Research Platform | PicnicHealth

Why PicnicHealth?

Best in class solutions for when off-the-shelf data isn't enough

By working directly with patients who contribute their medical data to research, we can build the most complete picture of patient health across all of their providers - not just one care site or specialist.

Rapid Recruitment

Building the right cohort of patients is easy with our existing patient communities and rapid recruitment through dozens of established direct-to-patient channels. Patients sign up and consent to participate in 10 minutes and get access to their medical records. Do you have patients in ongoing registries or trials? Send them to PicnicHealth and we’ll get them set up.

Recruit new patients

Onboard existing patients from trials, registries, or programs

IRB Management

Custom Inclusion / Exclusion Criteria

Data Collection & Abstraction

Our research platform delivers customized real-world data at the patient level. Specify the data elements to extract from medical records, including doctors' notes, narrative text, and more.

Longitudinal Record Collection

Data Model Development

Clinical Abstraction / Study-Specific Endpoints

Regulatory-grade Data

Patient Engagement

Our unique, patient-centric approach to real-world data empowers patients to contribute more. Through the PicnicHealth Patient Timeline and prospective collection of medical records and PROs, our patients continue to stay engaged and participate over the full lifecycle of a study.

Patient Timeline

Prospective Follow-up

PROs

Patient Education

Data Linkage

Complete medical records are just the beginning. With patient consent, we can further enhance the value of medical data by securely linking to other patient-level data sources using standard tokenization methods, including:

Claims Data

Clinical Trials

Genomics

Registry Data

Consumer Apps

Use Cases

Find out how leading researchers are using PicnicHealth

Wondering what PicnicHealth can do for you? Here’s a few ways our partners are using our research platform to support their evidence-generation needs.

Project Overview

FlywheelMS is a novel, patient-centric study that aims to create a meaningful real-world dataset to better understand disease course and patterns of care for Multiple Sclerosis (MS) in the U.S.
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Impact

By capturing both retrospective and prospective data for each patient from all of their providers, this study looks to uncover novel insights about the clinical profile of individuals prior to disease onset, and to study patterns of healthcare in the MS community and the impact on clinical and radiological outcomes.

Patient Recruitment

PicnicHealth recruited 5,000 MS patients working with advocacy groups, social media, and healthcare professionals.
Captured 7+ years of retrospective data and 5+ years of prospective data.
Patients were recruited from both urban and rural areas in 49 of 50 US states.

Custom Data Model

A research-ready dataset was built by abstracting both structured and unstructured (e.g., narrative text) data elements.
Custom abstraction methods were designed to extract MS-specific variables, including disability measurements, neurologic signs related to progression, disease subtype, and brain MRIs.

DICOM Retrieval & Analysis

DICOM images were uploaded into the PicnicHealth platform and de-identified.
Brain MRIs were quantified for changes in new and existing lesions and brain volume.

Linking to Claims Data

PicnicHealth provided linked medical and pharmacy claims data to enable additional analyses around healthcare resource utilization rates, complementing the clinical data available through EHR records.

Project Overview

Neratinib (Nerlynx), an irreversible pan-HER tyrosine kinase inhibitor, is approved for use in HER2+ breast cancer. A virtual patient registry (NEAT-HER) was developed to collect historical and ongoing medical data to evaluate neratinib (Nerlynx) in the real world.
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Impact

PicnicHealth’s methodology is feasible and efficient for building a virtual registry that collects useful information on patient/tumor characteristics, treatment patterns, and other important clinical outcomes in patients receiving extended adjuvant neratinib in real-world practice settings.

Patient Recruitment

Recruitment through social media, clinicians, emails and SMS.
Custom onboarding workflows for PicnicHealth Patient Platform.

Custom Data Model

A research-ready dataset was built by abstracting both structured and unstructured (e.g., narrative text) data elements.
Breast cancer-specific data (e.g., treatments, comorbidities, labs, vitals, procedures, surgeries, radiology assessments).
Tumor characteristics (e.g., HR status, genetic testing, histology grade, tumor stage).
Neratinib-specific data (e.g., neratinib-related diarrhea prophylaxis discussions, GI events, dose modifications, ER visits, IV administrations to treat diarrhea).

Project Overview

Medical records from select Huntington’s disease (HD) patients in the US will be matched at an individual level to data from Enroll-HD, an ongoing global observational study. This real-world data of routine medical care will fill in gaps, adding data collected prior to enrollment in Enroll-HD and between annual study visits.

Impact

By collecting real-world data of routine and HD-specific care, researchers hope to better understand patient journeys and identify early signs of HD and progression.

Patient Recruitment

PicnicHealth is enrolling up to 800 patients participating in Enroll-HD.
Capturing 7+ years of retrospective data and 3+ years of prospective data.

Custom Data Model

A research-ready dataset will be built by abstracting both structured and unstructured (e.g., narrative text) data elements.
Custom abstraction methods will extract HD symptoms, comorbidities, concurrent medication use, and health resource utilization measures such as supportive care including occupational, nutritional and pain management therapies.

DICOM Retrieval & Analysis

Brain MRI and CT DICOM images are uploaded into the PicnicHealth platform and de-identified.

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Project Overview

Hemophilia A and B are best treated through infusion of missing clotting factors to stop or prevent bleeding episodes. The experiences of patients with mild-to-moderate disease, however, differ from patients with severe hemophilia, and the development of novel gene therapies will require the quantification of longitudinal burden of disease to support regulatory decisions and payer discussions.

Impact

PicnicHealth has assembled a longitudinal, real-world hemophilia dataset including Hemophilia A and B patients with varying levels of disease severity (e.g., mild-to-moderate and severe).

Key Data Elements

Custom data abstraction models were developed to uncover hard to obtain bleed events (e.g., spontaneous and traumatic), bleed location, and annual bleed rates from narrative text.
Connect bleed events to patient symptoms, comorbidities and treatments to help characterize the complete patient experience.

Data Linkage

Retrieved EMR data can be enhanced by linking to other patient-level data sources.
Link to pharmacy claims data to better understand treatment adherence.
Prospectively collect PRO surveys to better understand the impact of disease burden on social and occupational factors.

Use Cases

Understand the longitudinal burden of treatment and disease.
Understand unmet needs.
Understand treatment patterns and outcomes across various products.
Understand the frequency and impact of treatment switching on outcomes.

Publications

Our data powers cutting edge research

We partner with leading academic and life sciences researchers to accelerate medical research and improve patient care across many different therapeutic areas, including rare diseases, hematology, immunology, neurology, and oncology.

Research Poster