Transformative data experience for healthcare delivery

A comprehensive analysis platform for healthcare analytics and data management. Deliver value-based care by enabling frontline physicians to instantly interact with data. for healthcare

Answer an infinite number of healthcare questions places the power of data science on the hands of physicians who have in-depth domain knowledge. With you can directly ask your data a series of questions until you land on actionable insights. healthcare analysis platform healthcare analysis platform

Make healthcare data & data science approachable

Manage and analyze healthcare data from a single platform. Perform statistical analysis and data science without coding.

Research Medical Centers

Accelerate biomedical research in your institution. Build data products that your physicians and analysts can rapidly access to analyze biomedicine data.

Use case examples:

  • Integrate biobanks and genomic data with EHR to improve overall patient outcomes
  • Build an oncology patient registry to follow the patients’ progress into clinical trials
  • Quickly deploy de-identified data products from sensitive source data research medical center

Clinical Decision Support

Enabling both healthcare providers and analysts to perform data science. Making healthcare analytics approachable to clinicians enables them to identify opportunities that might otherwise get overlooked.

Use case examples:

  • Identify opportunities where hospitalizations can be avoided
  • Compare length of stay outliers to non-outliers
  • Identify the usage frequency of off-label drugs by analyzing ICD 10 codes clinical decision support

Finance & Payers

Understand the financial side of value-based care. Integrate your financial and clinical data to get a comprehensive view of your healthcare delivery.

Use case examples:

  • Run exploratory analysis to identify direct total cost savings relating to a medical procedure
  • Identify cost per case of geriatric hospitalization as compared to a transfer case
  • Drive down costs associated with short stay admissions by identifying alternative clinical plan healthcare finance and payers

Healthcare Data Management

The healthcare industry has masses of data from disparate sources. With the analysis platform, you can turn siloed healthcare data into harmonized, analyzable data products. Save time and resources by making your data products actionable and reusable.

Use case examples:

  • Manage multiple patient registries related to lung cancer and follow the patients’ progress through clinical trials
  • Group different data products into categories for quick data discovery
  • Assign and manage user, group, or departmental access to different data products healthcare data management

Machine Learning & AI

Use a single platform to access cleaned, harmonized data products for your ML/AI initiatives.

  • AWS, Azure & Google Cloud
  • R, Python SDK, JupyterHub/JupyterLab Notebook & plugins
  • Integrated AutoML, SageMaker, Azure ML and Google AI services
  • Supports TensorFlow, PyTorch, mxnet, Keras, GLUON, SciML & DeepGraphLibrary healthcare machine learning and ai for research medical centers for clinical decision support for healthcare finance and payers for healthcare data management for healthcare machine learning and ai

Explore healthcare resources healthcare analysis platform ebook

Finding Value Faster In Healthcare Data

A practical guide to help you resolve healthcare data challenges using the data mesh approach. for research medical center webinar

A Clinical Data Mesh for Quality Improvement and Research in Healthcare

In this Campus LISA webinar, you will learn how you can utilize data mesh for healthcare. Panelists include: Mike Hogarth, Mark Mooney, and Tom Covington.

Enabling Doctors To Provide Instant Answers

“Having on demand information completely changes the culture. I can’t imagine doing my job without the platform.”

Get A Demo

See how works within your clinical workflow.

Redefine How Data Science Advances Healthcare

Use no-code analysis apps, embedded within your data products, to perform a wide range of analysis — from a simple statistical analysis to a complex machine learning algorithm.

Statistics currently available:
  • Hypergeometric test for categorical data and sets
  • Student’s T and Mann-Whitney U tests for numeric distributions
  • Univariate and Multivariate Linear Regression for numeric relationships
  • Paired analysis for repeated (longitudinal) measures
  • Matched analysis for control of confounding variables
  • Cox regression for survival analysis
  • K Means and DBSCAN clustering for segmentation
  • PCA, t-SNE and UMAP for projection/embedding
  • Fast event sequence queries
  • Pathway (systems) analysis via Hypergeometric test and GSEA
  • Gene signature analysis via ssGSEA
  • Chi-square test for categorical data
  • Logistic Regression and Random Forest (also many other options) for prediction/classification
  • Pearson/Spearman correlation for numeric distributions
Examples of data types:
  • Patient registries
  • Claims
  • Clinical trials
  • Medical tests
  • Administrative
Examples of data sources:
  • Epic/Clarity EMR
  • EPSi
  • OMOP (Observational Medical Outcomes Partnership)
  • Cerner
  • REDCap
  • FHIR
  • Patient registries
  • Any form of tabular data (CSV/TSV)
  • Relational Databases and Apache Spark (SQL)
  • Data Warehouses
  • Data Lakes

Data Product Examples analysis app - umap and clustering
Patient Encounters

This data product contains data on patient encounters and costs for 80,000 patients at 8 hospitals compared to standard Medicare costing. analysis app - umap and clustering
COVID-19 Synthetic Data

This data product contains synthetic patient data mimicking a population tested for COVID-19.

Analysis App Examples

Cox Survival

Perform a cox regression survival analysis for the specified cohort.


Download a subset of data.

Analysis Result Examples analysis - cox survival, analysis - survival analysis

Cox Survival analysis - r integration

Summary analysis - cohort comparison

Cohort Comparison analysis - umap and clustering

UMAP & Clustering analysis - pathway analysis

Download Subsets of Data analysis - python integration

R & Python Integration

“We are using to explore, confirm and evaluate care delivery using a variety of clinical, financial and operations data, including claims data generically.”

– Ralph Gonzales, MD, MSPH,
Associate Dean for Clinical Innovation, Chief Innovation Officer Internist
@ UCSF Department of Medicine

One platform. Multiple uses.

The flexibility and adaptability of’s platform can help you significantly advance the field of clinical research. for population health

Population Health

Bring healthcare informatics and analytics together. Use case examples:

  • Identify ICU occupancy and overall LOS in the alcohol withdrawal treatment pathway
  • Identify opportunities to roll out a new program for managing a chronic disease
  • Recall and re-run analyses over time to track utilization and cost metrics for healthcare operations

Healthcare Operations

Gain visibility into your organization’s value-based care operations. Use case examples:

  • Identify opportunities to free up hospital bed capacity
  • Compare hospital utilization between transferred and non-transferred patients
  • Identify direct and indirect costs associated with ambulatory services for precision medicine

Precision Medicine can facilitate collaboration between healthcare providers and pharma organizations. Use case examples:

  • Connect multi-omics data sources with EHR and real world clinical trial data
  • Identify patients who are at high risk for cancer based on gene mutations
  • Identify best treatment options for groups of patients based on omics and EHR data for immunology

Therapeutic Areas

With immunology connecting to many therapeutic areas, such as immuno-oncology, inflammation, and autoimmunity, you can use a single analysis platform to instantly pivot between data products from each of these therapeutic areas. data security for healthcare

Data Security in Healthcare runs within your secure network. The analysis environment is hosted entirely within your network and your cloud. Source data storage and access is tightly controlled in your network.

Learn More About Security

Let’s get the conversation started

From a 30-minute demo to an inquiry about our 4-week pilot project, we are here to answer all of your questions!