Patent Application
20180085008
This invention relates to systems for determining health conditions.
Every method of measuring physiological functions has inherent limitations. Medical devices and laboratory assays may provide inaccurate results for various reasons including user error, damaged components, or attempts to use the device or assay under conditions for which it was not designed. There are also circumstances under which the medical device or laboratory assay provides data that may not be properly interpreted without knowing specific information about the user which puts the data in proper context. Additionally, health care providers sometimes simultaneously use multiple health data inference methods, each associated with a different degree of accuracy and relevance, in an attempt to create a complex assessment of an individual's health or to select a single diagnosis out of a lengthy differential diagnosis. Each measurement may have a different shortcoming that must be taken into account when interpreting the data generated by the measurement. A way to determine the level of accuracy of health related data and to put the data in proper context to make it most meaningful is needed.
We disclose a novel system for identifying the level of validity of health metrics. This system may also be used to assess the best context in which to interpret health metrics by identifying the body type and/or other relevant physical characteristics. This system comprises the collection of a first metric which is relevant to the user's health status. A second metric is collected which is an indicator of the validity of the first metric. The first and second metrics are analyzed according to a first set of rules which assign a weight value to the first metric. A second set of rules calculates an indicator value for the first metric, the indicator value being a function of the weight value.
The first and second set of rules may vary depending on physiological characteristics, including, but not limited to body type, gender, skeletal structure (fine or heavy) and whether or not the user is afflicted with a certain disease. A healthcare provider may enter information about the user's specific physiological characteristics into the computer to trigger the alternative set of rules. Alternatively, the system may trigger the collection of a follow-up metric which may determine whether the user has a physiological characteristic that may then trigger the application of an alternate set of rules to calculate and/or interpret the first metric.
In some embodiments of the invention, the first and/or second metrics are conducted by a medical toilet. Some embodiments of the medical toilet may then transmit the metrics electronically to a computer programmed to analyze the data for validity. The system may then signal the medical toilet to conduct a follow-up metric as described herein.
Definitions
Toilet, as used herein, means a device that is configured to collect biological waste products of a mammal including urine and feces.
Medical toilet, as used herein, means a toilet that conducts one or more metrics relevant to a user's health status. This may include, but is not limited to, quantification of analytes in urine or feces as well as others, including cardiovascular parameters, bioimpedance measurements, and body weight.
Metric, as used herein, means a system, method, or standard of measurement.
Heath metric, as used herein, means a metric which measures a physiological characteristic or physiological function that is relevant to assessment of a user's health status.
Data, as used herein, means information, numerical or otherwise, that is collected using one or more of a variety of health metrics.
Health status, as used herein, means the current physiological state of a mammal, particularly with regard to disease status or injury. In general, this term refers to the overall health of the mammal. However, individual parameters relating to a specific body part or biological system may be measured for the purpose of diagnosing disease states or identifying physiological characteristics or functions that are outside of the normal range. Such individual physiological characteristics or functions may be used to define the health status of the mammal with regard to a specific physiological system.
User, as used herein, means any mammal, human or animal, for which the medical toilet disclosed herein is used to measure physiological functions which may be used to assess the mammal's health status.
Healthcare provider, as used herein, means any individual who performs a task, mental or physical, in relation to health-related services provided to a user. In addition to clinicians who practice medicine directly on a user, the term healthcare provider includes any person that enters data into a computer, when the data entry is used in analysis of a user's health status or to improve a user's health.
While this invention is susceptible of embodiment in many different forms, there are shown in the drawings, which will herein be described in detail, several specific embodiments with the understanding that the present disclosure is to be considered as an exemplification of the principals of the invention and is not intended to limit the invention to the illustrated embodiments.
Disclosed herein is a health metric validation system. A first metric that either directly indicates or infers a user's health status is collected. Normally, a clinician or other healthcare provider would interpret the data at this point with only a general knowledge about the inherent limitations of the health metric and no information about the validity of the health metric in this specific instance. However, according to the invention, a second metric is collected. The second metric may be known to provide an indication of the validity of the first metric. A first set of rules is then applied to the first and second metrics which assign a weight value to the first metric. The weight value is a function of the second metric. A second set of rules is applied to the weighted first metric to determine an indicator value. The indicator value is a function of the weight value and provides an indication of the validity of the first data set and, consequently, its relevance to a user's health status. The second set of rules may define a threshold value for the indicator value and may flag the first metric as invalid or to be excluded from multi-variable calculations that provide an assessment of the user's health status. A clinician may choose to interpret a first metric that has a mid-range indicator value in combination with more reliable health metrics to bolster the validity of a general trend shown by the first metric. Thus, the first metric provides some value but is not assigned more relevance than it merits. As one of skill in the art will understand, the combination of the first metric and the indicator value have a plurality of uses in assessing health metrics and their application to diagnostic efforts.
Referring now to the figures,
The second metrics that medical toilet 205 may measure include, but are not limited to, body temperature, body weight, body composition (i.e. percent body fat, intracellular and/or extracellular water), heart rate, pedal pulse rate, blood pressure, blood oxygen saturation, electrocardiogram measurement, urine constituents and parameters including urine color, glucose, urea, creatinine, specific gravity, urine protein, electrolytes, urine pH, osmolality, human chorionic gonadotropin (for detecting pregnancy), hemoglobin, white blood cells, red blood cells, ketone bodies, bilirubin, urobilinogen, free catecholamines, free cortisol, phenylalanine, and urine volume. The metrics may also include fecal analysis including fecal weight and volume, calprotectin, lactoferrin, and hemoglobin. Additionally, the flow or volume or weight sensor may determine periods of excretion activity to measure, for instance, urination or defecation exertions, or selectively record metrics that were collected during periods of low exertion. These metrics are useful because some metrics are best performed after complete voiding of the bowel and bladder for maximum accuracy.
