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| Funder | NATIONAL HEART, LUNG, AND BLOOD INSTITUTE |
|---|---|
| Recipient Organization | Duke University |
| Country | United States |
| Start Date | Jul 10, 2024 |
| End Date | Jun 30, 2026 |
| Duration | 720 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10816682 |
ABSTRACT: Urine and stool output tracking is essential for hospital treatment of diseases related to the heart, lungs, and blood. For patients who can walk, output monitoring currently involves patients using plastic waste collection hats. The manual nature of patient and nurse handling of collection hats leads to substantial error in
patient fluid balances and delays in reporting urine output data to providers. Challenges with urine output tracking are acute when managing cardiovascular or pulmonary complications in which accurate monitoring of patient waste is needed to manage volume overload and fine-tune diuretic dosing. Manual urine tracking also exposes
staff to hazardous chemicals and pathogens such as SARS-CoV-2. Our goal here is to develop a platform that will allow the accurate collection urine output data in the setting of clinical management of heart failure patients. Using a toilet-based sensor platform, we will automate the measurement of patient urination so that we are able
to mitigate the measurement inaccuracy and treatment delays that are currently caused by manual waste monitoring. Our current device builds on multiple generations of prototype design that have involved extensive simulations and hundreds of tests by human volunteers. Preliminary results from these tests suggest our current
prototype can detect urination with high sensitivity and measure urine mass with low error. To complete development of a device suitable for cardiology patient use in hospitals, we will first validate the accuracy and timeliness of our device in heart failure patients. We will measure the accuracy with which the device measures
urine volume, comparing device estimates of waste output to gold-standard data obtained from conventional urine collection vessels. Second, we will quantify the decrease in lag time from urination to urine output data reporting to physicians. Third, we will evaluate the feasibility of technology adoption. We will survey patients and
nurses to assess the potential increases in nurse and patient satisfaction associated with device usage. Since we expect our automated device to reduce nurse workload, we will also track impacts on nursing effort on waste tracking. In completing this Aim, we expect to develop the first automated platform for tracking urine output
among cardiology patients. More broadly, by developing our device in a challenging clinical unit involving frail patients who can excrete large fluid volumes, we set the stage for transforming patient care in other hospital settings relevant to NHBLI such as management of bone marrow transplant patients.
Duke University
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