Heart Rate Variability and the Digital Health Revolution - Voices 2015

Editor's Notes

• #3: 1. In 1966 it was a big klunky thing that hung around Dr. McKoy’s neck, in 1987 it was a flip phone like device and in 2012 it is a smartphone
• #4: Jo Beth Dow and I founded SWH in Feb, 2011 While we develop apps as part of our product, we are a software technology company Our mission is to analyze the patterns of the heart beat, known as Heart Rate Variability, AND the patterns of Heart Rate Variability to detect onset of specific conditions The app and mobile platform serves as a real time detection device and as a data collection platform that utilizes 3rd party sensors and heart rate monitors. Our backend database is mined and advanced analytics are utilized to detect disease specific patterns in the data A rich and graphical tool suite brings the data to life with application specific functionality and user interfaces
• #5: Jo Beth Dow and I founded SWH in Feb, 2011 While we develop apps as part of our product, we are a software technology company Our mission is to analyze the patterns of the heart beat, known as Heart Rate Variability, AND the patterns of Heart Rate Variability to detect onset of specific conditions The app and mobile platform serves as a real time detection device and as a data collection platform that utilizes 3rd party sensors and heart rate monitors. Our backend database is mined and advanced analytics are utilized to detect disease specific patterns in the data A rich and graphical tool suite brings the data to life with application specific functionality and user interfaces
• #6: Jo Beth Dow and I founded SWH in Feb, 2011 While we develop apps as part of our product, we are a software technology company Our mission is to analyze the patterns of the heart beat, known as Heart Rate Variability, AND the patterns of Heart Rate Variability to detect onset of specific conditions The app and mobile platform serves as a real time detection device and as a data collection platform that utilizes 3rd party sensors and heart rate monitors. Our backend database is mined and advanced analytics are utilized to detect disease specific patterns in the data A rich and graphical tool suite brings the data to life with application specific functionality and user interfaces
• #7: HRV is The variation between each heart beat and is a view into the ANS 30 years of research validates HRV as a significant metric for measuring health HRV is a mainstream topic of research Some HRV metrics SDNN – Standard Deviation of RR intervals pNN50 – Percentage of RR intervals/hour in which change in normal intervals exceeds 50msec rMSSD – Root Mean Square of Successive Differences of RR intervals SDNN, pNN50, rMSSD all have published cutoff points for risk of sudden death from MI HRV provides insight into the nature of heart-related diseases While there is still a gap in awareness of HRV between researchers and doctors in the medical community, HRV is an emerging biometric Insurance reimbursement codes accept HRV as a metric for measuring ANS Monitoring HRV allows individual to modify behavior, leading to positive change throughout the body’s tightly coupled system HRV measurements.CPT Coding 95921 and 95922 Two reimbursable CPT codes allow physicians to be paid for autonomic nervous system monitoring. These two reimbursable CPT codes for autonomic nervous system monitoring (95921 and 95922) were established in 1999. These CPT codes enable health care providers to be reimbursed for monitoring the autonomic nervous systems of patients where such monitoring is indicated. The reason for two CPT codes is simple. In order for physicians to get a complete look at autonomic nervous system functioning they must read both of its branches (Sympathetic and Parasympathetic) independently. CPT code 95921 is coded for parasympathetic nervous system monitoring and 95922 is coded for sympathetic nervous system monitoring. HRV measurements. CPT Coding 95921 and 95922 357.2 Polyneuropathy in DiabetesV628.9 Psychological Stress or Physical Stress not elsewhere classified308 Stress Reactional Emotional308.1 Predominant disturbance of consciousness308.3 Other acute reactions to Stress308.4 Mixed disorders as reaction to stress308.9 Unspecified acute reaction to stress458 Orthostatic Hypotension458.1 Chronic Hypotension429.9 Heart Disease unspecified
• #8: Jo Beth Dow and I founded SWH in Feb, 2011 While we develop apps as part of our product, we are a software technology company Our mission is to analyze the patterns of the heart beat, known as Heart Rate Variability, AND the patterns of Heart Rate Variability to detect onset of specific conditions The app and mobile platform serves as a real time detection device and as a data collection platform that utilizes 3rd party sensors and heart rate monitors. Our backend database is mined and advanced analytics are utilized to detect disease specific patterns in the data A rich and graphical tool suite brings the data to life with application specific functionality and user interfaces