In addition, multiple second metrics may be collected and used as described herein to assess the validity of the first metric. Alternatively, a single second metric may be used to assess the validity of multiple metrics that comprise the first metric in the disclosed health metric validation system.
As one of skill in the art will readily understand, the first metric may comprise of metrics other than an EKG reading. In alternative embodiments, the first metric may be any of those listed above as metrics that may be collected by medical toilet 205. In other embodiments, the first metric may comprise of any of stress test, blood pressure, hematocrit, serum insulin level, hemoglobin A1c, breathing rate, blood urea nitrogen, serum creatinine, alanine am inotransferase, aspartate am inotransferase, alkaline phosphatase, serum bilirubin, serum total protein, serum albumin, serum gamma-glutamyl transpeptidase, prothrombin time, Holter monitoring, serum levels of a pharmaceutical product, and serum levels of a metabolite of a pharmaceutical product.
For example, if the individual's height is entered into computer 115, a body weight measurement may be used to calculate a body mass index (BMI) which is weight expressed in kilograms divided by height squared in meters (BMI=Weight/(Height)2). An extremely healthy and fit athlete with a low percent body fat may have a high BMI and erroneously be interpreted to be unhealthy. But, a follow-up metric comprising a bioimpedance measurement may be used to determine the user's percent body fat. If this follow-up metric suggests that the user does indeed have a low percent body fat, an alternative second set of rules may be applied to the first metric. In this situation, the report provided by computer 115 may indicate that the BMI is accurate, but not valid because the user has a body type for which BMI is not a useful indicator of health status.
Other physiological characteristics that may suggest that a follow-up metric would assist in interpreting the first metric include metrics which identify dehydration, hypervolemia, hypovolemia; pregnancy, electrolyte imbalance, the presence of a metabolite of a food that interferes with the accurate measurement of the first metric, and the presence of a pharmaceutical product or a metabolite thereof, when the pharmaceutical product or its metabolite interferes with the accurate measurement of the first metric.
For example, the first metric may be a cardiovascular indicator such as heart rate or blood pressure. If the first metric is outside of normal range, the data suggest that the user has a compromised overall health status. However, a follow-up metric that comprises an analysis of the same individual's urine may indicate dehydration. In this scenario, the abnormal heart rate or blood pressure are likely to be temporary. The follow-up metric may trigger the application of an alternative second set of rules to the first metric. The report provided by computer 115 after applying the alternative second set of rules may indicate that the heart rate or blood pressure measurement is accurate, but not valid because the user is dehydrated. A set of measurements taken at another time, this time when the individual is properly hydrated, may then be used to give a more accurate health status assessment.
In another example, a first metric may be a heart rate measurement taken by a medical toilet through a stethoscope positioned on the tank of the medical toilet. A user that is seated on the toilet leans back against the stethoscope to begin collection of the metric. However, if the user is wearing heavy clothing or not leaning squarely against the stethoscope, a valid heart rate metric may not be collected. A second metric may comprise of a temperature sensor that may be positioned near the stethoscope. The temperature detected by the temperature sensor may provide an indication of whether stethoscope is directly against the user's skin. If the measured temperature is significantly below normal body temperature, the indicator value for the heart rate metric may suggest poor validity. A follow-up metric that does not rely on the user's skin coming in contact with the stethoscope may provide more a more valid indicator of the user's health status. For example, a follow-up metric may comprise of an alternative method of measuring heart rate such as bioimpedance measurements.
In addition, the follow-up measurement may be accompanied by a third metric which may be used to assess the validity of the follow-up metric. In this embodiment, the process for evaluating the follow-up metric is similar or identical to that of the first measurement except that the first and second sets of rules are applied to follow-up metric and third metric as if they were the first metric and the second metric. A weight value and indicator value are assigned to the follow-up metric as they were for the first metric. This process may be repeated until a valid metric is acquired.
The first set of rules is applied to the first and second metrics. A weight value is assigned to the first metric. A second set of rules is applied to the weighted first metric and an indicator value is assigned to the weighted first metric. In this embodiment, the first and second sets of rules are those that are appropriate for processing the metrics according to the information about the user's physiological characteristic(s).
Both the first set of rules and the second set of rules may vary with each type of metric. This is because rules that are specifically relevant to the particular metric may be included in the sets.
Examples of parameters which may be addressed in the first set of rules may include consistency of first metric signal, strength of first metric signal, consistency of first metric signal relative to consistency of second metric signal, strength of first metric signal relative to strength of second metric signal, presence or absence of related analyte(s) in second metric, quantitative amount of related analyte(s) in second metric, presence or absence of a defined and measurable second metric signal, and a minimum or maximum value of a quantitative signal measured by a second metric.
Examples of parameters which may be addressed in the second set of rules may include whether the weight value is above a threshold defined for the first metric, whether the weight value is within a medium range defined for the first metric, whether the weight value is within a high range defined for the first metric, and whether the weight value indicates a need for a follow up metric.
While specific embodiments have been illustrated and described above, it is to be understood that the disclosure provided is not limited to the precise configuration, steps, and components disclosed. Various modifications, changes, and variations apparent to those of skill in the art may be made in the arrangement, operation, and details of the methods and systems disclosed, with the aid of the present disclosure.
Without further elaboration, it is believed that one skilled in the art can use the preceding description to utilize the present disclosure to its fullest extent. The examples and embodiments disclosed herein are to be construed as merely illustrative and exemplary and not a limitation of the scope of the present disclosure in any way. It will be apparent to those having skill in the art that changes may be made to the details of the above-described embodiments without departing from the underlying principles of the disclosure herein.
