by evaluating therapies, drugs and diagnostic tools to drive discoveries into clinical practice.
Our team can reinforce your in-house team with AI capabilities as well as provide expertise, technologies, and support for R&D activities
Android Application Field Test in Tanzania
Meeting with Chief Veterinary Officer in FAO Headquarters in Italy in 2015
Epidemiology Surveillance System Implementation in RF in 2016
Meeting with Head of Division of Information in WHO Regional Office for Europe in Copenhagen in 2012
Participating SACID One Health Forum in Johannesburg in 2012
Delegations from DTRA and CDC Inspect Implementation in Kazakhstan in 2012
