Methods of Assessing Risk Based on Medical Data and Uses Thereof

• US 20100100392A1
• Filed: 10/21/2009
• Published: 04/22/2010
• Est. Priority Date: 10/21/2008
• Status: Active Grant

• Current Assignee: Spacelabs Healthcare LLC (OSI Systems Incorporated)
• Original Assignee: Rothman Healthcare Research, LLC
• Inventors: Rothman, Steven I., Rothman, Michael J.
• Granted Patent: US 8,355,925 B2
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16H 70/60 relating to pathologies

Abstract

Methods of assessing risk based on medical data are disclosed herein. In an embodiment, a method of assessing risk associated with medical data includes creating a dataset representing a plurality of patients, the dataset comprising (x,y) pairs for each patient, wherein x represents the medical data collected at a first time, and wherein y is an outcome measurement collected at a second time; binning the (x,y) pairs to form a plurality of binned data sets; computing an average value for x and an average value for y for each binned data set; determining a minimum average value of y based on all of the average values of y; subtracting the minimum average value of y from each average value of y to get a new average value of y for each binned data set; and deriving a function for assessing risk associated with the medical data.

Claims

1. A method of assessing risk associated with medical data comprising:

creating, by a computer, a dataset representing a plurality of patients, the dataset comprising (x,y) pairs for each patient, wherein x represents the medical data collected at a first time, and wherein y is an outcome measurement collected at a second time;

binning, by a computer, the (x,y) pairs to form a plurality of binned data sets;

computing, by a computer, an average value for x and an average value for y for each binned data set;

determining, by a computer, a minimum average value of y based on all of the average values of y;

subtracting, by a computer, the minimum average value of y from each average value of y to get a new average value of y for each binned data set; and

deriving, by a computer, a function for assessing risk associated with the medical data.

2. The method of claim 1 wherein the medical data for each patient is collected at discharge of the patient from a facility of care.

3. The method of claim 1 wherein the outcome measurement represents a mortality of each of the patients.

4. The method of claim 1 wherein the outcome measurement for each patient is collected one-year post discharge.

5. The method of claim 1 wherein the deriving of the function comprises:

computing, by a computer, a first function defined from average minimum value of x to average maximum value of x;

adding, by a computer, a second constant function to the first function, wherein the constant function covers values of x less than the average minimum value of x; and

adding, by a computer, a third constant function to the first function and the second constant function, wherein the third constant function covers values of x and greater than the average maximum value of x.

6. The method of claim 1 wherein the function defines excess risk due to deviation from normative values.

7. The method of claim 1 wherein the medical data is selected from one of a continuous variable, an ordinal score, a categorical class, a binary assessment or combinations thereof.

8. The method of claim 7 wherein the continuous variable is selected from the group consisting of albumin/globulin (A/G) ratio, an alanine aminotransferase (ALT or SGPT) value, an aspartate aminotransferase (AST or SGOT) value, an albumin value, an alkaline phosphatase value, a blood urea nitrogen (BUN) value, a calcium value, a carbon dioxide (CO₂) value, a chloride value, a creatinine value, a globulin value, a glucose value, a potassium value, a sodium value, a total bilirubin value, a total protein value, a tropon value, a base excess value, a fraction of inspired oxygen (FiO₂) value, a bicarbonate (HCO₃) value, a partial pressure of carbon dioxide (PCO₂) value, a partial pressure of oxygen (PO₂) value, a pH value, a hematocrit percentage, a hemoglobin value, a white blood cell count, a heart rate value, a diastolic blood pressure value, a systolic blood pressure value, a respiration rate, a percentage of arterial hemoglobin in oxyhemoglobin configuration (pulse Ox) and a temperature value.

9. The method of claim 7 wherein the ordinal score is a Braden Scale score.

10. The method of claim 7 wherein the categorical class is selected from the group consisting of sinus bradycardia, sinus rhythm, heart block, paced, atrial fibrillation, atrial flutter, sinus tachycardia and junctional rhythm.

11. The method of claim 7 wherein the binary assessment is a nursing assessment selected from the group consisting of a food assessment, a neurological assessment, a psychiatric assessment, a safety assessment, a skin assessment, a genitourinary assessment, a muscular-skeletal assessment, a respiratory assessment, a cardiac assessment, a peripheral vascular assessment, a gastrointestinal assessment, a Braden scale assessment and a pain assessment.

12. The method of claim 1 wherein the derived function can be used in calculating an overall risk inherent in a patient'"'"'s medical condition.

13. The method of claim 1 wherein the derived function can be used in determining a risk inherent in a value of corresponding medical data from a patient.

14. A method of determining an overall risk inherent in a patient'"'"'s current condition comprising:

receiving, by a computer, a plurality of medical data from an admitted patient;

converting, by a computer, each of the admitted patient'"'"'s medical data to Health Score values using a set of functions, wherein each of the functions defines risk associated with each of the medical data;

combining, by a computer, the Health Score values;

generating, by a computer, a Health Score from the combined data, the Health Score representing the admitted patient'"'"'s health; and

displaying, by a computer, the Health Score.

15. The method of claim 14 wherein the medical data is selected from one of a continuous variable, an ordinal score, a categorical class, a binary assessment or combinations thereof.

16. The method of claim 14 wherein the set of functions is derived using the following steps:

(a) creating, by a computer, a dataset representing a plurality of discharged patients, the dataset comprising (x,y) pairs for each patient, wherein x represents a single type of medical data collected at a first time, and wherein y is an outcome measurement collected at a second time;

(b) binning, by a computer, the (x,y) pairs to form a plurality of binned data sets;

(c) computing, by a computer, an average value for x and an average value for y for each binned data set;

(d) determining, by a computer, a minimum average value of y based on all of the average values of y;

(e) subtracting, by a computer, the minimum average value of y from each average value of y to get a new average value of y for each binned data set;

(f) deriving, by a computer, a function for assessing risk associated with the single type of medical data; and

(g) repeating steps (a)-(f) for other types of medical data to derive the set of functions.

17. The method of claim 16 wherein the medical data for each discharged patient is collected at discharge of the patient from a facility of care.

18. The method of claim 16 wherein the outcome measurement represents a mortality of each of the discharged patients.

19. The method of claim 16 wherein at least some of the functions are derived using the following steps:

computing, by a computer, a first function defined from average minimum value of x to average maximum value of x; and

adding, by a computer, a second constant function to the first function, wherein the constant function covers values of x less than the average minimum value of x; and

adding, by a computer, a third constant function to the first function and the second constant function, wherein the third constant function covers values of x and greater than the average maximum value of x.

20. A method of assessing excess risk associated with medical data comprising:

creating, by a computer, a dataset representing a plurality of patients, the dataset comprising (x,y) pairs for each patient, wherein x represents the medical data collected at a first time, and wherein y is an outcome measurement collected at a second time;

binning, by a computer, the (x,y) pairs to form a plurality of binned data sets;

computing, by a computer, an average value for x and an average value for y for each binned data set;

determining, by a computer, a minimum average value of y based on all of the average values of y;

subtracting, by a computer, the minimum average value of y from each average value of y to get a new average value of y for each binned data set; and

deriving, by a computer, a function for assessing excess risk associated with the medical data.