“Monitoring System for Assessing Control of a Disease State” in Patent Application Approval Process (USPTO 20240156401): Patent Application

2024 MAY 30 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- A patent application by the inventors Carchia, Michael (San Francisco, CA, US); Harris, Bronwyn (Redwood City, CA, US); Murphy, Todd (Baltimore, MD, US), filed on November 20, 2023, was made available online on May 16, 2024, according to news reporting originating from Washington, D.C., by NewsRx correspondents.

This patent application has not been assigned to a company or institution.

The following quote was obtained by the news editors from the background information supplied by the inventors: “Management of chronic diseases is a large and costly problem in the United States accounting for over 80% of the nation’s healthcare costs and for seven out of every ten deaths.

“Asthma is one example of a chronic disease that takes a significant toll on individual patients and the healthcare system as a whole. Asthma is a chronic inflammatory disease of the airways, characterized by variable and recurring symptoms. Periods of acute worsening in symptoms, known as exacerbations, are a major feature of the disease. Approximately 300 million individuals worldwide are affected by asthma, and in the United States there are approximately 23 million individuals with asthma, resulting in 1.7 million emergency department visits each year and 10.1 million lost workdays.

“Asthma is one of the most common chronic diseases in children, affecting 7.1 million children in the United States alone. If not managed properly, it can be life-threatening, with over 3,000 deaths due to asthma among children under the age of 15 years in the United States in 2011. Apart from being life-threatening, asthma also has a significant impact on morbidity and quality of life in children and their families. Asthma is the leading cause of school absenteeism. In 2008, for example, an estimated 14 million lost school days were attributed to asthma, and children with persistent asthma have been shown to perform lower on standardized testing.

“Asthma is costly to the healthcare system, totaling an estimated

“56 billion dollars in annual healthcare expenditures in the United States alone. A disproportionate amount of this spending can be attributed to poor disease control. According to Aetna, a major health insurance provider, an emergency department visit for a pediatric asthmatic patient can cost the insurer S600 and a hospitalization can cost S6,600. A person’s asthma can be classified in various ways. Using one common classification scheme, there are 2.9 million children in the United States with moderate to severe persistent asthma. A patient with moderate asthma has a 3% chance of being hospitalized and an 11% chance of going to the emergency department in a three-month period. A patient with severe asthma has a 10% chance of being hospitalized and a 21% chance of going to the emergency department in a three-month period.

“Some treatments and management strategies currently exist for asthma. For example, written asthma action plans have been demonstrated to be a relatively effective tool for some patients in improving control over asthma symptoms. Use of these tools is becoming more frequent, and increasing the proportion of persons with asthma who use these plans is part of the U.S. Department of Health and Human Services’ Healthy People 2020 goals. Typically, these written plans help individuals and families self-manage their illness by guiding their use of various environmental modifications or medical treatments available (e.g., inhalers, oral steroids) and when to contact their healthcare providers. These action plans, however, use relatively subjective criteria to define exacerbations, and many of the signs, such as tachypnea (abnormally rapid breathing) and nighttime cough frequency, are late findings and/or are difficult to measure. Some asthmatics also use peak flow meters-small devices into which the patient blows in order to measure lung function. Although the meters provide quantitative and objective measurements, the results obtained are effort-dependent and require longitudinal daily measurements. For this reason, the results obtained are highly variable, particularly in children.

“Another tool to help manage asthma, in particular to assess the control of the patient’s asthma and adjust controller medications accordingly, is the asthma control test. Similar to the asthma action plan, however, the asthma control test relies on the families of asthma patients to assess and report symptoms accurately and routinely.

“A number of technologies have been developed to allow asthma patients to better monitor their disease outside the hospital. These technologies mainly target improving adherence to therapy or detection of exacerbations. One challenge of some of these technologies, however, is that they use relatively late indicators of worsening disease status that limit their ability to improve the effectiveness of short-term and long-term disease management. Other technologies focus on trying to reduce exacerbation events, which represents only a small component of what it means to have control over a disease. These technologies do not provide insights into long-term control and are not developed as a management tool for clinicians that would inform pharmacologic therapy choices and other interventions designed to improve long-term control.

