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Introducing
Data Kinetic's
Healthcare Suite

A unique approach in solving practical healthcare workflow situations leveraging Applied AI

Private, secure, Applied AI models to support Healthcare workflows.

Today's healthcare providers face challenges such as managing patient volume, predicting equipment failure, and optimizing resource allocation. Applied AI can support medical practitioners by enhancing decision-making, improving efficiency, and enabling proactive interventions. For payers, AI aligns with goals and outcomes by enabling customized risk assessments, optimizing policy recommendations, and improving portfolio management.

In today's digital age, the need for secure solutions that leverage modern models without sending data to public APIs or cloud services is paramount. Healthcare organizations require systems that can harness the power of advanced AI and machine learning while ensuring data privacy and security. This approach enables businesses to benefit from cutting-edge technologies without exposing sensitive information to external environments, thus maintaining control over their data and complying with regulatory requirements.

Together, these AI-driven solutions contribute to greater patient outcomes by ensuring better healthcare delivery, reducing costs, and enhancing operational efficiency.

Private Fine Tuned LLMs Private fine-tuned LLMs are ideal for healthcare as they offer tailored, secure, and efficient AI solutions while ensuring patient data privacy and compliance. No Data Leakage Air-gapped secure models with zero data leakage are ideal for sensitive environments, ensuring complete data privacy and security without any external connectivity. Traceable Model Outcomes

Model traceability and auditing are crucial for maintaining transparency, accountability, and regulatory compliance in AI systems, especially in sensitive sectors like healthcare.

 Build on your existing data platform

Building on your existing data platform allows for seamless integration of AI capabilities, leveraging established infrastructure and data assets for enhanced analytics and decision-making.

 Predictable Outcomes Model traceability and auditing are crucial for maintaining transparency, accountability, and regulatory compliance in AI systems, especially in sensitive sectors like healthcare.
CMS Fraud Detection

DETECT OUTLIERS FASTER, BEFORE PAYMENT, REDUCING COSTS

Healthcare fraud, is responsible for driving up costs and disadvantaging patients that need care. 

Such fraud undermines the integrity of the system. Data Kinetic leverages connected graphs and large data analysis to detect such fraudulent behaviors, aiding government entities and insurance companies in mitigating financial losses and reducing healthcare costs.

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Social Determinants of Health

DELIVER EQUITABLE OUTCOMES LOCALIZED TO INDIVIDUAL NEEDS OF YOUR COMMUNITY

Data Kinetic builds social determinants of health data from sources like the AHRQ and US Census Bureau to support organizations in understanding the impact of demographics on health outcomes customized to their specific needs.

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Hospital Patient Volume Forecasting

MORE ACCURATELY PREDICT DEPARTMENT WORKLOADS AND REDUCE BURN OUT

The model focuses on predicting patient counts at multiple facilities across departments like Medical Surgery, Psychiatry, and ICU, using 24 models for each combination. Leveraging real time trends data and data aggregation methodologies, it utilizes real-time trends to forecast facility demand requirements.

This approach helps reduce staff burnout, ensures adequate coverage, and supports patient needs by enabling proactive resource allocation and informed decision-making.

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Hospital Length of Stay Prediction and Staffing Optimization

COMBINE MULTIPLE FACTORS TO ACCURATELY MANAGE RESOURCES

Accurate prediction of hospital stay length is crucial for effective patient care, resource optimization, and cost reduction in healthcare.

Data Kinetic's predictive model that integrates diverse data sources and employs advanced analytics is imperative for enhancing hospital efficiency and patient outcomes, as inaccurate predictions can lead to resource misallocation, suboptimal care, and increased operational expenses.

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Detecting Adverse Drug Impacts from Social Media Conversations

MONITOR FOR NEAR REAL TIME TRENDS AND INSIGHTS

Effective monitoring of adverse drug reactions (ADRs) is crucial for patient safety, especially as new side effects may emerge in diverse populations post-clinical trials.

Biopharmaceutical manufacturers must report ADRs to regulatory agencies like the FDA and EMA. However, less than 5% of ADRs are reported through official channels, with the majority captured in free-text formats like emails, social media, and patient forums.

Robust drug safety monitoring requires analyzing unstructured medical text from various sources, necessitating a modern, scalable data and AI application for near real-time insights.

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Data Kinetic Healthcare Suite
Medical Supply Chain

OPTIMIZE SUPPLIES AND ASSOCIATED COSTS

The medical supply chain is critical for ensuring the availability and distribution of healthcare products. It involves the coordination of manufacturing, procurement, storage, and delivery of medical supplies to healthcare facilities. Efficient management of the medical supply chain is essential for timely access to medical products, maintaining quality standards, and controlling costs. Challenges include demand forecasting, inventory management, and ensuring the integrity of products during transportation.

Data Kinetic focuses building unique models that optimize the medical supply chain and enhance its resilience against disruptions.

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Data Kinetic Blog

What we have to say

See our latest thinking and experiences delivering Applied AI to some of most complex use cases.
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