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Overcoming the Biggest Challenges of Life Sciences
Costly Care Provision
Ineffective Patient Coordination
Poor Data Management
Low Drug Quality
Enhancing Patient Engagement and Improving Clinical Operations for Greater Scientific Innovation
- Enhance Patient Engagement
- Improve Clinical and Operational Outcomes
- Accelerate Scientific Innovation
Smart Personalized Care
An AI-driven approach that can quickly assess the symptoms and risk factors for people worried about infection, provide information and suggest the next course of action such as contacting a medical provider or, for those who do not need in-person medical care, managing the illness safely at home.
Reducing emergency response time
Streamlining clinical workflows improves patient outcomes and satisfaction and enables providers to make informed decisions quickly based on real-time patient data
Reducing the high cost of providing better care
Enabling care providers to deliver better care and enhance patient engagement while reducing costs
AI-Driven Personalized Care Solution
Automate patient data collection and generate real-time insights to provide more personalized care, automate administrative tasks like appointment scheduling, payments, and insurance claims processing.
Smart Personalized Care Trends
97% of all patients expect any healthcare institution to have full access to their medical history.
80% of consumers are willing to wear smart watches that measure health data.
50% of patients in the United States utilized virtual appointments in recent years.
77% of consumers book medical appointments online.
$27M is the expected growth in the wearable medical device market by 2023.
- Claims Management & Automation
- Predictive Care Guidance
- Supply Chain & Logistics Optimization
- Clinical Analytics
- Operational Analytics
Claims Management & Automation
Making healthcare paperless through AI-based automation for improved data management and decision making.
Intelligent healthcare systems enable efficient handling of large volumes of documents, provide real-time data access for analysis and insights, and automate data extraction, reducing manual labor costs and improving data accuracy. These solutions also streamline claim processing, help organizations identify areas for improvement, and make informed decisions.
Transform large volumes of records into actionable data, digitize unstruectured documents, including handwritings, and go beyond OCR to classify type of documents, such as claims, insurance, invoices, contracts, and extract field names, and values.
Claims Management & Automation Trends
$6B is the yearly loss to data breaches amid growing pressures in security and compliance.
12 seconds is the time it takes for an RPA solution to check claim statuses (compared to 85 seconds it takes a human).
$68B fraud costs the nation’s healthcare payers annually.
$17B are the estimated savings per year by eliminating errors in claims.
$260B is the cost of claims denials annually for hospitals due to the complexity of claims management processes.
Predictive Care Guidance
Identifying and facilitating preventative diagnosis through AI to detect vulnerable individuals.
Predictive Care Guidance offers early disease detection, personalized care, and remote monitoring for patients, leading to improved population health management and reduced public health system burdens.
By identifying high-risk populations and targeting resources, it ensures safety in densely populated regions without compromising patient privacy. This approach results in improved patient outcomes, particularly in areas that are susceptible to diseases and viruses.
Predictive Care Guidance
Leverage predictive analytics to anticipate potential health risks and suggest preventative steps accordingly. Utilize machine learning models to analyze medical images faster and accurately detect diseases resulting in improved patient outcomes and reduced costs.
Predictive Care Guidance Trends
By 2026, the size of the telehealth market is expected to surpass $187B.
Medical virtual reality will be worth $5B by 2025.
44% of all medicare primary care visits utilized telehealth rather than in-person visits.
47% of all healthcare organizations are already using patient data predictive analytics.
By the end of 2023, the projected global healthcare chatbots market will surpass $317M.
Supply Chain & Logistics Optimization
Delivering intelligent supply chain to predict market demands, sense changes in supply, and demand. Smart connected supply chain to launch a range of highly personalized add-on services, and gaining insights about market needs based on trends, signals, and behavior patterns. Drive new growth with modern data estate, analytics, and AI by delivering exceptional customer experiences.
