SCALE

Machine-Scale Abstraction

Clinical language is intricate and patient records often contain discrepancies that require human expertise to decode. For example, fatigue can either be a symptom or a side effect, and a pathology report indicating Stage 4 may conflict with a doctor's note indicating a different stage."

Mendel's core is a novel proprietary AI technology, capable of understanding a vast and ever-increasing range of clinical contexts and attributes at human expert level and machine scale.

Clinico-genomic database in a week

QUALITY

Super-Human Quality

Navigating complex clinical attributes, such as outcomes and mortality, is daunting for both humans and machines. Our cutting-edge AI platform pre-indexes complex factors and provides confidence scores, making it easy for trained clinical teams to make decisions.

The resulting accuracy transcends a manual or an automated approach.

From identifying 2 patients to 250+ an hour

REDACTION

Expert-Grade Redaction

Sharing PHI-free medical records at scale is core to the mission of unlocking learnings from every patient journey. These records are full of edge cases that confuse traditional inclusion/exclusion technologies.

Our ability to understand clinical content and support a multi-system approach means we redact PHI at an expert grade level and enable clinical research without compromising patient privacy.

OPTIMIZE

Optimize across multiple factors

We help you navigate the four challenges of structuring unstructured data. Mendel ensures machine scale and analytics ready quality, while keeping cost per patient and turnaround time at a minimum.

How we can help you

De-identification

Get detailed and precise de-identification and never compromise patient privacy.

Sharing EMR data

Source Document Verification

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Cohort Selection

Catalog your patient data inventory and select the most relevant cohorts of patients with complex inclusion or exclusion criteria.

Selecting Patients to Abstract

Trial matching

Protocol Optimization

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Analytics & Research

Achieve research-grade quality with a 25%+ increase in efficiency compared to standard manual abstraction.

Real World Evidence

Prior-Auth

Code Optimization

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Unlock the power of unstructured clinical data

Mendel provides an end-to-end solution that uses the power of a machine and the nuanced understanding of a clinician to structure unstructured patient data at scale.

Industry Challenges and Mendel Solutions

Before healthcare organization attempt to build solutions themselves, consider the following:

The Challenge

How Mendel Solves It

Documents are not machine readable and searchable

Our NLP enhanced OCR engine is designed for healthcare and outperforms other engines in this space.

Documents are also extremely lengthy and it is difficult to identify individual document types

Our Segmentation algorithm that rebuilds the original document structure with metadata identifying source document type

Finding all of the clinical relevant facts is a challenge for human readers

Our NLP engine that extracts all of the clinically relevant facts across the entire document

There are way too many clinical facts to sift through

Our NLU engine weighs evidence across the entire patient record to populate the data model directly

Off the shelf tools do not scale

Abstraction workstation for highly efficient human in the loop interaction with our AI models

Mendel’s New Look: Website Update

We’ve changed our look. Our goal remains the same: make medicine objective. The new site highlights the way our proprietary AI enables organizations to achieve quality and scale when structuring unstructured data. It comes down supercharging your clinical abstraction. We’ve validated that our human in the loop abstraction approach can support a machine that understands medical context like a physician. In our own experiments, the number of variables needing correction decreased by 40%. High quality abstraction = high quality data for cohort selection, real-world evidence, and registries.

How to Approach De-Identification

Organizations that use patient data for internal or external research need to take steps to prevent the exposure of PHI to those who are not authorized to view it. They do this by redacting specific categories of identifiers from every patient document. Once the identifiers are masked, the risk profile of these datasets is significantly reduced. But how do you ensure that redaction engines are working to the highest accuracy?

Mendel Retreat: Adventures and Team Building in Cairo

The Mendel team is still buzzing from our week-long retreat in Cairo. The theme of the retreat was “coming together” and it was the first time the American and other remote employees were united with their Egyptian counterparts. Although there were many adventures–missing flights, seeing the pyramids, haggling at Khan el-Khalili–the highlight of the trip was collaborating together, as one global organization.

AI for healthcare needs clinical reasoning skills

Artificial intelligence (AI) is playing an increasingly important role in the healthcare industry. But to fully leverage the potential of AI, it must be equipped with clinical reasoning skills - the ability to truly comprehend clinical data, or in other words, to read it as a doctor would. When it comes to data processing tools, only a tool capable of clinical reasoning can effectively process unstructured clinical data.

