Welcome to our first Research Roundup. In this series, we highlight the latest research conducted on PicnicHealth.
PicnicHealth is simplifying observational research by combining a direct-to-patient approach, industry-leading AI and technology, and world-class clinical expertise to capture the patient experience in an unprecedented level of detail.
Real-World Clinical Characteristics and Disease Management of Immunoglobulin A Nephropathy Patients across the United States
Background: Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulonephritis in the world. With new therapies emerging, understanding disease management for IgAN patients is necessary to uncover unmet needs in this population. This study aims to describe the demographics, clinical characteristics, and disease management of IgAN patients in the United States.
Methods: PicnicHealth enrolled 165 patients with IgAN between August 2022 and November 2023. Structured and unstructured data were abstracted from patient medical records collected across all their U.S. sites of care. The study included patients with a confirmed IgAN diagnosis and at least one nephrology visit. Descriptive statistics for patient characteristics, healthcare resource utilization, and medication use were reported.
Results: Results demonstrated that although 79% of patients were prescribed a current standard of care medication for IgAN, their disease still progressed with 37% of those patients having at least one comorbidity, highlighting an unmet need among these patients.
How PicnicHealth simplified this observational study
Through PicnicHealth’s virtual recruitment and enrollment methods, researchers were able to enroll a diverse participant group– with 40 U.S states represented– across a median of 8 care sites per patient. The study also leveraged PicnicHealth’s human-in-the-loop machine learning for efficient and accurate data extraction. The comprehensive approach delivered the complete picture of IgAN patients' medical history and outcomes and enhanced the study's ability to deliver valuable insights into the condition´s management.
See the full poster here.
Baseline Characterization of Patient-Reported Disease Burden in a Virtual, Longitudinal Cohort of Myasthenia Gravis
Myasthenia gravis (MG) is a neuromuscular disorder characterized by fluctuating muscle weakness. Since feelings of weakness can fluctuate daily, it has historically been difficult to determine the disease's burden. This study investigated the feasibility of collecting patient-reported outcomes virtually to quantify disease burden and severity accurately.
Methods: PicnicHealth enrolled 249 U.S. patients with MG from 2021 to 2023. Medical records were collected across all patients’ sites of care, and structured and unstructured data were abstracted using human-in-the-loop AI. Patients were administered the MG Activities of Daily Living Profile (MG-ADL) patient reported outcomes (PRO) survey on PicnicHealth's virtual patient portal within 90 days of enrollment, allowing the researchers to categorize disease burden and severity and summarize treatment patterns and demographics with descriptive statistics.
Results: This study collected a median of 7.2 years of medical records per patient and 2 years of PRO responses. The data showed a median total MG-ADL score of 9, with 17% of patients classified as mild, 48% as moderate, and 35% as severe. Women had higher MG-ADL scores than men, indicating more severe symptoms. Patients with mild MG reported specific symptoms like breathing difficulties and eyelid droop, while those with moderate and severe MG had a broader range of symptoms. Mild patients used fewer unique treatments compared to moderate and severe patients.
The MG-ADL survey proved an effective way to classify patients with MG into severity categories.
How PicnicHealth simplified this observational study
Through PicnicHealth, researchers could efficiently streamline data collection and simplify PROs for patients through a single, easy-to-use virtual platform. This portal not only gave patients a streamlined way to complete PROs but also gave them access to their complete medical history, providing value outside of the study.
See the full poster here.
Quantifying the Effectiveness of a RWD Quality Framework; A Case Study Using Paroxysmal Nocturnal Hemoglobinuria (PNH)
Background: While traditional clinical trials are considered the gold standard for research, real-world data (RWD) offers valuable nuances and efficiency. This study evaluates the quality and data reliability of RWD in clinical research, focusing on PicnicHealth’s registry of patients with Paroxysmal Nocturnal Hemoglobinuria (PNH), a rare blood disorder.
Methods: PicnicHealth enrolled 90 patients with PNH between 2020 and 2023. Medical records were collected across all patients’ sites of care, and structured and unstructured data were abstracted using human-in-the-loop AI. The Duke Margolis quality framework was adapted to assess data reliability through programmatic rules identifying potential issues. The study included descriptive statistics for key data elements, focusing on identifying and correcting data errors.
Results: PicnicHealth collected a median of 222 records per patient over 10 years. The study applied 143 disease-agnostic and 19 PNH-specific quality rules, identifying 105 errors. Common errors included conditions before diagnosis and outliers in vital signs. Errors were reviewed by clinicians, leading to data corrections or justifications. Typical causes of errors included missing records, which led to requests for additional records; abstraction errors, which were corrected by clinicians; and errors in the source medical records, which were dismissed with a note from the reviewer. This process highlighted potential anomalies in PNH patient care, allowing for data corrections and improved data provenance and quality.
What this means
Through PicnicHealth’s technology and human verification processes, data corrections can be tracked and traceable to source records, not only ensuring high data quality, but also enhancing transparency.
See the full poster here.
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See more posters and publications at lifesciences.picnichealth.com/publications, and explore how PicnicHealth can drive your observational study forward at lifesciences.picnichealth.com.