scikiq logo
Marketplace Try for Free


Enhancing Quality of care & Affordability with Secure Healthcare Analytics

SCIKIQ employs a unique data lake & advanced data analytics to create insights into vital areas for improving patient care quality, affordability, and accessibility, while ensuring data privacy

Request For Demo


Navigating Healthcare Data: Privacy, Protection & compliance

The healthcare environments have been dealing with medical records for decades. As healthcare providers becomes increasingly dependent on digital technologies to use and exchange data, the industry has experienced globally known incidents.

The healthcare industry needs to be proactive in its approach to data protection and be mindful of legislative requirements Like HIPAA. It must have total control of assets; continuously assess gaps and processes; leverage best practices and experts from NIST, HITRUST.

The ScikIQ data platform is specifically designed to improve data governance and management by providing actionable insights. By bringing ScikIQ into the operations, institutions can establish internal data security controls, thereby reducing the likelihood of data breaches and enhancing regulatory compliance in no time.

feature-image

Modern Healthcare

The Synergy of Analytics, AI, and Predictive Insights

Data management and governance in healthcare industry is crucial as it’s the most sensitive information amongst any industry and like other management processes, it must have clear regulations on strategic and operational needs. With the significant growth of the healthcare industry and boom in health-related data, potential risks involved in managing data have become a matter of grave concern amongst stakeholders.

  • Safeguarding healthcare data
    Safeguarding healthcare data

    Healthcare data is one of the most valuable assets, and it is important to protect it from unauthorized access, disclosure, and misuse. A robust governance mechanism is vital to mitigate all forms of risks. Our systems and process are designed to level global standards in the healthcare sector and addresses these lapses at precession.

  • Regulation and compliance
    Regulation and compliance

    Healthcare industry one of the primary focus in enforcing regulations like The Health Insurance Portability and Accountability Act (HIPAA), the European Union’s General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), the Health Information Trust Alliance (HITRUST) Common Security Framework and other industry specific global regulations. Our system and process has worked in building required infrastructure that meets these regulations and standards.

  • Visibility and control
    Visibility and control

    Data management professional and data consumers many a time lack visibility into their own data landscape. Which data asset are available, where those assets are located and who has access to the data or whether they should have access to it. These uncertainty limits the further leverage of data impacting productivity and value. Our data fabric platform is based on no code principle for quick integration and customisation as per business needs. ScikIQ has been leveraging the power of data to give direction to business.

Data Analytics Use Cases in Healthcare

Analytics has become an integral part of the entire healthcare industry, speeding up decision making, better aligning valuable resources, and improving the overall patient experience. Below are some use cases of analytics playing a fundamental role in the healthcare industry:

Bed Utilization Forecasting
Hospitals have a difficult time managing the number of available beds across their units. To efficiently manage their bed utilization and forecast demand, hospitals enlist the help of data scientists to both predict future demand of hospital beds and predict when the occupied beds will become available.
Clinical Data Analysis
Analysing clinical data from electronic health records (EHRs) and other sources allows for the identification of trends, patterns, and insights to improve patient care and outcomes, with use cases encompassing predictive analytics for early disease detection, adverse event identification, treatment effectiveness evaluation, population health management, and personalized medicine.
Healthcare Fraud Detection
Applying advanced analytics and machine learning algorithms enables healthcare fraud detection by identifying fraudulent billing patterns, preventing insurance fraud, and protecting healthcare payers and providers from fraudulent activities within the healthcare system.
Inpatient Readmissions
Inpatient readmissions, costly and preventable, pose challenges for healthcare providers. Analysts leverage patient data to build predictive models, identifying at-risk patients for subsequent readmissions. Hospitals employ this insight to design preventive care strategies, reducing readmission rates and improving patient outcomes.
Medical Claims Fraud
Managing medical claims fraud, waste, and abuse poses challenges for hospitals and insurers. Data scientists employ outlier detection and prediction models to analyse claims data, identifying potential fraud areas. Focusing on small clusters of outlier claims at the provider and member level helps auditors pinpoint fraudulent parties effectively.
Bed Utilization Forecasting
Hospitals have a difficult time managing the number of available beds across their units. To efficiently manage their bed utilization and forecast demand, hospitals enlist the help of data scientists to both predict future demand of hospital beds and predict when the occupied beds will become available.
Clinical Data Analysis
Analysing clinical data from electronic health records (EHRs) and other sources allows for the identification of trends, patterns, and insights to improve patient care and outcomes, with use cases encompassing predictive analytics for early disease detection, adverse event identification, treatment effectiveness evaluation, population health management, and personalized medicine.
Healthcare Fraud Detection
Applying advanced analytics and machine learning algorithms enables healthcare fraud detection by identifying fraudulent billing patterns, preventing insurance fraud, and protecting healthcare payers and providers from fraudulent activities within the healthcare system.
Inpatient Readmissions
Inpatient readmissions, costly and preventable, pose challenges for healthcare providers. Analysts leverage patient data to build predictive models, identifying at-risk patients for subsequent readmissions. Hospitals employ this insight to design preventive care strategies, reducing readmission rates and improving patient outcomes.



ScikIQ's data governance system offers healthcare institutions valuable and actionable insights, promoting accelerated growth while ensuring internal security controls to prevent breaches and maintain regulatory compliance. The healthcare industry, with its increasing reliance on digital technologies and data exchange, must be proactive in safeguarding medical records and sensitive information. ScikIQ's platform provides a solution that aligns with global standards, such as HIPAA and GDPR, and enables healthcare providers to gain control over their data assets, identify and address gaps in processes, and leverage best practices and experts in the field.

By implementing ScikIQ's data management and governance system, institutions can protect their most valuable assets, mitigate potential risks, and comply with industry-specific regulations, ultimately leading to improved productivity and value for the benefit of society.

Blog

Healthcare Industry

article
Healthcare

Transforming Healthcare Data through Analytics

In today’s interconnected world where individuals have embraced a unified global identity, lifestyles and environmental changes[…]

Dr.Deepshikha Sharma
July 12, 2023
article
Healthcare

The Importance of Data Protection in Healthcare

The world is currently at a critical juncture where the digital revolution intersects with the fundamental right to privacy. […]

Dr.Deepshikha Sharma
July 6, 2023
article
Supply Chain

The essential pillars of Data Management for the Health Sector

Today Data has the potential to build market leaders out of pure information. It is essential to every business be it the […]

Dr.Deepshikha Sharma
July 4, 2023
Data Integration

Data Integration

The modern solution for multi-cloud & multi-vendor, real-time data integration.
shape
Data Curation

Data Curation

Gain a Competitive Edge with SCIKIQ's AI Driven, Data Profiling, Curation Capabilities.
Data Governance

Data Governance

Industry-leading automated data governance solutions that enable organizations.
Data Visualisation

Data Visualisation

Next-Level BI: SCIKIQ Redefines Reporting and Visualization Standards.
shape