Systems and Methods for Predicting Metabolic and Bariatric Surgery Outcomes

Patent metadata

Field	Value
Publication number	US-2017286610-A9
Application number	US-201514983083-A
Country	US
Kind code	A9
Filing date	Dec 29, 2015
Priority date	Sep 21, 2012
Publication date	Oct 5, 2017
Grant date	—

Abstract

Various systems and methods for predicting metabolic and bariatric surgery outcomes are provided. The systems and methods can also provide predictions for non-surgical metabolic and bariatric treatments. In general, a user can receive predictive outcomes of multiple bariatric procedures that could be performed on a patient. In one embodiment, a user can electronically access a metabolic and bariatric surgery outcome prediction system, e.g., using one or more web pages. The system can provide predictive outcomes of one or more different bariatric surgeries for the patient based on data gathered from the user and on historical data regarding outcomes of the different bariatric surgeries. The system can additionally provide predictive outcomes for not having any treatment and/or a comparison of the predictive outcomes of the one or more different bariatric surgeries to the predictive outcomes for not having any treatment.

First claim

What is claimed is:

1 - 19 . (canceled)

20 . A medical method, comprising:
receiving data over a network from a client terminal indicative of at least two characteristics specific to a patient; and predicting a risk of complications to the patient for each a plurality of different treatments that may be performed in the future for the patient and that if performed in the future for the patient would have a metabolic effect on the patient, the predicting including evaluating each of the plurality of treatments with respect to the received data, and the predicted risk of complications being effective to assist a medical professional in determining which one or more of the different treatments should be performed in the future for the patient.

21 . The method of claim 20 , wherein at least two of the treatments include different types of bariatric surgery.

22 . The method of claim 21 , wherein the types of bariatric surgery include sleeve gastrectomy, gastric banding, gastric bypass, biliopancreatic diversion, adjustable gastric banding, vertical banded gastroplasty, intragastric balloon therapy, gastric plication, Magenstrasse and Mill, small bowel transposition, biliary diversion, procedures involving an anastomotic connection of the gastrointestinal tract, and duodenal endoluminal barrier.

23 . The method of claim 20 , wherein at least one of the treatments includes a non-surgical treatment.

24 . The method of claim 23 , wherein the non-surgical treatment includes pharmaceutical therapy.

25 . The method of claim 20 , wherein at least one of the treatments includes bariatric surgery and at least one of the treatments includes a non-surgical treatment.

26 . The method of claim 20 , wherein the at least two characteristics specific to the patient include two or more of a height of the patient, a weight of the patient, a gender of the patient, an age of the patient, a medical history of the patient, a medical status of the patient, a body mass index (BMI) of the patient, an ethnicity of the patient, a medical prescription history of the patient, a medical prescription status of the patient, types of medical treatments for obesity previously received by the patient, types of medical treatments for health issues other than obesity previously received by the patient, insurance information for the patient, diet information for the patient, psychological history of the patient, and a genetic indicator of the patient.

27 . The method of claim 20 , wherein the at least two characteristics specific to the patient include two or more of a height of the patient, a weight of the patient, a body mass index (BMI) of the patient, a medical prescription history of the patient, a medical history of the patient, a capacity of physical activity of the patient, an education level of the patient, and a gender of the patient.

28 . The method of claim 20 , further comprising, for each of the plurality of different treatments, identifying historical data indicative of actual complications experienced by each of a plurality of patients having had the treatment performed thereon, wherein the predicting also includes evaluating each of the plurality of treatments with respect to the historical data.

29 . The method of claim 28 , wherein each of the plurality of patients is associated with at least two characteristics specific thereto that corresponds to the at least two characteristics specific to the patient.

30 . The method of claim 20 , wherein the predicting includes a processor executing a model in which each of the at least two characteristics specific to the patient are evaluated with respect to each of the plurality of different treatments.

31 . The method of claim 20 , wherein each of the characteristics specific to the patient is associated with a variable, the risk of each of complications for each of the plurality of different treatments is associated with a variable, and the predicting includes determining correlations for each of the variables associated with the characteristics specific to the patient with each of the variables associated with the plurality of different treatment.

32 . The method of claim 20 , further comprising causing the predicted risk of complications for each of the plurality of different treatments to be displayed to the medical professional on a client station.

33 . A medical system, comprising:
a network interface configured to receive data over a network from a client terminal indicative of at least two characteristics specific to a patient; a memory storing instructions therein; and a processor configured to execute the instructions and thereby predict a risk of complications to the patient for each a plurality of different treatments that may be performed in the future for the patient and that if performed in the future for the patient would have a metabolic effect on the patient, the predicting including evaluating each of the plurality of treatments with respect to the received data, and the predicted risk of complications being effective to assist a medical professional in determining which one or more of the different treatments should be performed in the future for the patient.

34 . The system of claim 33 , wherein at least two of the treatments include different types of bariatric surgery.

35 . The system of claim 33 , wherein at least one of the treatments includes a non-surgical treatment.

36 . The system of claim 33 , wherein at least one of the treatments includes bariatric surgery and at least one of the treatments includes a non-surgical treatment.

37 . The system of claim 33 , wherein the instructions include a model in which each of the at least two characteristics specific to the patient are evaluated with respect to each of the plurality of different treatments, and the processor executing the instructions includes the processor executing the model.

38 . The system of claim 33 , wherein each of the characteristics specific to the patient is associated with a variable, the risk of each of complications for each of the plurality of different treatments is associated with a variable, and executing the instructions includes the processor determining correlations for each of the variables associated with the characteristics specific to the patient with each of the variables associated with the plurality of different treatment.

39 . A medical method, comprising:
receiving an input indicative of a plurality of patient-specific characteristics, the plurality of patient-specific characteristics including two or more of a height of the patient, a weight of the patient, a gender of the patient, an age of the patient, a medical history of the patient, a medical status of the patient, a body mass index (BMI) of the patient, an ethnicity of the patient, a medical prescription history of the patient, a medical prescription status of the patient, types of medical treatments for obesity previously received by the patient, types of medical treatments for health issues other than obesity previously received by the patient, insurance information for the patient, diet information for the patient, psychological history of the patient, and a genetic indicator of the patient; storing the input indicative of the plurality of patient-specific characteristics in a memory; receiving an input indicative of a plurality of different treatments that may be performed in the future for the patient and that if performed in the future for the patient would have a metabolic e

Assignees

• Ethicon Endo Surgery Inc

Inventors

• Harris Jason L
• Hess Christopher J
• Jain Nitin Kumar
• Francis Diane M
• Albrecht Thomas E
• Hunter Tina Denise

Classifications

• G06F19/345 Primary

  Physics · mapped topic

• G06N5/04

  Inference or reasoning models · CPC title

• G16H50/20 Primary

  for computer-aided diagnosis, e.g. based on medical expert systems · CPC title