US 11,887,027 B1
Value of future adherence
Daniel Smith, McLean, VA (US); Joshua Benner, McLean, VA (US); Aaron McKethan, McLean, VA (US); and Loren Lidsky, McLean, VA (US)
Assigned to RXANTE, INC., Portland, ME (US)
Filed by RXANTE, INC., Portland, ME (US)
Filed on Jan. 30, 2023, as Appl. No. 18/103,015.
Application 18/103,015 is a continuation of application No. 16/918,517, filed on Jul. 1, 2020, granted, now 11,586,997.
Application 16/918,517 is a continuation of application No. 16/416,397, filed on May 20, 2019, granted, now 10,706,372, issued on Jul. 7, 2020.
Application 16/416,397 is a continuation of application No. 14/519,557, filed on Oct. 21, 2014, granted, now 10,318,897, issued on Jun. 11, 2019.
Claims priority of provisional application 61/893,750, filed on Oct. 21, 2013.
This patent is subject to a terminal disclaimer.
Int. Cl. G16H 10/60 (2018.01); G06Q 10/0631 (2023.01); G06Q 50/22 (2018.01)
CPC G06Q 10/0631 (2013.01) [G06Q 50/22 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system, comprising:
a processor; and
a memory configured to store computer readable instructions that, when executed by the processor, cause the system to:
generate a list of candidates using, at least, medical history data;
calculate one or more values associated with medication adherence for each candidate in the list of candidates, wherein calculating the one or more values includes:
determining a probability of non-adherence for each candidate in the list of candidates,
determining a probability of conversion from non-adherence to adherence for each candidate in the list of candidates, and
determining a cost reduction for each candidate, in the list of candidates, when the candidate is considered to be adherent;
calculate a score for each candidate by combining the probability of non-adherence, for each candidate, by the probability of conversion from non-adherence to adherence, for each candidate, and further combining the cost reduction for each candidate when the candidate is considered to be adherent;
apply the calculated score to each candidate and generate an ordered listing of each candidate;
based on the calculated score for each candidate, filter the ordered listing of each candidate;
generate a subset listing of candidates based on the filtered ordered listing; and
generate a user interface for display that includes, at least, the subset listing of each candidate, where each candidate in the subset listing is displayed in association with an indication of medication adherence and a value associated with the score and corresponding to possible future adherence to at least one medication for each candidate.