SYSTEM AND METHOD FOR A PATIENT DASHBOARD

1 . A computer-implemented method for providing measurable improvement in patient outcomes, the computer-implemented method comprising:

determining, by a dashboard computer having a processor, a memory, an interface, and a display, a medical recommendation for a patient in a medical care environment, the determining utilizing a machine learning algorithm, physician gestalt, evidence based guidelines, and clinical care bundles, wherein the physician gestalt is specific to the patient, wherein the evidence based guidelines are specific to the medical care environment, and wherein the clinical care bundles are associated with categories of treatment for the patient;

displaying, by the dashboard computer, the medical recommendation for the patient on the display;

receiving, by the dashboard computer through the interface, an outcome of the medical recommendation for the patient; and

updating, by the dashboard computer utilizing the outcome of the medical recommendation for the patient, the machine learning algorithm so as to improve recommendations made using the machine learning algorithm, wherein the recommendations thus improved provide a measurable improvement in patient outcomes.

2 . The computer-implemented method according to claim 1 , further comprising:

in a data repository, accumulating patient data from disparate sources; and

analyzing the patient data in the data repository, wherein the analyzing comprises determining a first trend in the patient data based on historical data associated with the patient.

3 . The computer-implemented method according to claim 2 , wherein the analyzing further comprises determining a second trend using, in addition to the historical data associated with the patient, historical values obtained from other patient data over time, such that the second trend includes correlated historical data associated with a plurality of patients.

4 . The computer-implemented method according to claim 1 , further comprising:

as data associated with the patient is collected from disparate sources, filtering the data associated with the patient based at least on a type of the patient to determine which data or what information derived from the data is to be presented on the display, including determining pertinent positives and pertinent negatives appropriate for the type of the patient, wherein the medical recommendation for the patient is one of the pertinent positives and pertinent negatives that exceeds a threshold associated with the machine learning algorithm.

5 . The computer-implemented method according to claim 4 , further comprising:

filtering the evidence based guidelines specific to the medical care environment using the data associated with the patient collected from the disparate sources.

6 . The computer-implemented method according to claim 4 , further comprising:

based on the patient's changing location within the medical care environment:

generating or discontinuing a location-specific guideline for the type of the patient; and

updating the display to reflect the generating or discontinuing the location-specific guideline for the type of the patient.

7 . The computer-implemented method according to claim 4 , wherein the disparate sources include a Health Level-7 (HL7) message feed.

8 . A patient dashboard system for providing measurable improvement in patient outcomes, the patient dashboard system comprising:

a display;

an interface;

a processor;

a non-transitory computer-readable medium; and

instructions stored on the non-transitory computer-readable medium and translatable by the processor for:

determining a medical recommendation for a patient in a medical care environment, the determining utilizing a machine learning algorithm, physician gestalt, evidence based guidelines, and clinical care bundles, wherein the physician gestalt is specific to the patient, wherein the evidence based guidelines are specific to the medical care environment, and wherein the clinical care bundles are associated with categories of treatment for the patient;

displaying the medical recommendation for the patient on the display;

receiving, through the interface, an outcome of the medical recommendation for the patient; and

updating, utilizing the outcome of the medical recommendation for the patient, the machine learning algorithm so as to improve recommendations made using the machine learning algorithm, wherein the recommendations thus improved provide a measurable improvement in patient outcomes.

9 . The patient dashboard system of claim 8 , wherein the instructions are further translatable by the processor for:

in a data repository, accumulating patient data from disparate sources; and

analyzing the patient data in the data repository, wherein the analyzing comprises determining a first trend in the patient data based on historical data associated with the patient.

10 . The patient dashboard system of claim 9 , wherein the analyzing further comprises determining a second trend using, in addition to the historical data associated with the patient, historical values obtained from other patient data over time, such that the second trend includes correlated historical data associated with a plurality of patients.

11 . The patient dashboard system of claim 8 , wherein the instructions are further translatable by the processor for:

as data associated with the patient is collected from disparate sources, filtering the data associated with the patient based at least on a type of the patient to determine which data or what information derived from the data is to be presented on the display, including determining pertinent positives and pertinent negatives appropriate for the type of the patient, wherein the medical recommendation for the patient is one of the pertinent positives and pertinent negatives that exceeds a threshold associated with the machine learning algorithm.

12 . The patient dashboard system of claim 11 , wherein the instructions are further translatable by the processor for:

filtering the evidence based guidelines specific to the medical care environment using the data associated with the patient collected from the disparate sources.

13 . The patient dashboard system of claim 11 , wherein the instructions are further translatable by the processor for:

based on the patient's changing location within the medical care environment:

generating or discontinuing a location-specific guideline for the type of the patient; and

updating the display to reflect the generating or discontinuing the location-specific guideline for the type of the patient.

14 . The patient dashboard system of claim 11 , wherein the disparate sources include a Health Level-7 (HL7) message feed.

15 . A computer program product for providing measurable improvement in patient outcomes, the computer program product comprising a non-transitory computer-readable medium storing instructions translatable by a processor of a patient dashboard system for:

determining a medical recommendation for a patient in a medical care environment, the determining utilizing a machine learning algorithm, physician gestalt, evidence based guidelines, and clinical care bundles, wherein the physician gestalt is specific to the patient, wherein the evidence based guidelines are specific to the medical care environment, and wherein the clinical care bundles are associated with categories of treatment for the patient;

displaying the medical recommendation for the patient on the display;

receiving, through the interface, an outcome of the medical recommendation for the patient; and

updating, utilizing the outcome of the medical recommendation for the patient, the machine learning algorithm so as to improve recommendations made using the machine learning algorithm, wherein the recommendations thus improved provide a measurable improvement in patient outcomes.

16 . The computer program product of claim 15 , wherein the instructions are further translatable by the processor for:

in a data repository, accumulating patient data from disparate sources; and

analyzing the patient data in the data repository, wherein the analyzing comprises determining a first trend in the patient data based on historical data associated with the patient.

17 . The computer program product of claim 16 , wherein the analyzing further comprises determining a second trend using, in addition to the historical data associated with the patient, historical values obtained from other patient data over time, such that the second trend includes correlated historical data associated with a plurality of patients.

18 . The computer program product of claim 15 , wherein the instructions are further translatable by the processor for:

as data associated with the patient is collected from disparate sources, filtering the data associated with the patient based at least on a type of the patient to determine which data or what information derived from the data is to be presented on the display, including determining pertinent positives and pertinent negatives appropriate for the type of the patient, wherein the medical recommendation for the patient is one of the pertinent positives and pertinent negatives that exceeds a threshold associated with the machine learning algorithm.

19 . The computer program product of claim 18 , wherein the instructions are further translatable by the processor for:

filtering the evidence based guidelines specific to the medical care environment using the data associated with the patient collected from the disparate sources.

20 . The computer program product of claim 18 , wherein the instructions are further translatable by the processor for:

based on the patient's changing location within the medical care environment:

generating or discontinuing a location-specific guideline for the type of the patient; and

updating the display to reflect the generating or discontinuing the location-specific guideline for the type of the patient.