Patent Application Titled “System And Methods For Managing Healthcare Resources” Published Online (USPTO 20220215910): Patent Application

2022 JUL 21 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- According to news reporting originating from Washington, D.C., by NewsRx journalists, a patent application by the inventor CHARLSON, Mary E. (New York, NY, US), filed on September 15, 2021, was made available online on July 7, 2022.

No assignee for this patent application has been made.

Reporters obtained the following quote from the background information supplied by the inventors: “Healthcare services are those that are rendered generally to diagnose, treat, and/or prevent the disease, illness, injury, and/or other physical and mental impairments of individuals. Multiple entities-including healthcare professionals, hospitals, health insurance providers, non-profit groups, private institutions, and/or government entities-provide, sustain, and/or support the delivery of healthcare services through the use of a variety of healthcare resources. The ability of these multiple entities to effectively deliver healthcare services may be affected by a variety of geographic, demographic, social, political, and/or economic factors. Some of these factors may change overtime. Some changes may lead to a change in the use of healthcare resources.

“The use of healthcare resources may be managed by accounting for hospitalizations, repeated hospitalizations, readmissions, outpatient services, laboratory services, pharmacology services, ambulatory services, and healthcare costs. It may, however, be more difficult to manage the use of healthcare resources by accounting for all healthcare resources because some may have a greater effect on the use of healthcare resources than others. Specifically, hospitalizations, repeated hospitalizations, readmissions, and healthcare costs have a greater effect on the use of healthcare resources. For the purposes of this invention, hospitalizations, repeated hospitalizations, readmissions, and healthcare costs may be termed hospitalization healthcare resources.

“Predicting the use of hospitalization healthcare resources including healthcare costs, risk of hospitalization, repeated hospitalization, and readmission may provide benefit to the multiple entities involved in the delivery of healthcare services. Certain government entities may subsidize the delivery of healthcare to their governed constituents. Predicting the use of hospitalization healthcare resources may prevent over subsidizing and/or under subsidizing. Predicting the use of hospitalization healthcare resources may benefit private institutions and/or health insurance providers that help support the costs of healthcare for their beneficiaries. In reaction to these predictions, private institutions and/or health insurance providers may, for example, organize wellness accountability programs or adjust beneficiaries’ contributions. In a clinical setting, predicting the use of hospitalization healthcare resources may allow healthcare professionals and/or hospitals to develop intervention strategies to manage healthcare costs, hospitalizations, repeated hospitalizations, and readmission.

“Many methods have been developed in attempt to predict the use of hospitalization healthcare resources. Some of these methods focus on individuals to determine whether individuals may be at risk for future high healthcare costs, hospitalizations, repeated hospitalizations and readmission. Some of these methods include steps of accepting information about the individuals from sources, processing the information accepted, and providing an output which may predict the use of hospitalization healthcare resources.

“Some known methods that include a step for accepting information from sources further include accepting information from prior medical records and/or prior insurance claims. These sources, however, can provide information largely at a time after a patient has been treated at a clinic. This information may be limited because it may be historic, outdated, and/or may not be current. In addition, these sources may store information in a digital and/or computer readable form and may further store information on servers owned by a variety of entities. Servers owned by private entities may require permission for access to the information. The span of time necessary to acquire permission may also cause information to be outdated.

“Some methods that include a step for processing information may further include categorizing information based on clinical diagnoses and/or demographics into groups. For example, one group may comprise males between the ages of 18 and 30 with diabetes. Groups may be assigned group codes.

“Some methods that include a step for processing information may further include placing group codes into hierarchies based on how likely the hierarchy is to use of hospitalization healthcare resources. In this way, an individual having certain clinical diagnoses and/or demographics may be associated with hierarchies correlating to the use of hospitalization healthcare resources. However, there may be uncertainty in predicting an individual’s use of hospitalization healthcare resources if that individual is associated with more than one hierarchy.

“Some methods that include a step for processing may further include using a comorbidity index. Generally, a comorbidity index is a list of chronic diseases in which each included chronic disease is assigned a value that predicts a future effect. Values may be weighted according to the likelihood of a future effect occurring. This Index may be used in methods which focus on individuals with multiple chronic diseases. Individuals may be assigned values from the Index based on whether the individuals have chronic diseases listed in the Index. Values may then be combined to predict a likelihood of a future effect for individuals with multiple chronic diseases. For example, the Index may provide scores of 1 for a prior myocardial infarction and 6 for metastatic cancer, but an individual afflicted with both chronic diseases may be assigned a value of 7.