Improved order fulfillment and promising
Enhanced logistics (tracking & traceability)
Efficient material sourcing and logistics
Sustainable load optimization
Improved product and service delivery
Reduced transportation costs
Better supply chain visibility
AI/ML-based Inventory Management
Boost business resilience by quickly responding to disruptions and intelligently selecting alternatives for supply shortages.
Intelligent & Connected Demand Planning
Respond to changing market demand with machine learning, connected processes, and increased visibility across sales and operations planning (S&OP), forecasting, supply, replenishment, and inventory functions.
Real-time Orders and Shipments Tracking
Optimize logistics processes with visibility into goods in transit, notify stakeholders about deviations, and monitor fulfillment.
Supply Chain & Logistics Optimization Trends
The global O&G logistics market is expected to reach $14.6 billion by 2025 at a CAGR of 8.8%.
IoT, AI, and big data analytics can bring down logistical costs by up to 15%.
Optimizing supply chain and logistics processes can improve operational efficiency by up to 25%.
82% of oil and gas companies have increased their focus on supply chain resilience after the pandemic.
Identifying and facilitating preventative diagnosis through AI-based insights to detect vulnerable individuals and recommend treatment plans for better care provision.
Proactive intervention to prevent hospitalization
Patient’s historical medical data to understand which treatments work for different persons
Prescriptive & predictive guidance that helps clinical teams provide better care
AI-based Clinical Analytics for Better Care Provision
Leverage historical patient data to recommend the best treatment plan and reduce the need for patient hospitalization by detecting diseases resulting in improved patient outcomes and reduced costs.
Clinical Analytics Trends
The global healthcare analytics market is expected to reach $84.2 billion by 2027, growing at a CAGR of 23.4%.
In a recent survey, 62% of respondents said their organizations plan to invest more in clinical analytics over the next few years.
For the past few years, the US has accounted for the largest share of the global healthcare analytics market, with a market size of $16.2 billion.
60% of healthcare organizations have started using predictive analytics to improve patient health outcomes to speed up trials.
Intelligent operational analytics help to enable more efficient use of resources by prioritizing care based on need, optimizing the use of expensive resources, improving access for patients and cutting wait times, all while increasing overall profitability.
Improve operational effectiveness and reduce costs
Predict disease surges and patient acuity, and leverage various care settings to ensure all patients are cared for
Empower clinicians to share information and analyze structured and unstructured data for accurate insights
Using data and analytics to improve the efficiency of systems and manage care processes
ML-based Operational Insights for Clinics
Utilizing machine learning to streamline clinic operations for predictive diagnosis, improved care settings, and structuring data for actionable insights that ramp our profitability and reduce operational costs.
Operational Analytics Trends
The global market for healthcare operational analytics is projected to reach USD 4.6 billion in a couple of years.
The adoption of data visualization and operational analytics in healthcare is expected to grow at a CAGR of 9.9% from 2020 to 2027, reaching USD 2.1 billion by 2027.
The adoption of cloud-based healthcare analytics solutions is expected to reach $68 billion by 2026, growing at a CAGR of 27.3%.
The use of AI in healthcare analytics is expected to grow rapidly, with the market size projected to reach USD 68.5 billion by 2028.
Leverage data from clinical trials to predict expected response to treatment plan for a cohort and correlate with field data to track accuracy.
Drug Discovery enables improved outcomes through new and more effective drugs and treatments while also reducing variation in care and generating revenue for pharmaceutical companies. This drives innovation in the life sciences industry, improves public health, and contributes to overall profitability.
Real-time Insights from Patient Data for Better Decision-making
Leverage predictive analytics to identify potential therapeutic targets and screen candidate molecules for further study. Utilize machine learning models to analyze existing medical data and improve understanding of disease mechanisms. Automate experimental processes such as laboratory research, clinical trials, and product testing. By leveraging these technologies, healthcare providers can speed up the drug development process while reducing costs.
Drug Discovery Trends
$2.6B is the cost that life sciences companies bear to introduce a single new prescription drug.
Over 2 billion people worldwide will be 60 or older by 2050.