Unlocking the power of data science

  • Visualize

    patient population while blending data from different sources

  • Predict

    future cost drivers in just a few clicks on a powerful predictive analytics engine

  • Stratify

    high-risk patients using person-centric approach

  • Scale-up

    patient engagement by creating clones of a human care manager

  • Track &report

    using national standard quality measures or create on your own


Welcome to HILABS Unlocking the power of data science

US Federal Contractor Registration

Our mission is to put healthcare organizations in the driver seat for data-driven healthcare decision making

We believe that the no one knows healthcare data better than the healthcare organizations that create it. However, healthcare organizations often lack the tools to generate insights from this data. Statisticians, data scientists and technology gurus can create tools, but these tools have no value until merged with the valuable domain knowledge that only healthcare organizations possess. We empower healthcare organizations with data science tools to leverage their deep domain knowledge and generate novel insights from their data.

The HILABS DO IT YOURSELF Data Analytics Platform

HILABS "DO-IT-YOURSELF" healthcare data mining platform empowers whole new group of employees within health organizations to intuitively explore their data and discover, by themselves, novel insights. Having all the complexities of data science under the hood, the HILABS powerful but easy-to-use platform puts the healthcare organizations in the driver seat to efficiently and effectively understand their data.

Our Products


Blend any type of data, interact with data visuals, customize your dashboards and generate new data attributes - all in just a few clicks

Data Mashup

Combine data from different sources such as claims, EMRs, devices, social media, and clinical notes with just a few clicks

Visual Interaction

interactive multidimensional data exploration by solely interacting with visual images or using drag-and-drop manipulation

Unlimited Expansion

Unlimited enhancements to the existing data dictionary with no additional cost



Predict the future in just a few clicks on a powerful predictive analytics engine that brings healthcare and the science of machine learning together.


% Accuracy in predicting the future cost drivers among 1.8 million Medicare patients


% Accuracy in predicting future ER Visits among Medicare patients

Also create your own predictive models with just a few clicks



Find anomalous high utilization of healthcare resources.


..anomalous utilization within episodes of care where patients incurred levels of utilization that are unexpected given their clinical characteristics.


..cost by systematic analysis and take corrective actions on reasons behind the anomalous utilization of healthcare resources.


..the quality of care as the system becomes smarter after learning iteratively from every new scenario of anomalous utilization.



Design better care management by segmenting your population based on disease, utilization and socio-economic factors.

Person-Based Segmentation

Segment patients according to similar health care needs, rhythms of needs, and priorities to make the segment useful for planning

Person-Based Engagement

Mine behavioural data including the unstructured external “big data” sources to identify which members may be most responsive to care management programs

Power of networks

Identify influential patients (the "peer-mentors”) based on patients relationships and affiliations identified through Facebook, Google, LinkedIn or HILABS social media



Scale up population engagement by creating clones of a human care manager into thousands of virtual care managers who work with each patient 24/7.

The virtual care managers do the following:


  • Follow plan set by a human care manager
  • Help find medical care based on geography, insurance network,or other attributes
  • Automatically identify care gaps and recommended care
  • Interact

  • Learn constantly from human care manager
  • Relay patient question if not sure about correct answer
  • Answers patient queries 24/7
  • Track

  • Track care effectiveness against set goals
  • Track patients with deteriorating health status and initiate instant communication with providers
  • Track pre-configured quality measures at the population level


    Tracks performance against home-grown and/or national standard quality measures.


    .. your own quality measures and/or use 400+ national quality measures in-built in the HILABS platform


    .. quality measures using behaviour interventions programs established in your organization


    .. generate/download reportable measures


    HILABS Team

    A cohort of experienced Engineers, Data Scientists and Physicians

    The HILABS team brings over 50 years of combined experience in healthcare, data science and technology. HILABS was spun out of Yale University in early 2014. The management team consists of alumni from Yale, Harvard, Johns Hopkins and the Indian Institute of Technology. The team brings a wealth of knowledge in the healthcare delivery, healthcare IT and the data analytics space.

    Amit Garg, MBA

    Amit has extensive experience in product strategy in the healthcare data analytics space for state and federal healthcare agencies. He has been involved in the successful start-ups of two IT companies. Previously, Amit served as a solution architect for designing and building the WA State Medicaid payments system responsible for the accurately auto-processing of approximately $6 billion annual payments to the healthcare provider population of the state. The system went live in 2010 and is considered one of the most successful MMIS implementations nationwide.Amit received his undergraduate degree in Engineering from Indian Institute of Technology, Roorkee and an MBA in healthcare management and entrepreneurship from Yale University.

    Prateek Bansal

    Prateek can be best viewed as an intraprenuer, instrumental in formulating product vision and an expert in product launch strategies. He built a start-up ground up when it just had two employees working in a 10X10 office in the western suburbs of Mumbai to a successful growing venture. He developed an award winning social media analytics and engagement platform which were used by top Indian firms such as Tata's Taj Hotels group for consumer marketing.

    Maulik Majmudar, MD

    Maulik Majmudar is the Associate Director of the Healthcare Transformation Lab and a clinical cardiologist at Massachusetts General Hospital. He is also an Instructor at Harvard Medical School. Maulik is an active member of the healthcare innovation and entrepreneurship community, with a specific interest in technology-enabled healthcare innovation. Before HILABS, he has served as a medical advisor to two venture-backed startups. Maulik attended Northwestern University Feinberg School of Medicine and then completed residency training in Internal Medicine at The Johns Hopkins Hospital, followed by a fellowship in Cardiology at the Brigham and Women's Hospital. He also holds a patent and has had several publications in high-impact journals, such as Nature, Circulation, and Circulation Research.

    Neel Butala, MD,MBA

    Neel Butala has worked for the Boston Consulting Group on engagements in healthcare strategy and is the first author of several publications in leading peer-reviewed academic journals in the field of healthcare quality and outcomes. Neel received his undergraduate degree in economics magna cum laude from Harvard University and dual degree of MD/MBA cum laude from Yale. He is currently a resident physician at Massachusetts General Hospital.

    Ashish Tendulkar, PhD

    Ashish Tendulkar has several years of experience in solving real life problems using Data Science, Machine Learning and Text mining techniques. He has been awarded as the Innovative Young Biotechnologist from the department of Biotechnology, Government of India. He is a Visiting Fellow at Tata Institute of Fundamental Research and Visiting Assistant Professor at Indian Institute of Technology, Madras. He received his PhD in Computer Science and Engineering (Machine Learning, Text Mining, Computational Biology) from Indian Institute of Technology, Bombay

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