Systems, methods and apparatuses for predicting capacity of resources in an institution
First Claim
1. A method comprising:
- analyzing data comprising information associated with a health care entity, said data comprising clinical data associated with one or more patients currently within the health care entity, wherein at least some of the data is generated in real-time during an actual time in which one or more events occur;
using at least a portion of the data to generate one or more predictions regarding one or more conditions to occur in the future that are associated with one or more resources of the entity;
analyzing, via a processor, one or more results of the predictions and recommending an allocation of at least one of the one or more resources on the basis of the results;
determining that one of the one or more conditions corresponds to a number of patient transfers and a number of patient discharges during a predetermined time period in the future;
determining that another of the conditions corresponds to a number of beds or rooms in one or more units of the entity that will be available at a predetermined time or during a predetermined time period in the future;
determining that another of the conditions corresponds to one or more levels of congestion within one or more units of the entity, the congestion corresponds to a number of patients assigned to a respective unit, the levels of congestion being determined based in part on a comparison of at least a subset of the number of the beds or rooms that are determined as unoccupied by a patient to a predetermined threshold signifying a level of patient congestion for the respective unit;
determining that the respective unit is congested with patients in an instance in which the number of the beds or the rooms that are determined as unoccupied is below the predetermined threshold;
utilizing at least one of the levels of congestion to determine whether to assign one or more other patients to another respective unit of the entity; and
generating at least one recommendation of a number of persons to schedule for providing medical care for a time period in the future for the patients in at least one of the units based in part on a prediction of a number of patients expected to occupy the unit during the time period in the future, wherein the number of persons to schedule and the prediction of the number of patients is determined based in part on analyzing historical data indicating an average patient to medical personnel ratio within the unit during a corresponding time period in the past.
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Accused Products
Abstract
A method, apparatus, system and computer program product are provided for determining one or more current or future conditions regarding capacity and allocation of resources in an institution. The apparatus enables personnel to utilize predictive tools to identify in real-time or in the near future areas of capacity constraints within the institution. The apparatus includes a processor configured to analyze data which includes information associated with the institution. A portion of the data is generated in real-time during an actual time in which events occur. The processor is capable of using at least a portion of the data to identify current conditions or generate one or more predictions regarding conditions to occur in the future that are associated with resources and capacity of the institution. Also, the processor is capable of analyzing results of the predictions and allocating resources of the institution on the basis of the predicted results.
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Citations
23 Claims
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1. A method comprising:
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analyzing data comprising information associated with a health care entity, said data comprising clinical data associated with one or more patients currently within the health care entity, wherein at least some of the data is generated in real-time during an actual time in which one or more events occur; using at least a portion of the data to generate one or more predictions regarding one or more conditions to occur in the future that are associated with one or more resources of the entity; analyzing, via a processor, one or more results of the predictions and recommending an allocation of at least one of the one or more resources on the basis of the results; determining that one of the one or more conditions corresponds to a number of patient transfers and a number of patient discharges during a predetermined time period in the future; determining that another of the conditions corresponds to a number of beds or rooms in one or more units of the entity that will be available at a predetermined time or during a predetermined time period in the future; determining that another of the conditions corresponds to one or more levels of congestion within one or more units of the entity, the congestion corresponds to a number of patients assigned to a respective unit, the levels of congestion being determined based in part on a comparison of at least a subset of the number of the beds or rooms that are determined as unoccupied by a patient to a predetermined threshold signifying a level of patient congestion for the respective unit; determining that the respective unit is congested with patients in an instance in which the number of the beds or the rooms that are determined as unoccupied is below the predetermined threshold; utilizing at least one of the levels of congestion to determine whether to assign one or more other patients to another respective unit of the entity; and generating at least one recommendation of a number of persons to schedule for providing medical care for a time period in the future for the patients in at least one of the units based in part on a prediction of a number of patients expected to occupy the unit during the time period in the future, wherein the number of persons to schedule and the prediction of the number of patients is determined based in part on analyzing historical data indicating an average patient to medical personnel ratio within the unit during a corresponding time period in the past. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. An apparatus comprising:
at least one processor and at least one memory storing computer code, which when executed by the processor causes the apparatus to; analyze data comprising information associated with a health care entity, said data comprising clinical data associated with one or more patients currently within the health care entity, wherein at least some of the data is generated in real-time during an actual time in which one or more events occur; use at least a portion of the data to generate one or more predictions regarding one or more conditions to occur in the future that are associated with one or more resources of the entity; analyze one or more results of the predictions and recommend an allocation of at least one of the one or more resources on the basis of the results; determine that one of the one or more conditions corresponds to a number of patient transfers and a number of patient discharges during a predetermined time period in the future; determine that another of the conditions corresponds to a number of beds or rooms in one or more units of the entity that will be available at a predetermined time or during a predetermined time period in the future; determine that another of the conditions corresponds to one or more levels of congestion within one or more units of the entity, the congestion corresponds to a number of patients assigned to a respective unit, the levels of congestion being determined based in part on a comparison of at least a subset of the number of the beds or rooms that are determined as unoccupied by a patient to a predetermined threshold signifying a level of patient congestion for the respective unit; determine that the respective unit is congested with patients in an instance in which the number of the beds or the rooms that are determined as unoccupied is below the predetermined threshold; utilize at least one of the levels of congestion to predict whether to assign one or more other patients to another respective unit of the entity; and generate at least one recommendation of a number of persons to schedule for providing medical care for a time period in the future for the patients in at least one of the units based in part on a prediction of a number of patients expected to occupy the unit during the time period in the future, wherein the number of persons to schedule and the prediction of the number of patients is determined based in part on analyzing historical data indicating an average patient to medical personnel ratio within the unit during a corresponding time period in the past. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17)
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18. A computer program product, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising:
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a first executable portion for analyzing data, comprising information associated with an entity, said data comprising clinical data associated with one or more patients currently within the health care entity, wherein at least some of the data is generated in real-time during an actual time in which one or more events occur; a second executable portion for using at least a portion of the data to generate one or more predictions regarding one or more conditions to occur in the future that are associated with one or more resources of the entity; a third executable portion for analyzing one or more results of the predictions and recommending an allocation of one or more resources on the basis of the results; a fourth executable portion for determining that one of the one or more conditions corresponds to a number of patient transfers and a number of patient discharges during a predetermined time period in the future; a fifth executable portion for determining that another of the conditions corresponds to a number of beds or rooms in one or more units of the entity that will be available at a predetermined time or during a predetermined time period in the future; a sixth executable portion for determining that another of the conditions corresponds to one or more levels of congestion within one or more units of the entity, the congestion corresponds to a number of patients assigned to a respective unit, the levels of congestion being determined based in part on a comparison of at least a subset of the number of the beds or rooms that are determined as unoccupied by a patient to a predetermined threshold signifying a level of patient congestion for the respective unit; a seventh executable portion for determining that the respective unit is congested with patients in an instance in which the number of beds or the rooms that are determined as unoccupied is below the predetermined threshold; an eighth executable portion for utilizing at least one of the levels of congestion to predict whether to assign one or more other patients to another respective unit of the entity; and a ninth executable portion for generating at least one recommendation of a number of persons to schedule for providing medical care for a time period in the future for the patients in at least one of the units based in part on a prediction of a number of patients expected to occupy the unit during the time period in the future, wherein the number of persons to schedule and the prediction of the number of patients is determined based in part on analyzing historical data indicating an average patient to medical personnel ratio within the unit during a corresponding time period in the past. - View Dependent Claims (19, 20, 21, 22, 23)
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Specification