“Indices similar to the comorbidity index were developed for specific purposes other than predicting the use of hospitalization healthcare resources. For example, indices included values weighted according to a risk that an individual will die. Also, indices may not have predicted future costs, future hospitalizations, repeated hospitalizations and readmissions. Methods which use these indices may introduce uncertainty in predicting whether individuals may use hospitalization healthcare resources by not targeting the individuals with chronic diseases most associated with high use of hospitalization healthcare resources.

“Some known methods that include a step for providing an output for predicting the use of hospitalization healthcare resources may further include providing group codes, hierarchy codes, and/or currency values. Group codes, and/or hierarchy codes may not be readily usable by healthcare entities because they are not clinically interpretable or mappable by a person unfamiliar with the codes. Even for people familiar with the codes, it may be difficult to immediately associate codes with the use of hospitalization healthcare resources. A graphical user interface displaying currency values may be too specific. Specific currency values may be misleading and introduce uncertainty in estimating the use of hospitalization healthcare resources.

“There is a need for a new test for predicting the use of hospitalization healthcare resources for both adults and children which may accept information from wider variety of sources, process the information in more simplified steps, and provide a more comprehensible output. The present invention satisfies these needs.”

In addition to obtaining background information on this patent application, NewsRx editors also obtained the inventor’s summary information for this patent application: “The present invention may be directed to a system and methods that may use non-transitory computer readable medium for predicting the use of hospitalization healthcare resources. Specifically, certain embodiments of the present invention may accept information from one or more sources, select one or more population units from the information to provide a selected group, define one or more population units from the selected group according to enhanced comorbidity to provide an enhanced comorbidity group, assign one or more values to one or more population units from the enhanced comorbidity group, and generate a graphical user interface on which one or more values may be depicted.

“In certain preferred embodiments, the present invention includes using an enhanced comorbidity index. The enhanced comorbidity index may be a comorbidity index which lists specific chronic diseases weighted according to a likelihood for the use of hospitalization healthcare resources. The enhanced comorbidity index may account for a wide range of physical and mental conditions including inflammatory bowel disease, major mental illnesses, and/or organ transplants. Enhanced comorbidity may also include conditions which affect children such as autism. The predicted effect of these specific chronic diseases on the use of hospitalization healthcare resources may also be termed for the purposes of this invention as “enhanced comorbidity”. Enhanced comorbidity may be assigned to patients regardless of age-that is, to both adults and children. Also, enhanced comorbidity may be used to predict future costs, future hospitalizations, repeated hospitalizations, and readmissions.

“Embodiments of the present invention may instruct a processor to accept information from a wider variety of sources. Sources of information that may be accepted and processed by the system may include an interview, a questionnaire, medical records, a registry or repository, and/or insurance claim data. Sources may provide information in analog form or in digital form. The sources may provide information including personal information, anonymous information, diagnostic information, demographic information, and/or geographic information.

“Advantageously, embodiments of the present invention may process and provide the information in more simplified steps. In some embodiments, a processor may be instructed to select one or more population units from the information to provide a selected group; define one or more population units from the selected group according to enhanced comorbidity to provide an enhanced comorbidity group; and assign one or more values to one or more population units from the enhanced comorbidity group.

“One or more population units may be selected based on information including personal information, anonymous information, diagnostic information, demographic information and/or geographic information of one or more individuals. One or more population units may be defined according to enhanced comorbidity based on whether information indicates one or more individuals comprising the one or more population units have one or more chronic diseases listed in an enhanced comorbidity index. Values may be assigned to one or more population units defined according to enhanced comorbidity based on whether the one or more chronic diseases are listed in an enhanced comorbidity index.

“Embodiments of the invention may provide a more comprehensible output. In some embodiments, a processor may be instructed to generate a graphical user interface on which one or more values may be depicted. The one or more values may be numbers weighted according to the use of hospitalization healthcare resources. It may be readily apparent from viewing the one or more values depicted whether one or more population units may use of hospitalization healthcare resources.

