System and method of prioritizing patients for clinician management

Patent metadata

Field	Value
Publication number	US-2020242566-A1
Application number	US-201916262592-A
Country	US
Kind code	A1
Filing date	Jan 30, 2019
Priority date	Jan 30, 2019
Publication date	Jul 30, 2020
Grant date	—

Abstract

A system for prioritizing patients for clinician management that includes one or more processors configured to execute program instructions. When executed the one or more processors determine a risk score for a patient, alter the risk score based on patient based parameters to determine a priority score of the patient, compare the priority score of the patient to priority scores of other patients, assign a rank to the patient based on the comparison of the priority score of the patient to the priority scores of the other patients, and schedule an appointment for the patient based on the rank.

First claim

What is claimed is:

1 . A system for prioritizing patients for clinician management comprising:
one or more processors configured to execute program instructions to:
determine a risk score for a patient;
alter the risk score based on patient based parameters to determine a priority score of the patient;
compare the priority score of the patient to priority scores of other patients;
assign a rank to the patient based on the comparison of the priority score of the patient to the priority scores of the other patients; and
schedule an appointment for the patient based on the rank.

2 . The system of claim 1 , wherein determining the priority score for a patient comprises:
estimating a probability of a predetermined event to determine the risk score for the patient; determining a time period since a last appointment; receiving medication titration data; inputting the probability of the predetermined event, the time period since the last appointment, and medication titration data into a patient prioritization algorithm.

3 . The system of claim 2 , wherein estimating the probability of the predetermined event comprises:
monitoring pulmonary artery pressure with a sensor to detect pulmonary artery pressure data; recording the pulmonary artery pressure data detected by the sensor; and calculating a risk estimate based on the recorded pulmonary artery pressure data.

4 . The system of claim 3 , wherein calculating the risk estimate includes determining one of patient heart rate or medication usage.

5 . The system of claim 3 , wherein estimating the probability of the predetermined event further comprises:
calculating the probability of the predetermined event based on historical data.

6 . The system of claim 6 , wherein the historical data includes one of previous patient risk estimates, patient co-morbidities, demographics, or medication changes.

7 . The system of claim 2 , wherein the predetermined event is heart failure.

8 . The system of claim 1 , wherein determining the risk score for the patient further comprises:
forming a linear model; receiving systolic pulmonary artery pressure, diastolic pulmonary artery pressure, and heart rate data from an existing group of patients; creating a generalizable estimator based on the received systolic pulmonary artery pressure, diastolic pulmonary artery pressure, and heart rate data from an existing group of patients; monitoring pulmonary artery pressure with a sensor to detect pulmonary artery pressure data; and utilizing the pulmonary artery pressure in with the generalizable estimator.

9 . The system of claim 1 , wherein determining the risk score for the patient further comprises:
forming a non-linear model; monitoring pulmonary artery pressure with a sensor to detect pulmonary artery pressure data; and utilizing the pulmonary artery pressure data in the non-linear model.

10 . A system for prioritizing patients for clinician management comprising:
one or more processors configured to execute program instructions to:
receive a risk score for a patient inputted into the one or more processors at an interface;
determine a first variable related to the patient based on historical data;
alter the risk score by a predetermined amount based on the determined first variable to provide an updated risk score;
determine a second variable related to the patient based on sensor data received by the one or more processors;
alter the updated risk score based on the determined second variable to provide a priority score of the patient;
compare the priority score of the patient to priority scores of other patients;
assign a ranking to the patient based on the comparison of the priority score of the patient to the priority scores of the other patients; and
schedule an appointment for the patient based on the ranking.

11 . The system of claim 10 , wherein the historical data includes one of previous patient risk estimates, patient co-morbidities, demographics, or medication changes.

12 . The system of claim 10 , wherein altering the risk score by a predetermined amount includes subtracting from the risk score.

13 . A method of prioritizing patients for clinician management comprising:
monitoring pulmonary artery pressure with a sensor to detect pulmonary artery pressure data; estimating the probability a patient will have a heart failure event during a predetermined period based on the detected pulmonary artery pressure data; determining a risk score for the patient based on the probability the patient will have the heart failure event during a predetermined period; altering the risk score based on patient based parameters to determine a priority score of the patient; comparing the priority score of the patient to priority scores of other patients; assigning a rank to the patient based on the comparison of the priority score of the patient to the priority scores of the other patients; and scheduling an appointment for the patient based on the rank.

14 . The method of claim 13 , wherein determining the priority score for the patient comprises:
determining a time period since a last appointment; receiving medication titration data; inputting the probability the patient will have the heart failure event during the predetermined period, the time period since the last appointment, and medication titration data into a patient prioritization algorithm.

15 . The method of claim 14 , further comprising:
determining a first weight related to the inputted probability the patient will have the heart failure event during the predetermined period; determining a second weight related to the inputted time period since the last appointment; and determining a third weight related to the inputted medication titration data.

16 . The method of claim 14 , wherein the medication titration data includes change in medication usage data.

17 . The method of claim 13 , wherein estimating the probability the patient will have the heart failure event during the predetermined period based on the detected pulmonary artery pressure data further comprises:
receiving historical data related to the probability the patient will have the heart failure event during the predetermined period; and comparing the historical data to the detected pulmonary artery pressure data.

18 . The method of claim 13 , wherein estimating the probability the patient will have the heart failure event during the predetermined period based on the detected pulmonary artery pressure data further comprises:
receiving historical data related to the probability the patient will have the heart failure event during the predetermined period; and inputting the historical data into a risk score algorithm.

19 . The method of claim 18 , wherein the historical data includes one of previous patient risk estimates, patient comorbidities, demographics, or medication changes.

20 . The method of claim 18 , wherein detecting pulmonary artery pressure data includes forming a pulmonary pressure waveform and extracting the detected pulmonary artery pressure data from the detected pulmonary pressure waveform; and
wherein the risk score is determined utilizing the risk score algorithm and the detected pulmonary artery pressure data.

Assignees

• Pacesetter Inc

Inventors

• Agarwal Rahul
• Bharmi Rupinder
• Kerr Matthew S D
• Adamson Phillip B
• Dalal Nirav

Classifications

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• G06N3/092

  Reinforcement learning · CPC title

• G06Q10/1093 Primary

  Calendar-based scheduling for persons or groups · CPC title

• G06N3/08

  Learning methods · CPC title

• G16H50/30

  for calculating health indices; for individual health risk assessment · CPC title