• #10: These images represent the capability of HRV analysis for detecting variance of the ANS. These sorts of analysis are being performed within research institutions today and are not proprietary to SWH. To our knowledge, these analyses are not part of any commercially available HRV measurement system. This research provides a proof of concept for an HRV product in the predictive diagnostic segment. SWH is seeking funds to develop such a system. Based on research and our knowledge of information contained in time series, we assert that at the onset of disease, and through its progression, new patterns will emerge in HRV, patterns that will be unique for different conditions. Existing research, in general, has looked at static HRV numbers and often results in tables of Time, Frequency and Non-Linear HRV values correlated with the disease being explored. The result has been a generic “Low HRV is associated with….[Heart disease, stress, diabetes, OSA, COPD, etc.] and a table with HRV values published in the results section of the clinical trials. SWH believes that because of the rich and dynamic nature of the ANS, HRV must be analyzed as a pattern rather than as a static number and that the analysis should include the patterns between time, frequency and complex calculations for a given measurement as well as through measurements taken over time. Just like Apple did not invent the MP3 player, we did not invent HRV Analysis. The SWH plan is to take existing technology and made it useable and accessible to a wide range of customers while at the same time collecting vital signs and demographics. We envision a novel application of HRV that provides meaningful and actionable user feedback. Our technology contribution is that we analyze HRV data for patterns rather than data points The challenge is how to collect the data needed for such an endeavor and how to make money during the extensive R&D phase. We have a strategy to do both.
• #11: Jo Beth Dow and I founded SWH in Feb, 2011 While we develop apps as part of our product, we are a software technology company Our mission is to analyze the patterns of the heart beat, known as Heart Rate Variability, AND the patterns of Heart Rate Variability to detect onset of specific conditions The app and mobile platform serves as a real time detection device and as a data collection platform that utilizes 3rd party sensors and heart rate monitors. Our backend database is mined and advanced analytics are utilized to detect disease specific patterns in the data A rich and graphical tool suite brings the data to life with application specific functionality and user interfaces
• #13: HRV is computationally intensive So before powerful mobile platforms…. Priced from $1,500 to $42k require proprietary EKG Circadian rhythm, body position, length of measurement not generally taken into account thus results were hard to interpret These systems produce standard HRV parameters presented in graphical and numeric formats SweetBeat differentiates through: Mobile Cost effective Leverage advances in 3rd party sensors Artificial Intelligence to detect specific conditions Meaningful and actionable feedback for a wide range of users
• #14: Underutilization of HRV in Mainstream HRV is a reliable reflection of the Autonomic Nervous System (ANS) HRV is a mainstream topic of research and yet is not part of mainstream medicine HRV viewed as a number 30 years of research has identified HRV as a systemic health metric Medicine has tried to associate disease with a “value” of HRV The nervous system is dynamic and non-linear so the patterns of HRV need to be studied and correlated with specific diseases Current HRV systems are lacking Current HRV systems are >$2500 and do not provide meaningful feedback SW runs on PCs; no mobile solutions available outside of a medical Holter Monitor Symptom driven medical culture Medical tests and treatment are sought once symptoms appear Few consumer friendly objective measurement tools for early detection and health improvement monitoring Stress, obesity, diabetes are epidemic It’s estimated that 90% of disease is caused by preventable stress 68% of adults are overweight or obese 26 million children and adults have diabetes and 79 million have pre-diabetes
• #16: Jo Beth Dow and I founded SWH in Feb, 2011 While we develop apps as part of our product, we are a software technology company Our mission is to analyze the patterns of the heart beat, known as Heart Rate Variability, AND the patterns of Heart Rate Variability to detect onset of specific conditions The app and mobile platform serves as a real time detection device and as a data collection platform that utilizes 3rd party sensors and heart rate monitors. Our backend database is mined and advanced analytics are utilized to detect disease specific patterns in the data A rich and graphical tool suite brings the data to life with application specific functionality and user interfaces
• #17: HRV is computationally intensive So before powerful mobile platforms…. Priced from $1,500 to $42k require proprietary EKG Circadian rhythm, body position, length of measurement not generally taken into account thus results were hard to interpret These systems produce standard HRV parameters presented in graphical and numeric formats SweetBeat differentiates through: Mobile Cost effective Leverage advances in 3rd party sensors Artificial Intelligence to detect specific conditions Meaningful and actionable feedback for a wide range of users