Periodic Reporting for period 2 - Sleep for All (Diagnostics of sleep disorders for all patient groups)
Reporting period: 2017-10-01 to 2018-09-30
There is growing awareness about the importance of sleep for health, both with the general public and health care professionals. It is estimated that the annual cost of society, due to poor sleep and sleep disorders, is € 300 billion in Europe and $ 411 billion in the US, with 1.5 – 3% of GDP lost annually due to poor sleep.
Many things cause poor sleep. This includes life style, stress, and medical disorders. It is estimated that the number of sleep studies will grow by 4.6% until 2021 reaching a market value of $ 9 billion. At the same time demand for sleep studies is growing, reimbursement to physicians who conduct sleep studies is shrinking. This drives demand for high through put and low-cost sleep studies.
Currently two main types of sleep studies are offered by physicians. One is the complete polysomnogram (PSG) where a patient sleeps at a hospital and sleep is measured with EEG and breathing is measured. The PSG study gives the most complete picture of the patients sleep health as possible but is costly and labor intensive. The other type of sleep studies is the polygraphy (PG) where the patient breathing is measured at home. The PG is a simple and inexpensive sleep study but does not measure sleep or sleep quality.
In this project Nox Medical developed a novel method to conduct a sleep study equivalent to the PSG, which is simple and self applied like the PG study. Furthermore, automation in data analysis was improved by developing AI driven models and workflow and data management was improved by incorporating a cloud-based patient management platform to the studies.
Many things cause poor sleep. This includes life style, stress, and medical disorders. It is estimated that the number of sleep studies will grow by 4.6% until 2021 reaching a market value of $ 9 billion. At the same time demand for sleep studies is growing, reimbursement to physicians who conduct sleep studies is shrinking. This drives demand for high through put and low-cost sleep studies.
Currently two main types of sleep studies are offered by physicians. One is the complete polysomnogram (PSG) where a patient sleeps at a hospital and sleep is measured with EEG and breathing is measured. The PSG study gives the most complete picture of the patients sleep health as possible but is costly and labor intensive. The other type of sleep studies is the polygraphy (PG) where the patient breathing is measured at home. The PG is a simple and inexpensive sleep study but does not measure sleep or sleep quality.
In this project Nox Medical developed a novel method to conduct a sleep study equivalent to the PSG, which is simple and self applied like the PG study. Furthermore, automation in data analysis was improved by developing AI driven models and workflow and data management was improved by incorporating a cloud-based patient management platform to the studies.
The work performed in the project focused on reducing the impact a sleep study has on the patient, by reducing the sleep system foot print on the patient. This is done by making the sleep studies available for home use, and ensuring that each patient only needs to undergo a sleep study once to get a complete diagnosis. The work also focused on increasing the efficiency for the health care professional by improving data quality, increasing analysis automation, reducing work flow complexity, and reducing the resources required to perform each study.
The new project results have been introduced to several key opinion leaders in sleep medicine the US and have stirred significant interest. The new approach was validated against the current gold standard, the PSG, by a leading sleep scientists. The project results are being tested in two large-scale sleep research projects, one in the US and another in Iceland. It is planed that the project results will be used in several large-scale multi-site sleep research projects in the US, starting in the spring of 2019. Furthermore, hospitals in the US have shown considerable interest in the project results but they need to wait for the new method to be accepted medical practice. The use of the method in the above-mentioned research projects will help making the method accepted in medical practice and will expose many hospitals and physicians to the product.
The new project results have been introduced to several key opinion leaders in sleep medicine the US and have stirred significant interest. The new approach was validated against the current gold standard, the PSG, by a leading sleep scientists. The project results are being tested in two large-scale sleep research projects, one in the US and another in Iceland. It is planed that the project results will be used in several large-scale multi-site sleep research projects in the US, starting in the spring of 2019. Furthermore, hospitals in the US have shown considerable interest in the project results but they need to wait for the new method to be accepted medical practice. The use of the method in the above-mentioned research projects will help making the method accepted in medical practice and will expose many hospitals and physicians to the product.
This project has pushed the state of the art in sleep science and is expected to completely change the way physicians think about sleep and what constitutes healthy sleep. The immediate impact of the project is breaking the bottleneck in collecting sleep data, by PSG equivalent sleep studies being conducted by shipping the sleep system to the patient in the post and not requiring the patient to spend 1 hour with a specially trained technician to set up the sleep study.
A scientist working on one of the large-scale pilot projects using the new solution mentioned that the project results have opened the flood gates of data. The project results have allowed scientist to collect data from 10-100 times as many patients as before using the same resources. This means that now scientists can start looking for new health indicators in large population studies. The potential impact of the project results for scientific discoveries is immense and may be a tipping point in understanding what constitutes healthy sleep and how to monitor patient’s health during sleep, not only look for isolated sleep disorders.
The socio-economic impact of the project could be immense. By increasing efficiency, allowing sleep studies being shipped to patients in the post, automating data analysis, and improving patient management, patients who live in areas where the health system cannot meet demand or is not well developed can now have access to an 8 hour long recording of their physiological signals such as EEG, ECG, and breathing. This can allow physicians to get a snap shot of the patients neurological, cardiac, and pulmonary health, without having to visit the patient’s local area.
A scientist working on one of the large-scale pilot projects using the new solution mentioned that the project results have opened the flood gates of data. The project results have allowed scientist to collect data from 10-100 times as many patients as before using the same resources. This means that now scientists can start looking for new health indicators in large population studies. The potential impact of the project results for scientific discoveries is immense and may be a tipping point in understanding what constitutes healthy sleep and how to monitor patient’s health during sleep, not only look for isolated sleep disorders.
The socio-economic impact of the project could be immense. By increasing efficiency, allowing sleep studies being shipped to patients in the post, automating data analysis, and improving patient management, patients who live in areas where the health system cannot meet demand or is not well developed can now have access to an 8 hour long recording of their physiological signals such as EEG, ECG, and breathing. This can allow physicians to get a snap shot of the patients neurological, cardiac, and pulmonary health, without having to visit the patient’s local area.