“Therefore, a substantial gap remains in the ability to reliably measure and monitor asthmatic status outside of healthcare facilities. It would thus be desirable to have a system and method for monitoring asthma status outside the hospital, which would empower families and healthcare providers to more effectively manage the disease. Ideally, such a system and method would help provide improved disease monitoring and management, relative to currently available systems and methods. Also ideally, the system and method might be used for monitoring other disease states, such as allergies, chronic obstructive pulmonary disease, diabetes, hypertension, autoimmune disorders, migraine or other neurologic disease, obstructive sleep apnea, cystic fibrosis, arthritis and other rheumatologic conditions, seizure disorders, cardiovascular disease, peripheral vascular disease and/or congestive heart failure. Common patient monitoring systems measure a variable, for example heart rate or blood oxygenation and alert or alarm if a simple threshold is breached. Prior work has described using parameters obtained while a patient is sleeping and instituting simple cut-offs or thresholds to define changes in control and potentially trigger alerts. However utilizing these simple cut-offs either results in too frequent false alarms or very high thresholds, which result in missing relevant early warning signs. The embodiments described below attempt to better utilize this data to improve disease control assessment and tie it to useful interventions.”

In addition to the background information obtained for this patent application, NewsRx journalists also obtained the inventors’ summary information for this patent application: “Devices, systems and methods are provided to assist with the monitoring or management of a patient’s medical condition, which has one or more sensors sensing individual patient data on or near the patient. This individual patient data corresponds to at least one physiological parameter of the patient and includes a sensor that does not require the patient to apply it or activate it. The data is then transmitted to a processor for computing a risk or status signal that is based on comparison from a baseline related to a patient or related population and an alert or alarm can be generated based on the result of the signal.

“In one embodiment, a system to assist in the controlling of a patient’s medical condition is provided, comprising one or more sensors configured to sense individual patient data on or near a patient, wherein the individual patient data is related to at least one physiological parameter of the patient, wherein at least one of the sensors comprises a passive sensor that does not require patient activation or patient contact, a transmitter configured to transmit the individual patient data to a processor, and a processor configured to calculate a signal using the individual patient data and at least one of a baseline patient data or population data, wherein the processor is further configured to calculate the signal using a combination of a proportional change, integral change and derivative change of the individual patient data and the at least one of the baseline patient data or population data. The individual patient data may be derived patient data. The processor may be further configured to generate the combination of the proportional change, integral change and derivative change from a combination of individual and non-individual data. The combination of individual and non-individual data utilizes a combination including at least two of the following: physiologic, home, local environment, or medical health records. The processor may be further configured to generate an alert to the patient or a care provider of the patient. The alert may include at least one of a medication change, avoidance of regional trigger, behavioral change, environmental change, or education. The system may also further comprise at least two sensors and wherein the processor is further configured to distinguish individual patient between different people in a bed. The processor may also be further configured to receive a response from the patient or a caregiver and to automatically adjust the status signal. The processor may also be further configured to calculate an inspiratory time, an expiratory time, and/or an inspiratory/expiratory (I/E) ratio using the one or more sensors.

“In another embodiment, a method to assist in the controlling of a patient’s medical condition is provided, comprising using one or more sensors configured to sense individual patient data on or near a patient, wherein the individual patient data is related to at least one physiological parameter of the patient, wherein at least one of the sensors comprises a passive sensor that does not require patient activation or patient contact, transmitting the individual patient data to a processor, and calculating a signal with the processor using the individual patient data and at least one of a baseline patient data and population data; and using a combination of a proportional change, integral change and derivative change in the individual patient data and the at least one of the baseline patient data and population data. The individual patient data may be derived individual patient data. The baseline patient data may be generated from patient medical health records. Calculating the signal further may optionally utilize home or local environment data, if available. The system may also generate an alert to the patient or a care provider of the patient. The alerts may include at least one of medication changes, an avoidance of regional trigger, a behavioral change, an environmental change, and patient education information. The method may optionally comprise calculating at least one of an inspiratory duration, an expiratory duration, and an I/E ratio using the one or more sensors, and comparing the at least one of the inspiratory duration, the expiratory duration, and the I/E ratio to a corresponding the inspiratory duration, the expiratory duration, and the I/E ratio to a corresponding threshold value. The corresponding threshold value may be an absolute value, and/or a patient-specific value derived from the at least one physiological parameter. The method may further comprise calculating the I/E ratio from a signal received from the passive sensor. The at least one of the inspiratory duration, the expiratory duration, and the I/E ratio may be calculated using beat-to-beat variations in the heart activity detected by the one or more sensors.”