Shanna Wells, Clinical Abstractor

Manually abstracting patient data at scale is an herculean task for humans alone. It is slow, expensive, difficult, and requires extreme precision and accuracy. Organizations have to choose between breadth and depth when it comes to making data useful for decision making. Because of these challenges, the Mendel team created Carbon. Carbon is an easy to use workspace that allows clinical abstraction teams to efficiently curate high quality clinical datasets at scale. The foundation of Carbon is Mendel’s AI. Carbon pulls directly from Mendel’s AI platform to give abstractors a headstart in identifying relevant data elements within a patient’s chart.

Creating Accurate Regulatory and Reference Data

Within the real world evidence space, the generally accepted process for creating a regulatory grade data set is to have two human abstractors work with the same set of documents and bring in a third reviewer to adjudicate the differences. These datasets also serve a second purpose - as a reference standard against which the performance of human abstractors can be measured. Although this remains the industry standard, it is expensive, time consuming and difficult to scale.

Reading Clinical Data Like a Doctor: What’s Missing from DIY Systems

Before embarking on any new endeavor or enterprise, certain questions come to mind: How are we going to handle this? Does our team have the expertise, bandwidth, resources, and time to handle this undertaking on our own? When it comes to finding a scalable way to structure your unstructured healthcare data, the answers to these questions will impact when/whether you deliver a top-tier product for your clients.

Clinical Data Abstraction

Clinical Record OCR

PHI De-identification

Clinical Search Engine

Clinical Trial Matching

Clinical Data Assets

Structure & redact

medical records

at superhuman quality and machine scale

for

Cohort Selection

Real-World Evidence

Registries

INTRODUCING MENDEL

Decoding the World’s Unstructured Patient Data

SCALE

Machine-Scale Abstraction

QUALITY

Super-Human Quality

REDACTION

Expert-Grade Redaction

OPTIMIZE

Optimize across multiple factors

How we can help you

De-identification

Cohort Selection

Analytics & Research

Unlock the power of unstructured clinical data

Mendel provides an end-to-end solution that uses the power of a machine and the nuanced understanding of a clinician to structure unstructured patient data at scale.

Document Categorization

De-identifies PHI

Clinical Grade OCR

Clinical NLP

Clinical NLU

Abstraction Workstation

Industry Challenges and Mendel Solutions

The Challenge

How Mendel Solves It

What the Experts are Saying

Enterprise validated de-identification

Enterprise validated de-identification

Mendel is the only company to validate outcomes with AI in a clinical setting

Mendel is the only company to validate outcomes with AI in a clinical setting

Deloitte features Mendel in their "Intelligent Trials" Report

Deloitte features Mendel in their "Intelligent Trials" Report

The Feed

Mendel’s New Look: Website Update

Mendel’s New Look: Website Update

How a diagnostic company was able to build a clinico-genomic database in a week

How a diagnostic company was able to build a clinico-genomic database in a week

How One Organization Changed The Way Patients are Identified for Clinical Trials with AI

How One Organization Changed The Way Patients are Identified for Clinical Trials with AI

How to Approach De-Identification

How to Approach De-Identification

Mendel Retreat: Adventures and Team Building in Cairo

Mendel Retreat: Adventures and Team Building in Cairo

AI for healthcare needs clinical reasoning skills

AI for healthcare needs clinical reasoning skills

Large Language Models

Large Language Models

Shanna Wells, Clinical Abstractor

Shanna Wells, Clinical Abstractor

Creating Accurate Regulatory and Reference Data

Creating Accurate Regulatory and Reference Data

How to Approach Document Categorization

How to Approach Document Categorization

Reading Clinical Data Like a Doctor: What’s Missing from DIY Systems

Reading Clinical Data Like a Doctor: What’s Missing from DIY Systems

What is the Gold Standard? Exploring the challenges of structuring unstructured data in healthcare

What is the Gold Standard? Exploring the challenges of structuring unstructured data in healthcare

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Products

Clinical Data Abstraction

Clinical Record OCR

PHI De-identification

Clinical Search Engine

Clinical Trial Matching

Clinical Data Assets

SOLUTIONS

Clinical Data De-Identification