US 11,694,239 B2
Method of optimizing patient-related outcomes
Shahram Shawn Dastmalchi, San Ramon, CA (US); Vishnuvyas Sethumadhavan, Mountain View, CA (US); Mary Ellen Campana, San Mateo, CA (US); Robert Derward Rogers, Pleasanton, CA (US); and Imran N. Chaudri, Potomac, MD (US)
Assigned to APIXIO, INC., San Mateo, CA (US)
Filed by APIXIO, INC., San Mateo, CA (US)
Filed on Nov. 9, 2021, as Appl. No. 17/522,649.
Application 17/522,649 is a continuation of application No. 13/801,947, filed on Mar. 13, 2013, granted, now 11,195,213.
Application 13/801,947 is a continuation in part of application No. 13/223,228, filed on Aug. 31, 2011, granted, now 10,176,541, issued on Jan. 8, 2019.
Claims priority of provisional application 61/639,805, filed on Apr. 27, 2012.
Claims priority of provisional application 61/379,228, filed on Sep. 1, 2010.
Prior Publication US 2022/0101395 A1, Mar. 31, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 30/02 (2023.01); G06Q 30/0283 (2023.01); G06Q 40/08 (2012.01); G16H 10/20 (2018.01); G16H 10/60 (2018.01); G16H 50/70 (2018.01)
CPC G06Q 30/0283 (2013.01) [G06Q 40/08 (2013.01); G16H 10/20 (2018.01); G16H 10/60 (2018.01); G16H 50/70 (2018.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for knowledge extraction and exchange, the method implemented by a Medical Information Navigation Engine (“MINE”) including at least one processor, the method comprising:
converting, by the at least one processor, medical information formatted in various formats into a format to facilitate search speed for data queried from the medical information, the medical information associated with a plurality of patients;
generating, by the at least one processor and using the converted medical information, a plurality of patient state timelines, wherein each patient state timeline corresponds to a particular patient of the plurality of patients, wherein each patient state timeline is an ordering of individual states in a time order, and wherein a subset of the plurality of patient state timelines includes at least one state of interest;
generating, by the at least one processor, a plurality of impact measures for each of the plurality of patient state timelines, wherein each impact measure is a cost of services provided at a given time to transition from one state to another;
generating, by the at least one processor, a probability distribution of future impacts by summing all impact measures after the at least one state of interest occurs for each of the subset of the plurality of patient state timelines;
generating, by the at least one processor, a suggestion model by analyzing the probability distribution of future impacts to select actions that change a likelihood of a future outcome that maximizes at least one organizational objective; and
applying, by the at least one processor, the suggestion model to one patient state timeline to generate recommendations for the corresponding patient.