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US 11,688,521 B2Granted
Risk stratification for adverse health outcomes
AssigneeHealth Solutions Research, Inc.
InventorsAjay Kumar Gupta, Ramani Peruvemba
Life of this patent
Estimating the term…
Abstract
Methods and systems to stratify risks for adverse health outcomes include aggregating data sets culled over a predetermined period of time; adjusting at least two variables within the aggregated data sets; and executing a regression analysis to identify an average causal effect between aggregated variables against at least one particular adverse health outcome.
Claims14
A method to stratify risks for adverse health outcomes, comprising:
- aggregating data sets from a predetermined period of time from health, social, and environmental resources to collect statistical reports for maternal and infant health, behavior, and/or demographic data;
- analyzing the aggregated data sets with a geospatial data analytic platform to establish a stratification for identifying mothers and infants at high risk of facing maternal mortality, maternal morbidity, infant mortality, or low birth weight for a child, wherein the analyzing comprises:
- adjusting at least two variables within the aggregated data sets;
- standardizing the at least two variables in the aggregated data sets to control differing data gathering capacities from the data sets;
- and
- executing an iterative correlation and a regression analysis to determine geospatial contributors of the maternal mortality, the maternal morbidity, the infant mortality, and the low birth weight for the child to identify the high risk mothers and infants based on the at least two variables, wherein a positive degree of correlation between the at least two variables is used to quantify individual risk factors of the mothers and the infants for the maternal mortality, the maternal morbidity, the infant mortality, and the low birth weight for the child;
- geospatially mapping the geospatial contributors of the maternal mortality, the maternal morbidity, the infant mortality, and the low birth weight for the child by visually representing the at least two variables on a map, wherein the mapping includes mapping the at least two variables having the positive degree of correlation as relevant numerators and denominators against each other to facilitate identification of key localities of at-risk mothers;
- and
- altering social and health interventions and policies directed to the at-risk mothers to reduce the maternal mortality, the maternal morbidity, the infant mortality, and the low birth weight for a child, including identifying the specific in-community locations where the delivery of clinical care will have the greatest impact on reducing preventable maternal and child health complications.
6 more elements
A non-transitory computer-readable medium having executable instructions stored thereon that, upon execution, cause one or more processors to:
- aggregate health data regarding a general population in a particular municipality over a predetermined period of time from health, social, and environmental resources to collect statistical reports for maternal and infant health, behavior, and/or demographic data;
- analyze the aggregated data sets using a geospatial data analytic platform to establish a stratification for identifying mothers and infants at high risk of facing maternal mortality, maternal morbidity, infant mortality, or low birth weight for a child, which comprises:
- adjusting at least two variables within the aggregated health data to eliminate subjects outside of an area of interest;
- standardizing the at least two variables in the aggregated data sets to control differing data gathering capacities from the data sets;
- and
- executing an iterative correlation and regression analysis to determine geospatial contributors of the maternal mortality, the maternal morbidity, the infant mortality, and the low birth weight for the child to identify high-risk mothers and infants based on the at least two variables, wherein a positive degree of correlation between the at least two variables is used to quantify individual risk factors of the mothers and the infants for the maternal mortality, the maternal morbidity, the infant mortality, and the low birth weight for the child;
- geospatially map the geospatial contributors of the maternal mortality, the maternal morbidity, the infant mortality, and the low birth weight for the child by visually representing the at least two variables on a map, wherein the mapping includes mapping the at least two variables having the positive degree of correlation as relevant numerators and denominators against each other to facilitate identification of key localities of at-risk mothers;
- and
- alter health policies directed to the at-risk mothers to reduce the maternal mortality, the maternal morbidity, the infant mortality, and the low birth weight for a child, including identifying the specific in-community locations where the delivery of clinical care will have the greatest impact on reducing preventable maternal and child health complications.
6 more elements
Dependencies are inferred from the claim text.