# Extensions of an Automated Algorithm to Examine CPR Compliance on and off Study

> **NIH NIH R21** · UNIVERSITY OF WASHINGTON · 2020 · $116,625

## Abstract

PROJECT SUMMARY
This application is in response to PAR-14-007, “Secondary Dataset Analysis in Heart, Lung, and
Blood Diseases and Sleep Disorders.” The full title of the proposal is “Extensions of an
Automated Algorithm to Examine CPR Compliance on and off Study.”
Out of hospital cardiac arrest remains a major health problem with prehospital care and quality
cardiopulmonary resuscitation (CPR) being key factors impacting survival. Prehospital
emergency agencies that utilize process improvement strategies to evaluate care delivery and
modify systems/procedures to achieve set standards provide better care and have better
outcomes. A previously developed algorithm was used to classify care provided as either
continuous chest compressions (CCC) or interrupted chest compressions (ICC). Use of such a
tool to determine compliance with local CPR standard of care during non-trial phases is
important. Automation of this step supports process improvement and better outcomes in the
setting of limited resources.
The purpose of this study is to acquire knowledge about prehospital emergency care through
the processing and analysis of chest compression data obtained from electrocardiogram (EGC)
files. The study will use existing cardiac arrest registry data collected by the Resuscitation
Outcomes Consortium. Results will inform agencies of CPR quality and compliance to local
standard of care when not part of a closely monitored clinical trial.
The primary study aim is to use an algorithm based on three metrics (chest compression
fraction, compression segment length and pauses per minute) to classify CPR strategy and then
determine compliance with local CPR standard of care.
Secondary aims of the study are to examine disparities in minorities and other important
subgroups; to extend the algorithm to account for advanced interventions such as intubation
and drug administration; to review CPR that was not classified as either strategy; and to
determine the feasibility of a pragmatic data extraction process.
Data exist as part of the Resuscitation Outcomes Consortium (ROC) out-of-hospital cardiac
arrest registry. This study includes investigators at the University of Washington who were
members of the ROC Data Coordinating Center. They have both the analytical and clinical
expertise to lead such a study.

## Key facts

- **NIH application ID:** 9842364
- **Project number:** 5R21HL145423-02
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Robert H. Schmicker
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $116,625
- **Award type:** 5
- **Project period:** 2019-01-01 → 2021-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9842364

## Citation

> US National Institutes of Health, RePORTER application 9842364, Extensions of an Automated Algorithm to Examine CPR Compliance on and off Study (5R21HL145423-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9842364. Licensed CC0.

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