|Sensor placed under the mattress--Courtesy of EarlySense|
The Centers for Medicare & Medicaid Services (CMS) penalizes hospitals financially for high rates of patient readmissions--making it obviously in a healthcare group's interest to reduce patient readmissions, particularly in chronic conditions that are prone to them.
A new study of an at-home vitals monitor, which is almost invisible to the patient since it's simply placed under the mattress, has found that this data can predict effectively hospital readmission for heart failure patients. This could be a step forward in encouraging the continuum of patient care from the hospital into the home, a widespread industry goal.
"These sensors are designed to assist clinicians' early detection of adverse events in a non-invasive manner, providing the opportunity for intervention prior to hospitalization," said VP of clinical and regulatory affairs at EarlySense Dalia Argaman in a statement. "These data may impact the financial wellbeing of health systems facing economic penalties for 30-day readmission. Predictive insights from a monitoring solution can translate into millions of dollars saved."
The study is of the EarlySense Home-Monitoring Technology--the startup dates back to 2004 and has a slew of major partners and investors including Samsung, Welch Allyn and Mitsui. EarlySense was a 2015 Fierce 15 pick by FierceMedicalDevices.
In this latest study published in the Journal of Telemedicine and Telecare, 29 patients were monitored for a total of 640 nights via the EarlySense monitor, which is a piezoelectric sensor that converts mechanical deformations into electrical signals. Without the need for any patient contact or activity, it continuously monitors respiration rate, heart rate and motion. The study found that change in respiratory rate is an effective predictor of hospital readmission for heart failure patients.
|Bedside unit--Courtesy of EarlySense|
The study was designed as a prospective observational study at home of 30 patients that were discharged following heart failure for hospitalization. Researchers collected data on heart rate, respiration rate, movement rate, rapid and shallow respiration duration, and a behavior score. One patient, who could not tolerate the monitoring, discontinued the study.
The researchers found that patients who were subsequently readmitted to the hospital for heart failure had higher average heart and respiration rates and more respiration variability, with average nightly respiratory rate being the most predictive of readmission.
"We are the first to study nocturnal physiological patterns of HF patients at home using a contactless under-the-mattress monitoring system," the researchers concluded. "We noted patterns that may be unique to patients at risk for readmission due to HF. Respiratory rate was the most important risk-adjusted associate of readmission for HF."
The lead researcher on the study was Dr. Eiran Gorodeski of the Cleveland Clinic.
- here is the announcement and the study