Remote Lung Sound Auscultation
Background
01 / Telemedicine
Dr. Wilman Ortega is a pulmonologist at Mercy Hospital working to improve telemedicine capabilities. Mercy is a forerunner in the field of using telemedicine (virtual and/or remote care), as a way to provide cheap, reliable treatment to patients who lack access to specialists. Specifically, Dr. Ortega is looking for a way to monitor the lung sounds and symptoms of frequent hospital patients from home. The hospital’s current method for obtaining patient data is to have nurses call patients at home once a day and ask them a ten minute questionnaire about their symptoms. This does not include any biological recording. As Mercy monitors over three thousand patients every year, this process represents a large strain on hospital financial and manpower resources. In general, the market for telemedicine solutions has expanded massively in both scale and valuation; the industry has grown two and a half times, from $14.3 billion to $36.2 billion, since 2014. While initial booms in telemedicine have focused on providing care to remote and developing countries, there is still a substantial untapped financial potential for domestically-focused solutions that can be easily integrated into the existing US healthcare system. The ability to provide basic at-home data acquisition and diagnostic services to patients who would normally need to make repeated hospital visits, or lengthy and potentially inaccurate phone surveys, is one such underdeveloped submarket.
02 / Specific Issues
Abnormal lung pathologies are often widespread but undiagnosed. For example, it is estimated that there are nearly 12 million adults in the US with undiagnosed COPD. Globally, 251 million cases of COPD were reported last year, and the disease is projected to be the 3rd most common death worldwide by 2030. COPD itself is a blanket terminology that includes bronchitis, emphysema, asthma, and other chronic respiratory illnesses. It is extremely useful for healthcare providers to get more specific information on the actual acoustic markers (abnormal lung sounds and symptoms) of the patient’s specific illness, in order to provide better care and risk management. Many lung diseases are deceptive because their symptoms may remain mild for long periods of time, coaxing patients to ignore the warning signs and rely solely on home treatment. However, symptoms can worsen drastically, leaving patients unprepared. With Mercy’s current home-monitoring capabilities, healthcare providers have no way of knowing the severity of patients’ symptoms, or even whether they are caused by respiratory illness, or unrelated conditions, such as cardiac issues.
03 / Project Scope
Mercy Hospital needs a more efficient way to monitor patients’ symptoms and lung sounds from home, in order to both free up human and financial resources, and increase remote diagnostic accuracy to improve patient outcomes. The client mainly treats older patients who have a limited range of motion, so the device must be easy to put on and take off. Additionally, no patients are the same size or shape, so it must be adjustable to fit a wide range of patient sizes while still able to get an accurate recording of the lung sounds. This data must be processed in order to better aid the nurses when diagnosing lung sound and to limit their time expenditure. There must be a phone or computer app that goes along with the device that can collect the lung data from each patient and prompt them to fill out an online version of the symptom questionnaire that the nurses ask the patients daily. This app must be simple enough for elderly patients with low technological literacy to use to ensure all data required for their care is collected. The completion of this project is a paired phone/computer app and apparatus that allows patients to easily record their lung sounds at home and send the recordings and a completed questionnaire directly to physicians at Mercy Hospital for analysis.
Product Design Requirements
Recording process should take less than 5 minutes
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Device should connect to a computer or phone using USB of Bluetooth
The device should be worn and removed by elderly patients in less than 1 minute
The wearable component should allow for a wide range of measurement locations, in the front, side and back
The stethoscope must have a sampling rate above 4 kHz
Wearable component should be less than 5 kg
The device must be adjustable to patients from 45-115 kg
Device operation should be understandable for elderly patients in less than an hour
Device battery should last longer than 6 hours
System should detect abnormal lung sounds with high degree of accuracy, agreeing with nurse diagnosis in more than 90 percent of trials
System must cost less than $250