SYSTEMS AND METHODS FOR ELECTRONIC HEALTH RECORDS
A method of generating a clinically supplemented risk score using data from an electronic health record system can include collecting data from a plurality of electronic health records; parsing the data into defined fields; comparing the parsed data to at least one look-up table to generate an inferred diagnostic condition; comparing the inferred diagnostic condition to a documented diagnostic condition; mapping the inferred diagnostic condition to at least one condition category; refining the at least one mapped inferred diagnostic condition into a hierarchy to generate a hierarchal mapped conditioned category; and determining via a processor, a risk score in response to the inferred diagnostic condition for the patient in response to the hierarchal mapped conditioned category, the risk score representing an expected total cost of care for the patient relative to the average per-patient cost of care over an entire population.
1 . A method of generating a clinically supplemented risk score by an electronic health record system having one or more processors, the method comprising:
collecting, via at least one of the one or more processors, data from a plurality of electronic health records of a patient;
parsing, via at least one of the one or more processors, the data into defined fields to generate parsed data;
comparing, via at least one of the one or more processors, the parsed data to at least one look-up table to generate an inferred diagnostic condition;
comparing, via at least one of the one or more processors, the inferred diagnostic condition to a documented diagnostic condition of the patient in the plurality of electronic health records;
mapping, via at least one of the one or more processors, the inferred diagnostic condition to at least one condition category to generate at least one mapped inferred diagnostic condition;
refining, via at least one of the one or more processors, the at least one mapped inferred diagnostic condition into a hierarchy to generate a hierarchal mapped conditioned category; and
determining, via at least one of the one or more processors, a risk score in response to the inferred diagnostic condition for the patient in response to the hierarchal mapped conditioned category, the risk score representing an expected total cost of care for the patient relative to the average per-patient cost of care over an entire population.
2 . The method as recited in claim 1 , further comprising identifying a physician associated with determining the documented diagnostic condition.
3 . The method as recited in claim 1 , further comprising identifying that the inferred diagnostic condition is associated with a medication.
4 . The method as recited in claim 1 , wherein the inferred diagnostic condition is determined retroactively.
5 . The method as recited in claim 1 , wherein the collecting data includes the collection of data from a source that is a closed gap that represents a condition for which there is documentation.
6 . The method as recited in claim 5 , wherein the closed gap is associated with the documented diagnostic condition.
7 . The method as recited in claim 5 , wherein the closed gap is associated with a physician that delivered the documented diagnostic condition.
8 . The method as recited in claim 1 , wherein the parsed data is based on a presence of a diagnosis code.
9 . The method as recited in claim 8 , wherein comparing the parsed data includes processing text notations to identify phrases that are then mapped to the diagnosis code.
10 . The method as recited in claim 9 , wherein comparing the parsed data includes identifying a previously un-notated condition.
11 . The method as recited in claim 1 , wherein the inferred diagnostic condition is inferred from medication records.
12 . The method as recited in claim 1 , wherein the inferred diagnostic condition is inferred from laboratory results.
13 . The method as recited in claim 1 , wherein the inferred diagnostic condition is inferred from patient vitals over a time period.
14 . The method as recited in claim 1 , further comprising:
determining the inferred diagnostic condition from a subset of the data;
determining the lack of an associated diagnosis code for the inferred diagnostic condition in the plurality of electronic health records of a patient; and
identifying the inferred diagnostic condition as a risk.
15 . The method as recited in claim 14 , wherein the subset of the data is from at least one of medication records, laboratory results and patient vitals over a time period.
16 . A method of generating a clinically supplemented risk score by an electronic health record system having one or more processors, the method comprising:
collecting data from a plurality of electronic health records of a patient via an electronic health record system having one or more processors;
determining, via at least one of the one or more processors, an inferred diagnostic condition from the plurality of electronic health records;
determining, via at least one of the one or more processors, the lack of an associated documented diagnostic condition for the inferred diagnostic condition;
identifying, via at least one of the one or more processors, the inferred diagnostic condition as a risk; and
determining, via at least one of the one or more processors, a risk score including the inferred diagnostic condition for the patient, the risk score representing an expected total cost of care for the patient relative to the average per-patient cost of care over an entire population.
17 . The method as recited in claim 16 , wherein the documented diagnostic condition is based on a diagnosis code.
18 . The method as recited in claim 17 , further composing processing text notations to identify phrases that are then mapped to the diagnosis code.
19 . The method as recited in claim 16 , wherein determining the inferred diagnostic condition is from parsed data.
20 . The method as recited in claim 19 , wherein the parsed data includes at least one of medication records, laboratory results, and patient vitals over a time period.