The claims supplied by the inventors are:

“1. A system to assist in the controlling of a patient’s medical condition, comprising: one or more sensors configured to sense individual patient data on or near a patient, wherein the individual patient data is related to at least one physiological parameter of the patient, wherein at least one of the sensors comprises a passive sensor that does not require patient activation or patient contact; a transmitter configured to transmit the individual patient data to a processor; and a processor configured to calculate a signal using the individual patient data and at least one of a baseline patient data or population data; wherein the processor is further configured to calculate the signal using a combination of a proportional change, integral change and derivative change of the individual patient data and the at least one of the baseline patient data or population data.

“2. The system of claim 1, wherein the individual patient data is derived individual patient data.

“3. The system of claim 1, wherein the processor is further configured to generate the combination of the proportional change, integral change and derivative change from a combination of individual and non-individual data.

“4. The system of claim 3, wherein the combination of individual and non-individual data utilizes a combination including at least two of the following: physiologic, home, local environment, and medical health records.

“5. The system of claim 1, wherein the processor is further configured to generate an alert to the patient or a care provider of the patient.

“6. The system of claim 5, wherein the alerts includes at least one of a medication change, avoidance of regional trigger, behavioral change, environmental change, education.

“7. The system of claim 1, further comprising at least two sensors and wherein the processor is further configured to distinguish individual patient between different people in a bed.

“8. The system of claim 1, wherein the processor is further configured to receive a response from the patient or a caregiver and to automatically adjust the status signal.

“9. The system of claim 1, wherein the processor is further configured to calculate an inspiratory time and an expiratory time using the one or more sensors.

“10. The system of claim 1, wherein the processor is further configured to calculate an I/E ratio using the one or more sensors.

“11. A method to assist in the controlling of a patient’s medical condition comprising: using one or more sensors configured to sense individual patient data on or near a patient, wherein the individual patient data is sensing at least one physiological parameter of the patient, wherein at least one of the sensors comprises a passive sensor that does not require patient activation or patient contact; transmitting the individual patient data to a processor; and calculating a signal with the processor using the individual patient data and at least one of a baseline patient data and population data; and using a combination of a proportional change, integral change and derivative change in the individual patient data and the at least one of the baseline patient data and population data.

“12. The method of claim 11, wherein the individual patient data is derived individual patient data.

“13. The method of claim 11, wherein the baseline patient data is generated from patient medical health records.

“14. The method of claim 11, wherein calculating the signal further utilizes home or local environment data.

“15. The method of claim 11, further comprising generating an alert to the patient or a care provider of the patient.

“16. The method of claim 11, wherein the alerts includes at least one of: a medication change, an avoidance of regional trigger, a behavioral change, an environmental change, and patient education information.

“17. The method of claim 11, further comprising: calculating at least one of an inspiratory duration, an expiratory duration, and an UE ratio using the one or more sensors; and comparing the at least one of the inspiratory duration, the expiratory duration, and the UE ratio to a corresponding the inspiratory duration, the expiratory duration, and the UE ratio to a corresponding threshold value.

“18. The method of claim 17, wherein the corresponding threshold value is an absolute value.

“19. The method of claim 17, wherein the corresponding threshold value is a patient-specific value derived from the at least one physiological parameter.

“20. The method of claim 17, further comprising calculating the UE ratio from a signal received from the passive sensor.

“21. The method of claim 17, wherein the at least one of the inspiratory duration, the expiratory duration, and the UE ratio is calculated using beat-to-beat variations in the heart activity detected by the one or more sensors.”

URL and more information on this patent application, see: Carchia, Michael; Harris, Bronwyn; Murphy, Todd. Monitoring System for Assessing Control of a Disease State. U.S. Patent Application Number 20240156401, filed November 20, 2023 and posted May 16, 2024. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(20240156401)&db=US-PGPUB&type=ids

(Our reports deliver fact-based news of research and discoveries from around the world.)