“Alternative embodiments of the present invention may be useful in determining whether one or more population units exceeds a use of hospitalization healthcare resources threshold. In some embodiments, a processor may be instructed to request a use of hospitalization healthcare resources threshold; compare one or more values to the use of hospitalization healthcare resources threshold; and generate a graphical user interface on which a determination of whether one or more population units exceed the use of hospitalization healthcare resources threshold may be depicted. A use of hospitalization healthcare resources threshold may be identified as value associated with use of hospitalization healthcare resources, and may be identified based on the range of weighted values listed in an enhanced comorbidity index.

“One object of the present invention may be to provide a new test for managing the use of hospitalization healthcare resources including healthcare costs, hospitalizations, repeated hospitalizations, and readmissions.

“A further object of the invention may be to predict whether one or more individuals may use of hospitalization healthcare resources.

“Another object of the present invention may be to determine whether one or more population units exceed a use of hospitalization healthcare resources threshold.

“An additional object of this invention may be to provide a new test capable of more accurately predicting whether one or more individuals may use of hospitalization healthcare resources in the usual clinical context.

“It may be an object of this invention to provide a new test capable of more accurately predicting whether one or more individuals may use of hospitalization healthcare resources for new health insurance beneficiary enrollees.

“The present invention, its attributes and advantages may be further understood with reference to the detailed description of presently contemplated embodiments, taken in conjunction with the accompanying drawings.”

The claims supplied by the inventors are:

“1.-20. (canceled)

“21. A predictive health management system comprising: one or more non-transitory computer-readable storage media bearing computer-readable executable instructions; one or more output devices; and one or more processors operatively associated with the one or more output devices and the one or more non-transitory computer-readable storage media, the one or more processors being configured, upon execution of the computer-readable executable instructions, to: select a group, via the one or more processors, from population information stored on the one or more non-transitory computer-readable storage media, the population information comprising predetermined chronic conditions associated with at least some members of the population; identify, via the one or more processors, at least one member within the selected group having a sum of predetermined chronic conditions equal to or greater than a selected threshold number of predetermined chronic conditions selected from a set of predetermined chronic conditions comprising a plurality of predetermined chronic conditions, each of the plurality of predetermined chronic conditions having a predefined comorbidity value associated therewith; determine, via the one or more processors, an enhanced comorbidity value for the at least one member within the selected group, the enhanced comorbidity value relating to a number of predetermined chronic conditions in excess of the threshold number of predetermined chronic conditions and further relating to predefined comorbidity values associated with each of the number of predetermined chronic conditions; determine, via the one or more processors, a level of use of at least one healthcare resource selected from a set of predefined healthcare resources corresponding to the determined enhanced comorbidity value for the at least one member; and output to at least one of the one or more output devices, via the one or more processors, a representation of level of use of the at least one healthcare resource corresponding to healthcare services delivery for the at least one member within the selected group.

“22. The predictive health management system according to claim 21, wherein the at least one member within the selected group comprises a plurality of members, and wherein the one or more processors are configured, upon execution of the computer-readable executable instructions, to: identify, via the one or more processors, a plurality of members within the selected group having the sum of predetermined chronic conditions equal to or greater than the selected threshold number of predetermined chronic conditions selected from the set of predetermined chronic conditions comprising the plurality of predetermined chronic conditions; determine, via the one or more processors, an enhanced comorbidity value for the plurality of members within the selected group, the enhanced comorbidity value for the plurality of members within the selected group relating to a number of predetermined chronic conditions in excess of the threshold number of predetermined chronic conditions and further relating to predefined comorbidity values associated with each of the number of predetermined chronic conditions; determine, via the one or more processors, a level of use of at least one healthcare resource selected from the set of predefined healthcare resources for the plurality of members within the selected group having a determined enhanced comorbidity value based on the determined enhanced comorbidity value for each of the plurality of members within the selected group; and output to at least one of the one or more output devices, via the one or more processors, a representation of the level of use of the at least one healthcare resource appropriate to healthcare services delivery for the plurality of members within the selected group.

“23. The predictive health management system according to claim 21, wherein the population information stored on the one or more non-transitory computer-readable storage media comprises age associated with each member of the population, and wherein the population information includes predetermined chronic conditions associated with at least some members of the population who are adults and includes predetermined chronic conditions associated with at least some members of the population who are children.

