About Pegwin Patient Safety Innovation

Pegwin Patient Safety Innovation helps healthcare institutions solve post-operative patient complications by leveraging Machine Learning and AI technology to alert clinicians on early identification of patient abnormalities.

On top of the EMR we create a risk profile for each patient that shows their co-morbidities ranked by severity and pushes the best practice and standard of care to the attending clinician in real-time, augmenting their knowledge to take timely preventive action.

Pegwin is the winner of two (2) ONC for IT Patient Safety Challenges and is an evidence-based solution addressing volatility in the patient state, the uncertainty in decision making, and complexity and ambiguity of data related to patient safety. Pegwin Insights uses live data in real-time from pre-op to homecare, allowing for early detection of patient deterioration to eliminate potential preventable harm.

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Team

Douglas B. Dotan

Founder

Problem statement

The third leading category of death globally, following cancer and heart disease, is mortality within 30-days of surgery. Nearly 1 in 4 hospitalized patients admitted to hospitals in the U.S. will experience harm. Despite decades of effort, U.S. hospitals still have a long way to go to improve patient safety.
Current systems, for monitoring post-operative patients, on surgical wards, are inadequate.
This results in higher costs, added liability, unreimbursed revenue, preventable patient harm and unnecessary loss of life. A recent study shows that 7% of total admissions experience preventable harm and 1% experienced serious preventable adverse events that resulted in serious harm or death.

Our data-driven tools will reduce the financial burden from adverse events.

Traction information

1. We have signed partner agreement with the #1 Cancer Center in the U.S. to conduct a feasibility and usability study of our Machine Learning models and medical AI algorithm.
2. We have won 2 patient safety technology awards from the HHS Office of the National Coordinator for IT.
3. We have developed and tested the Pegwin Insights Platform prototype that agnostically sits on top of any Electronic Health Record (EHR) to display each patient's Risk Profile to support nurses to do the right thing, to the right patient at the right time. This will help to continue timely, quality care even with the nursing shortages.
4. Partnered with ambulatory care providers to close the gap in 'Transitions of Care' between hospitals and primary care providers ensuring continuum of care for patients.

We are listed on clinical trials.gov and have an IRB approval and DUA with UT Health and the Memorial Hermann Health System.

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Milestones

February 2024

MOU Between Pegwin and Prism Care, Inc.

The Memorandum of Understanding between Pegwin and Prism Care is regarding joint efforts to provide integrated data analytic services and Total Care Management services to health care organizations (HCOs). The objective is to create an alliance that can support improvement in patient health outcomes and generate incremental revenue. Prism Care is a provider of remote patient monitoring (RPM), and chronic care management (CCM) that encompasses a full scope of services. This includes an advanced RPM digital momitoring platform, the Prism Care Patient Engagement Center (PEC), and allied services designed to improve patient outcomes. Pegwin is a visionary Digital Health IT company revolutionizing patient care with its groundbreaking product, Pegwin Insights. It provides predictive analytics using AI and Machine Learning to give providers (MD/DO, NP/PA) actionable information obtained from Prism Care (through chronic care management and RPM).

July 2022

Proof of Principle

The preliminary study performed on >15M randomized observations (SMART DST2; SMART STU3; MIT, Harvard, Boston Children’s Hospital) showed completeness, computability, and accuracy of the raw data sources (Fast Healthcare Interoperability Resources - FHIR).

RESULTS: Cross-validated (70/30) AI-Driven model demonstrated good discrimination for unplanned ICU Admission - AUC 0.90; 95% CI, 0.76-0.94) and performed as well, or better than the current models (C statistic ranges: 0.56– 0.74).

The model calibration across different risk categories showed a close association of predicted and observed outcomes (PSI11; PSI04).

July 2022

Agreement to conduct feasibility and usability study of our Machine Learning and medical AI algorithm

Harnessing the power of machine learning models to accurately predict risks, provide early alerts and reduce the incidence of critical postoperative pulmonary complications in a tertiary cancer center.
Pegwin has developed and tested the Pegwin Insights Platform prototype that agnostically sits on top of any Electronic Health Record (EHR) to display each patient’s Risk Profile to support nurses to do the right thing, to the right patient at the right time. This will help to continue timely, quality care even with the nursing shortages.
Pegwin has a signed agreement with the #1 Cancer Center in the U.S. to conduct a feasibility and usability study of our Machine Learning and medical AI algorithm. They have asked for the rights to be the first to publish the results.