The challenge: A cost-effective, reliable, and real-time information system for monitoring the stress of patients in intensive care units (ICUs) is missing from current ICU systems. This presents an important opportunity because:
- Five million patients are admitted annually to ICUs in the United States, with an average daily cost of over $10,000;
- Post-surgery ICU patients require a higher level of acute care than most other hospitalized patients because they need services such as cardiovascular support, invasive monitoring, and intensive observation;
- ICU patients, often unable to report on their stress and pain levels, rely primarily on nurses’ training and knowledge—yet, because nurses can visit patients only periodically, pain can only be assessed intermittently;
- Pain and stress ratings are often subjective, even guesswork, and nurses treating the same patients often disagree with each other because of their varying levels of training and experience; and
- The dramatically increasing demand for ICU beds has significantly added to the workload of nurses and physicians.
Here is a typical hospital setting in which patients are receiving intensive care and monitoring. Traditionally, nurses or medical staff check and record a patient’s status periodically.
Creating a means to remotely monitor stress and pain with real-time data visualization can help address these issues.
The approach: ICU Cam enables non-invasive monitoring of stress and pain using a remote smart camera mounted on top of a patient’s bed. Its capabilities include:
- remotely measuring stress during complex dexterity tasks, such as surgery; and
- transfer of reliable real-time results to physicians via data visualization;
ICU Cam uses a smart camera to automatically capture several patient vital signs and send this information to doctors in real time.
The tools: The embedded software system consists of four modules:
- Camera server-side data collection and processing
- Networking module for Wi-Fi transmission
- Client-side data receiver
- Graphical user interface that provides data regeneration and interpretation
The results: During lab testing, ICU Cam measured heart rate and heart rate variability with over 96 percent accuracy. Additional benefits may include:
- Early detection of pain to help doctors provide early relief to patients incapable of self-reporting;
- Reduced length of ICU stay, resulting in substantial savings for hospitals and insurance companies; and
- Increased ICU efficiency and reduced nurse workload.
Physicians can review patients’ information on tablets and smart phones even when they are not physically in the hospital. If patients need urgent attention, a text alert message will be sent along with key patient information.
Next steps: Last fall, we visited local healthcare facilities to help us better understand problems in current ICU systems. At Boston Medical Center, Gerardo Rodriguez, M.D., anesthesiologist and critical care physician at the surgical ICU in East Newton, MA, gave us a tour, explained how patients are monitored there, and described the system’s shortcomings. He expressed enthusiasm about testing ICU Cam in patient care settings and discussed additional applications of this system to, for example, provide support for new doctors.
In the coming months, the ICU Cam team will:
- improve the beta version prototype;
- research hardware alternatives to reduce costs;
- initialize clinical trial paperwork in MIT’s medical center to further understand the process; and
- identify a large hospital for a pilot system launch.
For further information, please contact Julia Somerdin at email@example.com.
About the Author
Julia Somerdin, SDM ’13, is an entrepreneur in healthcare/patient monitoring and a professional in the mobile communication industry specializing in system solution architecture and system integration. She holds a B.S. in electrical engineering from China’s Huazhong University of Science and Technology; an M.B.A. from Northeastern University; and, as an MIT System Design & Management student, she will earn an M.S. in engineering and management in 2015.