“24. The predictive health management system according to claim 23, wherein the at least one member within the selected group is associated with population information for a child.

“25. The predictive health management system according to claim 23, wherein the at least one member within the selected group is associated with a specific predetermined chronic condition.

“26. The predictive health management system according to claim 22, wherein the population information stored on the one or more non-transitory computer-readable storage media comprises age associated with each member of the population, and wherein the population information includes predetermined chronic conditions associated with at least some members of the population who are adults and includes predetermined chronic conditions associated with at least some members of the population who are children.

“27. The predictive health management system according to claim 26, wherein the at least one member within the selected group is associated with population information for a child.

“28. The predictive health management system according to claim 26, wherein the at least one member within the selected group is associated with a selected predetermined chronic condition.

“29. The predictive health management system according to claim 21, wherein the set of predefined healthcare resources includes at least one healthcare resource selected from the group consisting of a hospitalization, a repeated hospitalization, or a readmission.

“30. The predictive health management system according to claim 21, wherein the set of predefined healthcare resources includes at least one healthcare resource selected from the group consisting of an outpatient service, a laboratory service, a pharmacology service, or an ambulatory service.

“31. The predictive health management system according to claim 21, wherein the selected threshold number of predetermined chronic conditions comprises three chronic conditions.

“32. The predictive health management system according to claim 21, wherein the selected threshold number of predetermined chronic conditions comprises four chronic conditions.

“33. The predictive health management system according to claim 21, wherein the selected threshold number of predetermined chronic conditions comprises five chronic conditions.

“34. The predictive health management system according to claim 21, wherein the selected threshold number of predetermined chronic conditions comprises six, seven, eight, nine or ten chronic conditions.

“35. The predictive health management system according to claim 21, wherein the set of predetermined chronic conditions comprises a plurality of chronic conditions, at least one of which being selected from the group comprising: hypertension, blood thinner/anticoagulant usage, COPD/asthma, skin ulcers, cellulitis, dementia, transplant, inflammatory bowel disease, sickle cell disease, rheumatic disease, hemophilia, muscular dystrophy, developmental delay, mental retardation, Down’s syndrome, cystic fibrosis, Tay Sachs, cerebral palsy, uncontrolled seizures, autism, inherited diseases, schizophrenia, bipolar disease, substance abuse, congestive heart failure, diabetes, myocardial infarction, peripheral vascular disease, cerebrovascular disease, chronic pulmonary disease, connective tissue disease, ulcer disease, mild liver disease, hemiplegia, moderate or severe renal disease, diabetes with end organ damage, tumor, leukemia, lymphoma, moderate or severe liver disease, metastatic cancer, AIDs, depression, bipolar illness, or schizophrenia.

“36. The predictive health management system according to claim 21, wherein the set of predetermined chronic conditions comprises mental illness or substance abuse, and wherein one or more processors configured, upon execution of the computer-readable executable instructions, to identify, via the one or more processors, the at least one member within the selected group having population information associated with mental illness or substance abuse as one of the sum of predetermined chronic conditions.

“37. The predictive health management system according to claim 21, wherein the set of predetermined chronic conditions comprises skin ulcers or cellulitis, and wherein one or more processors configured, upon execution of the computer-readable executable instructions, to identify, via the one or more processors, the at least one member within the selected group having population information associated with skin ulcers or cellulitis as one of the sum of predetermined chronic conditions.

“38. The predictive health management system according to claim 21, wherein the set of predetermined chronic conditions comprises the Charlson comorbidity index and wherein the predefined comorbidity value associated with each of the plurality of predetermined chronic conditions in the corresponds to those values in the Charlson comorbidity index.

“39. The predictive health management system according to claim 21, wherein the representation of level of use of the at least one healthcare resource corresponding to healthcare services delivery for the at least one member within the selected group comprises a value corresponding to a risk of hospitalization, a repeated hospitalization or a readmission for the at least one member.”

There are additional claims. Please visit full patent to read further.

For more information, see this patent application: CHARLSON, Mary E. System And Methods For Managing Healthcare Resources. Filed September 15, 2021 and posted July 7, 2022. Patent URL: https://appft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PG01&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.html&r=1&f=G&l=50&s1=%2220220215910%22.PGNR.&OS=DN/20220215910&RS=DN/20220215910

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